true English en Pance Panov Adam Goldstein Alan Ruttenberg Albert Goldfain Ana Kostovska Barry Smith Bjoern Peters Carlo Torniai Chris Mungall Chris Stoeckert Christian A. Boelling Clint Dowland Darren Natale David Osumi-Sutherland Gwen Frishkoff Holger Stenzhorn James A. Overton James Malone Jennifer Fostel Jie Zheng Jonathan Rees Larisa Soldatova Larisa Soldatova Lawrence Hunter Mathias Brochhausen Matt Brush Melanie Courtot Michel Dumontier Pance Panov Paolo Ciccarese Pat Hayes Philippe Rocca-Serra Randy Dipert Ron Rudnicki Saso Dzeroski Satya Sahoo Sivaram Arabandi Werner Ceusters William Duncan William Hogan Yongqun (Oliver) He Pance Panov 06.05.2010 20.06.2018 The Information Artifact Ontology (IAO) is an ontology of information entities, originally driven by work by the OBI digital entity and realizable information entity branch. This ontology contains entities such as: datatype, datatype generator, datatype qualiy and others giving the possibility to represent arbitrary complex datatypes. The OntoDT ontology is based on and ISO/IEC 11404 (http://www.iso.org/iso/catalogue_detail.htm?csnumber=39479) standard and can be reused used independently by any domain ontology that requires representation and reasoning about general purpose datatypes. OWL-DL OntoDM-core English Data Mining and Knowledge Discovery Data Mining Datatypes External classes to OntoDM: IAO complete ontology importing both BFO and RO plus OBI classes extracted via OntoFox service inported from external_OBI.owl file Information Artifact Ontology (IAO) Ontology of Core Data Mining Entities Ontology of General Purpose Datatypes OntoDM-core http://kt.ijs.si/panovp/OntoDM/OntoDM.owl An information artifact is, loosely, a dependent continuant or its bearer that is created as the result of one or more intentional processes. Examples: uniprot, the english language, the contents of this document or a printout of it, the temperature measurements from a weather balloon. For more information, see the project home page at https://github.com/information-artifact-ontology/IAO IDs allocated to related efforts: PNO: IAO_0020000-IAO_0020999, D_ACTS: IAO_0021000-IAO_0021999 IDs allocated to subdomains of IAO. pno.owl: IAO_0020000-IAO_0020999, d-acts.owl: IAO_0021000-IAO_0021999 0.2 2.0 2022-11-07 Annotation property imported from OBI to denote terms that have been imported from other ontologies imported_from Relates an entity in the ontology to the name of the variable that is used to represent it in the code that generates the BFO OWL file from the lispy specification. Really of interest to developers only BFO OWL specification label Relates an entity in the ontology to the term that is used to represent it in the the CLIF specification of BFO2 Person:Alan Ruttenberg Really of interest to developers only BFO CLIF specification label editor preferred term The concise, meaningful, and human-friendly name for a class or property preferred by the ontology developers. (US-English) PERSON:Daniel Schober GROUP:OBI:<http://purl.obolibrary.org/obo/obi> editor preferred term example example of usage A phrase describing how a class name should be used. May also include other kinds of examples that facilitate immediate understanding of a class semantics, such as widely known prototypical subclasses or instances of the class. Although essential for high level terms, examples for low level terms (e.g., Affymetrix HU133 array) are not A phrase describing how a term should be used and/or a citation to a work which uses it. May also include other kinds of examples that facilitate immediate understanding, such as widely know prototypes or instances of a class, or cases where a relation is said to hold. PERSON:Daniel Schober GROUP:OBI:<http://purl.obolibrary.org/obo/obi> example of usage in branch An annotation property indicating which module the terms belong to. This is currently experimental and not implemented yet. GROUP:OBI OBI_0000277 in branch has curation status PERSON:Alan Ruttenberg PERSON:Bill Bug PERSON:Melanie Courtot OBI_0000281 has curation status definition The official OBI definition, explaining the meaning of a class or property. Shall be Aristotelian, formalized and normalized. Can be augmented with colloquial definitions. The official definition, explaining the meaning of a class or property. Shall be Aristotelian, formalized and normalized. Can be augmented with colloquial definitions. 2012-04-05: Barry Smith The official OBI definition, explaining the meaning of a class or property: 'Shall be Aristotelian, formalized and normalized. Can be augmented with colloquial definitions' is terrible. Can you fix to something like: A statement of necessary and sufficient conditions explaining the meaning of an expression referring to a class or property. Alan Ruttenberg Your proposed definition is a reasonable candidate, except that it is very common that necessary and sufficient conditions are not given. Mostly they are necessary, occasionally they are necessary and sufficient or just sufficient. Often they use terms that are not themselves defined and so they effectively can't be evaluated by those criteria. On the specifics of the proposed definition: We don't have definitions of 'meaning' or 'expression' or 'property'. For 'reference' in the intended sense I think we use the term 'denotation'. For 'expression', I think we you mean symbol, or identifier. For 'meaning' it differs for class and property. For class we want documentation that let's the intended reader determine whether an entity is instance of the class, or not. For property we want documentation that let's the intended reader determine, given a pair of potential relata, whether the assertion that the relation holds is true. The 'intended reader' part suggests that we also specify who, we expect, would be able to understand the definition, and also generalizes over human and computer reader to include textual and logical definition. Personally, I am more comfortable weakening definition to documentation, with instructions as to what is desirable. We also have the outstanding issue of how to aim different definitions to different audiences. A clinical audience reading chebi wants a different sort of definition documentation/definition from a chemistry trained audience, and similarly there is a need for a definition that is adequate for an ontologist to work with. PERSON:Daniel Schober GROUP:OBI:<http://purl.obolibrary.org/obo/obi> definition editor note An administrative note intended for its editor. It may not be included in the publication version of the ontology, so it should contain nothing necessary for end users to understand the ontology. PERSON:Daniel Schober GROUP:OBI:<http://purl.obfoundry.org/obo/obi> GROUP:OBI:<http://purl.obofoundry.org/obo/obi> editor note definition editor term editor Name of editor entering the definition in the file. The definition editor is a point of contact for information regarding the term. The definition editor may be, but is not always, the author of the definition, which may have been worked upon by several people Name of editor entering the term in the file. The term editor is a point of contact for information regarding the term. The term editor may be, but is not always, the author of the definition, which may have been worked upon by several people 20110707, MC: label update to term editor and definition modified accordingly. See https://github.com/information-artifact-ontology/IAO/issues/115. PERSON:Daniel Schober GROUP:OBI:<http://purl.obolibrary.org/obo/obi> definition editor term editor alternative label alternative term A label for a class or property that can be used to refer to the class or property instead of the preferred rdfs:label. Alternative labels should be used to indicate community- or context-specific labels, abbreviations, shorthand forms and the like. An alternative name for a class or property which means the same thing as the preferred name (semantically equivalent) OBO Operations committee PERSON:Daniel Schober GROUP:OBI:<http://purl.obolibrary.org/obo/obi> Consider re-defing to: An alternative name for a class or property which can mean the same thing as the preferred name (semantically equivalent, narrow, broad or related). alternative label alternative term definition source Formal citation, e.g. identifier in external database to indicate / attribute source(s) for the definition. Free text indicate / attribute source(s) for the definition. EXAMPLE: Author Name, URI, MeSH Term C04, PUBMED ID, Wiki uri on 31.01.2007 formal citation, e.g. identifier in external database to indicate / attribute source(s) for the definition. Free text indicate / attribute source(s) for the definition. EXAMPLE: Author Name, URI, MeSH Term C04, PUBMED ID, Wiki uri on 31.01.2007 PERSON:Daniel Schober Discussion on obo-discuss mailing-list, see http://bit.ly/hgm99w GROUP:OBI:<http://purl.obolibrary.org/obo/obi> definition source has obsolescence reason Relates an annotation property to an obsolescence reason. The values of obsolescence reasons come from a list of predefined terms, instances of the class obsolescence reason specification. PERSON:Alan Ruttenberg PERSON:Melanie Courtot has obsolescence reason curator note An administrative note of use for a curator but of no use for a user PERSON:Alan Ruttenberg curator note term tracker item the URI for an OBI Terms ticket at sourceforge, such as https://sourceforge.net/p/obi/obi-terms/772/ An IRI or similar locator for a request or discussion of an ontology term. Person: Jie Zheng, Chris Stoeckert, Alan Ruttenberg Person: Jie Zheng, Chris Stoeckert, Alan Ruttenberg The 'tracker item' can associate a tracker with a specific ontology term. term tracker item ontology term requester The name of the person, project, or organization that motivated inclusion of an ontology term by requesting its addition. Person: Jie Zheng, Chris Stoeckert, Alan Ruttenberg Person: Jie Zheng, Chris Stoeckert, Alan Ruttenberg The 'term requester' can credit the person, organization or project who request the ontology term. ontology term requester is denotator type Relates an class defined in an ontology, to the type of it's denotator In OWL 2 add AnnotationPropertyRange('is denotator type' 'denotator type') Alan Ruttenberg is denotator type imported from For external terms/classes, the ontology from which the term was imported PERSON:Alan Ruttenberg PERSON:Melanie Courtot GROUP:OBI:<http://purl.obolibrary.org/obo/obi> imported from expand expression to ObjectProperty: RO_0002104 Label: has plasma membrane part Annotations: IAO_0000424 "http://purl.obolibrary.org/obo/BFO_0000051 some (http://purl.org/obo/owl/GO#GO_0005886 and http://purl.obolibrary.org/obo/BFO_0000051 some ?Y)" A macro expansion tag applied to an object property (or possibly a data property) which can be used by a macro-expansion engine to generate more complex expressions from simpler ones Chris Mungall expand expression to expand assertion to ObjectProperty: RO??? Label: spatially disjoint from Annotations: expand_assertion_to "DisjointClasses: (http://purl.obolibrary.org/obo/BFO_0000051 some ?X) (http://purl.obolibrary.org/obo/BFO_0000051 some ?Y)" A macro expansion tag applied to an annotation property which can be expanded into a more detailed axiom. Chris Mungall expand assertion to first order logic expression PERSON:Alan Ruttenberg first order logic expression antisymmetric property part_of antisymmetric property xsd:true Use boolean value xsd:true to indicate that the property is an antisymmetric property Alan Ruttenberg antisymmetric property OBO foundry unique label An alternative name for a class or property which is unique across the OBO Foundry. The intended usage of that property is as follow: OBO foundry unique labels are automatically generated based on regular expressions provided by each ontology, so that SO could specify unique label = 'sequence ' + [label], etc. , MA could specify 'mouse + [label]' etc. Upon importing terms, ontology developers can choose to use the 'OBO foundry unique label' for an imported term or not. The same applies to tools . PERSON:Alan Ruttenberg PERSON:Bjoern Peters PERSON:Chris Mungall PERSON:Melanie Courtot GROUP:OBO Foundry <http://obofoundry.org/> OBO foundry unique label has ID digit count Ontology: <http://purl.obolibrary.org/obo/ro/idrange/> Annotations: 'has ID prefix': "http://purl.obolibrary.org/obo/RO_" 'has ID digit count' : 7, rdfs:label "RO id policy" 'has ID policy for': "RO" Relates an ontology used to record id policy to the number of digits in the URI. The URI is: the 'has ID prefix" annotation property value concatenated with an integer in the id range (left padded with "0"s to make this many digits) Person:Alan Ruttenberg has ID digit count has ID range allocated Datatype: idrange:1 Annotations: 'has ID range allocated to': "Chris Mungall" EquivalentTo: xsd:integer[> 2151 , <= 2300] Relates a datatype that encodes a range of integers to the name of the person or organization who can use those ids constructed in that range to define new terms Person:Alan Ruttenberg has ID range allocated to has ID policy for Ontology: <http://purl.obolibrary.org/obo/ro/idrange/> Annotations: 'has ID prefix': "http://purl.obolibrary.org/obo/RO_" 'has ID digit count' : 7, rdfs:label "RO id policy" 'has ID policy for': "RO" Relating an ontology used to record id policy to the ontology namespace whose policy it manages Person:Alan Ruttenberg has ID policy for has ID prefix Ontology: <http://purl.obolibrary.org/obo/ro/idrange/> Annotations: 'has ID prefix': "http://purl.obolibrary.org/obo/RO_" 'has ID digit count' : 7, rdfs:label "RO id policy" 'has ID policy for': "RO" Relates an ontology used to record id policy to a prefix concatenated with an integer in the id range (left padded with "0"s to make this many digits) to construct an ID for a term being created. Person:Alan Ruttenberg has ID prefix elucidation person:Alan Ruttenberg Person:Barry Smith Primitive terms in a highest-level ontology such as BFO are terms which are so basic to our understanding of reality that there is no way of defining them in a non-circular fashion. For these, therefore, we can provide only elucidations, supplemented by examples and by axioms elucidation has associated axiom(nl) Person:Alan Ruttenberg Person:Alan Ruttenberg An axiom associated with a term expressed using natural language has associated axiom(nl) has associated axiom(fol) Person:Alan Ruttenberg Person:Alan Ruttenberg An axiom expressed in first order logic using CLIF syntax has associated axiom(fol) is allocated id range Relates an ontology IRI to an (inclusive) range of IRIs in an OBO name space. The range is give as, e.g. "IAO_0020000-IAO_0020999" PERSON:Alan Ruttenberg Add as annotation triples in the granting ontology is allocated id range retired from use as of relates a class of CRID to the date after which further instances should not be made, according to the central authority In OWL 2 add AnnotationPropertyRange xsd:dateTimeStamp Alan Ruttenberg retired from use as of has ontology root term Ontology annotation property. Relates an ontology to a term that is a designated root term of the ontology. Display tools like OLS can use terms annotated with this property as the starting point for rendering the ontology class hierarchy. There can be more than one root. Nicolas Matentzoglu has ontology root term may be identical to A annotation relationship between two terms in an ontology that may refer to the same (natural) type but where more evidence is required before terms are merged. David Osumi-Sutherland #40 VFB Edges asserting this should be annotated with to record evidence supporting the assertion and its provenance. may be identical to scheduled for obsoletion on or after Used when the class or object is scheduled for obsoletion/deprecation on or after a particular date. Chris Mungall, Jie Zheng https://github.com/geneontology/go-ontology/issues/15532 https://github.com/information-artifact-ontology/ontology-metadata/issues/32 GO ontology scheduled for obsoletion on or after has axiom id Person:Alan Ruttenberg Person:Alan Ruttenberg A URI that is intended to be unique label for an axiom used for tracking change to the ontology. For an axiom expressed in different languages, each expression is given the same URI has axiom label term replaced by Use on obsolete terms, relating the term to another term that can be used as a substitute Person:Alan Ruttenberg Person:Alan Ruttenberg Add as annotation triples in the granting ontology term replaced by This is an annotation used on an object property to indicate a logical characterstic beyond what is possible in OWL. OBO Operations call logical characteristic of object property 'part disjoint with' 'defined by construct' """ PREFIX owl: <http://www.w3.org/2002/07/owl#> PREFIX : <http://example.org/ CONSTRUCT { [ a owl:Restriction ; owl:onProperty :part_of ; owl:someValuesFrom ?a ; owl:disjointWith [ a owl:Restriction ; owl:onProperty :part_of ; owl:someValuesFrom ?b ] ] } WHERE { ?a :part_disjoint_with ?b . } Links an annotation property to a SPARQL CONSTRUCT query which is meant to provide semantics for a shortcut relation. defined by construct An assertion that holds between an OWL Object Property and a temporal interpretation that elucidates how OWL Class Axioms that use this property are to be interpreted in a temporal context. temporal interpretation An alternative label for a class or property which has a more general meaning than the preferred name/primary label. https://github.com/information-artifact-ontology/ontology-metadata/issues/18 has broad synonym https://github.com/information-artifact-ontology/ontology-metadata/issues/18 An alternative label for a class or property which has the exact same meaning than the preferred name/primary label. https://github.com/information-artifact-ontology/ontology-metadata/issues/20 has exact synonym https://github.com/information-artifact-ontology/ontology-metadata/issues/20 An alternative label for a class or property which has a more specific meaning than the preferred name/primary label. https://github.com/information-artifact-ontology/ontology-metadata/issues/19 has narrow synonym https://github.com/information-artifact-ontology/ontology-metadata/issues/19 An alternative label for a class or property that has been used synonymously with the primary term name, but the usage is not strictly correct. https://github.com/information-artifact-ontology/ontology-metadata/issues/21 has related synonym https://github.com/information-artifact-ontology/ontology-metadata/issues/21 OntoDT_0000003 OntoDT_0000003s OntoDT_0000003ed represents OntoDT_0000009 OntoDT_0000009s OntoDT_0000009ed has_datatype_role is_datatype_role_of OntoDT_0000012 OntoDT_0000012s OntoDT_0000012ed is_quality_of is part of my brain is part of my body (continuant parthood, two material entities) my stomach cavity is part of my stomach (continuant parthood, immaterial entity is part of material entity) this day is part of this year (occurrent parthood) a core relation that holds between a part and its whole Everything is part of itself. Any part of any part of a thing is itself part of that thing. Two distinct things cannot be part of each other. Occurrents are not subject to change and so parthood between occurrents holds for all the times that the part exists. Many continuants are subject to change, so parthood between continuants will only hold at certain times, but this is difficult to specify in OWL. See http://purl.obolibrary.org/obo/ro/docs/temporal-semantics/ Parthood requires the part and the whole to have compatible classes: only an occurrent can be part of an occurrent; only a process can be part of a process; only a continuant can be part of a continuant; only an independent continuant can be part of an independent continuant; only an immaterial entity can be part of an immaterial entity; only a specifically dependent continuant can be part of a specifically dependent continuant; only a generically dependent continuant can be part of a generically dependent continuant. (This list is not exhaustive.) A continuant cannot be part of an occurrent: use 'participates in'. An occurrent cannot be part of a continuant: use 'has participant'. A material entity cannot be part of an immaterial entity: use 'has location'. A specifically dependent continuant cannot be part of an independent continuant: use 'inheres in'. An independent continuant cannot be part of a specifically dependent continuant: use 'bearer of'. part_of part of http://www.obofoundry.org/ro/#OBO_REL:part_of realized in this disease is realized in this disease course this fragility is realized in this shattering this investigator role is realized in this investigation is realized by realized_in [copied from inverse property 'realizes'] to say that b realizes c at t is to assert that there is some material entity d & b is a process which has participant d at t & c is a disposition or role of which d is bearer_of at t& the type instantiated by b is correlated with the type instantiated by c. (axiom label in BFO2 Reference: [059-003]) Paraphrase of elucidation: a relation between a realizable entity and a process, where there is some material entity that is bearer of the realizable entity and participates in the process, and the realizable entity comes to be realized in the course of the process realized in realizes this disease course realizes this disease this investigation realizes this investigator role this shattering realizes this fragility to say that b realizes c at t is to assert that there is some material entity d & b is a process which has participant d at t & c is a disposition or role of which d is bearer_of at t& the type instantiated by b is correlated with the type instantiated by c. (axiom label in BFO2 Reference: [059-003]) Paraphrase of elucidation: a relation between a process and a realizable entity, where there is some material entity that is bearer of the realizable entity and participates in the process, and the realizable entity comes to be realized in the course of the process realizes occurs in b occurs_in c =def b is a process and c is a material entity or immaterial entity& there exists a spatiotemporal region r and b occupies_spatiotemporal_region r.& forall(t) if b exists_at t then c exists_at t & there exist spatial regions s and s’ where & b spatially_projects_onto s at t& c is occupies_spatial_region s’ at t& s is a proper_continuant_part_of s’ at t occurs_in unfolds in unfolds_in Paraphrase of definition: a relation between a process and an independent continuant, in which the process takes place entirely within the independent continuant occurs in site of [copied from inverse property 'occurs in'] b occurs_in c =def b is a process and c is a material entity or immaterial entity& there exists a spatiotemporal region r and b occupies_spatiotemporal_region r.& forall(t) if b exists_at t then c exists_at t & there exist spatial regions s and s’ where & b spatially_projects_onto s at t& c is occupies_spatial_region s’ at t& s is a proper_continuant_part_of s’ at t Paraphrase of definition: a relation between an independent continuant and a process, in which the process takes place entirely within the independent continuant contains process The process of creation is, for example, writing down on paper the name of a friend by deliberately creating a certain pattern using ink. Here the ink + paper is the independent continuant and the carrier is the pattern in the ink. c = pattern in the ink b = paper + ink r = friend c specifically denotes r =def r is a portion of reality & c is a particular quality & c depends specifically on some independent continuant b & b acquired c as the result of the achievement of an objective to enable pointing to r repeatedly. Marked means there is a changed or additional quality of the bearer - the quality is the information carrier. Case 1 Memory trace as mark created when reading some description of some friend. The trace can denote. Case 2 Pattern of ink arrayed on paper as mark when writing down a friend's name Case 3 Pattern of magnetic domains on scattered pieces of a hard disk platter as mark when saving a file. 8/6/2009 Alan Ruttenberg: The suggestions is to deprecate specific and generically denotes in favor of a single denote relationship that corresponds to the generic sense see https://github.com/information-artifact-ontology/IAO/issues/25&q=denote Alan Ruttenberg Smith, Ceusters, Ruttenberg, 2000 years of philosophy obsolete_specifically denotes true An information artifact IA mentions an entity E exactly when it has a component/part that denotes E 7/6/2009 Alan Ruttenberg. P4 RC1 munges our GCI so remove it for now: mentions some entity equivalentTo has_part some ('generically denotes' some entity) 7/6/2009 Alan Ruttenberg: Add this relation following conversation with Jonathan Rees that N&S GCI for is_about was too strong. Really it was simply sufficient. To effect this change we introduce this relation, which is subproperty of is_about, and have previous GCI use this relation "mentions" in it's (logical) definition PERSON: Jonathan Rees Person: Alan Ruttenberg mentions Inverse of the relation 'mentions' 2022-01-28T07:20:08Z mentioned by see https://github.com/information-artifact-ontology/IAO/issues/25&q=denote obsolete_materially denotes true obsolete_describes true obsolete_represents true inverse of the relation 'denotes' Person: Jie Zheng, Chris Stoeckert, Mike Conlon denoted by relating a cartesian spatial coordinate datum to a unit label that together with the values represent a point has coordinate unit label relates a process to a time-measurement-datum that represents the duration of the process Person:Alan Ruttenberg is duration of inverse of the relation of is quality measurement of 2009/10/19 Alan Ruttenberg. Named 'junk' relation useful in restrictions, but not a real instance relationship Person:Alan Ruttenberg is quality measured as inverse of the relation of is quality specification of 2009/10/19 Alan Ruttenberg. Named 'junk' relation useful in restrictions, but not a real instance relationship Person:Alan Ruttenberg Person:Bjoern Peters quality is specified as relates a time stamped measurement datum to the time measurement datum that denotes the time when the measurement was taken Alan Ruttenberg has time stamp relates a time stamped measurement datum to the measurement datum that was measured Alan Ruttenberg has measurement datum OBI_0000295 OBI_0000295s OBI_0000295ed is_specified_input_of is_specified_input_of OBI_0000297 OBI_0000297s OBI_0000297ed http://purl.obofoundry.org/obo/obi.owl Is a relationship between a specifically dependent continuant and a generically dependent continuant. A generically dependent continuant may inhere in more than one entity. It does so by virtue of the fact that there is, for each entity that it inheres, a specifically dependent *concretization* of the generically dependent continuant that is specifically dependent. For instance, consider a story, which is an information artifact that inheres in some number of books. Each book bears some quality that carries the story. The relation between this quality and the generically dependent continuant is that the former is the concretization of the latter. is_concretized_as OBI_0000316 OBI_0000316s OBI_0000316ed has_role OBI_0000833 OBI_0000833s OBI_0000833ed objective_achieved_by inheres in this fragility is a characteristic of this vase this red color is a characteristic of this apple a relation between a specifically dependent continuant (the characteristic) and any other entity (the bearer), in which the characteristic depends on the bearer for its existence. inheres_in Note that this relation was previously called "inheres in", but was changed to be called "characteristic of" because BFO2 uses "inheres in" in a more restricted fashion. This relation differs from BFO2:inheres_in in two respects: (1) it does not impose a range constraint, and thus it allows qualities of processes, as well as of information entities, whereas BFO2 restricts inheres_in to only apply to independent continuants (2) it is declared functional, i.e. something can only be a characteristic of one thing. characteristic of bearer of this apple is bearer of this red color this vase is bearer of this fragility Inverse of characteristic_of A bearer can have many dependents, and its dependents can exist for different periods of time, but none of its dependents can exist when the bearer does not exist. bearer_of is bearer of has characteristic participates in this blood clot participates in this blood coagulation this input material (or this output material) participates in this process this investigator participates in this investigation a relation between a continuant and a process, in which the continuant is somehow involved in the process participates_in participates in A journal article is an information artifact that inheres in some number of printed journals. For each copy of the printed journal there is some quality that carries the journal article, such as a pattern of ink. The journal article (a generically dependent continuant) is concretized as the quality (a specifically dependent continuant), and both depend on that copy of the printed journal (an independent continuant). An investigator reads a protocol and forms a plan to carry out an assay. The plan is a realizable entity (a specifically dependent continuant) that concretizes the protocol (a generically dependent continuant), and both depend on the investigator (an independent continuant). The plan is then realized by the assay (a process). A relationship between a generically dependent continuant and a specifically dependent continuant, in which the generically dependent continuant depends on some independent continuant in virtue of the fact that the specifically dependent continuant also depends on that same independent continuant. A generically dependent continuant may be concretized as multiple specifically dependent continuants. is concretized as A journal article is an information artifact that inheres in some number of printed journals. For each copy of the printed journal there is some quality that carries the journal article, such as a pattern of ink. The quality (a specifically dependent continuant) concretizes the journal article (a generically dependent continuant), and both depend on that copy of the printed journal (an independent continuant). An investigator reads a protocol and forms a plan to carry out an assay. The plan is a realizable entity (a specifically dependent continuant) that concretizes the protocol (a generically dependent continuant), and both depend on the investigator (an independent continuant). The plan is then realized by the assay (a process). A relationship between a specifically dependent continuant and a generically dependent continuant, in which the generically dependent continuant depends on some independent continuant in virtue of the fact that the specifically dependent continuant also depends on that same independent continuant. Multiple specifically dependent continuants can concretize the same generically dependent continuant. concretizes this catalysis function is a function of this enzyme a relation between a function and an independent continuant (the bearer), in which the function specifically depends on the bearer for its existence A function inheres in its bearer at all times for which the function exists, however the function need not be realized at all the times that the function exists. function_of is function of This relation is modeled after the BFO relation of the same name which was in BFO2, but is used in a more restricted sense - specifically, we model this relation as functional (inherited from characteristic-of). Note that this relation is now removed from BFO2020. function of this red color is a quality of this apple a relation between a quality and an independent continuant (the bearer), in which the quality specifically depends on the bearer for its existence A quality inheres in its bearer at all times for which the quality exists. is quality of quality_of This relation is modeled after the BFO relation of the same name which was in BFO2, but is used in a more restricted sense - specifically, we model this relation as functional (inherited from characteristic-of). Note that this relation is now removed from BFO2020. quality of this investigator role is a role of this person a relation between a role and an independent continuant (the bearer), in which the role specifically depends on the bearer for its existence A role inheres in its bearer at all times for which the role exists, however the role need not be realized at all the times that the role exists. is role of role_of This relation is modeled after the BFO relation of the same name which was in BFO2, but is used in a more restricted sense - specifically, we model this relation as functional (inherited from characteristic-of). Note that this relation is now removed from BFO2020. role of this enzyme has function this catalysis function (more colloquially: this enzyme has this catalysis function) a relation between an independent continuant (the bearer) and a function, in which the function specifically depends on the bearer for its existence A bearer can have many functions, and its functions can exist for different periods of time, but none of its functions can exist when the bearer does not exist. A function need not be realized at all the times that the function exists. has_function has function this apple has quality this red color a relation between an independent continuant (the bearer) and a quality, in which the quality specifically depends on the bearer for its existence A bearer can have many qualities, and its qualities can exist for different periods of time, but none of its qualities can exist when the bearer does not exist. has_quality has quality this person has role this investigator role (more colloquially: this person has this role of investigator) a relation between an independent continuant (the bearer) and a role, in which the role specifically depends on the bearer for its existence A bearer can have many roles, and its roles can exist for different periods of time, but none of its roles can exist when the bearer does not exist. A role need not be realized at all the times that the role exists. has_role has role a relation between an independent continuant (the bearer) and a disposition, in which the disposition specifically depends on the bearer for its existence has disposition This relation is modeled after the BFO relation of the same name which was in BFO2, but is used in a more restricted sense - specifically, we model this relation as functional (inherited from characteristic-of). Note that this relation is now removed from BFO2020. disposition of this cell derives from this parent cell (cell division) this nucleus derives from this parent nucleus (nuclear division) a relation between two distinct material entities, the new entity and the old entity, in which the new entity begins to exist when the old entity ceases to exist, and the new entity inherits the significant portion of the matter of the old entity This is a very general relation. More specific relations are preferred when applicable, such as 'directly develops from'. derives_from derives from this parent cell derives into this cell (cell division) this parent nucleus derives into this nucleus (nuclear division) a relation between two distinct material entities, the old entity and the new entity, in which the new entity begins to exist when the old entity ceases to exist, and the new entity inherits the significant portion of the matter of the old entity This is a very general relation. More specific relations are preferred when applicable, such as 'directly develops into'. To avoid making statements about a future that may not come to pass, it is often better to use the backward-looking 'derives from' rather than the forward-looking 'derives into'. derives_into derives into is location of my head is the location of my brain this cage is the location of this rat a relation between two independent continuants, the location and the target, in which the target is entirely within the location Most location relations will only hold at certain times, but this is difficult to specify in OWL. See http://purl.obolibrary.org/obo/ro/docs/temporal-semantics/ location_of location of located in my brain is located in my head this rat is located in this cage a relation between two independent continuants, the target and the location, in which the target is entirely within the location Location as a relation between instances: The primitive instance-level relation c located_in r at t reflects the fact that each continuant is at any given time associated with exactly one spatial region, namely its exact location. Following we can use this relation to define a further instance-level location relation - not between a continuant and the region which it exactly occupies, but rather between one continuant and another. c is located in c1, in this sense, whenever the spatial region occupied by c is part_of the spatial region occupied by c1. Note that this relation comprehends both the relation of exact location between one continuant and another which obtains when r and r1 are identical (for example, when a portion of fluid exactly fills a cavity), as well as those sorts of inexact location relations which obtain, for example, between brain and head or between ovum and uterus Most location relations will only hold at certain times, but this is difficult to specify in OWL. See http://purl.obolibrary.org/obo/ro/docs/temporal-semantics/ located_in http://www.obofoundry.org/ro/#OBO_REL:located_in located in This is redundant with the more specific 'independent and not spatial region' constraint. We leave in the redundant axiom for use with reasoners that do not use negation. This is redundant with the more specific 'independent and not spatial region' constraint. We leave in the redundant axiom for use with reasoners that do not use negation. the surface of my skin is a 2D boundary of my body a relation between a 2D immaterial entity (the boundary) and a material entity, in which the boundary delimits the material entity A 2D boundary may have holes and gaps, but it must be a single connected entity, not an aggregate of several disconnected parts. Although the boundary is two-dimensional, it exists in three-dimensional space and thus has a 3D shape. 2D_boundary_of boundary of is 2D boundary of is boundary of 2D boundary of my body has 2D boundary the surface of my skin a relation between a material entity and a 2D immaterial entity (the boundary), in which the boundary delimits the material entity A 2D boundary may have holes and gaps, but it must be a single connected entity, not an aggregate of several disconnected parts. Although the boundary is two-dimensional, it exists in three-dimensional space and thus has a 3D shape. has boundary has_2D_boundary has 2D boundary An organism that is a member of a population of organisms is member of is a mereological relation between a item and a collection. is member of member part of SIO member of has member is a mereological relation between a collection and an item. SIO has member DEPRECATED This relation is similar to but different in important respects to the characteristic-of relation. See comments on that relation for more information. DEPRECATED inheres in true DEPRECATED bearer of true bearer_of bearer_ofs bearer_ofed http://purl.obofoundry.org/obo/obi.owl bearer_of inheres_in inhereses_in inheresed_in http://purl.org/obo/owl/OBO_REL OntoDM_462848 inheres_in quality_of quality_ofs quality_ofed quality_of has attribute is a relation that associates a entity with an attribute where an attribute is an intrinsic characteristic such as a quality, capability, disposition, function, or is an externally derived attribute determined from some descriptor (e.g. a quantity, position, label/identifier) either directly or indirectly through generalization of entities of the same type. http://semanticscience.org/ontology/sio.owl http://semanticscience.org/ontology/sio.owl has_attribute is attribute of is a relation that associates an attribute with an entity where an attribute is an intrinsic characteristic such as a quality, capability, disposition, function, or is an externally derived attribute determined from some descriptor (e.g. a quantity, position, label/identifier) either directly or indirectly through generalization of entities of the same type. http://semanticscience.org/ontology/sio.owl http://semanticscience.org/ontology/sio.owl attribute_of has member is a mereological relation between a collection and an item. http://semanticscience.org/ontology/sio.owl http://semanticscience.org/ontology/sio.owl has_member is member of is a mereological relation between a item and a collection. http://semanticscience.org/ontology/sio.owl http://semanticscience.org/ontology/sio.owl is_member_of a relation between an entity and an identifier. http://semanticscience.org/ontology/sio.owl http://semanticscience.org/ontology/sio.owl has_identifier a relation between an identifier and an entity. http://semanticscience.org/ontology/sio.owl http://semanticscience.org/ontology/sio.owl is_identifier_for has_representation has_representations has_representationed has_representation agent_in agents_in agented_in has_participant has_participants has_participanted part_of part_ofs part_ofed participates_in participateses_in participatesed_in precedes precedeses precedesed OntoDM_741560 OntoDM_741560s OntoDM_741560ed is_representation_of OntoDT_0000400 OntoDT_0000400s OntoDT_0000400ed has_operation is_operation_of is_node_component_of has_field_component has_alternative_component has_edge_component has_node_component has_base_datatype objectProperty_3 objectProperty_3s objectProperty_3ed has_information has measurement value has x coordinate value has z coordinate value has y coordinate value OntoDM_000039 OntoDM_000039s OntoDM_000039ed has_data_items_number OntoDM_000055 OntoDM_000055s OntoDM_000055ed has_description OntoDM_000068 OntoDM_000068s OntoDM_000068ed has_features_number OntoDM_000074 OntoDM_000074s OntoDM_000074ed has_name OntoDM_000088 OntoDM_000088s OntoDM_000088ed has_number OntoDM_000136 OntoDM_000136s OntoDM_000136ed has_identifyer OntoDM_000162 OntoDM_000162s OntoDM_000162ed is-labeled OntoDM_000311 OntoDM_000311s OntoDM_000311ed has_URL OntoDT_0000240 OntoDT_0000240s OntoDT_0000240ed has-value OntoDM_269620s OntoDM_269620 precentage train-test split evaluation algorithm OntoDM_349672s OntoDM_349672 separate test set evaluation algorithm OntoDM_361694s OntoDM_361694 cross validation evaluation algorithm OntoDM_562975s OntoDM_562975 train set evaluation algorithm OntoDT_0000002s OntoDT_0000002 Datatype Specification Language Representation OntoDT_0000005s OntoDT_0000005 list specification list specification OntoDT_0000006s OntoDT_0000006 datatype generator OntoDT_0000008s OntoDT_0000008 datatype role OntoDT_0000013s OntoDT_0000013 excluding subtype generator OntoDT_0000014s OntoDT_0000014 explicit subtype generator OntoDT_0000015s OntoDT_0000015 extending subtype generator OntoDT_0000016s OntoDT_0000016 range subtype generator OntoDT_0000017s OntoDT_0000017 selection subtype generator OntoDT_0000018s OntoDT_0000018 size subtype generator OntoDT_0000019s OntoDT_0000019 natural number OntoDT_0000020s OntoDT_0000020 modulo OntoDT_0000021s OntoDT_0000021 bit OntoDT_0000022s OntoDT_0000022 bit string OntoDT_0000023s OntoDT_0000023 character string OntoDT_0000024s OntoDT_0000024 time interval OntoDT_0000025s OntoDT_0000025 octet OntoDT_0000026s OntoDT_0000026 octet string OntoDT_0000027s OntoDT_0000027 private OntoDT_0000028s OntoDT_0000028 object identifier OntoDT_0000029s OntoDT_0000029 stack OntoDT_0000030s OntoDT_0000030 tree OntoDT_0000031s OntoDT_0000031 optional OntoDT_0000032s OntoDT_0000032 array generator OntoDT_0000033s OntoDT_0000033 bag generator OntoDT_0000034s OntoDT_0000034 class generator OntoDT_0000035s OntoDT_0000035 record generator OntoDT_0000036s OntoDT_0000036 sequence generator OntoDT_0000037s OntoDT_0000037 set generator OntoDT_0000038s OntoDT_0000038 table generator OntoDT_0000039s OntoDT_0000039 choice generator OntoDT_0000040s OntoDT_0000040 pointer generator OntoDT_0000041s OntoDT_0000041 procedure generator OntoDT_003508s OntoDT_003508 whose values are collections of values in the product space of one or more field datatypes, such that each value in the product space represents an association among the values of its fields. Although the field datatypes may be infinite, any given value of a table datatype contains a finite number of associations. table datatype OntoDT_016936s OntoDT_016936 attribute identifier OntoDT_017837s OntoDT_017837 An aggregate datatype has the ordering property, if and only if there is a canonical first element of each nonempty value in its value-space. This ordering is (externally) imposed by the aggregate value, as distinct from the value-space of the element datatype itself being (internally) ordered (see 6.3.2). It is also distinct from the value-space of the aggregate datatype being ordered. aggregate imposed ordering OntoDT_018988s OntoDT_018988 A datatype whose value space is defined either axiomatically or by enumeration is said to be a primitive datatype. identifiable datatype that cannot be decomposed into other identifiable datatypes without loss of all semantics associated with the datatype primitive datatype OntoDT_029503s OntoDT_029503 defined datatype parameter OntoDT_035818s OntoDT_035818 parameter identifier OntoDT_038213s OntoDT_038213 date-time factor OntoDT_041544s OntoDT_041544 graph aggregate component OntoDT_059114s OntoDT_059114 datatype which is a parametric datatype to a datatype generator parametric datatype datatype on which a datatype generator operates to produce a generated datatype field component OntoDT_067375s OntoDT_067375 Dyadic operation maps a pair of values of the given datatype into a value of the given datatype or into a value of datatype Boolean dyadic operation OntoDT_079536s OntoDT_079536 attribute-list OntoDT_089686s OntoDT_089686 discrete-value-list OntoDT_095716s OntoDT_095716 a value space is the collection of values for a given datatype ISO/IEC 11404:2007(E) value space OntoDT_099378s OntoDT_099378 tree datatype generator OntoDT_1000001s OntoDT_1000001 alternative-type identifier OntoDT_1000004s OntoDT_1000004 alternative component OntoDT_1000005s OntoDT_1000005 pointer-element-type OntoDT_1000006s OntoDT_1000006 procedure-parameter-list OntoDT_1000007s OntoDT_1000007 procedure-paremeter declaration OntoDT_1000008s OntoDT_1000008 direction OntoDT_1000009s OntoDT_1000009 parameter OntoDT_1000010s OntoDT_1000010 return-parameter specification OntoDT_110287s OntoDT_110287 whose values are associations between the product space of one or more finite datatypes, designated the index datatypes, and the value space of the element datatype, such that every value in the product space of the index datatypes associates to exactly one value of the element datatype. array datatype OntoDT_131075s OntoDT_131075 Scaled is a family of datatypes whose value spaces are subsets of the rational value space, each individual datatype having a fixed denominator, but the scaled datatypes possess the concept of approximate value. scaled datatype OntoDT_150012s OntoDT_150012 real is a family of datatypes which are computational approximations to the mathematical datatype comprising the “real numbers”. Specifically, each real datatype designates a collection of mathematical real values which are expressed to some finite precision and must be distinguishable to at least that precision. real datatype OntoDT_153781s OntoDT_153781 scaled factor OntoDT_158535s OntoDT_158535 An aggregate-value has the identifier uniqueness property if and only if no identifier (e.g., label, index) of the element datatype occurs more than once in the aggregate-value. The aggregate datatype has the identifier uniqueness property, if and only if all values in its value space do. aggregate-imposed identifier uniqueness OntoDT_176330s OntoDT_176330 non-aggregate generator OntoDT_184436s OntoDT_184436 identifier OntoDT_185557s OntoDT_185557 The computational model of a datatype may limit the degree to which values of the datatype can be distinguished. If every value in the value space of the conceptual datatype is distinguishable in the computational model from every other value in the value space, then the datatype is said to be exact. Certain mathematical datatypes having values which do not have finite representations are said to be approximate exactness OntoDT_191754s OntoDT_191754 A generated datatype is a datatype resulting from an application of a datatype generator. generated datatype OntoDT_194081s OntoDT_194081 A datatype is said to be numeric if its values are conceptually quantities (in some mathematical number system). A datatype whose values do not have this property is said to be non-numeric. numericalness OntoDT_205502s OntoDT_205502 An aggregate datatype is homogeneous, if and only if all components must belong to a single datatype. If different components may belong to different datatypes, the aggregate datatype is said to be heterogeneous. The component datatype of a homogeneous aggregate is also called the element datatype. homogenity OntoDT_207563s OntoDT_207563 vector datatype OntoDT_210187s OntoDT_210187 directed labeled graph datatype generator OntoDT_220858s OntoDT_220858 maximum-size OntoDT_233572s OntoDT_233572 discrete field component OntoDT_236485s OntoDT_236485 whose values constitutes a means of reference to values of another datatype, designated the element datatype. The values of a pointer datatype are atomic. pointer datatype OntoDT_245924s OntoDT_245924 tree datatype OntoDT_251157s OntoDT_251157 The size of an aggregate-value is the number of component values it contains. The size of the aggregate datatype is fixed, if and only if all values in its value space contain the same number of component values. The size is variable, if different values of the aggregate datatype may have different numbers of component values. Variability is the more general case; fixed-size is a constraint. agregate size OntoDT_261649s OntoDT_261649 An aggregate-value has the uniqueness property if and only if no value of the element datatype occurs more than once in the aggregate-value. The aggregate datatype has the uniqueness property, if and only if all values in its value space do. uniqueness OntoDT_267718s OntoDT_267718 real factor OntoDT_283020s OntoDT_283020 aggregate generator property OntoDT_293023s OntoDT_293023 index-type OntoDT_295799s OntoDT_295799 defined generator parameter 1 OntoDT_296536s OntoDT_296536 upper bound OntoDT_310738s OntoDT_310738 defined datatype OntoDT_318874s OntoDT_318874 A value space has the mathematical concept of cardinality: it may be finite, denumerably infinite (countable), or non-denumerably infinite (uncountable). A datatype is said to have the cardinality of its value space. In the computational model, there are three significant cases: ⎯ datatypes whose value spaces are finite, ⎯ datatypes whose value spaces are exact and denumerably infinite, ⎯ datatypes whose value spaces are approximate and therefore have a finite or denumerably infinite computational model, although the conceptual value space may be non-denumerably infinite. Every conceptually finite datatype is necessarily exact. No computational datatype is non-denumerably infinite. cardinality OntoDT_321211s OntoDT_321211 character is a family of datatypes whose value spaces are character-sets. character datatype OntoDT_329404s OntoDT_329404 defined generator OntoDT_334619s OntoDT_334619 enumerated-value identifier OntoDT_335173s OntoDT_335173 defined generator parameter-list OntoDT_339517s OntoDT_339517 non-directed labeled graph generator OntoDT_339518s OntoDT_339518 discrete base type OntoDT_344884s OntoDT_344884 select-item specification OntoDT_360708s OntoDT_360708 record of boolean datatype OntoDT_369036s OntoDT_369036 A datatype is said to be ordered if an order relation is defined on its value space. order OntoDT_369421s OntoDT_369421 date-time unit OntoDT_372249s OntoDT_372249 defined datatype parameter-list OntoDT_377271s OntoDT_377271 set of discrete datatype OntoDT_378476s OntoDT_378476 An aggregate datatype is a generated datatype, each of whose values is, in principle, made up of values of the parametric datatypes. The parametric datatypes of an aggregate datatype or its generator are also called component datatypes. synonim: structured datatype aggregate datatype OntoDT_379444s OntoDT_379444 enumerated is a family of datatypes, each of which comprises a finite number of distinguished values having an intrinsic order. synonim: discrete datatype enumerated datatype OntoDT_382564s OntoDT_382564 whose values is a single value from any of a set of alternative datatypes. The alternative datatypes of a choice datatype are logically distinguished by their correspondence to values of another datatype, called the tag datatype. choice datatype OntoDT_387093s OntoDT_387093 datatype property OntoDT_387565s OntoDT_387565 real field component 1 OntoDT_390995s OntoDT_390995 lower bound OntoDT_393702s OntoDT_393702 date-time radix OntoDT_395046s OntoDT_395046 boolean field component OntoDT_396145s OntoDT_396145 A datatype is said to be bounded above if it is ordered and there is a value U in the value space such that, for all values s in the value space, s ≤ U . The value U is then said to be an upper bound of the value space. Similarly, a datatype is said to be bounded below if it is ordered and there is a value L in the space such that, for all values s in the value space, L ≤ s . The value L is then said to be a lower bound of the value space. A datatype is said to be bounded if its value space has both an upper bound and a lower bound. boundedness OntoDT_436502s OntoDT_436502 A datatype generator is a conceptual operation on one or more datatypes which yields a datatype. A datatype generator operates on datatypes to generate a datatype, rather than on values to generate a value. Specifically, a datatype generator is the combination of: ⎯ a collection of criteria for the number and characteristics of the datatypes to be operated upon, ⎯ a construction procedure which, given a collection of datatypes meeting those criteria, creates a new value space from the value spaces of those datatypes, and ⎯ a collection of characterizing operations which attach to the resulting value space to complete the definition of a new datatype. The application of a datatype generator to a specific collection of datatypes meeting the criteria for the datatype generator forms a generated datatype. The generated datatype is sometimes called the resulting datatype, and the collection of datatypes to which the datatype generator was applied are called its parametric datatypes. ISO/IEC 11404:2007(E) synonim: datatype constructor generated datatype generator OntoDT_442100s OntoDT_442100 factor 1 OntoDT_447351s OntoDT_447351 size OntoDT_459594s OntoDT_459594 time is a family of datatypes whose values are points in time to various common resolutions: year, month, day, hour, minute, second, and fractions thereof. date and time datatype OntoDT_460533s OntoDT_460533 complex factor OntoDT_467794s OntoDT_467794 discrete-value identifier OntoDT_470848s OntoDT_470848 The components of an aggregate datatype may not all be required to have a valid value of the datatype, i.e., the actual value space of the datatype may include values for which some of the component values are unspecified. When a component of the datatype is required to have a valid value in order for the aggregate value to be a valid value of the datatype, the component is said to be a mandatory component. When a component of the datatype is not required to have a valid value in order for the aggregate value to be a valid value of the datatype, the component is said to be an optional component. component mandatoriness OntoDT_471356s OntoDT_471356 record of real datatype OntoDT_477213s OntoDT_477213 extended-value identifier OntoDT_487147s OntoDT_487147 Since this collection is unbounded, there are four formal methods used in the definition of the datatypes: ⎯ explicit specification of primitive datatypes, which have universal well-defined abstract notions, each independent of any other datatype. ⎯ implicit specification of generated datatypes, which are syntactically and in some ways semantically dependent on other datatypes used in their specification. Generated datatypes are specified implicitly by means of explicit specification of datatype generators, which themselves embody independent abstract notions. ⎯ specification of the means of datatype declaration, which permits the association of additional identifiers and refinements to primitive and generated datatypes and to datatype generators. ⎯ specification of the means of defining subtypes of the datatypes defined by any of the foregoing methods. set of distinct values, characterized by properties of those values, and by operations on those values ISO/IEC 11404:2007(E) datatype OntoDT_488636s OntoDT_488636 real base type 1 OntoDT_501513s OntoDT_501513 index upperbound OntoDT_521859s OntoDT_521859 record of primitives datatype OntoDT_523040s OntoDT_523040 value expression OntoDT_576464s OntoDT_576464 non-directed labeled graph datatype OntoDT_582224s OntoDT_582224 complex radix OntoDT_582642s OntoDT_582642 complex is a family of datatypes, each of which is a computational approximation to the mathematical datatype comprising the “complex numbers”. Specifically, each complex datatype designates a collection of mathematical complex values which are known to certain applications to some finite precision and must be distinguishable to at least that precision in those applications. complex datatype OntoDT_589006s OntoDT_589006 select-list OntoDT_591397s OntoDT_591397 labeled graph datatype OntoDT_595741s OntoDT_595741 record of discrete datatype OntoDT_596819s OntoDT_596819 sequence of discrete datatype OntoDT_598925s OntoDT_598925 class datatype OntoDT_608148s OntoDT_608148 state is a family of datatypes, each of which comprises a finite number of distinguished but unordered values. discrete datatype OntoDT_614962s OntoDT_614962 Aggregate datatypes are: ⎯ conceptually structured, having both the component datatypes and the access method specified, or ⎯ conceptually semi-structured, having either the component datatypes or the access method specified, but not both, or ⎯ conceptually unstructured, having neither the component datatype nor the access method specified. structurness OntoDT_621008s OntoDT_621008 extended-value-list OntoDT_645869s OntoDT_645869 DAG datatype OntoDT_648082s OntoDT_648082 whose values are ordered sequences of values from the element datatype. The ordering is imposed on the values and not intrinsic in the underlying datatype; the same value may occur more than once in a given sequence. sequence datatype OntoDT_658939s OntoDT_658939 Niladic operations yield values of the given datatype. niladic operation OntoDT_691902s OntoDT_691902 base type 1 OntoDT_698187s OntoDT_698187 index lowerbound OntoDT_699579s OntoDT_699579 bag datatype OntoDT_701140s OntoDT_701140 radix OntoDT_713630s OntoDT_713630 index-type list OntoDT_717333s OntoDT_717333 range OntoDT_721277s OntoDT_721277 whose values is an operation on values of other datatypes, designated the parameter datatypes. That is, a procedure datatype comprises the set of all operations on values of a particular collection of datatypes. All values of a procedure datatype are conceptually atomic. procedure datatype OntoDT_755846s OntoDT_755846 vector generator OntoDT_758099s OntoDT_758099 An aggregate datatype generator generates a datatype by ⎯ applying an algorithmic procedure to the value spaces of its component datatypes to yield the value space of the aggregate datatype, and ⎯ providing a set of characterizing operations specific to the generator. synonim: aggregate datatype constructor aggregate generator OntoDT_758650s OntoDT_758650 A datatype is said to be recursive if a value of the datatype can contain (or refer to) another value of the datatype. recursiveness OntoDT_775509s OntoDT_775509 node component OntoDT_776664s OntoDT_776664 Monadic operations map a value of the given datatype into a value of the given datatype or into a value of datatype Boolean. monadic operation OntoDT_776867s OntoDT_776867 character-set identifier OntoDT_814373s OntoDT_814373 whose value-space is the set of all subsets of the value space of the element datatype, with operations appropriate to the mathematical set. set datatype OntoDT_844136s OntoDT_844136 minimum-size OntoDT_856705s OntoDT_856705 real radix OntoDT_863955s OntoDT_863955 The set of characterising operations for a datatype comprises those operations on, or yielding values of, the datatype that distinguish this datatype from other datatypes having value spaces which are identical except possibly for substitution of symbols. characterizing operation OntoDT_869983s OntoDT_869983 A subtype is a datatype derived from an existing datatype, designated the base datatype, by restricting the value space to a subset of that of the base datatype whilst maintaining all characterizing operations. Subtypes are created by a kind of datatype generator which is unusual in that its only function is to define the relationship between the value spaces of the base datatype and the subtype. subtype generator OntoDT_877338s OntoDT_877338 non-aggregate datatype OntoDT_878284s OntoDT_878284 set of real datatype OntoDT_886531s OntoDT_886531 N-adic operations map ordered n-tuples of values, each of whichh is of a specified datatype, which may be the given datatype or a parametric datatype, into values of the given datatype or parametric datatype. n-adic operation OntoDT_888670s OntoDT_888670 The access method for an aggregate datatype is the property which determines how component values can be extracted from a given aggregate-value. access type OntoDT_903401s OntoDT_903401 edge component OntoDT_905914s OntoDT_905914 In every value space there is a notion of equality, for which the following rules hold: ⎯ for any two instances (a, b) of values from the value space, either a is equal to b, denoted a = b , or a is not equal to b, denoted a ≠ b ; ⎯ there is no pair of instances (a, b) of values from the value space such that both a = b and a ≠ b ; ⎯ for every value a from the value space, a = a ; ⎯ for any two instances (a, b) of values from the value space, a = b if and only if b = a ; ⎯ for any three instances (a, b, c) of values from the value space, if a = b and b = c , then a = c . On every datatype, the operation Equal is defined in terms of the equality property of the value space, by: ⎯ for any values a, b drawn from the value space, Equal(a,b) is true if a = b , and false otherwise. ISO/IEC 11404:2007 equality OntoDT_908515s OntoDT_908515 scaled radix OntoDT_925110s OntoDT_925110 attribute component OntoDT_950419s OntoDT_950419 whose values are heterogeneous aggregations of values of component datatypes, each aggregation having one value for each component datatype, keyed by a fixed field-identifier. synonim: tuple datatype record (tuple) datatype OntoDT_959638s OntoDT_959638 enumerated-value-list OntoDT_972766s OntoDT_972766 DAG datatype generator OntoDT_974622s OntoDT_974622 sequence of real datatype OntoDT_inst_293543s OntoDT_inst_293543 aggregate field component OntoDT_inst_507131s OntoDT_inst_507131 field identifier OntoDT_inst_621884s OntoDT_inst_621884 primitive field component OBI_0000069s OBI_0000069 http://purl.obofoundry.org/obo/obi.owl OBI_0000260s OBI_0000260 http://purl.obofoundry.org/obo/obi.owl plan OBI_0000587s OBI_0000587 http://purl.obofoundry.org/obo/obi.owl protocol_paricipant_role APOLLO_SV:00000008 A planned process that has specified output a software product and that involves the creation of source code. Mathias Brochhausen William R. Hogan http://en.wikipedia.org/wiki/Software_development A planned process resulting in a software product involving the creation of source code. software development APOLLO_SV:00000032 A measurement datum that is the output of counting. Mathias Brochhausen A measurement datum that is the output of counting. count APOLLO_SV:00000033 The planned process of finding the number of elements in a finite set of objects. Mathias Brochhausen http://en.wikipedia.org/wiki/Counting The planned process of finding the number of elements in a finite set of objects. counting APOLLO_SV:00000522 software source code version control repository A document that comprises at least one source code module and provenance data about who contributed the set of files making up the module(s), and optionally comprises also multiple versions of files with detailed change history about who committed files and when, a license for the software, readme files, documentation, executables, etc. William R. Hogan Refers to the stuff that lives on GitHub, not to GitHub or the git software on which it is based source code repository APOLLO_SV:00000524 process of compiling software A planned process that converts human-written or curated software into a machine-executable or interpretable set of instructions. William R. Hogan It's compiling "software" (scare quotes) and not "source code" because you can compile Java bytecode to machine code, and Java bytecode is not technically "source code". Compiling source code would be a subclass of this class (as would compiling Java bytecode, etc.). Source code can be automatically generated to some extent, but we're assuming humans still curate it minimally. Also, in the case of Java and its JVM, it's machine interpretable instructions, not directly executable. Ditto for other languages with intermediate form like Java byte code. compiling software APOLLO_SV:00000796 creating a data set A planned process that has a data set as its specified output. William R. Hogan data set creation dataset creation dataset creating BFO:0000001 entity Entity Julius Caesar Verdi’s Requiem the Second World War your body mass index BFO 2 Reference: In all areas of empirical inquiry we encounter general terms of two sorts. First are general terms which refer to universals or types:animaltuberculosissurgical procedurediseaseSecond, are general terms used to refer to groups of entities which instantiate a given universal but do not correspond to the extension of any subuniversal of that universal because there is nothing intrinsic to the entities in question by virtue of which they – and only they – are counted as belonging to the given group. Examples are: animal purchased by the Emperortuberculosis diagnosed on a Wednesdaysurgical procedure performed on a patient from Stockholmperson identified as candidate for clinical trial #2056-555person who is signatory of Form 656-PPVpainting by Leonardo da VinciSuch terms, which represent what are called ‘specializations’ in [81 Entity doesn't have a closure axiom because the subclasses don't necessarily exhaust all possibilites. For example Werner Ceusters 'portions of reality' include 4 sorts, entities (as BFO construes them), universals, configurations, and relations. It is an open question as to whether entities as construed in BFO will at some point also include these other portions of reality. See, for example, 'How to track absolutely everything' at http://www.referent-tracking.com/_RTU/papers/CeustersICbookRevised.pdf An entity is anything that exists or has existed or will exist. (axiom label in BFO2 Reference: [001-001]) entity Entity doesn't have a closure axiom because the subclasses don't necessarily exhaust all possibilites. For example Werner Ceusters 'portions of reality' include 4 sorts, entities (as BFO construes them), universals, configurations, and relations. It is an open question as to whether entities as construed in BFO will at some point also include these other portions of reality. See, for example, 'How to track absolutely everything' at http://www.referent-tracking.com/_RTU/papers/CeustersICbookRevised.pdf per discussion with Barry Smith An entity is anything that exists or has existed or will exist. (axiom label in BFO2 Reference: [001-001]) BFO:0000002 continuant Continuant An entity that exists in full at any time in which it exists at all, persists through time while maintaining its identity and has no temporal parts. BFO 2 Reference: Continuant entities are entities which can be sliced to yield parts only along the spatial dimension, yielding for example the parts of your table which we call its legs, its top, its nails. ‘My desk stretches from the window to the door. It has spatial parts, and can be sliced (in space) in two. With respect to time, however, a thing is a continuant.’ [60, p. 240 Continuant doesn't have a closure axiom because the subclasses don't necessarily exhaust all possibilites. For example, in an expansion involving bringing in some of Ceuster's other portions of reality, questions are raised as to whether universals are continuants A continuant is an entity that persists, endures, or continues to exist through time while maintaining its identity. (axiom label in BFO2 Reference: [008-002]) if b is a continuant and if, for some t, c has_continuant_part b at t, then c is a continuant. (axiom label in BFO2 Reference: [126-001]) if b is a continuant and if, for some t, cis continuant_part of b at t, then c is a continuant. (axiom label in BFO2 Reference: [009-002]) if b is a material entity, then there is some temporal interval (referred to below as a one-dimensional temporal region) during which b exists. (axiom label in BFO2 Reference: [011-002]) (forall (x y) (if (and (Continuant x) (exists (t) (continuantPartOfAt y x t))) (Continuant y))) // axiom label in BFO2 CLIF: [009-002] (forall (x y) (if (and (Continuant x) (exists (t) (hasContinuantPartOfAt y x t))) (Continuant y))) // axiom label in BFO2 CLIF: [126-001] (forall (x) (if (Continuant x) (Entity x))) // axiom label in BFO2 CLIF: [008-002] (forall (x) (if (Material Entity x) (exists (t) (and (TemporalRegion t) (existsAt x t))))) // axiom label in BFO2 CLIF: [011-002] continuant Continuant doesn't have a closure axiom because the subclasses don't necessarily exhaust all possibilites. For example, in an expansion involving bringing in some of Ceuster's other portions of reality, questions are raised as to whether universals are continuants A continuant is an entity that persists, endures, or continues to exist through time while maintaining its identity. (axiom label in BFO2 Reference: [008-002]) if b is a continuant and if, for some t, c has_continuant_part b at t, then c is a continuant. (axiom label in BFO2 Reference: [126-001]) if b is a continuant and if, for some t, cis continuant_part of b at t, then c is a continuant. (axiom label in BFO2 Reference: [009-002]) if b is a material entity, then there is some temporal interval (referred to below as a one-dimensional temporal region) during which b exists. (axiom label in BFO2 Reference: [011-002]) (forall (x y) (if (and (Continuant x) (exists (t) (continuantPartOfAt y x t))) (Continuant y))) // axiom label in BFO2 CLIF: [009-002] (forall (x y) (if (and (Continuant x) (exists (t) (hasContinuantPartOfAt y x t))) (Continuant y))) // axiom label in BFO2 CLIF: [126-001] (forall (x) (if (Continuant x) (Entity x))) // axiom label in BFO2 CLIF: [008-002] (forall (x) (if (Material Entity x) (exists (t) (and (TemporalRegion t) (existsAt x t))))) // axiom label in BFO2 CLIF: [011-002] BFO:0000003 occurrent Occurrent An entity that has temporal parts and that happens, unfolds or develops through time. BFO 2 Reference: every occurrent that is not a temporal or spatiotemporal region is s-dependent on some independent continuant that is not a spatial region BFO 2 Reference: s-dependence obtains between every process and its participants in the sense that, as a matter of necessity, this process could not have existed unless these or those participants existed also. A process may have a succession of participants at different phases of its unfolding. Thus there may be different players on the field at different times during the course of a football game; but the process which is the entire game s-depends_on all of these players nonetheless. Some temporal parts of this process will s-depend_on on only some of the players. Occurrent doesn't have a closure axiom because the subclasses don't necessarily exhaust all possibilites. An example would be the sum of a process and the process boundary of another process. Simons uses different terminology for relations of occurrents to regions: Denote the spatio-temporal location of a given occurrent e by 'spn[e]' and call this region its span. We may say an occurrent is at its span, in any larger region, and covers any smaller region. Now suppose we have fixed a frame of reference so that we can speak not merely of spatio-temporal but also of spatial regions (places) and temporal regions (times). The spread of an occurrent, (relative to a frame of reference) is the space it exactly occupies, and its spell is likewise the time it exactly occupies. We write 'spr[e]' and `spl[e]' respectively for the spread and spell of e, omitting mention of the frame. An occurrent is an entity that unfolds itself in time or it is the instantaneous boundary of such an entity (for example a beginning or an ending) or it is a temporal or spatiotemporal region which such an entity occupies_temporal_region or occupies_spatiotemporal_region. (axiom label in BFO2 Reference: [077-002]) Every occurrent occupies_spatiotemporal_region some spatiotemporal region. (axiom label in BFO2 Reference: [108-001]) b is an occurrent entity iff b is an entity that has temporal parts. (axiom label in BFO2 Reference: [079-001]) (forall (x) (if (Occurrent x) (exists (r) (and (SpatioTemporalRegion r) (occupiesSpatioTemporalRegion x r))))) // axiom label in BFO2 CLIF: [108-001] (forall (x) (iff (Occurrent x) (and (Entity x) (exists (y) (temporalPartOf y x))))) // axiom label in BFO2 CLIF: [079-001] occurrent Occurrent doesn't have a closure axiom because the subclasses don't necessarily exhaust all possibilites. An example would be the sum of a process and the process boundary of another process. per discussion with Barry Smith Simons uses different terminology for relations of occurrents to regions: Denote the spatio-temporal location of a given occurrent e by 'spn[e]' and call this region its span. We may say an occurrent is at its span, in any larger region, and covers any smaller region. Now suppose we have fixed a frame of reference so that we can speak not merely of spatio-temporal but also of spatial regions (places) and temporal regions (times). The spread of an occurrent, (relative to a frame of reference) is the space it exactly occupies, and its spell is likewise the time it exactly occupies. We write 'spr[e]' and `spl[e]' respectively for the spread and spell of e, omitting mention of the frame. An occurrent is an entity that unfolds itself in time or it is the instantaneous boundary of such an entity (for example a beginning or an ending) or it is a temporal or spatiotemporal region which such an entity occupies_temporal_region or occupies_spatiotemporal_region. (axiom label in BFO2 Reference: [077-002]) Every occurrent occupies_spatiotemporal_region some spatiotemporal region. (axiom label in BFO2 Reference: [108-001]) b is an occurrent entity iff b is an entity that has temporal parts. (axiom label in BFO2 Reference: [079-001]) (forall (x) (if (Occurrent x) (exists (r) (and (SpatioTemporalRegion r) (occupiesSpatioTemporalRegion x r))))) // axiom label in BFO2 CLIF: [108-001] (forall (x) (iff (Occurrent x) (and (Entity x) (exists (y) (temporalPartOf y x))))) // axiom label in BFO2 CLIF: [079-001] BFO:0000004 ic IndependentContinuant a chair a heart a leg a molecule a spatial region an atom an orchestra. an organism the bottom right portion of a human torso the interior of your mouth b is an independent continuant = Def. b is a continuant which is such that there is no c and no t such that b s-depends_on c at t. (axiom label in BFO2 Reference: [017-002]) For any independent continuant b and any time t there is some spatial region r such that b is located_in r at t. (axiom label in BFO2 Reference: [134-001]) For every independent continuant b and time t during the region of time spanned by its life, there are entities which s-depends_on b during t. (axiom label in BFO2 Reference: [018-002]) (forall (x t) (if (IndependentContinuant x) (exists (r) (and (SpatialRegion r) (locatedInAt x r t))))) // axiom label in BFO2 CLIF: [134-001] (forall (x t) (if (and (IndependentContinuant x) (existsAt x t)) (exists (y) (and (Entity y) (specificallyDependsOnAt y x t))))) // axiom label in BFO2 CLIF: [018-002] (iff (IndependentContinuant a) (and (Continuant a) (not (exists (b t) (specificallyDependsOnAt a b t))))) // axiom label in BFO2 CLIF: [017-002] independent continuant b is an independent continuant = Def. b is a continuant which is such that there is no c and no t such that b s-depends_on c at t. (axiom label in BFO2 Reference: [017-002]) For any independent continuant b and any time t there is some spatial region r such that b is located_in r at t. (axiom label in BFO2 Reference: [134-001]) For every independent continuant b and time t during the region of time spanned by its life, there are entities which s-depends_on b during t. (axiom label in BFO2 Reference: [018-002]) (forall (x t) (if (IndependentContinuant x) (exists (r) (and (SpatialRegion r) (locatedInAt x r t))))) // axiom label in BFO2 CLIF: [134-001] (forall (x t) (if (and (IndependentContinuant x) (existsAt x t)) (exists (y) (and (Entity y) (specificallyDependsOnAt y x t))))) // axiom label in BFO2 CLIF: [018-002] (iff (IndependentContinuant a) (and (Continuant a) (not (exists (b t) (specificallyDependsOnAt a b t))))) // axiom label in BFO2 CLIF: [017-002] BFO:0000006 s-region SpatialRegion BFO 2 Reference: Spatial regions do not participate in processes. Spatial region doesn't have a closure axiom because the subclasses don't exhaust all possibilites. An example would be the union of a spatial point and a spatial line that doesn't overlap the point, or two spatial lines that intersect at a single point. In both cases the resultant spatial region is neither 0-dimensional, 1-dimensional, 2-dimensional, or 3-dimensional. A spatial region is a continuant entity that is a continuant_part_of spaceR as defined relative to some frame R. (axiom label in BFO2 Reference: [035-001]) All continuant parts of spatial regions are spatial regions. (axiom label in BFO2 Reference: [036-001]) (forall (x y t) (if (and (SpatialRegion x) (continuantPartOfAt y x t)) (SpatialRegion y))) // axiom label in BFO2 CLIF: [036-001] (forall (x) (if (SpatialRegion x) (Continuant x))) // axiom label in BFO2 CLIF: [035-001] spatial region Spatial region doesn't have a closure axiom because the subclasses don't exhaust all possibilites. An example would be the union of a spatial point and a spatial line that doesn't overlap the point, or two spatial lines that intersect at a single point. In both cases the resultant spatial region is neither 0-dimensional, 1-dimensional, 2-dimensional, or 3-dimensional. per discussion with Barry Smith A spatial region is a continuant entity that is a continuant_part_of spaceR as defined relative to some frame R. (axiom label in BFO2 Reference: [035-001]) All continuant parts of spatial regions are spatial regions. (axiom label in BFO2 Reference: [036-001]) (forall (x y t) (if (and (SpatialRegion x) (continuantPartOfAt y x t)) (SpatialRegion y))) // axiom label in BFO2 CLIF: [036-001] (forall (x) (if (SpatialRegion x) (Continuant x))) // axiom label in BFO2 CLIF: [035-001] BFO:0000008 t-region TemporalRegion Temporal region doesn't have a closure axiom because the subclasses don't exhaust all possibilites. An example would be the mereological sum of a temporal instant and a temporal interval that doesn't overlap the instant. In this case the resultant temporal region is neither 0-dimensional nor 1-dimensional A temporal region is an occurrent entity that is part of time as defined relative to some reference frame. (axiom label in BFO2 Reference: [100-001]) All parts of temporal regions are temporal regions. (axiom label in BFO2 Reference: [101-001]) Every temporal region t is such that t occupies_temporal_region t. (axiom label in BFO2 Reference: [119-002]) (forall (r) (if (TemporalRegion r) (occupiesTemporalRegion r r))) // axiom label in BFO2 CLIF: [119-002] (forall (x y) (if (and (TemporalRegion x) (occurrentPartOf y x)) (TemporalRegion y))) // axiom label in BFO2 CLIF: [101-001] (forall (x) (if (TemporalRegion x) (Occurrent x))) // axiom label in BFO2 CLIF: [100-001] temporal region Temporal region doesn't have a closure axiom because the subclasses don't exhaust all possibilites. An example would be the mereological sum of a temporal instant and a temporal interval that doesn't overlap the instant. In this case the resultant temporal region is neither 0-dimensional nor 1-dimensional per discussion with Barry Smith A temporal region is an occurrent entity that is part of time as defined relative to some reference frame. (axiom label in BFO2 Reference: [100-001]) All parts of temporal regions are temporal regions. (axiom label in BFO2 Reference: [101-001]) Every temporal region t is such that t occupies_temporal_region t. (axiom label in BFO2 Reference: [119-002]) (forall (r) (if (TemporalRegion r) (occupiesTemporalRegion r r))) // axiom label in BFO2 CLIF: [119-002] (forall (x y) (if (and (TemporalRegion x) (occurrentPartOf y x)) (TemporalRegion y))) // axiom label in BFO2 CLIF: [101-001] (forall (x) (if (TemporalRegion x) (Occurrent x))) // axiom label in BFO2 CLIF: [100-001] BFO:0000009 2d-s-region TwoDimensionalSpatialRegion an infinitely thin plane in space. the surface of a sphere-shaped part of space A two-dimensional spatial region is a spatial region that is of two dimensions. (axiom label in BFO2 Reference: [039-001]) (forall (x) (if (TwoDimensionalSpatialRegion x) (SpatialRegion x))) // axiom label in BFO2 CLIF: [039-001] two-dimensional spatial region A two-dimensional spatial region is a spatial region that is of two dimensions. (axiom label in BFO2 Reference: [039-001]) (forall (x) (if (TwoDimensionalSpatialRegion x) (SpatialRegion x))) // axiom label in BFO2 CLIF: [039-001] BFO:0000011 st-region SpatiotemporalRegion the spatiotemporal region occupied by a human life the spatiotemporal region occupied by a process of cellular meiosis. the spatiotemporal region occupied by the development of a cancer tumor A spatiotemporal region is an occurrent entity that is part of spacetime. (axiom label in BFO2 Reference: [095-001]) All parts of spatiotemporal regions are spatiotemporal regions. (axiom label in BFO2 Reference: [096-001]) Each spatiotemporal region at any time t projects_onto some spatial region at t. (axiom label in BFO2 Reference: [099-001]) Each spatiotemporal region projects_onto some temporal region. (axiom label in BFO2 Reference: [098-001]) Every spatiotemporal region occupies_spatiotemporal_region itself. Every spatiotemporal region s is such that s occupies_spatiotemporal_region s. (axiom label in BFO2 Reference: [107-002]) (forall (r) (if (SpatioTemporalRegion r) (occupiesSpatioTemporalRegion r r))) // axiom label in BFO2 CLIF: [107-002] (forall (x t) (if (SpatioTemporalRegion x) (exists (y) (and (SpatialRegion y) (spatiallyProjectsOntoAt x y t))))) // axiom label in BFO2 CLIF: [099-001] (forall (x y) (if (and (SpatioTemporalRegion x) (occurrentPartOf y x)) (SpatioTemporalRegion y))) // axiom label in BFO2 CLIF: [096-001] (forall (x) (if (SpatioTemporalRegion x) (Occurrent x))) // axiom label in BFO2 CLIF: [095-001] (forall (x) (if (SpatioTemporalRegion x) (exists (y) (and (TemporalRegion y) (temporallyProjectsOnto x y))))) // axiom label in BFO2 CLIF: [098-001] spatiotemporal region A spatiotemporal region is an occurrent entity that is part of spacetime. (axiom label in BFO2 Reference: [095-001]) All parts of spatiotemporal regions are spatiotemporal regions. (axiom label in BFO2 Reference: [096-001]) Each spatiotemporal region at any time t projects_onto some spatial region at t. (axiom label in BFO2 Reference: [099-001]) Each spatiotemporal region projects_onto some temporal region. (axiom label in BFO2 Reference: [098-001]) Every spatiotemporal region s is such that s occupies_spatiotemporal_region s. (axiom label in BFO2 Reference: [107-002]) (forall (r) (if (SpatioTemporalRegion r) (occupiesSpatioTemporalRegion r r))) // axiom label in BFO2 CLIF: [107-002] (forall (x t) (if (SpatioTemporalRegion x) (exists (y) (and (SpatialRegion y) (spatiallyProjectsOntoAt x y t))))) // axiom label in BFO2 CLIF: [099-001] (forall (x y) (if (and (SpatioTemporalRegion x) (occurrentPartOf y x)) (SpatioTemporalRegion y))) // axiom label in BFO2 CLIF: [096-001] (forall (x) (if (SpatioTemporalRegion x) (Occurrent x))) // axiom label in BFO2 CLIF: [095-001] (forall (x) (if (SpatioTemporalRegion x) (exists (y) (and (TemporalRegion y) (temporallyProjectsOnto x y))))) // axiom label in BFO2 CLIF: [098-001] BFO:0000015 process Process a process of cell-division, \ a beating of the heart a process of meiosis a process of sleeping the course of a disease the flight of a bird the life of an organism your process of aging. p is a process = Def. p is an occurrent that has temporal proper parts and for some time t, p s-depends_on some material entity at t. (axiom label in BFO2 Reference: [083-003]) BFO 2 Reference: The realm of occurrents is less pervasively marked by the presence of natural units than is the case in the realm of independent continuants. Thus there is here no counterpart of ‘object’. In BFO 1.0 ‘process’ served as such a counterpart. In BFO 2.0 ‘process’ is, rather, the occurrent counterpart of ‘material entity’. Those natural – as contrasted with engineered, which here means: deliberately executed – units which do exist in the realm of occurrents are typically either parasitic on the existence of natural units on the continuant side, or they are fiat in nature. Thus we can count lives; we can count football games; we can count chemical reactions performed in experiments or in chemical manufacturing. We cannot count the processes taking place, for instance, in an episode of insect mating behavior.Even where natural units are identifiable, for example cycles in a cyclical process such as the beating of a heart or an organism’s sleep/wake cycle, the processes in question form a sequence with no discontinuities (temporal gaps) of the sort that we find for instance where billiard balls or zebrafish or planets are separated by clear spatial gaps. Lives of organisms are process units, but they too unfold in a continuous series from other, prior processes such as fertilization, and they unfold in turn in continuous series of post-life processes such as post-mortem decay. Clear examples of boundaries of processes are almost always of the fiat sort (midnight, a time of death as declared in an operating theater or on a death certificate, the initiation of a state of war) (iff (Process a) (and (Occurrent a) (exists (b) (properTemporalPartOf b a)) (exists (c t) (and (MaterialEntity c) (specificallyDependsOnAt a c t))))) // axiom label in BFO2 CLIF: [083-003] process p is a process = Def. p is an occurrent that has temporal proper parts and for some time t, p s-depends_on some material entity at t. (axiom label in BFO2 Reference: [083-003]) (iff (Process a) (and (Occurrent a) (exists (b) (properTemporalPartOf b a)) (exists (c t) (and (MaterialEntity c) (specificallyDependsOnAt a c t))))) // axiom label in BFO2 CLIF: [083-003] BFO:0000016 disposition Disposition an atom of element X has the disposition to decay to an atom of element Y certain people have a predisposition to colon cancer children are innately disposed to categorize objects in certain ways. the cell wall is disposed to filter chemicals in endocytosis and exocytosis BFO 2 Reference: Dispositions exist along a strength continuum. Weaker forms of disposition are realized in only a fraction of triggering cases. These forms occur in a significant number of cases of a similar type. b is a disposition means: b is a realizable entity & b’s bearer is some material entity & b is such that if it ceases to exist, then its bearer is physically changed, & b’s realization occurs when and because this bearer is in some special physical circumstances, & this realization occurs in virtue of the bearer’s physical make-up. (axiom label in BFO2 Reference: [062-002]) If b is a realizable entity then for all t at which b exists, b s-depends_on some material entity at t. (axiom label in BFO2 Reference: [063-002]) (forall (x t) (if (and (RealizableEntity x) (existsAt x t)) (exists (y) (and (MaterialEntity y) (specificallyDepends x y t))))) // axiom label in BFO2 CLIF: [063-002] (forall (x) (if (Disposition x) (and (RealizableEntity x) (exists (y) (and (MaterialEntity y) (bearerOfAt x y t)))))) // axiom label in BFO2 CLIF: [062-002] disposition b is a disposition means: b is a realizable entity & b’s bearer is some material entity & b is such that if it ceases to exist, then its bearer is physically changed, & b’s realization occurs when and because this bearer is in some special physical circumstances, & this realization occurs in virtue of the bearer’s physical make-up. (axiom label in BFO2 Reference: [062-002]) If b is a realizable entity then for all t at which b exists, b s-depends_on some material entity at t. (axiom label in BFO2 Reference: [063-002]) (forall (x t) (if (and (RealizableEntity x) (existsAt x t)) (exists (y) (and (MaterialEntity y) (specificallyDepends x y t))))) // axiom label in BFO2 CLIF: [063-002] (forall (x) (if (Disposition x) (and (RealizableEntity x) (exists (y) (and (MaterialEntity y) (bearerOfAt x y t)))))) // axiom label in BFO2 CLIF: [062-002] RealizableEntities RealizableEntity BFO:0000017 realizable RealizableEntity the disposition of this piece of metal to conduct electricity. the disposition of your blood to coagulate the function of your reproductive organs the role of being a doctor the role of this boundary to delineate where Utah and Colorado meet A specifically dependent continuant that inheres in continuant entities and are not exhibited in full at every time in which it inheres in an entity or group of entities. The exhibition or actualization of a realizable entity is a particular manifestation, functioning or process that occurs under certain circumstances. To say that b is a realizable entity is to say that b is a specifically dependent continuant that inheres in some independent continuant which is not a spatial region and is of a type instances of which are realized in processes of a correlated type. (axiom label in BFO2 Reference: [058-002]) All realizable dependent continuants have independent continuants that are not spatial regions as their bearers. (axiom label in BFO2 Reference: [060-002]) (forall (x t) (if (RealizableEntity x) (exists (y) (and (IndependentContinuant y) (not (SpatialRegion y)) (bearerOfAt y x t))))) // axiom label in BFO2 CLIF: [060-002] (forall (x) (if (RealizableEntity x) (and (SpecificallyDependentContinuant x) (exists (y) (and (IndependentContinuant y) (not (SpatialRegion y)) (inheresIn x y)))))) // axiom label in BFO2 CLIF: [058-002] realizable entity To say that b is a realizable entity is to say that b is a specifically dependent continuant that inheres in some independent continuant which is not a spatial region and is of a type instances of which are realized in processes of a correlated type. (axiom label in BFO2 Reference: [058-002]) All realizable dependent continuants have independent continuants that are not spatial regions as their bearers. (axiom label in BFO2 Reference: [060-002]) (forall (x t) (if (RealizableEntity x) (exists (y) (and (IndependentContinuant y) (not (SpatialRegion y)) (bearerOfAt y x t))))) // axiom label in BFO2 CLIF: [060-002] (forall (x) (if (RealizableEntity x) (and (SpecificallyDependentContinuant x) (exists (y) (and (IndependentContinuant y) (not (SpatialRegion y)) (inheresIn x y)))))) // axiom label in BFO2 CLIF: [058-002] BFO:0000018 0d-s-region ZeroDimensionalSpatialRegion A zero-dimensional spatial region is a point in space. (axiom label in BFO2 Reference: [037-001]) (forall (x) (if (ZeroDimensionalSpatialRegion x) (SpatialRegion x))) // axiom label in BFO2 CLIF: [037-001] zero-dimensional spatial region A zero-dimensional spatial region is a point in space. (axiom label in BFO2 Reference: [037-001]) (forall (x) (if (ZeroDimensionalSpatialRegion x) (SpatialRegion x))) // axiom label in BFO2 CLIF: [037-001] OntoDM_419544s Qualities OntoDM_419544 Quality BFO:0000019 quality Quality the ambient temperature of this portion of air the color of a tomato the length of the circumference of your waist the mass of this piece of gold. the shape of your nose the shape of your nostril a quality is a specifically dependent continuant that, in contrast to roles and dispositions, does not require any further process in order to be realized. (axiom label in BFO2 Reference: [055-001]) If an entity is a quality at any time that it exists, then it is a quality at every time that it exists. (axiom label in BFO2 Reference: [105-001]) (forall (x) (if (Quality x) (SpecificallyDependentContinuant x))) // axiom label in BFO2 CLIF: [055-001] (forall (x) (if (exists (t) (and (existsAt x t) (Quality x))) (forall (t_1) (if (existsAt x t_1) (Quality x))))) // axiom label in BFO2 CLIF: [105-001] quality quality a quality is a specifically dependent continuant that, in contrast to roles and dispositions, does not require any further process in order to be realized. (axiom label in BFO2 Reference: [055-001]) If an entity is a quality at any time that it exists, then it is a quality at every time that it exists. (axiom label in BFO2 Reference: [105-001]) (forall (x) (if (Quality x) (SpecificallyDependentContinuant x))) // axiom label in BFO2 CLIF: [055-001] (forall (x) (if (exists (t) (and (existsAt x t) (Quality x))) (forall (t_1) (if (existsAt x t_1) (Quality x))))) // axiom label in BFO2 CLIF: [105-001] BFO:0000020 sdc SpecificallyDependentContinuant Reciprocal specifically dependent continuants: the function of this key to open this lock and the mutually dependent disposition of this lock: to be opened by this key of one-sided specifically dependent continuants: the mass of this tomato of relational dependent continuants (multiple bearers): John’s love for Mary, the ownership relation between John and this statue, the relation of authority between John and his subordinates. the disposition of this fish to decay the function of this heart: to pump blood the mutual dependence of proton donors and acceptors in chemical reactions [79 the mutual dependence of the role predator and the role prey as played by two organisms in a given interaction the pink color of a medium rare piece of grilled filet mignon at its center the role of being a doctor the shape of this hole. the smell of this portion of mozzarella b is a specifically dependent continuant = Def. b is a continuant & there is some independent continuant c which is not a spatial region and which is such that b s-depends_on c at every time t during the course of b’s existence. (axiom label in BFO2 Reference: [050-003]) Specifically dependent continuant doesn't have a closure axiom because the subclasses don't necessarily exhaust all possibilites. We're not sure what else will develop here, but for example there are questions such as what are promises, obligation, etc. (iff (SpecificallyDependentContinuant a) (and (Continuant a) (forall (t) (if (existsAt a t) (exists (b) (and (IndependentContinuant b) (not (SpatialRegion b)) (specificallyDependsOnAt a b t))))))) // axiom label in BFO2 CLIF: [050-003] specifically dependent continuant b is a specifically dependent continuant = Def. b is a continuant & there is some independent continuant c which is not a spatial region and which is such that b s-depends_on c at every time t during the course of b’s existence. (axiom label in BFO2 Reference: [050-003]) Specifically dependent continuant doesn't have a closure axiom because the subclasses don't necessarily exhaust all possibilites. We're not sure what else will develop here, but for example there are questions such as what are promises, obligation, etc. per discussion with Barry Smith (iff (SpecificallyDependentContinuant a) (and (Continuant a) (forall (t) (if (existsAt a t) (exists (b) (and (IndependentContinuant b) (not (SpatialRegion b)) (specificallyDependsOnAt a b t))))))) // axiom label in BFO2 CLIF: [050-003] Roles Role BFO:0000023 role Role John’s role of husband to Mary is dependent on Mary’s role of wife to John, and both are dependent on the object aggregate comprising John and Mary as member parts joined together through the relational quality of being married. the priest role the role of a boundary to demarcate two neighboring administrative territories the role of a building in serving as a military target the role of a stone in marking a property boundary the role of subject in a clinical trial the student role A realizable entity the manifestation of which brings about some result or end that is not essential to a continuant in virtue of the kind of thing that it is but that can be served or participated in by that kind of continuant in some kinds of natural, social or institutional contexts. BFO 2 Reference: One major family of examples of non-rigid universals involves roles, and ontologies developed for corresponding administrative purposes may consist entirely of representatives of entities of this sort. Thus ‘professor’, defined as follows,b instance_of professor at t =Def. there is some c, c instance_of professor role & c inheres_in b at t.denotes a non-rigid universal and so also do ‘nurse’, ‘student’, ‘colonel’, ‘taxpayer’, and so forth. (These terms are all, in the jargon of philosophy, phase sortals.) By using role terms in definitions, we can create a BFO conformant treatment of such entities drawing on the fact that, while an instance of professor may be simultaneously an instance of trade union member, no instance of the type professor role is also (at any time) an instance of the type trade union member role (any more than any instance of the type color is at any time an instance of the type length).If an ontology of employment positions should be defined in terms of roles following the above pattern, this enables the ontology to do justice to the fact that individuals instantiate the corresponding universals – professor, sergeant, nurse – only during certain phases in their lives. b is a role means: b is a realizable entity & b exists because there is some single bearer that is in some special physical, social, or institutional set of circumstances in which this bearer does not have to be& b is not such that, if it ceases to exist, then the physical make-up of the bearer is thereby changed. (axiom label in BFO2 Reference: [061-001]) (forall (x) (if (Role x) (RealizableEntity x))) // axiom label in BFO2 CLIF: [061-001] role b is a role means: b is a realizable entity & b exists because there is some single bearer that is in some special physical, social, or institutional set of circumstances in which this bearer does not have to be& b is not such that, if it ceases to exist, then the physical make-up of the bearer is thereby changed. (axiom label in BFO2 Reference: [061-001]) (forall (x) (if (Role x) (RealizableEntity x))) // axiom label in BFO2 CLIF: [061-001] BFO:0000024 fiat-object-part FiatObjectPart or with divisions drawn by cognitive subjects for practical reasons, such as the division of a cake (before slicing) into (what will become) slices (and thus member parts of an object aggregate). However, this does not mean that fiat object parts are dependent for their existence on divisions or delineations effected by cognitive subjects. If, for example, it is correct to conceive geological layers of the Earth as fiat object parts of the Earth, then even though these layers were first delineated in recent times, still existed long before such delineation and what holds of these layers (for example that the oldest layers are also the lowest layers) did not begin to hold because of our acts of delineation.Treatment of material entity in BFOExamples viewed by some as problematic cases for the trichotomy of fiat object part, object, and object aggregate include: a mussel on (and attached to) a rock, a slime mold, a pizza, a cloud, a galaxy, a railway train with engine and multiple carriages, a clonal stand of quaking aspen, a bacterial community (biofilm), a broken femur. Note that, as Aristotle already clearly recognized, such problematic cases – which lie at or near the penumbra of instances defined by the categories in question – need not invalidate these categories. The existence of grey objects does not prove that there are not objects which are black and objects which are white; the existence of mules does not prove that there are not objects which are donkeys and objects which are horses. It does, however, show that the examples in question need to be addressed carefully in order to show how they can be fitted into the proposed scheme, for example by recognizing additional subdivisions [29 the FMA:regional parts of an intact human body. the Western hemisphere of the Earth the division of the brain into regions the division of the planet into hemispheres the dorsal and ventral surfaces of the body the upper and lower lobes of the left lung BFO 2 Reference: Most examples of fiat object parts are associated with theoretically drawn divisions b is a fiat object part = Def. b is a material entity which is such that for all times t, if b exists at t then there is some object c such that b proper continuant_part of c at t and c is demarcated from the remainder of c by a two-dimensional continuant fiat boundary. (axiom label in BFO2 Reference: [027-004]) (forall (x) (if (FiatObjectPart x) (and (MaterialEntity x) (forall (t) (if (existsAt x t) (exists (y) (and (Object y) (properContinuantPartOfAt x y t)))))))) // axiom label in BFO2 CLIF: [027-004] fiat object part b is a fiat object part = Def. b is a material entity which is such that for all times t, if b exists at t then there is some object c such that b proper continuant_part of c at t and c is demarcated from the remainder of c by a two-dimensional continuant fiat boundary. (axiom label in BFO2 Reference: [027-004]) (forall (x) (if (FiatObjectPart x) (and (MaterialEntity x) (forall (t) (if (existsAt x t) (exists (y) (and (Object y) (properContinuantPartOfAt x y t)))))))) // axiom label in BFO2 CLIF: [027-004] BFO:0000026 1d-s-region OneDimensionalSpatialRegion an edge of a cube-shaped portion of space. A one-dimensional spatial region is a line or aggregate of lines stretching from one point in space to another. (axiom label in BFO2 Reference: [038-001]) (forall (x) (if (OneDimensionalSpatialRegion x) (SpatialRegion x))) // axiom label in BFO2 CLIF: [038-001] one-dimensional spatial region A one-dimensional spatial region is a line or aggregate of lines stretching from one point in space to another. (axiom label in BFO2 Reference: [038-001]) (forall (x) (if (OneDimensionalSpatialRegion x) (SpatialRegion x))) // axiom label in BFO2 CLIF: [038-001] BFO:0000027 object-aggregate ObjectAggregate a collection of cells in a blood biobank. a swarm of bees is an aggregate of members who are linked together through natural bonds a symphony orchestra an organization is an aggregate whose member parts have roles of specific types (for example in a jazz band, a chess club, a football team) defined by fiat: the aggregate of members of an organization defined through physical attachment: the aggregate of atoms in a lump of granite defined through physical containment: the aggregate of molecules of carbon dioxide in a sealed container defined via attributive delimitations such as: the patients in this hospital the aggregate of bearings in a constant velocity axle joint the aggregate of blood cells in your body the nitrogen atoms in the atmosphere the restaurants in Palo Alto your collection of Meissen ceramic plates. An entity a is an object aggregate if and only if there is a mutually exhaustive and pairwise disjoint partition of a into objects BFO 2 Reference: object aggregates may gain and lose parts while remaining numerically identical (one and the same individual) over time. This holds both for aggregates whose membership is determined naturally (the aggregate of cells in your body) and aggregates determined by fiat (a baseball team, a congressional committee). ISBN:978-3-938793-98-5pp124-158#Thomas Bittner and Barry Smith, 'A Theory of Granular Partitions', in K. Munn and B. Smith (eds.), Applied Ontology: An Introduction, Frankfurt/Lancaster: ontos, 2008, 125-158. b is an object aggregate means: b is a material entity consisting exactly of a plurality of objects as member_parts at all times at which b exists. (axiom label in BFO2 Reference: [025-004]) (forall (x) (if (ObjectAggregate x) (and (MaterialEntity x) (forall (t) (if (existsAt x t) (exists (y z) (and (Object y) (Object z) (memberPartOfAt y x t) (memberPartOfAt z x t) (not (= y z)))))) (not (exists (w t_1) (and (memberPartOfAt w x t_1) (not (Object w)))))))) // axiom label in BFO2 CLIF: [025-004] object aggregate An entity a is an object aggregate if and only if there is a mutually exhaustive and pairwise disjoint partition of a into objects An entity a is an object aggregate if and only if there is a mutually exhaustive and pairwise disjoint partition of a into objects ISBN:978-3-938793-98-5pp124-158#Thomas Bittner and Barry Smith, 'A Theory of Granular Partitions', in K. Munn and B. Smith (eds.), Applied Ontology: An Introduction, Frankfurt/Lancaster: ontos, 2008, 125-158. b is an object aggregate means: b is a material entity consisting exactly of a plurality of objects as member_parts at all times at which b exists. (axiom label in BFO2 Reference: [025-004]) (forall (x) (if (ObjectAggregate x) (and (MaterialEntity x) (forall (t) (if (existsAt x t) (exists (y z) (and (Object y) (Object z) (memberPartOfAt y x t) (memberPartOfAt z x t) (not (= y z)))))) (not (exists (w t_1) (and (memberPartOfAt w x t_1) (not (Object w)))))))) // axiom label in BFO2 CLIF: [025-004] BFO:0000028 3d-s-region ThreeDimensionalSpatialRegion a cube-shaped region of space a sphere-shaped region of space, A three-dimensional spatial region is a spatial region that is of three dimensions. (axiom label in BFO2 Reference: [040-001]) (forall (x) (if (ThreeDimensionalSpatialRegion x) (SpatialRegion x))) // axiom label in BFO2 CLIF: [040-001] three-dimensional spatial region A three-dimensional spatial region is a spatial region that is of three dimensions. (axiom label in BFO2 Reference: [040-001]) (forall (x) (if (ThreeDimensionalSpatialRegion x) (SpatialRegion x))) // axiom label in BFO2 CLIF: [040-001] BFO:0000029 site Site Manhattan Canyon) a hole in the interior of a portion of cheese a rabbit hole an air traffic control region defined in the airspace above an airport the Grand Canyon the Piazza San Marco the cockpit of an aircraft the hold of a ship the interior of a kangaroo pouch the interior of the trunk of your car the interior of your bedroom the interior of your office the interior of your refrigerator the lumen of your gut your left nostril (a fiat part – the opening – of your left nasal cavity) b is a site means: b is a three-dimensional immaterial entity that is (partially or wholly) bounded by a material entity or it is a three-dimensional immaterial part thereof. (axiom label in BFO2 Reference: [034-002]) (forall (x) (if (Site x) (ImmaterialEntity x))) // axiom label in BFO2 CLIF: [034-002] site b is a site means: b is a three-dimensional immaterial entity that is (partially or wholly) bounded by a material entity or it is a three-dimensional immaterial part thereof. (axiom label in BFO2 Reference: [034-002]) (forall (x) (if (Site x) (ImmaterialEntity x))) // axiom label in BFO2 CLIF: [034-002] BFO:0000030 object Object atom cell cells and organisms engineered artifacts grain of sand molecule organelle organism planet solid portions of matter star BFO 2 Reference: BFO rests on the presupposition that at multiple micro-, meso- and macroscopic scales reality exhibits certain stable, spatially separated or separable material units, combined or combinable into aggregates of various sorts (for example organisms into what are called ‘populations’). Such units play a central role in almost all domains of natural science from particle physics to cosmology. Many scientific laws govern the units in question, employing general terms (such as ‘molecule’ or ‘planet’) referring to the types and subtypes of units, and also to the types and subtypes of the processes through which such units develop and interact. The division of reality into such natural units is at the heart of biological science, as also is the fact that these units may form higher-level units (as cells form multicellular organisms) and that they may also form aggregates of units, for example as cells form portions of tissue and organs form families, herds, breeds, species, and so on. At the same time, the division of certain portions of reality into engineered units (manufactured artifacts) is the basis of modern industrial technology, which rests on the distributed mass production of engineered parts through division of labor and on their assembly into larger, compound units such as cars and laptops. The division of portions of reality into units is one starting point for the phenomenon of counting. BFO 2 Reference: Each object is such that there are entities of which we can assert unproblematically that they lie in its interior, and other entities of which we can assert unproblematically that they lie in its exterior. This may not be so for entities lying at or near the boundary between the interior and exterior. This means that two objects – for example the two cells depicted in Figure 3 – may be such that there are material entities crossing their boundaries which belong determinately to neither cell. Something similar obtains in certain cases of conjoined twins (see below). BFO 2 Reference: To say that b is causally unified means: b is a material entity which is such that its material parts are tied together in such a way that, in environments typical for entities of the type in question,if c, a continuant part of b that is in the interior of b at t, is larger than a certain threshold size (which will be determined differently from case to case, depending on factors such as porosity of external cover) and is moved in space to be at t at a location on the exterior of the spatial region that had been occupied by b at t, then either b’s other parts will be moved in coordinated fashion or b will be damaged (be affected, for example, by breakage or tearing) in the interval between t and t.causal changes in one part of b can have consequences for other parts of b without the mediation of any entity that lies on the exterior of b. Material entities with no proper material parts would satisfy these conditions trivially. Candidate examples of types of causal unity for material entities of more complex sorts are as follows (this is not intended to be an exhaustive list):CU1: Causal unity via physical coveringHere the parts in the interior of the unified entity are combined together causally through a common membrane or other physical covering\. The latter points outwards toward and may serve a protective function in relation to what lies on the exterior of the entity [13, 47 BFO 2 Reference: an object is a maximal causally unified material entity BFO 2 Reference: ‘objects’ are sometimes referred to as ‘grains’ [74 b is an object means: b is a material entity which manifests causal unity of one or other of the types CUn listed above & is of a type (a material universal) instances of which are maximal relative to this criterion of causal unity. (axiom label in BFO2 Reference: [024-001]) object b is an object means: b is a material entity which manifests causal unity of one or other of the types CUn listed above & is of a type (a material universal) instances of which are maximal relative to this criterion of causal unity. (axiom label in BFO2 Reference: [024-001]) BFO:0000031 gdc GenericallyDependentContinuant The entries in your database are patterns instantiated as quality instances in your hard drive. The database itself is an aggregate of such patterns. When you create the database you create a particular instance of the generically dependent continuant type database. Each entry in the database is an instance of the generically dependent continuant type IAO: information content entity. the pdf file on your laptop, the pdf file that is a copy thereof on my laptop the sequence of this protein molecule; the sequence that is a copy thereof in that protein molecule. b is a generically dependent continuant = Def. b is a continuant that g-depends_on one or more other entities. (axiom label in BFO2 Reference: [074-001]) BFO (iff (GenericallyDependentContinuant a) (and (Continuant a) (exists (b t) (genericallyDependsOnAt a b t)))) // axiom label in BFO2 CLIF: [074-001] generically dependent continuant b is a generically dependent continuant = Def. b is a continuant that g-depends_on one or more other entities. (axiom label in BFO2 Reference: [074-001]) (iff (GenericallyDependentContinuant a) (and (Continuant a) (exists (b t) (genericallyDependsOnAt a b t)))) // axiom label in BFO2 CLIF: [074-001] BFO:0000034 function Function the function of a hammer to drive in nails the function of a heart pacemaker to regulate the beating of a heart through electricity the function of amylase in saliva to break down starch into sugar BFO 2 Reference: In the past, we have distinguished two varieties of function, artifactual function and biological function. These are not asserted subtypes of BFO:function however, since the same function – for example: to pump, to transport – can exist both in artifacts and in biological entities. The asserted subtypes of function that would be needed in order to yield a separate monoheirarchy are not artifactual function, biological function, etc., but rather transporting function, pumping function, etc. A function is a disposition that exists in virtue of the bearer’s physical make-up and this physical make-up is something the bearer possesses because it came into being, either through evolution (in the case of natural biological entities) or through intentional design (in the case of artifacts), in order to realize processes of a certain sort. (axiom label in BFO2 Reference: [064-001]) (forall (x) (if (Function x) (Disposition x))) // axiom label in BFO2 CLIF: [064-001] function A function is a disposition that exists in virtue of the bearer’s physical make-up and this physical make-up is something the bearer possesses because it came into being, either through evolution (in the case of natural biological entities) or through intentional design (in the case of artifacts), in order to realize processes of a certain sort. (axiom label in BFO2 Reference: [064-001]) (forall (x) (if (Function x) (Disposition x))) // axiom label in BFO2 CLIF: [064-001] BFO:0000035 p-boundary ProcessBoundary the boundary between the 2nd and 3rd year of your life. p is a process boundary =Def. p is a temporal part of a process & p has no proper temporal parts. (axiom label in BFO2 Reference: [084-001]) Every process boundary occupies_temporal_region a zero-dimensional temporal region. (axiom label in BFO2 Reference: [085-002]) (forall (x) (if (ProcessBoundary x) (exists (y) (and (ZeroDimensionalTemporalRegion y) (occupiesTemporalRegion x y))))) // axiom label in BFO2 CLIF: [085-002] (iff (ProcessBoundary a) (exists (p) (and (Process p) (temporalPartOf a p) (not (exists (b) (properTemporalPartOf b a)))))) // axiom label in BFO2 CLIF: [084-001] process boundary p is a process boundary =Def. p is a temporal part of a process & p has no proper temporal parts. (axiom label in BFO2 Reference: [084-001]) Every process boundary occupies_temporal_region a zero-dimensional temporal region. (axiom label in BFO2 Reference: [085-002]) (forall (x) (if (ProcessBoundary x) (exists (y) (and (ZeroDimensionalTemporalRegion y) (occupiesTemporalRegion x y))))) // axiom label in BFO2 CLIF: [085-002] (iff (ProcessBoundary a) (exists (p) (and (Process p) (temporalPartOf a p) (not (exists (b) (properTemporalPartOf b a)))))) // axiom label in BFO2 CLIF: [084-001] BFO:0000038 1d-t-region OneDimensionalTemporalRegion the temporal region during which a process occurs. BFO 2 Reference: A temporal interval is a special kind of one-dimensional temporal region, namely one that is self-connected (is without gaps or breaks). A one-dimensional temporal region is a temporal region that is extended. (axiom label in BFO2 Reference: [103-001]) (forall (x) (if (OneDimensionalTemporalRegion x) (TemporalRegion x))) // axiom label in BFO2 CLIF: [103-001] one-dimensional temporal region A one-dimensional temporal region is a temporal region that is extended. (axiom label in BFO2 Reference: [103-001]) (forall (x) (if (OneDimensionalTemporalRegion x) (TemporalRegion x))) // axiom label in BFO2 CLIF: [103-001] BFO:0000040 material MaterialEntity a flame a forest fire a human being a hurricane a photon a puff of smoke a sea wave a tornado an aggregate of human beings. an energy wave an epidemic the undetached arm of a human being An independent continuant that is spatially extended whose identity is independent of that of other entities and can be maintained through time. BFO 2 Reference: Material entities (continuants) can preserve their identity even while gaining and losing material parts. Continuants are contrasted with occurrents, which unfold themselves in successive temporal parts or phases [60 BFO 2 Reference: Object, Fiat Object Part and Object Aggregate are not intended to be exhaustive of Material Entity. Users are invited to propose new subcategories of Material Entity. BFO 2 Reference: ‘Matter’ is intended to encompass both mass and energy (we will address the ontological treatment of portions of energy in a later version of BFO). A portion of matter is anything that includes elementary particles among its proper or improper parts: quarks and leptons, including electrons, as the smallest particles thus far discovered; baryons (including protons and neutrons) at a higher level of granularity; atoms and molecules at still higher levels, forming the cells, organs, organisms and other material entities studied by biologists, the portions of rock studied by geologists, the fossils studied by paleontologists, and so on.Material entities are three-dimensional entities (entities extended in three spatial dimensions), as contrasted with the processes in which they participate, which are four-dimensional entities (entities extended also along the dimension of time).According to the FMA, material entities may have immaterial entities as parts – including the entities identified below as sites; for example the interior (or ‘lumen’) of your small intestine is a part of your body. BFO 2.0 embodies a decision to follow the FMA here. A material entity is an independent continuant that has some portion of matter as proper or improper continuant part. (axiom label in BFO2 Reference: [019-002]) Every entity which has a material entity as continuant part is a material entity. (axiom label in BFO2 Reference: [020-002]) every entity of which a material entity is continuant part is also a material entity. (axiom label in BFO2 Reference: [021-002]) (forall (x) (if (MaterialEntity x) (IndependentContinuant x))) // axiom label in BFO2 CLIF: [019-002] (forall (x) (if (and (Entity x) (exists (y t) (and (MaterialEntity y) (continuantPartOfAt x y t)))) (MaterialEntity x))) // axiom label in BFO2 CLIF: [021-002] (forall (x) (if (and (Entity x) (exists (y t) (and (MaterialEntity y) (continuantPartOfAt y x t)))) (MaterialEntity x))) // axiom label in BFO2 CLIF: [020-002] material entity A material entity is an independent continuant that has some portion of matter as proper or improper continuant part. (axiom label in BFO2 Reference: [019-002]) Every entity which has a material entity as continuant part is a material entity. (axiom label in BFO2 Reference: [020-002]) every entity of which a material entity is continuant part is also a material entity. (axiom label in BFO2 Reference: [021-002]) (forall (x) (if (MaterialEntity x) (IndependentContinuant x))) // axiom label in BFO2 CLIF: [019-002] (forall (x) (if (and (Entity x) (exists (y t) (and (MaterialEntity y) (continuantPartOfAt x y t)))) (MaterialEntity x))) // axiom label in BFO2 CLIF: [021-002] (forall (x) (if (and (Entity x) (exists (y t) (and (MaterialEntity y) (continuantPartOfAt y x t)))) (MaterialEntity x))) // axiom label in BFO2 CLIF: [020-002] BFO:0000140 cf-boundary ContinuantFiatBoundary b is a continuant fiat boundary = Def. b is an immaterial entity that is of zero, one or two dimensions and does not include a spatial region as part. (axiom label in BFO2 Reference: [029-001]) BFO 2 Reference: In BFO 1.1 the assumption was made that the external surface of a material entity such as a cell could be treated as if it were a boundary in the mathematical sense. The new document propounds the view that when we talk about external surfaces of material objects in this way then we are talking about something fiat. To be dealt with in a future version: fiat boundaries at different levels of granularity.More generally, the focus in discussion of boundaries in BFO 2.0 is now on fiat boundaries, which means: boundaries for which there is no assumption that they coincide with physical discontinuities. The ontology of boundaries becomes more closely allied with the ontology of regions. BFO 2 Reference: a continuant fiat boundary is a boundary of some material entity (for example: the plane separating the Northern and Southern hemispheres; the North Pole), or it is a boundary of some immaterial entity (for example of some portion of airspace). Three basic kinds of continuant fiat boundary can be distinguished (together with various combination kinds [29 Continuant fiat boundary doesn't have a closure axiom because the subclasses don't necessarily exhaust all possibilites. An example would be the mereological sum of two-dimensional continuant fiat boundary and a one dimensional continuant fiat boundary that doesn't overlap it. The situation is analogous to temporal and spatial regions. Every continuant fiat boundary is located at some spatial region at every time at which it exists (iff (ContinuantFiatBoundary a) (and (ImmaterialEntity a) (exists (b) (and (or (ZeroDimensionalSpatialRegion b) (OneDimensionalSpatialRegion b) (TwoDimensionalSpatialRegion b)) (forall (t) (locatedInAt a b t)))) (not (exists (c t) (and (SpatialRegion c) (continuantPartOfAt c a t)))))) // axiom label in BFO2 CLIF: [029-001] continuant fiat boundary b is a continuant fiat boundary = Def. b is an immaterial entity that is of zero, one or two dimensions and does not include a spatial region as part. (axiom label in BFO2 Reference: [029-001]) Continuant fiat boundary doesn't have a closure axiom because the subclasses don't necessarily exhaust all possibilites. An example would be the mereological sum of two-dimensional continuant fiat boundary and a one dimensional continuant fiat boundary that doesn't overlap it. The situation is analogous to temporal and spatial regions. (iff (ContinuantFiatBoundary a) (and (ImmaterialEntity a) (exists (b) (and (or (ZeroDimensionalSpatialRegion b) (OneDimensionalSpatialRegion b) (TwoDimensionalSpatialRegion b)) (forall (t) (locatedInAt a b t)))) (not (exists (c t) (and (SpatialRegion c) (continuantPartOfAt c a t)))))) // axiom label in BFO2 CLIF: [029-001] BFO:0000141 immaterial ImmaterialEntity BFO 2 Reference: Immaterial entities are divided into two subgroups:boundaries and sites, which bound, or are demarcated in relation, to material entities, and which can thus change location, shape and size and as their material hosts move or change shape or size (for example: your nasal passage; the hold of a ship; the boundary of Wales (which moves with the rotation of the Earth) [38, 7, 10 immaterial entity BFO:0000142 1d-cf-boundary OneDimensionalContinuantFiatBoundary The Equator all geopolitical boundaries all lines of latitude and longitude the line separating the outer surface of the mucosa of the lower lip from the outer surface of the skin of the chin. the median sulcus of your tongue a one-dimensional continuant fiat boundary is a continuous fiat line whose location is defined in relation to some material entity. (axiom label in BFO2 Reference: [032-001]) (iff (OneDimensionalContinuantFiatBoundary a) (and (ContinuantFiatBoundary a) (exists (b) (and (OneDimensionalSpatialRegion b) (forall (t) (locatedInAt a b t)))))) // axiom label in BFO2 CLIF: [032-001] one-dimensional continuant fiat boundary a one-dimensional continuant fiat boundary is a continuous fiat line whose location is defined in relation to some material entity. (axiom label in BFO2 Reference: [032-001]) (iff (OneDimensionalContinuantFiatBoundary a) (and (ContinuantFiatBoundary a) (exists (b) (and (OneDimensionalSpatialRegion b) (forall (t) (locatedInAt a b t)))))) // axiom label in BFO2 CLIF: [032-001] BFO:0000144 process-profile ProcessProfile On a somewhat higher level of complexity are what we shall call rate process profiles, which are the targets of selective abstraction focused not on determinate quality magnitudes plotted over time, but rather on certain ratios between these magnitudes and elapsed times. A speed process profile, for example, is represented by a graph plotting against time the ratio of distance covered per unit of time. Since rates may change, and since such changes, too, may have rates of change, we have to deal here with a hierarchy of process profile universals at successive levels One important sub-family of rate process profiles is illustrated by the beat or frequency profiles of cyclical processes, illustrated by the 60 beats per minute beating process of John’s heart, or the 120 beats per minute drumming process involved in one of John’s performances in a rock band, and so on. Each such process includes what we shall call a beat process profile instance as part, a subtype of rate process profile in which the salient ratio is not distance covered but rather number of beat cycles per unit of time. Each beat process profile instance instantiates the determinable universal beat process profile. But it also instantiates multiple more specialized universals at lower levels of generality, selected from rate process profilebeat process profileregular beat process profile3 bpm beat process profile4 bpm beat process profileirregular beat process profileincreasing beat process profileand so on.In the case of a regular beat process profile, a rate can be assigned in the simplest possible fashion by dividing the number of cycles by the length of the temporal region occupied by the beating process profile as a whole. Irregular process profiles of this sort, for example as identified in the clinic, or in the readings on an aircraft instrument panel, are often of diagnostic significance. The simplest type of process profiles are what we shall call ‘quality process profiles’, which are the process profiles which serve as the foci of the sort of selective abstraction that is involved when measurements are made of changes in single qualities, as illustrated, for example, by process profiles of mass, temperature, aortic pressure, and so on. b is a process_profile =Def. there is some process c such that b process_profile_of c (axiom label in BFO2 Reference: [093-002]) b process_profile_of c holds when b proper_occurrent_part_of c& there is some proper_occurrent_part d of c which has no parts in common with b & is mutually dependent on b& is such that b, c and d occupy the same temporal region (axiom label in BFO2 Reference: [094-005]) (forall (x y) (if (processProfileOf x y) (and (properContinuantPartOf x y) (exists (z t) (and (properOccurrentPartOf z y) (TemporalRegion t) (occupiesSpatioTemporalRegion x t) (occupiesSpatioTemporalRegion y t) (occupiesSpatioTemporalRegion z t) (not (exists (w) (and (occurrentPartOf w x) (occurrentPartOf w z))))))))) // axiom label in BFO2 CLIF: [094-005] (iff (ProcessProfile a) (exists (b) (and (Process b) (processProfileOf a b)))) // axiom label in BFO2 CLIF: [093-002] process profile b is a process_profile =Def. there is some process c such that b process_profile_of c (axiom label in BFO2 Reference: [093-002]) b process_profile_of c holds when b proper_occurrent_part_of c& there is some proper_occurrent_part d of c which has no parts in common with b & is mutually dependent on b& is such that b, c and d occupy the same temporal region (axiom label in BFO2 Reference: [094-005]) (forall (x y) (if (processProfileOf x y) (and (properContinuantPartOf x y) (exists (z t) (and (properOccurrentPartOf z y) (TemporalRegion t) (occupiesSpatioTemporalRegion x t) (occupiesSpatioTemporalRegion y t) (occupiesSpatioTemporalRegion z t) (not (exists (w) (and (occurrentPartOf w x) (occurrentPartOf w z))))))))) // axiom label in BFO2 CLIF: [094-005] (iff (ProcessProfile a) (exists (b) (and (Process b) (processProfileOf a b)))) // axiom label in BFO2 CLIF: [093-002] BFO:0000145 r-quality RelationalQuality John’s role of husband to Mary is dependent on Mary’s role of wife to John, and both are dependent on the object aggregate comprising John and Mary as member parts joined together through the relational quality of being married. a marriage bond, an instance of requited love, an obligation between one person and another. b is a relational quality = Def. for some independent continuants c, d and for some time t: b quality_of c at t & b quality_of d at t. (axiom label in BFO2 Reference: [057-001]) (iff (RelationalQuality a) (exists (b c t) (and (IndependentContinuant b) (IndependentContinuant c) (qualityOfAt a b t) (qualityOfAt a c t)))) // axiom label in BFO2 CLIF: [057-001] relational quality b is a relational quality = Def. for some independent continuants c, d and for some time t: b quality_of c at t & b quality_of d at t. (axiom label in BFO2 Reference: [057-001]) (iff (RelationalQuality a) (exists (b c t) (and (IndependentContinuant b) (IndependentContinuant c) (qualityOfAt a b t) (qualityOfAt a c t)))) // axiom label in BFO2 CLIF: [057-001] BFO:0000146 2d-cf-boundary TwoDimensionalContinuantFiatBoundary a two-dimensional continuant fiat boundary (surface) is a self-connected fiat surface whose location is defined in relation to some material entity. (axiom label in BFO2 Reference: [033-001]) (iff (TwoDimensionalContinuantFiatBoundary a) (and (ContinuantFiatBoundary a) (exists (b) (and (TwoDimensionalSpatialRegion b) (forall (t) (locatedInAt a b t)))))) // axiom label in BFO2 CLIF: [033-001] two-dimensional continuant fiat boundary a two-dimensional continuant fiat boundary (surface) is a self-connected fiat surface whose location is defined in relation to some material entity. (axiom label in BFO2 Reference: [033-001]) (iff (TwoDimensionalContinuantFiatBoundary a) (and (ContinuantFiatBoundary a) (exists (b) (and (TwoDimensionalSpatialRegion b) (forall (t) (locatedInAt a b t)))))) // axiom label in BFO2 CLIF: [033-001] BFO:0000147 0d-cf-boundary ZeroDimensionalContinuantFiatBoundary the geographic North Pole the point of origin of some spatial coordinate system. the quadripoint where the boundaries of Colorado, Utah, New Mexico, and Arizona meet zero dimension continuant fiat boundaries are not spatial points. Considering the example 'the quadripoint where the boundaries of Colorado, Utah, New Mexico, and Arizona meet' : There are many frames in which that point is zooming through many points in space. Whereas, no matter what the frame, the quadripoint is always in the same relation to the boundaries of Colorado, Utah, New Mexico, and Arizona. a zero-dimensional continuant fiat boundary is a fiat point whose location is defined in relation to some material entity. (axiom label in BFO2 Reference: [031-001]) (iff (ZeroDimensionalContinuantFiatBoundary a) (and (ContinuantFiatBoundary a) (exists (b) (and (ZeroDimensionalSpatialRegion b) (forall (t) (locatedInAt a b t)))))) // axiom label in BFO2 CLIF: [031-001] zero-dimensional continuant fiat boundary zero dimension continuant fiat boundaries are not spatial points. Considering the example 'the quadripoint where the boundaries of Colorado, Utah, New Mexico, and Arizona meet' : There are many frames in which that point is zooming through many points in space. Whereas, no matter what the frame, the quadripoint is always in the same relation to the boundaries of Colorado, Utah, New Mexico, and Arizona. requested by Melanie Courtot a zero-dimensional continuant fiat boundary is a fiat point whose location is defined in relation to some material entity. (axiom label in BFO2 Reference: [031-001]) (iff (ZeroDimensionalContinuantFiatBoundary a) (and (ContinuantFiatBoundary a) (exists (b) (and (ZeroDimensionalSpatialRegion b) (forall (t) (locatedInAt a b t)))))) // axiom label in BFO2 CLIF: [031-001] BFO:0000148 0d-t-region ZeroDimensionalTemporalRegion a temporal region that is occupied by a process boundary right now the moment at which a child is born the moment at which a finger is detached in an industrial accident the moment of death. temporal instant. A zero-dimensional temporal region is a temporal region that is without extent. (axiom label in BFO2 Reference: [102-001]) (forall (x) (if (ZeroDimensionalTemporalRegion x) (TemporalRegion x))) // axiom label in BFO2 CLIF: [102-001] zero-dimensional temporal region A zero-dimensional temporal region is a temporal region that is without extent. (axiom label in BFO2 Reference: [102-001]) (forall (x) (if (ZeroDimensionalTemporalRegion x) (TemporalRegion x))) // axiom label in BFO2 CLIF: [102-001] BFO:0000182 history History A history is a process that is the sum of the totality of processes taking place in the spatiotemporal region occupied by a material entity or site, including processes on the surface of the entity or within the cavities to which it serves as host. (axiom label in BFO2 Reference: [138-001]) history A history is a process that is the sum of the totality of processes taking place in the spatiotemporal region occupied by a material entity or site, including processes on the surface of the entity or within the cavities to which it serves as host. (axiom label in BFO2 Reference: [138-001]) IAO:0000001 conditional specification A directive information entity that specifies what should happen if the trigger condition is fulfilled. PlanAndPlannedProcess Branch OBI branch derived OBI_0000349 conditional specification IAO:0000003 measurement unit label Examples of measurement unit labels are liters, inches, weight per volume. A measurement unit label is as a label that is part of a scalar measurement datum and denotes a unit of measure. 2009-03-16: provenance: a term measurement unit was proposed for OBI (OBI_0000176) , edited by Chris Stoeckert and Cristian Cocos, and subsequently moved to IAO where the objective for which the original term was defined was satisfied with the definition of this, different, term. 2009-03-16: review of this term done during during the OBI workshop winter 2009 and the current definition was considered acceptable for use in OBI. If there is a need to modify this definition please notify OBI. PERSON: Alan Ruttenberg PERSON: Melanie Courtot measurement unit label IAO_0000005s IAO_0000005 IAO:0000005 http://purl.obofoundry.org/obo/iao.owl objective specification In the protocol of a ChIP assay the objective specification says to identify protein and DNA interaction. A directive information entity that describes an intended process endpoint. When part of a plan specification the concretization is realized in a planned process in which the bearer tries to effect the world so that the process endpoint is achieved. 2009-03-16: original definition when imported from OBI read: "objective is an non realizable information entity which can serve as that proper part of a plan towards which the realization of the plan is directed." 2014-03-31: In the example of usage ("In the protocol of a ChIP assay the objective specification says to identify protein and DNA interaction") there is a protocol which is the ChIP assay protocol. In addition to being concretized on paper, the protocol can be concretized as a realizable entity, such as a plan that inheres in a person. The objective specification is the part that says that some protein and DNA interactions are identified. This is a specification of a process endpoint: the boundary in the process before which they are not identified and after which they are. During the realization of the plan, the goal is to get to the point of having the interactions, and participants in the realization of the plan try to do that. Answers the question, why did you do this experiment? PERSON: Alan Ruttenberg PERSON: Barry Smith PERSON: Bjoern Peters PERSON: Jennifer Fostel goal specification OBI Plan and Planned Process/Roles Branch OBI_0000217 objective specification IAO:0000006 narrative object Examples of narrative objects are reports, journal articles, and patents submission. A narrative object is an information content entity that is a set of propositions. 2009-08-10 Alan Ruttenberg: Larry Hunter suggests that this be obsoleted and replaced by 'textual entity' and 'figure'. Alan restored as there are OBI dependencies and this merits further discussion agree - DENRIE. Issue(alan) do we only mean text? What about a story told by mime. Does music count? (no) what about an oral report. Regarding definition, saying it is a set of propositions means we loose the idea that wording matters. Maybe adjust saying a narrative object has some relationshop to a set of propositions person:Chris Stoeckert OBI_0000013 group:OBI narrative object IAO:0000007 Pour the contents of flask 1 into flask 2 A directive information entity that describes an action the bearer will take. Alan Ruttenberg OBI Plan and Planned Process branch action specification IAO:0000008 obsolete_artifact true IAO_0000009s IAO_0000009 IAO:0000009 datum label A label is a symbol that is part of some other datum and is used to either partially define the denotation of that datum or to provide a means for identifying the datum as a member of the set of data with the same label http://www.golovchenko.org/cgi-bin/wnsearch?q=label#4n GROUP: IAO 9/22/11 BP: changed the rdfs:label for this class from 'label' to 'datum label' to convey that this class is not intended to cover all kinds of labels (stickers, radiolabels, etc.), and not even all kind of textual labels, but rather the kind of labels occuring in a datum. IAO datum label label IAO_0000010s IAO_0000010 IAO:0000010 software Software is a plan specification composed of a series of instructions that can be interpreted by or directly executed by a processing unit. see sourceforge tracker discussion at http://sourceforge.net/tracker/index.php?func=detail&aid=1958818&group_id=177891&atid=886178 PERSON: Alan Ruttenberg PERSON: Bjoern Peters PERSON: Chris Stoeckert PERSON: Melanie Courtot GROUP: OBI software IAO:0000012 obsolete_digital entity A digital entity is an information entity which is a collection of bits that can be interpreted by a computer. Two digital entities are the same if they are bitwise identical. 3/22/2009 Alan Ruttenberg, obsoleted per http://groups.google.com/group/information-ontology/browse_thread/thread/789ad4b7708d5cf4 Superclass was 'digitial quality' person:Chris Stoeckert OBI_0000261 group:OBI obsolete2_digital entity true IAO:0000013 journal article Examples are articles published in the journals, Nature and Science. The content can often be cited by reference to a paper based encoding, e.g. Authors, Title of article, Journal name, date or year of publication, volume and page number. A report that is published in a journal. PERSON: Alan Ruttenberg PERSON: Chris Stoeckert OBI_0000159 group:OBI journal article IAO:0000015 information carrier In the case of a printed paperback novel the physicality of the ink and of the paper form part of the information bearer. The qualities of appearing black and having a certain pattern for the ink and appearing white for the paper form part of the information carrier in this case. A quality of an information bearer that imparts the information content 12/15/09: There is a concern that some ways that carry information may be processes rather than qualities, such as in a 'delayed wave carrier'. 2014-03-10: We are not certain that all information carriers are qualities. There was a discussion of dropping it. PERSON: Alan Ruttenberg Smith, Ceusters, Ruttenberg, 2000 years of philosophy information carrier IAO:0000017 model number A model number is an information content entity specifically borne by catalogs, design specifications, advertising materials, inventory systems and similar that is about manufactured objects of the same class. The model number is an alternative term for the class. The manufactered objects may or may not also bear the model number. Model numbers can be encoded in a variety of other information objects, such as bar codes, numerals, or patterns of dots. manufactered items may have more than one model number, sometimes by rebranding, or because companies are sold and the products issued new model numbers Person: Alan Ruttenberg model number IAO:0000018 obsolete_material_entity true IAO:0000019 binary digital entity MS Word document, ZIP file, DICOM file, JPEG file A binary digital entity is a digital entity that is encoded in a way that is not easily human readable and that contains other than text characters. 3/22/2009 Alan Ruttenberg, obsoleted per http://groups.google.com/group/information-ontology/browse_thread/thread/789ad4b7708d5cf4 Superclass was 'digital entity' digital_entity person:Chris Stoeckert OBI_0000244 group:OBI obsolete2_binary digital entity true IAO:0000024 The length of a ruler. a unit of measure is the quality of some material entity compared to which another quality is some multiple of. Alan Ruttenberg Smith, Ceusters, Ruttenberg, 2000 years of philosophy obsolete_unit of measure true IAO_0000025s IAO_0000025 IAO:0000025 programming language R, Perl, Java A language in which source code is written that is intended to be executed/run by a software interpreter. Programming languages are ways to write instructions that specify what to do, and sometimes, how to do it. person:Alan Ruttenberg person:Chris Stoeckert OBI_0000058 group:OBI programming language IAO_0000027s IAO_0000027 IAO:0000027 data item Data items include counts of things, analyte concentrations, and statistical summaries. An information content entity that is intended to be a truthful statement about something (modulo, e.g., measurement precision or other systematic errors) and is constructed/acquired by a method which reliably tends to produce (approximately) truthful statements. 2/2/2009 Alan and Bjoern discussing FACS run output data. This is a data item because it is about the cell population. Each element records an event and is typically further composed a set of measurment data items that record the fluorescent intensity stimulated by one of the lasers. 2009-03-16: data item deliberatly ambiguous: we merged data set and datum to be one entity, not knowing how to define singular versus plural. So data item is more general than datum. 2009-03-16: removed datum as alternative term as datum specifically refers to singular form, and is thus not an exact synonym. 2014-03-31: See discussion at http://odontomachus.wordpress.com/2014/03/30/aboutness-objects-propositions/ JAR: datum -- well, this will be very tricky to define, but maybe some information-like stuff that might be put into a computer and that is meant, by someone, to denote and/or to be interpreted by some process... I would include lists, tables, sentences... I think I might defer to Barry, or to Brian Cantwell Smith JAR: A data item is an approximately justified approximately true approximate belief PERSON: Alan Ruttenberg PERSON: Chris Stoeckert PERSON: Jonathan Rees data data item IAO_0000028s IAO_0000028 IAO:0000028 symbol a serial number such as "12324X" a stop sign a written proper name such as "OBI" An information content entity that is a mark(s) or character(s) used as a conventional representation of another entity. 20091104, MC: this needs work and will most probably change 2014-03-31: We would like to have a deeper analysis of 'mark' and 'sign' in the future (see https://github.com/information-artifact-ontology/IAO/issues/154). PERSON: James A. Overton PERSON: Jonathan Rees based on Oxford English Dictionary symbol IAO:0000029 numeral A symbol that denotes a number. PERSON: Jonathan Rees numeral IAO_0000030s IAO_0000030 IAO:0000030 http://purl.obofoundry.org/obo/iao.owl information content entity Examples of information content entites include journal articles, data, graphical layouts, and graphs. A generically dependent continuant that is about some thing. 2014-03-10: The use of "thing" is intended to be general enough to include universals and configurations (see https://groups.google.com/d/msg/information-ontology/GBxvYZCk1oc/-L6B5fSBBTQJ). information_content_entity 'is_encoded_in' some digital_entity in obi before split (040907). information_content_entity 'is_encoded_in' some physical_document in obi before split (040907). Previous. An information content entity is a non-realizable information entity that 'is encoded in' some digital or physical entity. PERSON: Chris Stoeckert OBI_0000142 IAO information content entity IAO:0000031 integer numeral A numeral that denotes an integer PERSON: Jonathan Rees integer numeral 1 1 IAO:0000032 10 feet. 3 ml. A scalar measurement datum is a measurement datum that is composed of two parts, numerals and a unit label. 2009-03-16: we decided to keep datum singular in scalar measurement datum, as in this case we explicitly refer to the singular form Would write this as: has_part some 'measurement unit label' and has_part some numeral and has_part exactly 2, except for the fact that this won't let us take advantage of OWL reasoning over the numbers. Instead use has measurment value property to represent the same. Use has measurement unit label (subproperty of has_part) so we can easily say that there is only one of them. PERSON: Alan Ruttenberg PERSON: Melanie Courtot scalar measurement datum IAO_0000033s IAO_0000033 IAO:0000033 http://purl.obofoundry.org/obo/iao.owl An information content entity whose concretizations indicate to their bearer how to realize them in a process. 2009-03-16: provenance: a term realizable information entity was proposed for OBI (OBI_0000337) , edited by the PlanAndPlannedProcess branch. Original definition was "is the specification of a process that can be concretized and realized by an actor" with alternative term "instruction".It has been subsequently moved to IAO where the objective for which the original term was defined was satisfied with the definitionof this, different, term. 2013-05-30 Alan Ruttenberg: What differentiates a directive information entity from an information concretization is that it can have concretizations that are either qualities or realizable entities. The concretizations that are realizable entities are created when an individual chooses to take up the direction, i.e. has the intention to (try to) realize it. 8/6/2009 Alan Ruttenberg: Changed label from "information entity about a realizable" after discussions at ICBO Werner pushed back on calling it realizable information entity as it isn't realizable. However this name isn't right either. An example would be a recipe. The realizable entity would be a plan, but the information entity isn't about the plan, it, once concretized, *is* the plan. -Alan PERSON: Alan Ruttenberg PERSON: Bjoern Peters directive information entity directive information entity IAO:0000034 time trigger PlanAndPlannedProcess Branch time trigger IAO:0000035 obsolete_study interpretation A study interpretation is a textual entity about the implications of a study result. Examples include discussion of whether a hypothesis is false, whether the study failed to address the hypothesis, and whether the study results have led to new hypotheses 2009-03-16: definition was "A conclusion is a narrative object which can be published in a paper summerizing and interpreting a protocol application." 2009-03-16: work has been done on this term during during the OBI workshop winter 2009 and the current definition was considered acceptable for use in OBI. If there is a need to modify this definition please notify OBI. The obsoleting of narrative object required a modest change in the definition of this term. Circularity with "interpretation... interprets" has been removed, using "about the implications" instead. Lawrence Hunter PERSON: Alan Ruttenberg PERSON: Jennifer Fostel PERSON: Melanie Courtot conclusion OBI_0000005 obsolete_study interpretation true IAO:0000037 dot plot Dot plot of SSC-H and FSC-H. A dot plot is a report graph which is a graphical representation of data where each data point is represented by a single dot placed on coordinates corresponding to data point values in particular dimensions. person:Allyson Lister person:Chris Stoeckert OBI_0000123 group:OBI dot plot IAO_0000038s IAO_0000038 IAO:0000038 graph A diagram that presents one or more tuples of information by mapping those tuples in to a two dimensional space in a non arbitrary way. PERSON: Lawrence Hunter person:Alan Ruttenberg person:Allyson Lister OBI_0000240 group:OBI graph IAO:0000047 text based digital entity XML file, C++ source code file A text based digital entity is a digital entity that is encoded so that it only contains text characters. 3/22/2009 Alan Ruttenberg, obsoleted per http://groups.google.com/group/information-ontology/browse_thread/thread/789ad4b7708d5cf4 superclass was 'digital document' digital_entity person:Chris Stoeckert OBI_0000132 group:OBI obsolete2_text based digital entity true IAO:0000055 rule example to be added A rule is an executable which guides, defines, restricts actions. MSI PRS OBI_0500021 PRS rule IAO:0000057 contour plot Contour plot of SSC-H, FSC-H, and FL1-H. generically_dependent_continuants person:Allyson Lister person:Chris Stoeckert OBI_0000246 group:Flow Cytometry community contour plot IAO:0000059 report figure A report figure is a report display element that has some aspect of illustration, but may be a composite of figures, images, and other elements I prepended the 'report ' to make it clear that we mean parts of reports here. We may want a more generic version of 'figure', in which case this would become a defined class - figure and part_of some report Replaced by defined version of figure person:Alan Ruttenberg person:Allyson Lister OBI_0000027 group:OBI obsolete2_report figure true IAO_0000064s IAO_0000064 IAO:0000064 algorithm PMID: 18378114.Genomics. 2008 Mar 28. LINKGEN: A new algorithm to process data in genetic linkage studies. A plan specification which describes the inputs and output of mathematical functions as well as workflow of execution for achieving an predefined objective. Algorithms are realized usually by means of implementation as computer programs for execution by automata. Philippe Rocca-Serra PlanAndPlannedProcess Branch OBI_0000270 adapted from discussion on OBI list (Matthew Pocock, Christian Cocos, Alan Ruttenberg) algorithm IAO_0000065s IAO_0000065 IAO:0000065 software interpreter R program, Perl interpreter, Java virtual machine A software interpreter is a software application that executes some specified input software. Do we care? Jennifer: Yes, there was a particular version of R that had a bug and it was fixed later. That would imply that we mean specific version of an interpreter. So an instance of this would be a particular version of the interpreter person:Alan Ruttenberg person:Chris Stoeckert OBI_0000199 group:OBI software interpreter IAO_0000078s IAO_0000078 IAO:0000078 curation status specification The curation status of the term. The allowed values come from an enumerated list of predefined terms. See the specification of these instances for more detailed definitions of each enumerated value. Better to represent curation as a process with parts and then relate labels to that process (in IAO meeting) PERSON:Bill Bug GROUP:OBI:<http://purl.obolibrary.org/obo/obi> OBI_0000266 curation status specification IAO:0000079 density plot Density plot of SSC-H and FSC-H. A density plot is a report graph which is a graphical representation of data where the tint of a particular pixel corresponds to some kind of function corresponding the the amount of data points relativelly with their distance from the the pixel. person:Allyson Lister person:Chris Stoeckert OBI_0000179 group:Flow Cytometry community density plot IAO_0000088s IAO_0000088 IAO:0000088 report Examples of reports are gene lists and investigation reports. These are not published (journal) articles but may be included in a journal article. A document assembled by an author for the purpose of providing information for the audience. A report is the output of a documenting process and has the objective to be consumed by a specific audience. Topic of the report is on something that has completed. A report is not a single figure. Examples of reports are journal article, patent application, grant progress report, case report (not patient record). 2009-03-16: comment from Darren Natale: I am slightly uneasy with the sentence "Topic of the report is on something that has completed." Should it be restricted to those things that are completed? For example, a progress report is (usually) about something that definitely has *not* been completed, or may include (only) projections. I think the definition would not suffer if the whole sentence is deleted. 2009-03-16: this was report of results with definition: A report is a narrative object that is a formal statement of the results of an investigation, or of any matter on which definite information is required, made by some person or body instructed or required to do so. 2009-03-16: work has been done on this term during during the OBI workshop winter 2009 and the current definition was considered acceptable for use in OBI. If there is a need to modify this definition please notify OBI. 2009-08-10 Alan Ruttenberg: Larry Hunter suggests that this be obsoleted and replaced by 'document'. Alan restored as there are OBI dependencies and this merits further discussion disagreement about where reports go. alan: only some gene lists are reports. Is a report all the content of some document? The example of usage suggests that a report may be part of some article. Term needs clarification PERSON: Alan Ruttenberg PERSON: Chris Stoeckert PERSON: Melanie Courtot GROUP: OBI OBI_0000099 report IAO:0000091 report element A report element is a narrative object in which information is presented and consumed by a human being, and is part of a report. Examples of report elements are figure (dot plot), table, text portion (may include a movie or audio clip on a web page). 2009-03-16: needs some more work (clarify relations). 2009-03-16: was report display element with definition: A report display element is a narrative object that is part of a report. Report display elements are set off from the textual parts of a report and are typically given a label(e.g. Figure 2) which is used to refer to the element from the text. Typically the 2d layout is part of the identity of such elements. 2009-03-16: work has been done on this term during during the OBI workshop winter 2009 and the current definition was considered acceptable for use in OBI. If there is a need to modify this definition please notify OBI. 2009-08-10 Alan Ruttenberg: Larry Hunter suggests that this be obsoleted and replaced by 'textual entity' and 'figure'. Alan restored as there are OBI dependencies and this merits further discussion Replaced by textual entity and figure There will be some issue here about whether these are defined classes. As intended these are meant to denote the parts of the report that are not textual but are typically boxed and set within the text, labelled with some identifier, and referred to in the text PERSON: Alan Ruttenberg PERSON: Allyson Lister PERSON: Melanie Courtot GROUP:OBI OBI_0000001 obsolete_report element true IAO:0000093 binary executable Binary executable is a digital entity consisting of the binary representation of machine instructions of a specific processor or they may be binary pseudocode for a virtual machine. A non-source executable file is also called an object program. It is assumed that the binary executable file contains properly-formatted computer instructions. (derived from Wikipedia, Nov 1, 2007) 3/22/2009 Alan Ruttenberg, obsoleted per http://groups.google.com/group/information-ontology/browse_thread/thread/789ad4b7708d5cf4 superclass was 'digital entity' person:Jennifer Fostel OBI_0000222 group:OBI obsolete2_binary executable true IAO_0000096s IAO_0000096 IAO:0000096 source code module The written source code that implements part of an algorithm. Test - if you know that it was written in a specific language, then it can be source code module. We mean here, roughly, the wording of a document such as a perl script. A source code module is a directive information entity that specifies, using a programming language, some algorithm. person:Alan Ruttenberg person:Chris Stoeckert OBI_0000039 group:OBI source code module IAO:0000097 report table A report table is a report display element consisting of a matrix of cells layed out in a grid, some set of which are filled with some information content 2009-08-10 Alan Ruttenberg: Larry Hunter suggests that this be obsoleted and replaced by 'textual entity table'. Alan restored as there are OBI dependencies and this merits further discussion person:Alan Ruttenberg person:Allyson Lister OBI_0000265 group:OBI obsolete_report table true IAO_0000098s IAO_0000098 IAO:0000098 data format specification A data format specification is the information content borne by the document published defining the specification. Example: The ISO document specifying what encompasses an XML document; The instructions in a XSD file 2009-03-16: provenance: term imported from OBI_0000187, which had original definition "A data format specification is a plan which organizes information. Example: The ISO document specifying what encompasses an XML document; The instructions in a XSD file" PERSON: Alan Ruttenberg PlanAndPlannedProcess Branch OBI branch derived OBI_0000187 data format specification IAO_0000100s IAO_0000100 IAO:0000100 data set Intensity values in a CEL file or from multiple CEL files comprise a data set (as opposed to the CEL files themselves). A data item that is an aggregate of other data items of the same type that have something in common. Averages and distributions can be determined for data sets. 2009/10/23 Alan Ruttenberg. The intention is that this term represent collections of like data. So this isn't for, e.g. the whole contents of a cel file, which includes parameters, metadata etc. This is more like java arrays of a certain rather specific type 2014-05-05: Data sets are aggregates and thus must include two or more data items. We have chosen not to add logical axioms to make this restriction. person:Allyson Lister person:Chris Stoeckert OBI_0000042 group:OBI data set IAO_0000101s IAO_0000101 IAO:0000101 image An image is an affine projection to a two dimensional surface, of measurements of some quality of an entity or entities repeated at regular intervals across a spatial range, where the measurements are represented as color and luminosity on the projected on surface. person:Alan Ruttenberg person:Allyson person:Chris Stoeckert OBI_0000030 group:OBI image IAO:0000102 data about an ontology part Data about an ontology part is a data item about a part of an ontology, for example a term Person:Alan Ruttenberg data about an ontology part IAO_0000104s IAO_0000104 IAO:0000104 plan specification PMID: 18323827.Nat Med. 2008 Mar;14(3):226.New plan proposed to help resolve conflicting medical advice. A directive information entity with action specifications and objective specifications as parts, and that may be concretized as a realizable entity that, if realized, is realized in a process in which the bearer tries to achieve the objectives by taking the actions specified. 2009-03-16: provenance: a term a plan was proposed for OBI (OBI_0000344) , edited by the PlanAndPlannedProcess branch. Original definition was " a plan is a specification of a process that is realized by an actor to achieve the objective specified as part of the plan". It has been subsequently moved to IAO where the objective for which the original term was defined was satisfied with the definitionof this, different, term. 2014-03-31: A plan specification can have other parts, such as conditional specifications. 2022-01-16 Updated definition to that proposed by Clint Dowloand, IAO Issue 231. Alternative previous definition: a plan is a set of instructions that specify how an objective should be achieved Alan Ruttenberg Clint Dowland OBI Plan and Planned Process branch OBI_0000344 2/3/2009 Comment from OBI review. Action specification not well enough specified. Conditional specification not well enough specified. Question whether all plan specifications have objective specifications. Request that IAO either clarify these or change definitions not to use them plan specification https://github.com/information-artifact-ontology/IAO/issues/231#issuecomment-1010455131 IAO:0000105 digital document A digital document is a digital entity consisting of an electronic file which can be rendered into human-readable form by one or more computational applications. The digital document does not refer to the information content of the document but to an instance of the file. 3/22/2009 Alan Ruttenberg, obsoleted per http://groups.google.com/group/information-ontology/browse_thread/thread/789ad4b7708d5cf4 superclass was 'digial entity' person:Jennifer Fostel OBI_0000195 group:OBI obsolete2_digital document true IAO_0000109s IAO_0000109 IAO:0000109 measurement datum Examples of measurement data are the recoding of the weight of a mouse as {40,mass,"grams"}, the recording of an observation of the behavior of the mouse {,process,"agitated"}, the recording of the expression level of a gene as measured through the process of microarray experiment {3.4,luminosity,}. A measurement datum is an information content entity that is a recording of the output of a measurement such as produced by a device. 2/2/2009 is_specified_output of some assay? person:Chris Stoeckert OBI_0000305 group:OBI measurement datum IAO:0000128 _identifier is a container under information content entity for collecting types of terms to indicate a specific instance or clas of what was used or participated in an investigation. Identifiers are borne by a product or its packaging, and can be encoded in a variety of other information objects, such as bar codes, numerals, or patterns of dots. Note: everybody agreed that identifier is probably a too general term. We however felt that it would be appropriate to group "identifiying" terms under some kind of umbrella. We therefore propose to use _identifier for that purpose. As per OBI conventions, the _ prefixing identifier indicates that this is a helper class and shouldn't be considered as final. obsolete_identifier true IAO_0000129s IAO_0000129 IAO:0000129 version number A version number is an information content entity which is a sequence of characters borne by part of each of a class of manufactured products or its packaging and indicates its order within a set of other products having the same name. Note: we feel that at the moment we are happy with a general version number, and that we will subclass as needed in the future. For example, see 7. genome sequence version GROUP: IAO version number IAO:0000131 serial number A serial number is an information content entity which is a unique sequence of characters borne by part of manufactured product or its packaging that is assigned to each individual in some class of products, and so can serve as a way to identify an individual product within the class. Serial numbers can be encoded in a variety of other information objects, such as bar codes, numerals, or patterns of dots. Note: during the call there was some confusion between serial number and model number. We agreed that it would be very helpful for all those terms to have example of usages - please add if you have any :-) GROUP: IAO serial number IAO:0000132 lot number A lot number is an information content entity which is an identical sequence of character borne by part of manufactured product or its packaging for each instances of a product class in a discrete batch of an item. Lot numbers are usually assigned to each separate production run of an item. Manufacturing as a lot might be due to a variety of reasons, for example, a single process during which many individuals are made from the same portion of source material. Lot numbers can be encoded in a pattern of other information objects, such as bar codes, numerals, or patterns of dots. GROUP: IAO batch number lot number IAO:0000140 A settings datum is a datum that denotes some configuration of an instrument. 2/3/2009 Feedback from OBI This should be a "setting specification". There is a question of whether it is information about a realizable or not. Pro other specification are about realizables. Cons sometimes specifies a quality which is not a realizable. Alan grouped these in placeholder for the moment. Name by analogy to measurement datum. setting datum IAO:0000141 3/22/2009 Alan Ruttenberg, obsoleted per http://groups.google.com/group/information-ontology/browse_thread/thread/789ad4b7708d5cf4 Need to rework digital entity. Digital quality was suggested by Barry. obsolete_digital quality true IAO:0000144 conclusion textual entity that fucoidan has a small statistically significant effect on AT3 level but no useful clinical effect as in-vivo anticoagulant, a paraphrase of part of the last paragraph of the discussion section of the paper 'Pilot clinical study to evaluate the anticoagulant activity of fucoidan', by Lowenthal et. al.PMID:19696660 A textual entity that expresses the results of reasoning about a problem, for instance as typically found towards the end of scientific papers. 2009/09/28 Alan Ruttenberg. Fucoidan-use-case 2009/10/23 Alan Ruttenberg: We need to work on the definition still Person:Alan Ruttenberg conclusion textual entity IAO:0000178 material information bearer A page of a paperback novel with writing on it. The paper itself is a material information bearer, the pattern of ink is the information carrier. a brain a hard drive A material entity in which a concretization of an information content entity inheres. GROUP: IAO material information bearer IAO:0000179 histogram A histogram is a report graph which is a statistical description of a distribution in terms of occurrence frequencies of different event classes. PERSON:Chris Stoeckert PERSON:James Malone PERSON:Melanie Courtot GROUP:OBI histogram IAO:0000180 heatmap A heatmap is a report graph which is a graphical representation of data where the values taken by a variable(s) are shown as colors in a two-dimensional map. PERSON:Chris Stoeckert PERSON:James Malone PERSON:Melanie Courtot GROUP:OBI heatmap IAO:0000181 Venn diagram A Venn diagram is a report graph showing all hypothetically possible logical relations between a finite collection of sets. PERSON:Chris Stoeckert PERSON:James Malone PERSON:Melanie Courtot WEB: http://en.wikipedia.org/wiki/Venn_diagram Venn diagram IAO:0000182 obsolete_survival curve A survival curve is a report graph which is a graphical representation of data where the percentage of survival is plotted as a function of time. PERSON:Chris Stoeckert PERSON:James Malone PERSON:Melanie Courtot WEB: http://www.graphpad.com/www/book/survive.htm obsolete_survival curve true IAO:0000183 dendrogram Dendrograms are often used in computational biology to illustrate the clustering of genes. A dendrogram is a report graph which is a tree diagram frequently used to illustrate the arrangement of the clusters produced by a clustering algorithm. PERSON:Chris Stoeckert PERSON:James Malone PERSON:Melanie Courtot WEB: http://en.wikipedia.org/wiki/Dendrogram dendrogram IAO:0000184 scatter plot Comparison of gene expression values in two samples can be displayed in a scatter plot A scatterplot is a graph which uses Cartesian coordinates to display values for two variables for a set of data. The data is displayed as a collection of points, each having the value of one variable determining the position on the horizontal axis and the value of the other variable determining the position on the vertical axis. PERSON:Chris Stoeckert PERSON:James Malone PERSON:Melanie Courtot scattergraph WEB: http://en.wikipedia.org/wiki/Scatterplot scatter plot IAO:0000185 A photograph is created by projecting an image onto a photosensitive surface such as a chemically treated plate or film, CCD receptor, etc. PERSON:Alan Ruttenberg PERSON:Joanne Luciano PERSON:Melanie Courtot WEB: http://en.wiktionary.org/wiki/photograph photograph IAO:0000186 photographic print A photographic print is a material entity upon which a photograph generically depends. PERSON:Alan Ruttenberg PERSON:Melanie Courtot photographic print IAO:0000225 obsolescence reason specification The reason for which a term has been deprecated. The allowed values come from an enumerated list of predefined terms. See the specification of these instances for more detailed definitions of each enumerated value. The creation of this class has been inspired in part by Werner Ceusters' paper, Applying evolutionary terminology auditing to the Gene Ontology. PERSON: Alan Ruttenberg PERSON: Melanie Courtot obsolescence reason specification IAO_0000300s IAO_0000300 IAO:0000300 textual entity Words, sentences, paragraphs, and the written (non-figure) parts of publications are all textual entities A textual entity is a part of a manifestation (FRBR sense), a generically dependent continuant whose concretizations are patterns of glyphs intended to be interpreted as words, formulas, etc. AR, (IAO call 2009-09-01): a document as a whole is not typically a textual entity, because it has pictures in it - rather there are parts of it that are textual entities. Examples: The title, paragraph 2 sentence 7, etc. MC, 2009-09-14 (following IAO call 2009-09-01): textual entities live at the FRBR (http://en.wikipedia.org/wiki/Functional_Requirements_for_Bibliographic_Records) manifestation level. Everything is significant: line break, pdf and html versions of same document are different textual entities. PERSON: Lawrence Hunter text textual entity IAO:0000301 citation Verspoor, K., Cohen, KB., Hunter, L. Textual characteristics of traditional and Open Access scientific journals are similar, BMC Bioinformatics 2009, 10:183. A textual entity intended to identify a particular publication. PERSON: Lawrence Hunter citation IAO_0000302s IAO_0000302 IAO:0000302 author identification L. Hunter A textual entity intended to identify a particular author PERSON: Lawrence Hunter author identification IAO:0000303 institutional identification University of Colorado Denver School of Medicine A textual entity intended to identify a particular institution PERSON: Lawrence Hunter institutional identification IAO:0000304 caption Figure 1: A system diagram describing the modules of the Hanalyzer. Reading methods (green) take external sources of knowledge (blue) and extract information from them, either by parsing structured data or biomedical language processing to extract information from unstructured data. Reading modules are responsible for tracking the provenance of all knowledge. Reasoning methods (yellow) enrich the knowledge that results from reading by, for example, noting two genes that are annotated to the same ontology term or database entry. All knowledge sources, read or reasoned, are assigned a reliability score, and all are combined using that score into a knowledge network (orange) that represents the integration of all sorts of relationship between a pair of genes and a combined reliability score. A data network (also orange) is created from experimental results to be analyzed. The reporting modules (pink) integrate the data and knowledge networks, producing visualizations that can be queried with the associated drill-down tool. A textual entity that describes a figure PERSON: Lawrence Hunter caption IAO:0000305 document title Textual characteristics of traditional and Open Access scientific journals are similar A textual entity that names a document PERSON: Lawrence Hunter document title IAO:0000306 table | T F --+----- T | T F F | F F A textual entity that contains a two-dimensional arrangement of texts repeated at regular intervals across a spatial range, such that the spatial relationships among the constituent texts expresses propositions PERSON: Lawrence Hunter table IAO:0000307 table of abbreviations IAO information artifact ontology OBI ontology of biomedical investiations GO gene ontology A table where the constituent texts are abbreviations and their expansions PERSON: Lawrence Hunter table of abbreviations IAO:0000308 figure Any picture, diagram or table An information content entity consisting of a two dimensional arrangement of information content entities such that the arrangement itself is about something. PERSON: Lawrence Hunter figure IAO:0000309 diagram A molecular structure ribbon cartoon showing helices, turns and sheets and their relations to each other in space. A figure that expresses one or more propositions PERSON: Lawrence Hunter diagram IAO_0000310s IAO_0000310 IAO:0000310 document A journal article, patent application, laboratory notebook, or a book A collection of information content entities intended to be understood together as a whole PERSON: Lawrence Hunter document document document IAO_0000311s IAO_0000311 IAO:0000311 publication journal article, newspaper story, book, etc. A document that is the output of a publishing process. PERSON: Chris Stoeckert PERSON: Jie Zheng PERSON: Lawrence Hunter published document Revisit the term in Octorber 2020. Improve the defintion. publication IAO:0000312 publication about an investigation Most scientific journal articles A publication that is about an investigation PERSON: Lawrence Hunter scientific publication publication about an investigation IAO:0000313 patent US Patent 6,449,603 A document that has been accepted by a patent authority PERSON: Lawrence Hunter patent IAO_0000314s IAO_0000314 IAO:0000314 document part An abstract, introduction, method or results section. An information content entity that is part of a document. PERSON: Lawrence Hunter document part document part IAO:0000315 abstract The profusion of high-throughput instruments and the explosion of new results in the scientific literature, particularly in molecular biomedicine, is both a blessing and a curse to the bench researcher. Even knowledgeable and experienced scientists can benefit from computational tools that help navigate this vast and rapidly evolving terrain. In this paper, we describe a novel computational approach to this challenge, a knowledge-based system that combines reading, reasoning and reporting methods to facilitate analysis of experimental data. Reading methods extract information from external resources, either by parsing structured data or biomedical language processing to extract information from unstructured data, and track knowledge provenance. Reasoning methods enrich the knowledge that results from reading by, for example, noting two genes that are annotated to the same ontology term or database entry. Reasoning is also used to combine all sources into a knowledge network that represents the integration of all sorts of relationships between a pair of genes, and to calculate a combined reliability score. Reporting methods combine the knowledge network with a congruent network constructed from experimental data and visualize the combined network in a tool that facilitates the knowledge-based analysis of that data. A summary of the entire document that is substantially smaller than the document it summarizes. It is about the document it summarizes. PERSON: Lawrence Hunter precis abstract IAO:0000316 introduction to a publication about an investigation Section labelled 'introduction' of a typical scientific journal article A part of a publication about an investigation that is about the objective specification (why the investigation is being done) PERSON: Lawrence Hunter background introduction overview introduction to a publication about an investigation IAO:0000317 methods section The section labelled 'Methods' or 'Materials and Methods' in a typical scientific journal article. A part of a publication about an investigation that is about the study design of the investigation PERSON: Lawrence Hunter experimental experimental methods experimental procedures experimental section method methodology methods methods section IAO:0000318 results section The section labelled 'results' in a typical scientific journal article A part of a publication about an investigation that is about a study design execution PERSON: Lawrence Hunter results results section IAO:0000319 discussion section of a publication about an investigation A part of a publication about an investigation that is about the study interpretation of the investigation PERSON: Lawrence Hunter discussion discussion section discussions discussion section of a publication about an investigation IAO:0000320 references section The list of citations found at the end of a scientific publication, grant proposal or patent application, sometimes called "literature cited" or "bibliography" A part of a document that has citations as parts PERSON: Lawrence Hunter literature cited reference reference list references references section IAO:0000321 author list Lawrence Hunter and Kevin Brettonel Cohen A part of a document that enumerates the authors of the document PERSON: Lawrence Hunter author list IAO:0000322 institution list The University of Colorado Denver School of Medicine and the University of Colorado Boulder. A part of a document that has parts that are institution identifications associated with the authors of the document PERSON: Lawrence Hunter institution list IAO:0000323 author contributions section LH conceived of the hypothesis, designed the study and contributed to the writing of the manuscript. KBC executed the experiments, analyzed the data, and contributed to the writing of the manuscript. A part of a publication that is about the specific contributions of each author PERSON: Lawrence Hunter author contributions authors' contribution authors' contributions authors' roles contributions by the authors contributorship author contributions section IAO:0000324 acknowledgements section The authors wish to thank Alan Ruttenberg for his constructive comments about an earlier draft of this manuscript Part of a publication that is about the contributions of people or institutions other than the authors. PERSON: Lawrence Hunter acknowledgement acknowledgements acknowledgment acknowledgments acknowledgements section IAO:0000325 footnote The referent in the text is usually indicated by a special typographic character such as * or a superscripted number, which is also used to indicate the footnote that refers to that text. A part of a document that is about a specific other part of the document. Usually footnotes are spatially segregated from the rest of the document. PERSON: Lawrence Hunter endnote footnotes footnote IAO:0000326 supplementary material to a document A part of a document that is segregated from the rest of the document due to its size PERSON: Lawrence Hunter additional file additional files additional information appendix electronic supplementary material electronic supplementary materials supplemental data supplemental information supplemental material supplementary data supplementary files supplementary information supplementary material supplementary materials supporting information supplementary material to a document IAO:0000327 table of contents A table that relates document parts to specific locations in a document (usually page numbers). This is also a document part (subsumption there should be inferred). PERSON: Lawrence Hunter table of contents IAO:0000328 table of figures A table that relates figures in a document to specific locations in that document (usually page numbers). This is also a document part (subsumption there should be inferred). PERSON: Lawrence Hunter table of figures IAO:0000329 running title A shorter version of a document title PERSON: Lawrence Hunter running title IAO:0000330 copyright section This work is licensed under a Creative Commons Attribution-Share Alike 3.0 United States License. A document part that describes legal restrictions on making or distributing copies of the document PERSON: Lawrence Hunter copyright section 1 IAO:0000400 A cartesian spatial coordinate datum is a representation of a point in a spatial region, in which equal changes in the magnitude of a coordinate value denote length qualities with the same magnitude 2009-08-18 Alan Ruttenberg - question to BFO list about whether the BFO sense of the lower dimensional regions is that they are always part of actual space (the three dimensional sort) http://groups.google.com/group/bfo-discuss/browse_thread/thread/9d04e717e39fb617 Alan Ruttenberg AR notes: We need to discuss whether it should include site. cartesian spatial coordinate datum http://groups.google.com/group/bfo-discuss/browse_thread/thread/9d04e717e39fb617 1 IAO:0000401 A cartesion spatial coordinate datum that uses one value to specify a position along a one dimensional spatial region Alan Ruttenberg one dimensional cartesian spatial coordinate datum 1 1 IAO:0000402 A cartesion spatial coordinate datum that uses two values to specify a position within a two dimensional spatial region Alan Ruttenberg two dimensional cartesian spatial coordinate datum 1 1 1 IAO:0000403 A cartesion spatial coordinate datum that uses three values to specify a position within a three dimensional spatial region Alan Ruttenberg three dimensional cartesian spatial coordinate datum IAO:0000408 A scalar measurement datum that is the result of measurement of length quality Alan Ruttenberg length measurement datum IAO:0000409 denotator type The Basic Formal Ontology ontology makes a distinction between Universals and defined classes, where the formal are "natural kinds" and the latter arbitrary collections of entities. A denotator type indicates how a term should be interpreted from an ontological perspective. Alan Ruttenberg Barry Smith, Werner Ceusters denotator type IAO:0000414 A scalar measurement datum that is the result of measurement of mass quality 2009/09/28 Alan Ruttenberg. Fucoidan-use-case Person:Alan Ruttenberg mass measurement datum IAO:0000415 hypothesis textual entity that fucoidan has a small statistically significant effect on AT3 level but no useful clinical effect as in-vivo anticoagulant, a paraphrase of part of the last paragraph of the discussion section of the paper 'Pilot clinical study to evaluate the anticoagulant activity of fucoidan', by Lowenthal et. al.PMID:19696660 A textual entity that expresses an assertion that is intended to be tested. 2009/09/28 Alan Ruttenberg. Fucoidan-use-case Person:Alan Ruttenberg hypothesis textual entity IAO:0000416 A scalar measurement datum that is the result of measuring a temporal interval 2009/09/28 Alan Ruttenberg. Fucoidan-use-case Person:Alan Ruttenberg time measurement datum IAO:0000422 A textual entity that is used as directive to deliver something to a person, or organization 2010-05-24 Alan Ruttenberg. Use label for the string representation. See issue https://github.com/information-artifact-ontology/IAO/issues/59 postal address IAO:0000429 email address Alan Ruttenberg 1/3/2012 - Provisional id, see issue at https://github.com/information-artifact-ontology/IAO/issues/130&thanks=130&ts=1325636583 Person:Alan Ruttenberg Person:Chris Stoeckart email address OntoDM_247286s OntoDM_247286 IAO:0000442 author role A role inhering in a person or organization that is realized when the bearer participates in the work which is the basis of the document, in the writing of the document, and signs it with their name. PERSON: Alan Ruttenberg PERSON: Melanie Courtot agent role author role IAO:0000443 A planned process in which journal articles are read or processed and data items are extracted, typically for further analysis or indexing Person:Alan Ruttenberg data item extraction from journal article IAO:0000444 A planned process of making information, such as literature, music, and software etc., available to the public for sale or for free. Person: Jie Zheng https://en.wikipedia.org/wiki/Publishing VEuPathDB publishing process IAO:0000445 A document that is in preparation for submission to be published. PERSON: Jie Zheng EFO_0001795 in preparation VEuPathDB document in preparation for publication IAO_0000572s IAO_0000572 IAO:0000572 Recording the current temperature in a laboratory notebook. Writing a journal article. Updating a patient record in a database. A planned process in which a document is created or added to by including the specified input in it. a planned process of capturing information in an enduring form with the intent to communicate this information 6/11/9: Edited at OBI workshop. We need to be able identify a child form of information artifact which corresponds to something enduring (not brain like). This used to be restricted to physical document or digital entity as the output, but that excludes e.g. an audio cassette tape Bjoern Peters wikipedia http://en.wikipedia.org/wiki/Documenting documenting documenting IAO:0000573 line graph A line graph is a type of graph created by connecting a series of data points together with a line. PERSON:Chris Stoeckert PERSON:Melanie Courtot line chart GROUP:OBI WEB: http://en.wikipedia.org/wiki/Line_chart line graph IAO:0000574 A new pubmed ID being created for a journal article, and the associated pubmed record containing information to the journal article. A license plate number registered at the DMV to be belonging to a specific vehicle and owner. Placing a barcode on a product and entering information in a database that this barcode is assigned. A planned process in which a new CRID is created, associated with an entity, and stored in the CRID registry thereby registering it as being associated with some entity 2014-05-05: It is the CRID registry that assigns CRIDs, not the users of the registry. Person:Alan Ruttenberg Person:Bjoern Peters Person:Melanie Courtot assigning a CRID assigning a centrally registered identifier IAO:0000575 Articles in Pubmed are reviewed by curators who add MESH terms to the Pubmed records in order to categorize them better and improve the ability to search for them. A planned process in which a CRID registry associates an information content entity with a CRID symbol PERSON:Alan Ruttenberg associating information with a CRID in the CRID registry associating information with a centrally registered identifier in its registry IAO:0000576 a planned process with the objective to establish a system that allows to refer to specific entities of a certain kind and store information about them, by establishing a CRID registry and plan specifications for the process of 1) assigning a CRID and 2) looking up a CRID. MC, 20101124: deprecated following discussion at IAO call 20101124. Term was deemed not necessary - no use case for now. obsolete_establishing a CRID registry true IAO:0000577 The sentence "The article has Pubmed ID 12345." contains a CRID that has two parts: one part is the CRID symbol, which is '12345'; the other part denotes the CRID registry, which is Pubmed. A symbol that is part of a CRID and that is sufficient to look up a record from the CRID's registry. PERSON: Alan Ruttenberg PERSON: Bill Hogan PERSON: Bjoern Peters PERSON: Melanie Courtot CRID symbol Original proposal from Bjoern, discussions at IAO calls centrally registered identifier symbol IAO:0000578 The sentence "The article has Pubmed ID 12345." contains a CRID that has two parts: one part is the CRID symbol, which is '12345'; the other part denotes the CRID registry, which is Pubmed. An information content entity that consists of a CRID symbol and additional information about the CRID registry to which it belongs. 2014-05-05: In defining this term we take no position on what the CRID denotes. In particular do not assume it denotes a *record* in the CRID registry (since the registry might not have 'records'). Alan, IAO call 20101124: potentially the CRID denotes the instance it was associated with during creation. Note, IAO call 20101124: URIs are not always CRID, as not centrally registered. We acknowledge that CRID is a subset of a larger identifier class, but this subset fulfills our current needs. OBI PURLs are CRID as they are registered with OCLC. UPCs (Universal Product Codes from AC Nielsen)are not CRID as they are not centrally registered. PERSON: Alan Ruttenberg PERSON: Bill Hogan PERSON: Bjoern Peters PERSON: Melanie Courtot CRID Original proposal from Bjoern, discussions at IAO calls centrally registered identifier IAO:0000579 PubMed is a CRID registry. It has a code set of PubMed identifiers associated with journal articles. A code set of CRID records, each consisting of a CRID symbol and additional information which was recorded in the code set through an assigning a centrally registered identifier process. Justin Whorton PERSON: Alan Ruttenberg PERSON: Bill Hogan PERSON: Bjoern Peters PERSON: Melanie Courtot CRID registry Original proposal from Bjoern, discussions at IAO calls https://github.com/information-artifact-ontology/IAO/issues/237 centrally registered identifier registry IAO:0000580 Going to the PubMed website and entering a PubMed ID in order to retrieve the Pubmed information associated with that ID. A planned process in which a request to a CRID registry is made to return the information associated with a CRID symbol PERSON: Alan Ruttenberg PERSON: Bill Hogan PERSON: Bjoern Peters PERSON: Melanie Courtot looking up a CRID looking up a centrally registered identifier IAO:0000582 time stamped measurement datum IAO:0000584 pmid:20604925 - time-lapse live cell microscopy A data set that is an aggregate of data recording some measurement at a number of time points. The time series data set is an ordered list of pairs of time measurement data and the corresponding measurement data acquired at that time. Alan Ruttenberg experimental time series time sampled measurement data set IAO:0000590 written name "Bill Clinton" "The Eiffel Tower" "United States of America" A textual entity that denotes a particular in reality. PERSON: Bill Hogan https://github.com/information-artifact-ontology/IAO/issues/114 The qualifier "written" is to set it apart from spoken names. Also, note the restrictions to particulars. We are not naming universals. We could however, be naming, attributive collections which are particulars, so "All people located in the boundaries of the city of Little Rock, AR on June 18, 2011 at 9:50a CDT" would be a name. written name IAO:0000591 A software method (also called subroutine, subprogram, procedure, method, function, or routine) is software designed to execute a specific task. PERSON: Melanie Courtot PERSON: Michel Dumontier https://github.com/information-artifact-ontology/IAO/issues/80 software method IAO:0000592 A software module is software composed of a collection of software methods. PERSON: Melanei Courtot PERSON: Michel Dumontier https://github.com/information-artifact-ontology/IAO/issues/80 software module IAO:0000593 A software library is software composed of a collection of software modules and/or software methods in a form that can be statically or dynamically linked to some software application. PERSON: Melanie Courtot PERSON: Michel Dumontier https://github.com/information-artifact-ontology/IAO/issues/80 software library IAO:0000594 A software application is software that can be directly executed by some processing unit. PERSON: Melanie Courtot PERSON: Michel Dumontier https://github.com/information-artifact-ontology/IAO/issues/80 software application IAO:0000595 A software script is software whose instructions can be executed using a software interpreter. PERSON: Melanie Courtot PERSON: Michel Dumontier https://github.com/information-artifact-ontology/IAO/issues/80 software script IAO:0000605 abbreviation textual entity From Shiba et al. Acta Neuropathol Commun. 2013; 1: 45. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3893467/): BAC: Bacterial artificial chromosome; CR: Calretinin; GFAP: Glial fibrillary acidic protein; MAP: Microtubule-associated protein; MRI: Magnetic resonance imaging; NSC: Neural stem cell; PDA: Patent ductus arteriosus; PMG: Polymicrogyria; PNH: Periventricular nodular heterotopia; VSD: Ventricular septal defect. A textual entity listing abbreviations and their expansions that are used in a document. PERSON: Bill Baumgartner abbreviation textual entity IAO:0000606 abbreviations section The section labelled 'abbreviations' in a typical scientific journal article. A part of a document where abbreviations and their long-forms used within the document are listed. PERSON: Bill Baumgartner abbreviation and acronyms abbreviation list abbreviations abbreviations and acronyms abbreviations list abbreviations used definitions for abbreviations list of abbreviations list of abbreviations used non-standard abbreviations nonstandard abbreviations nonstandard abbreviations and acronyms abbreviations section IAO:0000607 author information section The section labelled 'author information' in a typical scientific journal article, e.g. in Takon. Ann Gen Psychiatry. 2011; 10: 25. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3204268/) A part of a document about the authors that provides biographical information and may discuss how the authors' professional experiences are relevant to the work described in the document. PERSON: Bill Baumgartner author information authors’ information biographies contributor information author information section IAO:0000608 author information textual entity From Takon. Ann Gen Psychiatry. 2011; 10: 25. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3204268/): IT [the author] is the lead paediatrician for ADHD services in East Hertfordshire, UK, where she runs a weekly joint ADHD clinic with the Child and Adolescent psychiatrist and works within an ADHD specialist team. IT also sees children with other neurodisability issues who may have comorbid ADHD, where the presentation may be more complex and challenging to manage. IT has vast experience in managing children with complex ADHD. She has 18 years of experience in paediatrics and also has extensive experience in the use of psychopharmacologic agents in managing children with ADHD. A textual entity expression information about an author of a document. This information may include biographical information and may discuss how the authors' professional experiences are relevant to the work described in the document. PERSON: Bill Baumgartner author information textual entity IAO:0000609 author summary section The section labelled 'synopsis' in a typical scientific journal article, e.g. in Pendse et al. BMC Genomics. 2013; 14: 136. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3608171/) A part of a document, distinct from the abstract, that describes the significance and broader context of the document content. The author summary is often written in a non-technical manner and is aimed at both scientists and non-scientist readers. PERSON: Bill Baumgartner author summary summary synopsis Article submission guidelines for PLoS Genetics (http://journals.plos.org/plosgenetics/s/submission-guidelines) author summary section IAO:0000610 author summary textual entity From Pendse et al. BMC Genomics. 2013; 14: 136. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3608171/): The search for genetic risk factors for common human diseases often relies on the use of linkage and association studies to establish correlation between genomic markers and disease risk. These studies require additional functional evaluation of candidate genes, including their possible interaction with diet and environment. The number of candidate genes is typically large and the development of appropriate genetic tools in mammalian systems is slow. By contrast, large-scale genetic screens, using widely available genetic tools, are routinely conducted in the fruit fly Drosophila melanogaster. In this study, we used Drosophila to screen candidate genes identified in human genome-wide scans as associated with risk of metabolic abnormalities such as type 2 diabetes. We show that a number of human candidate genes have fly orthologs that play an important role in Drosophila tolerance to high dietary sucrose. We further explored some of the specific metabolic abnormalities that can result when these genes’ activities are reduced in flies, focusing on a gene we call dHHEX (CG7056), the fly ortholog of human HHEX. A textual entity, distinct from the abstract, that describes the significance and broader context of the document content. The author summary is often written in a non-technical manner and is aimed at both scientists and non-scientist readers, e.g as described in the article submission guidelines for PLoS Genetics (http://journals.plos.org/plosgenetics/s/submission-guidelines). PERSON: Bill Baumgartner Article submission guidelines for PLoS Genetics (http://journals.plos.org/plosgenetics/s/submission-guidelines). author summary textual entity IAO:0000611 availability section The section labelled 'availability and requirements' in a typical scientific journal article, e.g. Qi et al. BMC Bioinformatics. 2014; 15: 11. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3897912/). A part of a document about a resource described in the document, e.g. software, that describes where and/or how that resource can be obtained. PERSON: Bill Baumgartner availability availability of data data archiving data availability data availability statement data sharing statement availability section IAO:0000612 availability textual entity From Qi et al. BMC Bioinformatics. 2014; 15: 11. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3897912/): Project home page:http://krux.googlecode.com A textual entity expressing the location of a resource, e.g. software, or the manner in which a resource can be obtained. PERSON: Bill Baumgartner availability textual entity IAO:0000613 case report section The section labelled 'case report' in a typical scientific journal article, e.g. in Taglia et al. Acta Myol. 2012 Dec; 31(3): 201–203. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3631801/) A part of a document about the medical history of a specific patient as it relates to the topic of the document. PERSON: Bill Baumgartner case presentation case report case report section IAO:0000614 case report textual entity Excerpt from Taglia et al. Acta Myol. 2012 Dec; 31(3): 201–203. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3631801/): The patient is a 50-year-old man. His medical history was not contributory. At the age of 37 years, he complained of persistent fatigue and dyspnoea even for modest efforts and oedema of lower limbs. The patient was examined at the department of internal medicine of the local hospital, and hospitalised with a diagnosis of dilated cardiomyopathy probably consequence of a myocarditis process. Soon after he was transferred to the cardiologic department of the regional hospital, and pharmacologically treated for heart failure and pulmonary hypertension. A textual entity that expresses a detailed account of a portion of the medical history for a specific patient. PERSON: Bill Baumgartner case report textual entity IAO:0000615 conclusion section The section labelled 'conclusion' in a typical scientific journal article. A part of a document used to summarize the findings discussed in the document. The conclusion section is typically found near the end of a document. PERSON: Bill Baumgartner concluding remarks conclusion conclusions findings summary conclusion section IAO:0000616 conflict of interest section The section labelled 'conflict of interest statement' in a typical scientific journal article. A part of a document used to declare any competing interests regarding the authors and/or funding organization for the work described in the document. PERSON: Bill Baumgartner authors' disclosures of potential conflicts of interest competing financial interests competing interests conflict of interest conflict of interest statement conflict of interests conflicts of interest declaration of competing interest declaration of competing interests declaration of interest declaration of interests disclosure of conflict of interest disclosure of potential conflicts of interest duality of interest statement of interest conflict of interest section IAO:0000617 conflict of interest statement SD [an author] is a Merck employee and Merck is the sponsor of this study. [Taken from 'Effects of obstructive sleep apnoea risk on postoperative respiratory complications: protocol for a hospital-based registry study' Shin et al. 2016 (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4735131/)] A textual entity that expresses a situation involving one or more of the authors, or the funding source of a document whereby the authors or funding source stand to potentially gain (typically financially) from the results reported in the document. PERSON: Bill Baumgartner conflict of interest textual entity IAO:0000618 consent section The section labelled 'consent' in a typical scientific journal article, e.g. Shiba et al. Acta Neuropathol Commun. 2013; 1: 45. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3893467/) A part of a document about the consent process that was used to enroll patients in a study. PERSON: Bill Baumgartner consent consent section IAO:0000619 consent textual entity From Shiba et al. Acta Neuropathol Commun. 2013; 1: 45. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3893467/): Written informed consent was obtained from the patient’s parents for publication of this Case report and any accompanying images. A copy of the written consent is available for review by the Editor-in chief of this journal. A textual entity that documents the consenting process used to enroll patients in a study. PERSON: Bill Baumgartner consent textual entity IAO:0000620 ethical approval section The section labelled 'ethical approval' in a typical scientific journal article. A part of a document about the governance body responsible for approving the work discussed in a document on an ethical basis. PERSON: Bill Baumgartner ethical approval ethical requirements ethics ethics statement ethical approval section IAO:0000621 ethical approval textual entity From McLean et al. Br J Gen Pract. 2014 Jul; 64(624): e440–e447 (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4073730/): The NHS National Research Ethics Service had previously approved the use of these anonymised data for research purposes and this analysis did not require independent review. A textual entity that documents the ethical approval of some study design. PERSON: Bill Baumgartner ethical approval textual entity IAO:0000622 figures section The section labelled 'figures' in a typical scientific journal article. A part of a document that contains one or more figures. PERSON: Bill Baumgartner figures figures section IAO:0000623 funding source declaration section The section labelled 'funding' in a typical scientific journal article. A part of a document used to detail information regarding the source of funding used in support of the generation of the document content. PERSON: Bill Baumgartner financial support funding funding information funding sources funding statement funding/support grants role of the funding source source of funding sources of funding study funding funding source declaration section IAO:0000624 funding souce declaration textual entity From Stephan et al. Accid Anal Prev. 2011 May; 43(3): 1062–1067. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3062852/): This study was supported by the International Collaborative Research Grants Scheme with joint grants from the Wellcome Trust UK (GR071587MA) and the Australian NHMRC (268055). The funding sources played no role in study design, data collection, analysis or interpretation, writing the report, or the decision to submit the paper for publication. A textual entity documenting the source of funding that supported some study. PERSON: Bill Baumgartner funding source declaration textual entity IAO:0000625 future directions section The section labelled 'future directions' in a typical scientific journal article. A part of a document detailing extensions of the described work that may be implemented at some future point in time. PERSON: Bill Baumgartner future challenges future considerations future developments future directions future outlook future perspectives future plans future prospects future research future research directions future studies future work outlook future directions section IAO:0000626 future directions textual entity Excerpt from Wang and Li. Acta Pharmacol Sin. 2016 Jan; 37(1): 25–33. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4722976/): In the future, several questions will need to be resolved regarding the physiological assembly of KCNQ channels and their functional implications in complex neural circuits. First, we still lack sufficiently selective inhibitors and activators among the KCNQ family members. A textual entity expressing ideas regarding future work relevant to work described in a document that could be done. PERSON: Bill Baumgartner future directions textual entity IAO:0000627 genome announcement section The section labelled 'genome announcement' in a typical scientific journal article, e.g. in Kim et al. J Bacteriol. 2011 Oct; 193(19): 5537. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3187466/) A document part announcing the publication of a novel draft genome sequence. PERSON: Bill Baumgartner genome announcement genome announcement section IAO:0000628 genome announcement textual entity Excerpt from Kim et al. J Bacteriol. 2011 Oct; 193(19): 5537. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3187466/): Here we report the genome sequence of Lactobacillus malefermentans KCTC 3548, which we obtained using a whole-genome shotgun strategy (4) with Roche 454 GS (FLX Titanium) pyrosequencing (257,559 reads totaling ∼89.8 Mb; ∼45-fold coverage of the genome) at the Genome Resource Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB). A textual entity that describes the generation and public release of a novel, draft genome sequence. PERSON: Bill Baumgartner genome announcement textual entity IAO:0000629 keyword textual entity From: Fu and Lin. Identification of gene-oriented exon orthology between human and mouse. BMC Genomics. 2012; 13(Suppl 1): S10. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3303729/): Exon orthology; alternative splicing; exon duplication; intron-exon structure. A textual entity listing keywords indicating the major theme(s) of a document. PERSON: Bill Baumgartner keyword textual entity IAO:0000630 keywords section The section labelled 'keywords' in a typical scientific journal article. A part of a document where keywords selected by the author to categorize the major theme(s) of a document are listed. PERSON: Bill Baumgartner keywords keywords section IAO:0000631 study limitations section The section labelled 'limitations' in a typical scientific journal article. A part of a document about biases or short comings related to the study design and execution. PERSON: Bill Baumgartner limitations study limitations Author guidelines published by The Society for Academic Emergency Medicine. (http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1553-2712/homepage/ForAuthors.html) study limitations section IAO:0000632 study limitations textual entity Excerpt from the Limitations section of Fermann et al 2015, Acad Emerg Med. 2015 Mar; 22(3): 299–307 (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4405051/). Owing to the nature of a post hoc study, any significant values must be interpreted with caution. In the current analysis, no multiple testing was conducted and p-values remain unadjusted. Moreover, a selection bias arising from the randomized open-label design of the original EINSTEIN PE study cannot be ruled out. A textual entity addressing a shortcoming or bias of a study design or execution. PERSON: Bill Baumgartner Author guidelines published by The Society for Academic Emergency Medicine. (http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1553-2712/homepage/ForAuthors.html) study limitations textual entity IAO:0000633 materials section The section labelled 'materials' in a typical scientific journal article, e.g. Nguyen et al. BMC Bioinformatics. 2010; 11: 279. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2889936/) A part of a document about the materials required to reproduce the content of the document. PERSON: Bill Baumgartner materials materials section IAO:0000634 notes section The section labelled 'notes' in a typical scientific journal article, e.g. McLean et al. Br J Gen Pract. 2014 Jul; 64(624): e440–e447 (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4073730/): A part of a document containing typically short notes about the document itself and/or the authors. Often the notes section contains subsections related to funding, competing interests, ethical approval, etc. PERSON: Bill Baumgartner notes notes section IAO:0000635 patients section The section labelled 'patients' in a typical scientific journal article, e.g. in Citak et al. Acta Orthop. 2013 Jun; 84(3): 326–327. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3715825/) A part of a document about the patients that participated in a study. PERSON: Bill Baumgartner patients section IAO:0000636 patients textual entity Excerpt from Citak et al. Acta Orthop. 2013 Jun; 84(3): 326–327. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3715825/): Between January 1996 and February 2012, we treated 4 patients with interprosthetic femoral fractures (3 of them women) (Figure 2) using a custom-made interposition device (Waldemar Link GmbH, Hamburg, Germany) (Figure 1). Mean age was 74 (59–86) years. The fractures occurred mean 18 (13–28) years after primary THA and mean 14 (10–17) years after primary TKA. At the latest follow-up, after mean 8 (0.5–16) years, revision surgery with a total femur replacement was required in 1 case due to aseptic loosening. No other complications requiring revision surgery occurred. A textual entity expressing information regarding the patients used in a study. PERSON: Bill Baumgartner patients textual entity IAO:0000637 pre-publication history section The section labelled 'pre-publication history' in a typical scientific journal article, e.g. in Xiao et al. BMC Anesthesiol. 2013; 13: 33. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4016475/) A part of the document about the publication history of a document. This section typically details dates of document submission to a journal and dates of any re-submissions as well as reviewer comments and responses to reviewers by the authors. PERSON: Bill Baumgartner notice of republication pre-publication history pre-publication history section IAO:0000638 pre-publication history textual entity From Xiao et al. BMC Anesthesiol. 2013; 13: 33. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4016475/): The pre-publication history for this paper can be accessed here: http://www.biomedcentral.com/1471-2253/13/33/prepub A textual entity that expresses the pre-publication history (submission dates, reviewer comments, etc) for a document, often including a hyperlink to a web page detailing the information. PERSON: Bill Baumgartner pre-publication history textual entity IAO:0000639 related work section The section labelled 'related work' in a typical scientific journal article, e.g. Žitnik and Zupan. Bioinformatics. 2015 Jun 15; 31(12): i230–i239. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4542780/) A part of a document about work in other publications that is relevant to the content of the document. PERSON: Bill Baumgartner related literature related work related work section IAO:0000640 related work textual entity Excerpt from Žitnik and Zupan. Bioinformatics. 2015 Jun 15; 31(12): i230–i239. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4542780/): Our work presented here is similar in spirit to our recently developed methodology for data fusion via collective matrix factorization (Žitnik and Zupan, 2015). A textual entity that discusses work from other publications and expresses their relevancy to the content of a document. PERSON: Bill Baumgartner related work textual entity IAO:0000641 requirements section The section labelled 'availability and requirements' in a typical scientific journal article, e.g. Qi et al. BMC Bioinformatics. 2014; 15: 11. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3897912/). A part of a document about a resource described in the document, e.g. software, that describes the requirements necessary to use the resource, e.g. operating systems, hardware, etc. in the case of a software resource. PERSON: Bill Baumgartner requirements requirements section IAO:0000642 requirements textual entity From Qi et al. BMC Bioinformatics. 2014; 15: 11. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3897912/): • Operating systems: Platform independent • Programming language: Matlab, R, Python • Other requirements: None • License: GNU GPL v3 • Any restrictions to use by non-academics: None A textual entity that expresses the requirements necessary to use a resource, e.g. software. PERSON: Bill Baumgartner requirements textual entity IAO:0000643 statistical analysis textual entity From Mondo et al. Cardiovasc J Afr. 2013 Mar; 24(2): 28–33. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3734881/): Data were captured into EPI-DATA (version 3.1), cleaned and then exported to Stata version 10 for analysis. Continuous variables were summarised as mean (± standard deviation) and median (inter-quartile range), and presented in the tables. Categorical data were analysed using frequency and percentages, and results are presented in frequency tables and bar charts. Test of significance (p-value) was determined using the chi-square test. A p-value of less than 0.05 was considered significant. A textual entity documenting statistical analysis tools and techniques employed. PERSON: Bill Baumgartner statistical analysis textual entity IAO:0000644 statistical analysis section The section labelled 'statistical analysis' in a typical scientific journal article, e.g. Mondo et al. Cardiovasc J Afr. 2013 Mar; 24(2): 28–33. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3734881/) A part of the document used to describe the statistical methodologies employed in the work presented in the document. PERSON: Bill Baumgartner statistical analysis statistical analysis section IAO:0000645 tables section The section labelled 'tables' in a typical scientific journal article. A part of a document that contains one or more tables. PERSON: Bill Baumgartner tables tables section IAO:0000646 An identifier that denotes some postal delivery route, some aggregate of postal delivery routes or a geographical region and was created for the purpose of sorting and delivering mail. Mathias Brochhausen postal code IAO:0000647 A plan specification that if realized, is realized by the delivery of mail to some facility or mailbox within some geographical region. Mathias Brochhausen Postal delivery route IAO:0000648 A postal code that is used in the United States for the purpose of sorting and delivering mail, and that denotes some postal delivery route or some aggregate of postal delivery routes. Mathias Brochhausen ZIP code zone improvement plan code IAO:0000650 database extract, transform, and load process A planned process which takes as input a database and fills another database by extracting concretizations of information entities from the first, transforming them, and loading the transformed concretizations into the second. Alan Ruttenberg 12/21/16: Maybe this definition instead: A planned process which takes as input a database and copies concretizations from the first, optionally transforms then copies the result to the second Alan Ruttenberg 12/21/16: We don't define database in IAO, currently, as the bare word is ambiguous. Reasonable interpretations of the word might be the material entity, an information structure, an information content entity. However this definition commits, at least, to there being some material thing which bear concretizations of information entities and that there are new concretizations created during the process. We consider the ETL process in terms of information entities rather than the concretizations. No committment is made as to whether the specified output. PERSON:Alan Ruttenberg ETL WEB:https://en.wikipedia.org/wiki/Extract,_transform,_load database extract, transform, and load process IAO:0000701 descriptive data section A document part that lists and defines data variables, describes data characteristics (e.g. missing data information) and any assumptions and simplifications made. PERSON: Chen Yang PERSON: Jie Zheng https://www.equator-network.org/reporting-guidelines/prisma/ ONE ontology descriptive data section IAO:0000702 additional results section A results section that reports analyses other than main results of the study (e.g. subgroups analyses, adjusted analyses, sensitivity analyses, etc.) PERSON: Chen Yang PERSON: Jie Zheng https://www.equator-network.org/reporting-guidelines/consort/ https://www.equator-network.org/reporting-guidelines/prisma/ https://www.equator-network.org/reporting-guidelines/strobe/ ONE ontology additional results section IAO:0000703 research participants section A document part that describes human subject(s) that participated in a study (e.g. inclusion & exclusion criteria, recruitment methods, reasons for non-participation, grouping and randomisation, methods of follow-up, etc.). PERSON: Chen Yang PERSON: Jie Zheng https://www.equator-network.org/reporting-guidelines/consort/ https://www.equator-network.org/reporting-guidelines/prisma/ https://www.equator-network.org/reporting-guidelines/strobe-nut/ ONE ontology research participants section IAO:0000704 measurement methods section A methods section that describes details of data assessment methods (data measurement). PERSON: Chen Yang PERSON: Jie Zheng https://www.equator-network.org/reporting-guidelines/strobe/ ONE ontology measurement methods section IAO:0000705 research settings section A document part that describes the physical/social/cultural conditions around a research trial. PERSON: Chen Yang PERSON: Jie Zheng https://www.ncbi.nlm.nih.gov/books/NBK262175/ ONE ontology research settings section IAO:0000706 study bias section A study limitations section that describes systematic error introduced into sampling or testing by selecting or encouraging one outcome or answer over others. PERSON: Chen Yang PERSON: Jie Zheng DOI: 10.1097/PRS.0b013e3181de24bc ONE ontology study bias section IAO:0000707 graphical abstract An abstract that is pictorial summary of the main findings described in the document. PERSON: Jie Zheng PERSON: Tim Beck visual abstract https://www.elsevier.com/authors/journal-authors/graphical-abstract Biomedical literature NLP project graphical abstract IAO:0000708 A centrally registered identifier that is issued by ORCID (https://orcid.org/) and used to persistantly identify oneself as a human researcher or contributor. "You can connect your iD with your professional information — affiliations, grants, publications, peer review, and more. You can use your iD to share your information with other systems, ensuring you get recognition for all your contributions, saving you time and hassle, and reducing the risk of errors." [https://orcid.org/] This class was originally defined in Apollo_SV (http://purl.obolibrary.org/obo/APOLLO_SV_00000496) but due to it being more in scope of IAO, it was decided to add it to IAO and deprecate its Apollo_SV equivalent. (2022-10-25) http://orcid.org/0000-0002-1595-3213 ORCID ID ORCiD Open Researcher and Contributor ID Open Researcher and Contributor Identifier https://orcid.org/ https://github.com/information-artifact-ontology/IAO/issues/259 ORCID identifier IAO:0020000 identifier An information content entity that is the outcome of a dubbing process and is used to refer to one instance of entity shared by a group of people to refer to that individual entity. Justin Whorton Mathias Brochhausen proper name https://github.com/information-artifact-ontology/IAO/issues/237 Mathias Brochhausen Sep 29, 2016: The current definition has been amended from the previous version: "A proper name is an information content entity that is the outcome of a dubbing process and is used to refer to one instance of entity shared by a group of people to refer to that individual entity." to more accuratly reflect the necessary and sufficient condition on the class. (MB) identifier IAO:0020001 alphabetic letters, Chinese characters, numerical digits, punctuation marks, and the individual symbols of any of the world's writing systems An information content entity that is a fundamental unit in a written language. Justin Whorton http://en.wikipedia.org/wiki/Grapheme https://github.com/information-artifact-ontology/IAO/issues/237 Mathias Brochhausen Grapheme is not about anything and hence is likely to not be an information content entity. If a new subclass of GDC for information structure entities is created it should move there. grapheme IAO:0020010 A planned process that provides a reference to an individual entity shared by a group of subscribers to refer to that individual entity. Justin Whorton Mathias Brochhausen dubbing process naming https://github.com/information-artifact-ontology/IAO/issues/237 Mathias Brochhausen identifier creating process IAO:0020015 An identifier referring to an individual entity that is ascribed personhood by the user of the identifier. Justin Whorton Mathias Brochhausen http://en.wikipedia.org/wiki/Personal_name https://github.com/information-artifact-ontology/IAO/issues/237 Personal names "today usually comprises a given name bestowed at birth or at a young age plus a surname. It is nearly universal for a human to have a name; except in rare cases, for example feral children growing up in isolation, or infants orphaned by natural disaster for whom no written record survives.[citation needed] The Convention on the Rights of the Child specifies that a child has the right from birth to a name. Certain isolated tribes, such as the Machiguenga of the Amazon, also lack personal names." (http://en.wikipedia.org/wiki/Personal_name) Personal names to not include names of fictional characters, e.g. Sherlock Holmes. Sep 29, 2016: The comment that including the wikipedia definition of personal name is not to be interpreted in a way that restricts this class to only contain strings of letters. A numerical or alphanumerical identifier that denotes a human is being is a personal name, too. (MB) personal name IAO:0020016 A personal name that specifies and differentiates between members of a group of individuals, especially in a family, all of whose members usually share the same family name (surname). A given name is purposefully given, usually by a child's parents at or near birth, in contrast to an inherited one such as a family name Justin Whorton Mathias Brochhausen first name http://en.wikipedia.org/wiki/Given_name https://github.com/information-artifact-ontology/IAO/issues/237 given name IAO:0020017 An identifier that is typically a part of a person's name which has been passed, according to law or custom, from one or both parents to their children. Justin Whorton Mathias Brochhausen last name surname http://en.wikipedia.org/wiki/Family_name https://github.com/information-artifact-ontology/IAO/issues/237 family name IAO:0020020 An information content entity that is a collection of other information content entities that has been created to identify or annotate things in a specified domain, and where the intention of its creators is that the collection has a one-to-one correspondence with those things. Alan Ruttenberg Justin Whorton Mathias Brochhausen code map code system codeset coding system controlled vocabulary https://github.com/information-artifact-ontology/IAO/issues/237 Alan Ruttenberg Clint Dowland Matt Diller Sarah Bost William R. Hogan Code sets might include non-entities/things (e.g. missing thumbs). Does not imply absence vs. presence of any taxonomy. Does not imply that aggregated entities denote particulars, universals, or defined classes (a.k.a. attributive collections) or even that they denote only one of these three types of entities. Each aggregated entity is often (but not necessarily) associated with a text string—variously called a “description,” “name,” “title,” or “label”—that helps humans reach the target of denotation. When there is no such string, it is almost always because the entities take the form of human language words. For example, a “sex” or “gender” code set could contain “MALE” and “FEMALE,” or even “M” and “F” (by convention, we understand what these mean). For National Drug Codes (NDCs) and similar code sets, there doesn’t even have to be a single, fully-concretized copy somewhere (for example, for NDCs there is no centralized database or repository where they all live as one instance of concretization of code set). The code set can be “distributively” concretized. This seems like an unusual exception, but it also likely applies to Universal Product Codes (UPCs) and their follow on Global Trade Item Numbers (GTINs). For each given domain, there can potentially exist multiple code sets. The multiplicity of code sets is partially due to the different specific purposes of those code sets. Many code sets are created for a specific purpose in addition to merely identifying or annotating core ideas of a specified domain. The information content entities do not denote each other. code set IAO:8000000 ontology module I have placed this under 'data about an ontology part', but this can be discussed. I think this is OK if 'part' is interpreted reflexively, as an ontology module is the whole ontology rather than part of it. ontology file This class and it's subclasses are applied to OWL ontologies. Using an rdf:type triple will result in problems with OWL-DL. I propose that dcterms:type is instead used to connect an ontology URI with a class from this hierarchy. The class hierarchy is not disjoint, so multiple assertions can be made about a single ontology. ontology module IAO:8000001 base ontology module An ontology module that comprises only of asserted axioms local to the ontology, excludes import directives, and excludes axioms or declarations from external ontologies. base ontology module IAO:8000002 editors ontology module An ontology module that is intended to be directly edited, typically managed in source control, and typically not intended for direct consumption by end-users. source ontology module editors ontology module IAO:8000003 main release ontology module An ontology module that is intended to be the primary release product and the one consumed by the majority of tools. TODO: Add logical axioms that state that a main release ontology module is derived from (directly or indirectly) an editors module main release ontology module IAO:8000004 bridge ontology module An ontology module that consists entirely of axioms that connect or bridge two distinct ontology modules. For example, the Uberon-to-ZFA bridge module. bridge ontology module IAO:8000005 import ontology module A subset ontology module that is intended to be imported from another ontology. TODO: add axioms that indicate this is the output of a module extraction process. import file import ontology module IAO:8000006 subset ontology module An ontology module that is extracted from a main ontology module and includes only a subset of entities or axioms. ontology slim subset ontology subset ontology module IAO:8000007 curation subset ontology module A subset ontology that is intended as a whitelist for curators using the ontology. Such a subset will exclude classes that curators should not use for curation. curation subset ontology module IAO:8000008 analysis ontology module An ontology module that is intended for usage in analysis or discovery applications. analysis subset ontology module IAO:8000009 single layer ontology module A subset ontology that is largely comprised of a single layer or strata in an ontology class hierarchy. The purpose is typically for rolling up for visualization. The classes in the layer need not be disjoint. ribbon subset single layer subset ontology module IAO:8000010 exclusion subset ontology module A subset of an ontology that is intended to be excluded for some purpose. For example, a blacklist of classes. antislim exclusion subset ontology module IAO:8000011 external import ontology module An imported ontology module that is derived from an external ontology. Derivation methods include the OWLAPI SLME approach. external import external import ontology module IAO:8000012 species subset ontology module A subset ontology that is crafted to either include or exclude a taxonomic grouping of species. taxon subset species subset ontology module IAO:8000013 reasoned ontology module An ontology module that contains axioms generated by a reasoner. The generated axioms are typically direct SubClassOf axioms, but other possibilities are available. reasoned ontology module IAO:8000014 generated ontology module An ontology module that is automatically generated, for example via a SPARQL query or via template and a CSV. TODO: Add axioms (using PROV-O?) that indicate this is the output-of some reasoning process generated ontology module IAO:8000015 template generated ontology module An ontology module that is automatically generated from a template specification and fillers for slots in that template. template generated ontology module IAO:8000016 taxonomic bridge ontology module taxonomic bridge ontology module IAO:8000017 ontology module subsetted by expressivity ontology module subsetted by expressivity IAO:8000018 obo basic subset ontology module A subset ontology that is designed for basic applications to continue to make certain simplifying assumptions; many of these simplifying assumptions were based on the initial version of the Gene Ontology, and have become enshrined in many popular and useful tools such as term enrichment tools. Examples of such assumptions include: traversing the ontology graph ignoring relationship types using a naive algorithm will not lead to cycles (i.e. the ontology is a DAG); every referenced term is declared in the ontology (i.e. there are no dangling clauses). An ontology is OBO Basic if and only if it has the following characteristics: DAG Unidirectional No Dangling Clauses Fully Asserted Fully Labeled No equivalence axioms Singly labeled edges No qualifier lists No disjointness axioms No owl-axioms header No imports obo basic subset ontology module IAO:8000019 ontology module subsetted by OWL profile ontology module subsetted by OWL profile IAO:8000020 EL++ ontology module EL++ ontology module OBI_0000011s OBI_0000011 OBI:0000011 planned process planned process Injecting mice with a vaccine in order to test its efficacy A process that realizes a plan which is the concretization of a plan specification. A processual entity that realizes a plan which is the concretization of a plan specification. 'Plan' includes a future direction sense. That can be problematic if plans are changed during their execution. There are however implicit contingencies for protocols that an agent has in his mind that can be considered part of the plan, even if the agent didn't have them in mind before. Therefore, a planned process can diverge from what the agent would have said the plan was before executing it, by adjusting to problems encountered during execution (e.g. choosing another reagent with equivalent properties, if the originally planned one has run out.) Bjoern Peters branch derived planned process OBI_0000047s OBI_0000047 Is a material entity that is created or changed during material processing. OBI OBI consortium processed material OBI:0000066 investigation a planned process that consists of parts: planning, study design execution, documentation and which produce conclusion(s). investigation OBI_0000227s OBI_0000227 OBI:0000227 data encoding storage of measurement results from an assay into a text file, such as a documenting process to encode an information entity into a digital document PlanAndPlannedProcess Branch OBI branch derived data encoding OBI_0000245s OBI_0000245 OBI:0000245 organization PMID: 16353909.AAPS J. 2005 Sep 22;7(2):E274-80. Review. The joint food and agriculture organization of the United Nations/World Health Organization Expert Committee on Food Additives and its role in the evaluation of the safety of veterinary drug residues in foods. An organization is a continuant entity which can play roles, has members, and has a set of organization rules. Members of organizations are either organizations themselves or individual people. Members can bear specific organization member roles that are determined in the organization rules. The organization rules also determine how decisions are made on behalf of the organization by the organization members. PERSON: Alan Ruttenberg PERSON: Bjoern Peters PERSON: Philippe Rocca-Serra PERSON: Susanna Sansone GROUP: OBI organization OBI_0000272s OBI_0000272 OBI:0000272 http://purl.obofoundry.org/obo/obi.owl protocol protocol OBI_0000338s OBI_0000338 OBI:0000338 interpreting data Identifiying and removing outliers from data by eye. Examining data to and deriving a new hypothesis. the process of evaluating the data gathered in an investigation in the context of literature knowledge with the objective to generate more general conclusions or to identify what additional data is necessary to draw conclusions the process of evaluating the data gathered in an investigation in the context of literature knowledge with the objective to generate more general conclusions or to identify what additional data is necessary to draw conclusions PERSON: Bjoern Peters PERSON: Jennifer Fostel Bjoern Peters http://purl.obofoundry.org/obo/obi.owl interpreting data interpreting data OBI_0000339s OBI_0000339 OBI:0000339 planning the process of a scientist thinking about and deciding what reagents to use as part of a protocol for an experiment. a process of creating or modifying a plan. Bjoern Peters Bjoern Peters PPPB branch planning planning OBI:0000471 study design execution a planned process that carries out a study design study design execution OBI_0000658s OBI_0000658 OBI:0000658 data representational model gene regulatory graph model phylogenetic tree protein interaction network Data representational model is an information content entity of the relationships between data items. A data representational model is encoded in a data format specification such as for cytoscape or biopax. Melanie Courtot data structure data structure specification GROUP: OBI data representational model OBI_0000968s OBI_0000968 A device is a processed material which is designed to perform some function or functions OBI OBI consortium device OBI_0200000s OBI_0200000 OBI:0200000 data transformation The application of a clustering protocol to microarray data or the application of a statistical testing method on a primary data set to determine a p-value. A data transformation is a process which produces output data from input data A planned process that produces output data from input data. Elisabetta Manduchi Helen Parkinson James Malone Melanie Courtot Philippe Rocca-Serra Richard Scheuermann Ryan Brinkman Tina Hernandez-Boussard data analysis data processing Branch editors data transformation OBI_0200111s OBI_0200111 OBI:0200111 data visualization Generation of a heatmap from a microarray dataset An planned process that creates images, diagrams or animations from the input data. Elisabetta Manduchi James Malone Melanie Courtot Tina Boussard data encoding as image visualization PERSON: Elisabetta Manduchi PERSON: James Malone PERSON: Melanie Courtot PERSON: Tina Boussard data visualization OBI_0200166s OBI_0200166 OBI:0200166 data transformation objective normalize objective A data transformation objective is an objective specification that a data transformation may have towards which the realization of that transformation is directed. James Malone PERSON: James Malone data transformation objective OBI_0302838s OBI_0302838 OBI:0302838 validated information PMID: 20084519: "..Three of four interactions were validated via functional magnetic resonance imaging (fMRI) in an independent sample of healthy controls;..." an information content entity which results from a validation process aimed at confirming a claim, a finding or a predicted information entity about a material entity or a process by experimental means. Person:Philippe Rocca-Serra OBI validated information OBI_0302874s OBI_0302874 OBI:0302874 edited document The OBI manuscript is (much) edited imformation A document which is the output of a document editing process Person:Bjoern Peters Philippe Rocca-Serra edited document OBI_0302908s OBI_0302908 OBI:0302908 document editing is a planned process with specified input original document and specified output edited document Philippe Rocca-Serra and OBI consortium adapted from wikipedia document editing OBI_0302910s OBI_0302910 OBI:0302910 prediction Prediction of TF target sites based on atomistic models of protein-DNA complexes. BMC Bioinformatics. 2008 Oct 16;9(1):436. PMID: 18922190 a process by which an event or an entity is described before it actually happens or is being discovered and identified. Philippe Rocca-Serra OBI prediction OBI_0302911s OBI_0302911 OBI:0302911 validation PMID: 18557814 . Chemical and genetic validation of dihydrofolate reductase-thymidylate synthase as a drug target in African trypanosomes. Mol Microbiol. 2008 Jun 16. a planned process with objective to check that the accuracy or the quality of a claim or prediction satisfies some criteria and which is assessed by comparing with independent results Philippe Rocca-Serra adapted from wordnet (wkipedia) http://purl.obofoundry.org/obo/obi.owl validation OBI_0400107s OBI_0400107 A computer is an instrument which manipulates (stores, retrieves, and processes) data according to a list of instructions. OBI OBI consortium computer OBI_0500000s OBI_0500000 OBI:0500000 study design a matched pairs study design describes criteria by which subjects are identified as pairs which then undergo the same protocols, and the data generated is analyzed by comparing the differences between the paired subjects, which constitute the results of the executed study design. A plan specification comprised of protocols (which may specify how and what kinds of data will be gathered) that are executed as part of an investigation and is realized during a study design execution. A study design is a plan specification comprised of protocols (which may specify how and what kinds of data will be gathered) that are executed as part of an investigation and is realized during a study design execution. Editor note: there is at least an implicit restriction on the kind of data transformations that can be done based on the measured data available. PERSON: Chris Stoeckert experimental design study design OBI_0600008s OBI_0600008 OBI:0600008 acquisition the process of obtaining a continuant from a source. Bjoern Peters IEDB acquisition acquisition OBI_0600013s OBI_0600013 OBI:0600013 data acquisition Gathering all influenza HA sequences from GenBank, Retrieveing HLA allele frequencies in the North American populations from dbMHC an acquisition in which information acquisition from an organization that provides information. This is not an assay. It consists of specifiying a query what information is desired, putting this query to an organization, and retrieveing the requested information from the organization. Bjoern Peters data collection OBI branch derived data acquisition PATO:0000051 morphology A quality of a single physical entity inhering in the bearer by virtue of the bearer's size or shape or structure. morphology PATO:0000122 length A 1-D extent quality which is equal to the distance between two points. length PATO:0000125 mass A physical quality that inheres in a bearer by virtue of the proportion of the bearer's amount of matter. mass PATO:0001018 physical quality A quality of a physical entity that exists through action of continuants at the physical level of organisation in relation to other entities. physical quality PATO:0001241 physical object quality A quality which inheres in a continuant. physical object quality UO:0000001 length unit length unit UO:0000002 mass unit mass unit UO:0000003 time unit time unit SWO_0000393s SWO_0000393 http://www.ebi.ac.uk/efo/swo Information processing is a process in which input information is analysed or transformed in order to produce information as output. James Malone information processing oboInOwl:ObsoleteClass ProcessualEntities ProcessualEntity span:ProcessualEntity processual_entity OntoDM_000000s OntoDM_000000 OntoDM_000000 prediction_error OntoDM_000001s OntoDM_000001 OntoDM_000001 A predictive modelling ensemble is a realizable entity that is a concretization of a predictive model ensemble specification specification and it is a specified output of a predictive modeling algorithm execution. predictive models ensemble OntoDM_000002 feature-based unlabeled data stream OntoDM_000003 structure-based unlabeled data stream OntoDM_000004s OntoDM_000004 OntoDM_000004 A probability distribution ensemble is a realizable entity that is a concretization of a probability distribution ensemble specification and it is a specified output of a probability distribution estimation algorithm execution. probability distribution ensemble OntoDM_0000045s OntoDM_0000045 OntoDM_0000045 SubBag OntoDM_000005 transactional data stream OntoDM_000006s OntoDM_000006 OntoDM_000006 OntoDM_000008s OntoDM_000008 OntoDM_000008 prototype OntoDM_000009s OntoDM_000009 OntoDM_000009 probability distribution representation OntoDM_000011s OntoDM_000011 OntoDM_000011 Set of distance functions is a collection of distance functions. distance functions set OntoDM_000014s OntoDM_000014 OntoDM_000014 Evaluation functions measure the validity of generalizations on a given set of data. evaluation function specification OntoDM_000015s OntoDM_000015 OntoDM_000015 An clustering ensemble is a realizable entity that is a concretization of a clusterings ensemble specification and it is a specified output of a clustering algorithm execution. clustering ensemble OntoDM_000016s OntoDM_000016 OntoDM_000016 OntoDM_000017s OntoDM_000017 OntoDM_000017 test set role OntoDM_000020s OntoDM_000020 OntoDM_000020 A pattern P on type T is a boolean function on objects of type T, i.e has the signature p::T-->boolean. OntoDM_000021s OntoDM_000021 OntoDM_000021 complex constraint OntoDM_000022s OntoDM_000022 OntoDM_000022 pattern quality OntoDM_000027s OntoDM_000027 OntoDM_000027 output datatype specification is a datatype specification that denotes the datatype of the data on the output part of the dataset. The output data is used for predictive modeling tasks. output data specification OntoDM_000029s OntoDM_000029 OntoDM_000029 predictive model evaluation function specification OntoDM_000031s OntoDM_000031 OntoDM_000031 a dataset specification is a data item specification about a dataset defined with a datatype specification of the data examples aggregated in the dataset. dataset specification OntoDM_000033s OntoDM_000033 OntoDM_000033 data mining algorithm execution OntoDM_000034s OntoDM_000034 OntoDM_000034 Generalization specification of a directive informational entity class that specifies the type of generalization. It includes information about the types of data used to produced the generalization and the language in which the generalization is expressed. represents class of generalizations as in Dzeroski paper generalization specification OntoDM_000036s OntoDM_000036 OntoDM_000036 A predictive model M for types Td and Tc is a function that takes an object of type Td and returns and object of type Tc, i.e. has the signature m::Td-->Tc. predictive model OntoDM_000037s OntoDM_000037 OntoDM_000037 A ensemble of generalizations specification is a generalization specification and denotes a type of generalization that is produced by a ensemble algorithm. This algorithm produces a set of generalizations at its output. ensemble specification OntoDM_000038s OntoDM_000038 OntoDM_000038 A data mining algorithm is an algorithm that solves a data mining task and as a results outputs a generalization. It is usually published in some document (journal publication or technical report). data mining algorithm 1 OntoDM_000041s OntoDM_000041 OntoDM_000041 bootstrap sampling process OntoDM_000042s OntoDM_000042 OntoDM_000042 OntoDM_000043s OntoDM_000043 OntoDM_000043 subsumtion based laguage constraint OntoDM_000044s OntoDM_000044 OntoDM_000044 public available resource OntoDM_000047s OntoDM_000047 OntoDM_000047 OntoDM_000048s OntoDM_000048 OntoDM_000048 generalization interpreter specification OntoDM_000049s OntoDM_000049 OntoDM_000049 OntoDM_000050s OntoDM_000050 OntoDM_000050 An ensemble of generalizations is a realizable entity that is a concretization of an ensemble specification and it is a specified output of a data mining algorithm execution. ensemble of generalizations OntoDM_000051s OntoDM_000051 OntoDM_000051 predictive model quality OntoDM_000052s OntoDM_000052 OntoDM_000052 mathematical function specification OntoDM_000053s OntoDM_000053 OntoDM_000053 a fold is a dataset that is an output of a cross validation sampling process. fold OntoDM_000059s OntoDM_000059 OntoDM_000059 status OntoDM_000063s OntoDM_000063 OntoDM_000063 probability distribution quality OntoDM_000069s OntoDM_000069 OntoDM_000069 optimization evaluation constraint OntoDM_000070s OntoDM_000070 OntoDM_000070 An evaluation datum is a data item that is a specified output of generalization evaluation process. evaluation datum OntoDM_000071s OntoDT_0000001s OntoDM_000071 OntoDT_0000001 OntoDM_000071 representation OntoDM_000072s OntoDM_000072 OntoDM_000072 Clustering algorithm is a data mining algorithm that solves a clustering task and as a result produces a clustering. clustering algorithm OntoDM_000075s OntoDM_000075 OntoDM_000075 OntoDM_000076s OntoDM_000076 OntoDM_000076 A single generalization is a realizable entity that is a concretization of a single generalization specification and it is a specified output of a data mining algorithm execution. single generalization OntoDM_000078s OntoDM_000078 OntoDM_000078 A patten specification is a single generalization specification and denotes a pattern P on type T which is a boolean funtion on objects of type T. pattern specification OntoDM_000081s OntoDM_000081 OntoDM_000081 mean_squared_error OntoDM_000084s OntoDM_000084 OntoDM_000084 generalization evaluation OntoDM_000085s OntoDM_000085 OntoDM_000085 predictive_modeling_algorithm_implementation OntoDM_000087s OntoDM_000087 OntoDM_000087 The task of estimating the joint probability distribution involves constructing a probability disctribution given a set of data of a certain datatype. batch probability distribution estimation task OntoDM_000089s OntoDM_000089 OntoDM_000089 language cost function constraint OntoDM_000092s OntoDM_000092 OntoDM_000092 The task of pattern discovery is to find all local patterns from a given pattern language that satisfy the required conditions. batch pattern discovery task OntoDM_000095s OntoDM_000095 OntoDM_000095 OntoDM_000096s OntoDM_000096 OntoDM_000096 OntoDM_000098s OntoDM_000098 OntoDM_000098 A data mining task is an objective specification that specifies the objective that a data mining algorithm needs to achieve when executed on a dataset to produce as output a generalization. data mining task OntoDM_000099s OntoDM_000099 OntoDM_000099 query specification OntoDM_000100s OntoDM_000100 OntoDM_000100 discreteness OntoDM_000101s OntoDM_000101 OntoDM_000101 soft language cost function constraint OntoDM_000102s OntoDM_000102 OntoDM_000102 probability distribution execution OntoDM_000103s OntoDM_000103 OntoDM_000103 hard language cost function constraint OntoDM_000105s OntoDM_000105 OntoDM_000105 distance OntoDM_000106s OntoDM_000106 OntoDM_000106 Scoring functions often combine evaluation functions and language cost functions. scoring function OntoDM_000107s OntoDM_000107 OntoDM_000107 penalty function OntoDM_000109s OntoDM_000109 OntoDM_000109 sampling_objective OntoDM_000111s OntoDM_000111 OntoDM_000111 OntoDM_000112s OntoDM_000112 OntoDM_000112 Clustering specification is a single generalization specification is a generalization specification and denotes a type of generalization that models the mapping of a set of objects S of type T from S to a set of natural numbers {1,...K}. This generalization is obtained by appliing a clustering algorithm on a set of data. clustering specification OntoDM_000114s OntoDM_000114 OntoDM_000114 OntoDM_000118s OntoDM_000118 OntoDM_000118 Defines properties of a generalization generalization quality OntoDM_000121s OntoDM_000121 OntoDM_000121 a bag is a dataset that is an output of a bootstrap sampling process bag OntoDM_000122s OntoDM_000122 OntoDM_000122 Function that is used to combine other functions combining function OntoDM_000125s OntoDM_000125 OntoDM_000125 integrated_average_squared_error OntoDM_000127s OntoDM_000127 OntoDM_000127 clustering algorithm execution OntoDM_000128s OntoDM_000128 OntoDM_000128 a feature set specification is a data item specification that specifies a set of features used in a specific data mining task. feature set specification OntoDM_000130s OntoDM_000130 OntoDM_000130 A parameter is a quality of an algorithm implementation,and it refers to one of the pieces of data provided as input to the algorithm implementation. The parameter influences the flow of the execution of algorithm realized by a data mining operator that has information about the specific parameter setting used in the execution process . parameter OntoDM_000132s OntoDM_000132 OntoDM_000132 A background knowledge is a data item that is input to data mining algorithm along with the data examples, and represents domain information that is essential to proper functioning of an algorithm. Background knowledge can be seen as a set of mappings that generate new features bi:T-->Ti. background knowledge OntoDM_000134s OntoDM_000134 OntoDM_000134 clustering_algorithm_implementation OntoDM_000137s OntoDM_000137 OntoDM_000137 constraint specification OntoDM_000138 feature-based data example OntoDM_000139 feature-based DM-dataset OntoDM_000140s OntoDM_000140 OntoDM_000140 dataset representation OntoDM_000142s OntoDM_000142 OntoDM_000142 aggregate function OntoDM_000143s OntoDM_000143 OntoDM_000143 dataset sampling OntoDM_000144s OntoDM_000144 OntoDM_000144 Dataset is an aggregate of data examples. DM-dataset OntoDM_000145s OntoDM_000145 OntoDM_000145 A constant value of some property of a generalization. It is used to define constraints. constraint threshold OntoDM_000149s OntoDM_000149 OntoDM_000149 holdout sampling process OntoDM_000155s OntoDM_000155 OntoDM_000155 frequency OntoDM_000160s OntoDM_000160 OntoDM_000160 Predictive modeling algorithm is a data mining algorithm that solves a predictive modeling task and as a result produces a predictive model. predictive modeling algorithm OntoDM_000167s OntoDM_000167 OntoDM_000167 pattern set execution OntoDM_000168s OntoDM_000168 OntoDM_000168 A data specifcation is-a specifcation entity that specifies on which concrete part of the data the datatype applies to. data specification OntoDM_000170s OntoDM_000170 OntoDM_000170 optimization language cost function constraint OntoDM_000172s OntoDM_000172 OntoDM_000172 The output data type should be the same as the input datatype because IQ asc as filters This should be put as a axiom or rule in PROLOG inductive query OntoDM_000173s OntoDM_000173 OntoDM_000173 The language cost functions are used in language constraints concern the data part of generalizations. Most often they are related to the size/complexity of generalizations. language cost function OntoDM_000175s OntoDM_000175 OntoDM_000175 predictive modelling algorithm execution OntoDM_000178s OntoDM_000178 OntoDM_000178 A distance function d for type T is a mapping from apirs of objects of type T to non negative reals. It has to satisfy 3 main properties distance function OntoDM_000179s OntoDM_000179 OntoDM_000179 An pattern set ensemble is a realizable entity that is a concretization of a pattern set ensemble specification and it is a specified output of a pattern discovery algorithm execution. pattern set ensemble OntoDM_000182s OntoDM_000182 OntoDM_000182 OntoDM_000185s OntoDM_000185 OntoDM_000185 separate test set evaluation process OntoDM_000191s OntoDM_000191 OntoDM_000191 database OntoDM_000192s OntoDM_000192 OntoDM_000192 Pattern discovery algorithm is a data mining algorithm that solves a pattern discovery task and as a result produces a set of patterns. pattern discovery algorithm OntoDM_000195s OntoDM_000195 OntoDM_000195 training set evaluation process OntoDM_000196s OntoDM_000196 OntoDM_000196 algorithm_component_specification OntoDM_000197s OntoDM_000197 OntoDM_000197 data creation query OntoDM_000199s OntoDM_000199 OntoDM_000199 cost function OntoDM_000200s OntoDM_000200 OntoDM_000200 prototype function OntoDM_000201s OntoDM_000201 OntoDM_000201 not_discrete OntoDM_000207s OntoDM_000207 OntoDM_000207 discrete OntoDM_000209s OntoDM_000209 OntoDM_000209 data transformation with generalization query OntoDM_000212s OntoDM_000212 OntoDM_000212 language constraint OntoDM_000214s OntoDM_000214 OntoDM_000214 draft OntoDM_000219s OntoDM_000219 OntoDM_000219 clustering evaluation function specification OntoDM_000223s OntoDM_000223 OntoDM_000223 clustering representation OntoDM_000224s OntoDM_000224 OntoDM_000224 generalization selection query OntoDM_000228s OntoDM_000228 OntoDM_000228 predictive model specification is a single generalization specification and denotes a type of generalization that represents a mapping taking objects of type Td and returns objects of type To. predictive model specification OntoDM_000229s OntoDM_000229 OntoDM_000229 data mining algorithm implementation OntoDM_000232s OntoDM_000232 OntoDM_000232 OntoDM_000233s OntoDM_000233 OntoDM_000233 full fledged query OntoDM_000234s OntoDM_000234 OntoDM_000234 clustering execution OntoDM_000235s OntoDM_000235 OntoDM_000235 In the task of predictive modeling, we are given a dataset that consists of examples of the form (d,o), where d is of type Td and each o is of type To. To learn a predictive model means to find a mapping from description to output m::Td--->To that fits data closly. predictive modelling task OntoDM_000237s OntoDM_000237 OntoDM_000237 soft evaluation constraint OntoDM_000238s OntoDM_000238 OntoDM_000238 OntoDM_000239s OntoDM_000239 OntoDM_000239 data selection query OntoDM_000243s OntoDM_000243 OntoDM_000243 example weight OntoDM_000247s OntoDM_000247 OntoDM_000247 Descriptive datatype specification is a data item specification that denotes the datatype of the data from the descriptive part of a dataset. descriptive data specification OntoDM_000249s OntoDM_000249 OntoDM_000249 evaluation constraint OntoDM_000250s OntoDM_000250 OntoDM_000250 pattern representation OntoDM_000253s OntoDM_000253 OntoDM_000253 Probability distribution estimation algorithm is a data mining algorithm that solves a probability distribution estimation task and as a result produces a probability distribution. probability distribution estimation algorithm 1 OntoDM_000255s OntoDM_000255 OntoDM_000255 cross validation sampling process OntoDM_000256s OntoDM_000256 OntoDM_000256 generalization representation OntoDM_000258s OntoDM_000258 OntoDM_000258 background knowledge representation OntoDM_000259s OntoDM_000259 OntoDM_000259 pattern discovery evaluation function specification OntoDM_000260s OntoDM_000260 OntoDM_000260 N fold validation evaluation process OntoDM_000261s OntoDM_000261 OntoDM_000261 knowledge discovery scenario objective OntoDM_000264s OntoDM_000264 OntoDM_000264 The task of clustering in general is concerned with grouping objects into classes of similar objects. Given a set of examples (object descriptions), the task of clustering is to partition these examples into subsets, called clusters. batch clustering task OntoDM_000265s OntoDM_000265 OntoDM_000265 probability_distribution_estimation_algorithm_implementation OntoDM_000266s OntoDM_000266 OntoDM_000266 selection composition of generalizations query OntoDM_000269s OntoDM_000269 OntoDM_000269 train set role OntoDM_000270s OntoDM_000270 OntoDM_000270 primitive constraint OntoDM_000271s OntoDM_000271 OntoDM_000271 probability distribution evaluation function specification OntoDM_000273s OntoDM_000273 OntoDM_000273 generalizations and data from generalizations query OntoDM_000276s OntoDM_000276 OntoDM_000276 hard evaluation constraint OntoDM_000280s OntoDM_000280 OntoDM_000280 predictive model representation OntoDM_000282s OntoDM_000282 OntoDM_000282 predictive model evaluation OntoDM_000285s OntoDM_000285 OntoDM_000285 A probability distribution specification is a single generalization specification and denotes a type of generalization that is a mapping from objects of type T to non-negative reals. This generalization is an output of a probability distribution estimation algorithm. probability distribution specification OntoDM_000287s OntoDM_000287 OntoDM_000287 pattern discovery algorithm execution OntoDM_000288s OntoDM_000288 OntoDM_000288 pattern_discovery_algorithm_implementation OntoDM_000290s OntoDM_000290 OntoDM_000290 OntoDM_000291s OntoDM_000291 OntoDM_000291 refinement operator OntoDM_000293s OntoDM_000293 OntoDM_000293 intra_cluster_variance OntoDM_000294s OntoDM_000294 OntoDM_000294 probability_distribution_scoring_function OntoDM_000297s OntoDM_000297 OntoDM_000297 generalization execution OntoDM_000298s OntoDM_000298 OntoDM_000298 A feature specification is a data item specification that specifies a primitive data feature (belonging to a primitive datatype), used in propositional data mining where the descriptive datatype is usually a tuple of primitive features. feature specification OntoDM_000299s OntoDM_000299 OntoDM_000299 OntoDM_000300s OntoDM_000300 OntoDM_000300 generalizations and data from data query OntoDM_000302s OntoDM_000302 OntoDM_000302 optimization function OntoDM_000306s OntoDM_000306 OntoDM_000306 probability distribution estimation algorithm execution OntoDM_000309s OntoDM_000309 OntoDM_000309 predictive model execution OntoDM_000316s OntoDM_000316 OntoDM_000316 A clustering C on a set of objects S of type T is a function from S to {1,...,k} where k is the number of clusters. clustering OntoDM_000333s OntoDM_000333 OntoDM_000333 itemized list OntoDM_000343s OntoDM_000343 OntoDM_000343 A generalization is a realizable entity that is a concretization of a generalization specification and it is a specified output of a data mining algorithm execution. generalization OntoDM_001019s OntoDM_001019 OntoDM_001019 tuple output specification OntoDM_001020s OntoDM_001020 OntoDM_001020 tuple of booleanORdiscrete output specification OntoDM_001021s OntoDM_001021 OntoDM_001021 set output specification output specification OntoDM_001022s OntoDM_001022 OntoDM_001022 booleanORdiscrete output data specification OntoDM_001334s OntoDM_001334 OntoDM_001334 Regression algorithm is a data mining algorithm that solves a regression task and as a result produces a regression model. regression algorithm OntoDM_003932s OntoDM_003932 OntoDM_003932 A predictive model for primitive output is a predictive model specification and denotes predictive models that are built on data having primitive datatype on the output part. predictive model for primitive output OntoDM_004843s OntoDM_004843 OntoDM_004843 dataset role OntoDM_020420s OntoDM_020420 OntoDM_020420 LCPN DAG-based hierarchical classification algorithm is a data mining algorithm that solves a DAG-based hierarchical classification task and as a result produces a hierarchical classification model using a local classifier per parent node (LCPN) approach. LCPN DAG based HC algorithm OntoDM_036834s OntoDM_036834 OntoDM_036834 LCPN tree-based hierarchical classification algorithm for multiple path and mandatory leaf node prediction is a data mining algorithm that solves a tree-based hierarchical classification task with multiple label paths and full depth labeling and as a result produces a hierarchical classification model using a local classifier per parent node (LCPN) approach. LPCN tree based HC algorithm for multiple path and mandatory leaf node prediction OntoDM_038162s OntoDM_038162 OntoDM_038162 data mining operator OntoDM_039503s OntoDM_039503 OntoDM_039503 A binary classification model is a classification model and denotes predictive models that are built on data having a boolean datatype on the output part, and set of features (represented by a descriptive tuple of primitives) on the descriptive part. binary classification model OntoDM_056700s OntoDM_056700 OntoDM_056700 DAG based hierarchical classification task with multiple label paths and full depth labeling is a DAG based hierarchical classification task where the objective is to predict a set of labels organized in a DAG (represented with a output DAG with boolean edges and discrete nodes) from a set of features (represented by a descriptive tuple of primitives datatype), where the data instances are allowed to have multiple paths of labels and all instances have full depth of labeling. DAG based hierarchical classification task with multiple label paths and full depth labeling OntoDM_057491s OntoDM_057491 OntoDM_057491 DAG based hierarchical classification task with single label paths is a DAG based hierarchical classification task where the objective is to predict a set of labels organized in a DAG (represented with a output DAG with boolean edges and discrete nodes) from a set of features (represented by a descriptive tuple of primitives datatype), where the data instances are allowed to have single paths of labels. DAG based hierarchical classification task with single label paths OntoDM_063973s OntoDM_063973 OntoDM_063973 DAG-based hierarchical classification dataset is a dataset specification of a labeled dataset with tuple of primitives datatype (specified with the feature set specification) on the descriptive part and a labeled DAG datatype with boolean edges and discrete nodes on the output part of the data. DAG-based hierarchical classification dataset OntoDM_067028s OntoDM_067028 OntoDM_067028 Multi-target binary classification model is a multi-target classification model and denotes predictive models that are built on data having a tuple of boolean (set of output features) on the output part, and set of features (represented by a descriptive tuple of primitives) on the descriptive part. multi-target binary classification model OntoDM_071450s OntoDM_071450 OntoDM_071450 LCL DAG-based hierarchical classification algorithm is a data mining algorithm that solves a DAG-based hierarchical classification task and as a result produces a hierarchical classification model using a local classifier per level (LCL) approach. LCL DAG based HC algorithm OntoDM_078701s OntoDM_078701 OntoDM_078701 transactional dataset is a dataset specification of unlabeled dataset with a set of discrete datatype on the descriptive part of the data. transactional dataset OntoDM_081165s OntoDM_081165 OntoDM_081165 LCN tree-based hierarchical classification algorithm for multiple path prediction is a data mining algorithm that solves a tree-based hierarchical classification task with multiple label paths and as a result produces a hierarchical classification model using a local classifier per node (LCN) approach. LCN tree based HC algorithm for multiple path prediction OntoDM_086891s OntoDM_086891 OntoDM_086891 LCL DAG-based hierarchical classification algorithm for single path and mandatory leaf node prediction is a data mining algorithm that solves a DAG-based hierarchical classification task with single label paths and full depth labeling and as a result produces a hierarchical classification model using a local classifier per level (LCL) approach. LCL DAG based HC algorithm for single path and mandatory leaf node prediction OntoDM_099826s OntoDM_099826 OntoDM_099826 predictive models ensemble specification is a ensemble specification and denotes a type of generalization that is produced by a predictive model ensemble algorithm. This algorithm produces a collection of predictive models at its output. predictive models ensemble specification OntoDM_10000000135 data stream OntoDM_10000000136 data stream example OntoDM_10000000137 data stream representation OntoDM_10000000138 data stream quality OntoDM_101020s OntoDM_101020 OntoDM_101020 tag OntoDM_104594s OntoDM_104594 OntoDM_104594 LCN DAG-based hierarchical classification algorithm for single path prediction is a data mining algorithm that solves a DAG-based hierarchical classification task with single label paths and as a result produces a hierarchical classification model using a local classifier per node (LCN) approach. LCN DAG based HC algorithm for single path prediction OntoDM_107836s OntoDM_107836 OntoDM_107836 Hierarchical classification model is afeature-based predictive model for structured output and denotes predictive models that are built on data having a labeled graph datatype on the output part, and set of features (represented by a descriptive tuple of primitives) on the descriptive part. hierarchical classification model OntoDM_108244s OntoDM_108244 OntoDM_108244 Multi-class classification is a data mining algorithm that solves a multi-class classification task and as a result produces a multi-class classification model. multi-class classification algorithm OntoDM_108452s OntoDM_108452 OntoDM_108452 GC DAG based HC algorithm for multiple path and mandatory leaf node prediction OntoDM_112569s OntoDM_112569 OntoDM_112569 algorithm implementation OntoDM_112772s OntoDM_112772 OntoDM_112772 A classification model is a feature-based predictive model for primitive output and denotes predictive models that are built on data having boolean or discrete datatype on the output part, and set of features (represented by a descriptive tuple of primitives) on the descriptive part. classification model OntoDM_114697s OntoDM_114697 OntoDM_114697 Multi-target prediction task is a feature-based structured output prediction task where the objective is to predict a set of features (represented with a output tuple of primitives datatype) from a set of features (represented by a descriptive tuple of primitives datatype). supervised multi-target prediction task OntoDM_135761s OntoDM_135761 OntoDM_135761 GC DAG-based hierarchical classification algorithm for single path prediction is a data mining algorithm that solves a DAG-based hierarchical classification task with single label paths and as a result produces a hierarchical classification model using a global classifier (GC) approach. GC DAG based HC algorithm for single path prediction OntoDM_136533s OntoDM_136533 OntoDM_136533 Multi-target regression tree is a multi-target regression model and denotes predictive models that are built on data having a tuple of reals (set of output features) on the output part, set of features (represented by a descriptive tuple of primitives) on the descriptive part, and is expressed in the language of decision trees. multi-target regression tree OntoDM_139240s OntoDM_139240 OntoDM_139240 scenario title OntoDM_139258s OntoDM_139258 OntoDM_139258 Multi-label decision tree is a multi-label classification model and denotes predictive models that are built on data having a set of discrete datatype on the output part, set of features (represented by a descriptive tuple of primitives) on the descriptive part, and it is expressed in the language of decision trees. multi-label decision tree OntoDM_145996s OntoDM_145996 OntoDM_145996 output tuple of boolean specification is an output tuple of primitives specification that denotes a tuple of boolean datatype on the output part of the data. output:tuple of boolean OntoDM_147247s OntoDM_147247 OntoDM_147247 algorithm execution OntoDM_150825s OntoDM_150825 OntoDM_150825 output discrete specification is an output primitive datatype specification that denotes a discrete datatype on the output part of the data. output:discrete OntoDM_153542s OntoDM_153542 OntoDM_153542 output set of reals specification is an output set specification that denotes a set of reals datatype on the output part of the data. output:set of reals OntoDM_155699s OntoDM_155699 OntoDM_155699 Binary classification is a data mining algorithm that solves a binary classification task and as a result produces a binary classification model. binary classification algorithm OntoDM_157687s OntoDM_157687 OntoDM_157687 A structure-based predictive model for structured output is a predictive model specification and denotes predictive models that are built on data having structured datatype on the output part, and a structured datatype on the descriptive part. structure-based predictive model for structured output OntoDM_165764s OntoDM_165764 OntoDM_165764 A feature-based predictive model for structured output is a predictive model specification and denotes predictive models that are built on data having a structured datatype on the output part, and set of features (represented by a descriptive tuple of primitives) on the descriptive part. feature-based predictive model for structured output OntoDM_169891s OntoDM_169891 OntoDM_169891 unlabeled structure-based dataset is a dataset specification of unlabeled dataset with a structured descriptive datatype specification. structure-based unlabeled dataset OntoDM_171503s OntoDM_171503 OntoDM_171503 Flat classification algorithm is a data mining algorithm that solves a classification task and as a result produces a classification model. flat classification algorithm OntoDM_174112s OntoDM_174112 OntoDM_174112 LCPN tree-based hierarchical classification algorithm for multiple path prediction is a data mining algorithm that solves a tree-based hierarchical classification task with multiple label paths and as a result produces a hierarchical classification model using a local classifier per parent node (LCPN) approach. LPCN tree based HC algorithm for multiple path prediction OntoDM_180345s OntoDM_180345 OntoDM_180345 LCN DAG-based hierarchical classification algorithm for multiple path prediction is a data mining algorithm that solves a DAG-based hierarchical classification task with multiple label paths and as a result produces a hierarchical classification model using a local classifier per node (LCN) approach. LCN DAG based HC algorithm for multiple path prediction OntoDM_182357s OntoDM_182357 OntoDM_182357 data mining scenario OntoDM_191108s OntoDM_191108 OntoDM_191108 output real specification is an output primitive datatype specification that denotes a real datatype on the output part of the data. output:real OntoDM_201436s OntoDM_201436 OntoDM_201436 parameter specification is a specification entity that is about a parameter. parameter specification OntoDM_205203s OntoDM_205203 OntoDM_205203 Feature-based primitive output prediction task is a predicting primitive output task where the objective is to predict a primitive output (represented with a primitive datatype) from a set of features (represented by a descriptive tuple of primitives datatype). supervised feature-based primitive output prediction task OntoDM_207566s OntoDM_207566 OntoDM_207566 A feature-based predictive model for primitive output is a predictive model specification and denotes predictive models that are built on data having primitive datatype on the output part, and set of features (represented by a descriptive tuple of primitives) on the descriptive part. feature-based predictive model for primitive output OntoDM_208012s OntoDM_208012 OntoDM_208012 Time-series prediction task is a feature-based structured output prediction task where the objective is to predict a time series (represented with a output sequence of real datatype) from a set of features (represented by a descriptive tuple of primitives datatype). supervised time-series prediction task OntoDM_208659s OntoDM_208659 OntoDM_208659 binary classification task is a flat classification task where the objective is to predict a boolean output (represented with a boolean datatype) from a set of features (represented by a descriptive tuple of primitives datatype). supervised binary classification task OntoDM_213136s OntoDM_213136 OntoDM_213136 GC DAG-based hierarchical classification algorithm is a data mining algorithm that solves a DAG-based hierarchical classification task and as a result produces a hierarchical classification model using a global classifier (GC) approach. GC DAG based HC algorithm OntoDM_221045s OntoDM_221045 OntoDM_221045 LCN DAG-based hierarchical classification algorithm for single path and mandatory leaf node prediction is a data mining algorithm that solves a DAG-based hierarchical classification task with single label paths and full depth labeling and as a result produces a hierarchical classification model using a local classifier per parent node (LCPN) approach. LCPN DAG based HC algorithm for single path and mandatory leaf node prediction OntoDM_225681s OntoDM_225681 OntoDM_225681 Multi-target prediction model is afeature-based predictive model for structured output and denotes predictive models that are built on data having a tuple of primitives (set of output features) on the output part, and set of features (represented by a descriptive tuple of primitives) on the descriptive part. multi-target prediction model OntoDM_231548s OntoDM_231548 OntoDM_231548 Multi-target binary classification task is a multi-target classification task where the objective is to predict a set of binary features (represented with a output tuple of booleans ) from a set of features (represented by a descriptive tuple of primitives datatype). supervised multi-target binary classification OntoDM_232231s OntoDM_232231 OntoDM_232231 LCPN DAG-based hierarchical classification algorithm for multiple path prediction is a data mining algorithm that solves a DAG-based hierarchical classification task with multiple label paths and as a result produces a hierarchical classification model using a local classifier per parent node (LCPN) approach. LCPN DAG based HC algorithm for multiple path prediction OntoDM_242219s OntoDM_242219 OntoDM_242219 predicting primitive output task is a predictive modeling task where the objective is to predict a primitive output (represented with a primitive datatype). supervised primitive output prediction task OntoDM_246002s OntoDM_246002 OntoDM_246002 descriptive structured data specification is a descriptive datatype specification that denotes a structured datatype on the descriptive part of the data. structure-based descriptive data specification OntoDM_246907s OntoDM_246907 OntoDM_246907 Tree based hierarchical classification task with single label paths and partial depth labeling is a tree based hierarchical classification task where the objective is to predict a set of labels organized in a tree (represented with a output tree with boolean edges and discrete nodes) from a set of features (represented by a descriptive tuple of primitives datatype), where the data instances are allowed to have single paths of labels and at least one instance has a partial depth of labeling. tree-based hierarchical classification task with single label paths and partial depth labeling OntoDM_247241s OntoDM_247241 OntoDM_247241 Multi-label classification model is afeature-based predictive model for structured output and denotes predictive models that are built on data having a set of discrete datatype on the output part, and set of features (represented by a descriptive tuple of primitives) on the descriptive part. multi-label classification model OntoDM_247510s OntoDM_247510 OntoDM_247510 output set specification is an output structured datatype specification that denotes a set datatype on the output part of the data. output:set of primitives OntoDM_251508s OntoDM_251508 OntoDM_251508 LCPN tree-based hierarchical classification algorithm for multiple path and non-mandatory leaf node prediction is a data mining algorithm that solves a tree-based hierarchical classification task with multiple label paths and partial depth labeling and as a result produces a hierarchical classification model using a local classifier per parent node (LCPN) approach. LPCN tree based HC algorithm for single path and non-mandatory leaf node prediction OntoDM_257039s OntoDM_257039 OntoDM_257039 flat classification dataset is a dataset specification of a labeled dataset with tuple of primitives datatype (specified with the feature set specification) on the descriptive part and a boolean or discrete datatype on the output part of the data (specified with the feature specification). flat classification dataset OntoDM_257366s OntoDM_257366 OntoDM_257366 LCN tree-based hierarchical classification algorithm for multiple path and non-mandatory leaf node prediction is a data mining algorithm that solves a tree-based hierarchical classification task with multiple label paths and partial depth labeling and as a result produces a hierarchical classification model using a local classifier per node (LCN) approach. LCN tree based HC algorithm for single path and non-mandatory leaf node prediction OntoDM_278835s OntoDM_278835 OntoDM_278835 output sequence of discrete specification is an output sequence datatype specification that denotes a sequence of discrete datatype on the output part of the data. output:sequence of discrete OntoDM_279492s OntoDM_279492 OntoDM_279492 output DAG specification is an output labeled graph specification that denotes a DAG datatype on the output part of the data. output:DAG OntoDM_279507s OntoDM_279507 OntoDM_279507 OntoDM_280661s OntoDM_280661 OntoDM_280661 A regression tree is a regression model and denotes predictive models that are built on data having a real datatype on the output part, set of features (represented by a descriptive tuple of primitives) on the descriptive part, and it is expressed in the language of decision trees. regression tree OntoDM_281640s OntoDM_281640 OntoDM_281640 DAG based hierarchical classification task with single label paths and partial depth labeling is a DAG based hierarchical classification task where the objective is to predict a set of labels organized in a DAG (represented with a output DAG with boolean edges and discrete nodes) from a set of features (represented by a descriptive tuple of primitives datatype), where the data instances are allowed to have single paths of labels and at least one instance has a partial depth of labeling. DAG based hierarchical classification task with single label paths and partial depth labeling OntoDM_285570s OntoDM_285570 OntoDM_285570 workflow execution OntoDM_295724s OntoDM_295724 OntoDM_295724 Structure-based predictive modeling algorithm for structured output is a data mining algorithm that solves a structure-based structured output prediction task and as a result produces a structure-based predictive model for structured output. structure-based predictive modeling algorithm for structured output OntoDM_300937s OntoDM_300937 OntoDM_300937 GC tree-based hierarchical classification algorithm for single path prediction is a data mining algorithm that solves a tree-based hierarchical classification task with single label paths and as a result produces a hierarchical classification model using a global classifier (GC) approach. GC tree based HC algorithm for single path prediction OntoDM_308048s OntoDM_308048 OntoDM_308048 hierarchical classification dataset is a dataset specification of a labeled dataset with tuple of primitives datatype (specified with the feature set specification) on the descriptive part and a labeled tree with boolean edges and discrete nodes datatype on the output part of the data. tree-based hierarchical classification dataset OntoDM_311225s OntoDM_311225 OntoDM_311225 DAG-based hierarchical classification algorithm is a data mining algorithm that solves a DAG-based hierarchical classification task and as a result produces a hierarchical classification model. DAG based HC algorithm OntoDM_316568s OntoDM_316568 OntoDM_316568 A binary decision tree is a binary classification model and denotes predictive models that are built on data having a boolean datatype on the output part, set of features (represented by a descriptive tuple of primitives) on the descriptive part, and it is expressed in the language of decision trees. binary decision tree OntoDM_318626s OntoDM_318626 OntoDM_318626 Pattern set ensemble specification is a ensemble specification and denotes a type of generalization that is produced by a pattern set ensemble algorithm. This algorithm produces a collection of pattern sets at its output. pattern set ensemble specification OntoDM_319168s OntoDM_319168 OntoDM_319168 LCL DAG-based hierarchical classification algorithm for multiple path prediction is a data mining algorithm that solves a DAG-based hierarchical classification task with multiple label paths and as a result produces a hierarchical classification model using a local classifier per level (LCL) approach. LCL DAG based HC algorithm for multiple path prediction OntoDM_328701s OntoDM_328701 OntoDM_328701 LCN DAG-based hierarchical classification algorithm is a data mining algorithm that solves a DAG-based hierarchical classification task and as a result produces a hierarchical classification model using a local classifier per node (LCN) approach. LCN DAG based HC algorithm OntoDM_330210s OntoDM_330210 OntoDM_330210 specification specification entity OntoDM_341564s OntoDM_341564 OntoDM_341564 output tuple of primitives specification is an output structured datatype specification that denotes a tuple of primitives datatype on the output part of the data. output:tuple of primitives OntoDM_352467s OntoDM_352467 OntoDM_352467 output tuple of discrete specification is an output tuple of primitives specification that denotes a tuple of discrete datatype on the output part of the data. output:tuple of discrete OntoDM_353154s OntoDM_353154 OntoDM_353154 LCN tree-based hierarchical classification algorithm for single path and mandatory leaf node prediction is a data mining algorithm that solves a tree-based hierarchical classification task with single label paths and full depth labeling and as a result produces a hierarchical classification model using a local classifier per node (LCN) approach. LCN tree based HC algorithm for single path and mandatory leaf node prediction OntoDM_354620s OntoDM_354620 OntoDM_354620 Feature-based structured output prediction task is a predicting structured output task where the objective is to predict a structured output (represented with a output structured datatype) from a set of features (represented by a descriptive tuple of primitives datatype). supervised feature-based structured output prediction task OntoDM_357792s OntoDM_357792 OntoDM_357792 Random Subspaces OntoDM_361570s OntoDM_361570 OntoDM_361570 data processing algorithm OntoDM_368254s OntoDM_368254 OntoDM_368254 Time-series prediction model is afeature-based predictive model for structured output and denotes predictive models that are built on data having a sequence of reals on the output part, and set of features (represented by a descriptive tuple of primitives) on the descriptive part. time series prediction model OntoDM_368779s OntoDM_368779 OntoDM_368779 Predictive modeling ensemble algorithm is a data mining algorithm that solves a predictive modeling task and as a result produces a ensemble of predictive models. predictive modelling ensemble algorithm OntoDM_369100s OntoDM_369100 OntoDM_369100 A multi-class decision tree is a multi-class classification model and denotes predictive models that are built on data having a discrete datatype on the output part, set of features (represented by a descriptive tuple of primitives) on the descriptive part, and it is expressed in the language of decision trees. multi-class decision tree OntoDM_372340s OntoDM_372340 OntoDM_372340 DAG based hierarchical classification task with multiple label paths is a DAG based hierarchical classification task where the objective is to predict a set of labels organized in a DAG (represented with a output DAG with boolean edges and discrete nodes) from a set of features (represented by a descriptive tuple of primitives datatype), where the data instances are allowed to have multiple paths of labels. DAG based hierarchical classification task with multiple label paths OntoDM_372936s OntoDM_372936 OntoDM_372936 labeled dataset is a dataset specification for datasets that have both a descriptive and output specification of the data examples contained in the dataset. labeled dataset OntoDM_373964s OntoDM_373964 OntoDM_373964 Tree based hierarchical classification task with multiple label paths and full depth labeling is a tree based hierarchical classification task where the objective is to predict a set of labels organized in a tree (represented with a output treewith boolean edges and discrete nodes) from a set of features (represented by a descriptive tuple of primitives datatype), where the data instances are allowed to have multiple paths of labels and all instances have full depth of labeling. tree-based hierarchical classification task with multiple label paths and full depth labeling OntoDM_374511s OntoDM_374511 OntoDM_374511 Time-series prediction decision tree is a time-series prediction model and denotes predictive models that are built on data having a sequence of reals on the output part, set of features (represented by a descriptive tuple of primitives) on the descriptive part, and is expressed in the language of decision trees. time-series prediction decision tree OntoDM_376810s OntoDM_376810 OntoDM_376810 LCN tree-based hierarchical classification algorithm for single path and mandatory leaf node prediction is a data mining algorithm that solves a tree-based hierarchical classification task with single label paths and full depth labeling and as a result produces a hierarchical classification model using a local classifier per parent node (LCPN) approach. LPCN tree based HC algorithm for single path and mandatory leaf node prediction OntoDM_379153s OntoDM_379153 OntoDM_379153 descriptive tuple of primitives specification is a descriptive datatype specification that denotes a tuple of primitives datatype on the descriptive part of the data. feature-based descriptive data specification OntoDM_382943s OntoDM_382943 OntoDM_382943 Predictive modeling algorithm for primitive output is a data mining algorithm that solves a predicting primitive output task and as a result produces a predictive model for primitive output. predictive modeling algorithm for primitive output OntoDM_387728s OntoDM_387728 OntoDM_387728 flat classification task is a feature-based primitive output task where the objective is to predict a boolean or discrete output (represented with a boolean or discrete datatype) from a set of features (represented by a descriptive tuple of primitives datatype). supervised flat classification task OntoDM_388961s OntoDM_388961 OntoDM_388961 LCL tree-based hierarchical classification algorithm for multiple path prediction is a data mining algorithm that solves a tree-based hierarchical classification task with multiple label paths and as a result produces a hierarchical classification model using a local classifier per level (LCL) approach. LCL tree based HC algorithm for multiple path prediction OntoDM_398436s OntoDM_398436 OntoDM_398436 GC tree-based hierarchical classification algorithm is a data mining algorithm that solves a tree-based hierarchical classification task and as a result produces a hierarchical classification model using a global classifier (GC) approach. GC tree-based HC algorithm OntoDM_400000 data specification OntoDM_400001 batch data mining task OntoDM_400002 online data mining task OntoDM_400003 online clustering task OntoDM_400004 online pattern discovery task OntoDM_400005 online probability distribution estimation task OntoDM_408772s OntoDM_408772 OntoDM_408772 LCN DAG-based hierarchical classification algorithm for multiple path and non-mandatory leaf node prediction is a data mining algorithm that solves a DAG-based hierarchical classification task with multiple label paths and partial depth labeling and as a result produces a hierarchical classification model using a local classifier per node (LCN) approach. LCN DAG based HC algorithm for multiple path and non-mandatory leaf node prediction OntoDM_419418s OntoDM_419418 OntoDM_419418 Tree-based hierarchical classification algorithm is a data mining algorithm that solves a tree-based hierarchical classification task and as a result produces a hierarchical classification model. tree-based HC algorithm OntoDM_419460s OntoDM_419460 OntoDM_419460 A single generalization specification is a generalization specification and denotes a type of generalization that is produced by a single generalization data mining algorithm. This algorithm produces only one generalization at its output. single generalization specification OntoDM_419544s OntoDM_419544 OntoDM_419544 information content entity quality OntoDM_429658s OntoDM_429658 OntoDM_429658 Clustering ensemble algorithm is a data mining algorithm that solves a clustering task and as a result produces an ensemble of clusterings. clustering ensemble algorithm OntoDM_433774s OntoDM_433774 OntoDM_433774 language of markov chains OntoDM_452759s OntoDM_452759 OntoDM_452759 Bagging OntoDM_458784s OntoDM_458784 OntoDM_458784 output tree specification is an output labeled graph specification that denotes a tree datatype on the output part of the data. output:tree OntoDM_462575s OntoDM_462575 OntoDM_462575 Time-series predictive modeling algorithm is a data mining algorithm that solves a time-series classification task and as a result produces a time series predictive model. time-series predictive modelling algorithm OntoDM_464319s OntoDM_464319 OntoDM_464319 LCN tree-based hierarchical classification algorithm is a data mining algorithm that solves a tree-based hierarchical classification task and as a result produces a hierarchical classification model using a local classifier per node (LCN) approach. LCN tree based HC algorithm OntoDM_464484s OntoDM_464484 OntoDM_464484 Probability distribution estimation ensemble algorithm is a data mining algorithm that solves a probablility distribution estimation task and as a result produces a ensemble of probability distributions. probability distribution estimation ensemble algorithm OntoDM_467074s OntoDM_467074 OntoDM_467074 LCPN DAG-based hierarchical classification algorithm for multiple path and non-mandatory leaf node prediction is a data mining algorithm that solves a DAG-based hierarchical classification task with multiple label paths and partial depth labeling and as a result produces a hierarchical classification model using a local classifier per parent node (LCPN) approach. LCPN DAG based HC algorithm for multiple path and non-mandatory leaf node prediction OntoDM_470460s OntoDM_470460 OntoDM_470460 LCPN tree-based hierarchical classification algorithm for single path prediction is a data mining algorithm that solves a tree-based hierarchical classification task with single label paths and as a result produces a hierarchical classification model using a local classifier per parent node (LCPN) approach. LPCN tree based HC algorithm for single path prediction OntoDM_474912s OntoDM_474912 OntoDM_474912 LCL tree-based hierarchical classification algorithm for multiple path and non-mandatory leaf node prediction is a data mining algorithm that solves a tree-based hierarchical classification task with multiple label paths and partial depth labeling and as a result produces a hierarchical classification model using a local classifier per level (LCL) approach. LCL tree based HC algorithm for single path and non-mandatory leaf node prediction OntoDM_478450s OntoDM_478450 OntoDM_478450 workflow OntoDM_481568s OntoDM_481568 OntoDM_481568 Multi-target multi-class classification model is a multi-target classification model and denotes predictive models that are built on data having a tuple of discrete (set of output features) on the output part, and set of features (represented by a descriptive tuple of primitives) on the descriptive part. multi-target multi-class classification model OntoDM_485256s OntoDM_485256 OntoDM_485256 GC DAG-based hierarchical classification algorithm for multiple path prediction is a data mining algorithm that solves a DAG-based hierarchical classification task with multiple label paths and as a result produces a hierarchical classification model using a global classifier (GC) approach. GC DAG based HC algorithm for multiple path prediction OntoDM_490530s OntoDM_490530 OntoDM_490530 clusterings ensemble specification is a ensemble specification and denotes a type of generalization that is produced by a clustering ensemble algorithm. This algorithm produces a set of clusterings at its output. clusterings ensemble specification OntoDM_491182s OntoDM_491182 OntoDM_491182 DAG based hierarchical classification task is a hierarchical classification task where the objective is to predict a set of labels organized in a DAG (represented with a output DAG with boolean edges and discrete nodes) from a set of features (represented by a descriptive tuple of primitives datatype). supervised DAG based hierarchical classification task OntoDM_495960s OntoDM_495960 OntoDM_495960 Multi-target classification model is a multi-target prediction model and denotes predictive models that are built on data having a tuple of boolean or discrete (set of output features) on the output part, and set of features (represented by a descriptive tuple of primitives) on the descriptive part. multi-target classification model OntoDM_506961s OntoDM_506961 OntoDM_506961 Multi-target regression task is a multi-target prediction task where the objective is to predict a set of real features (represented with a output tuple of reals) from a set of features (represented by a descriptive tuple of primitives datatype). supervised multi-target regression task OntoDM_507935s OntoDM_507935 OntoDM_507935 Hierarchical classification algorithm is a data mining algorithm that solves a hierarchical classification task and as a result produces a hierarchical classification model. hierarchical classification algorithm OntoDM_510504s OntoDM_510504 OntoDM_510504 Multi-label classification task is a feature-based structured output prediction task where the objective is to predict a set of discrete output labels (represented with a output set of discrete datatype) from a set of features (represented by a descriptive tuple of primitives datatype). supervised multi-label classification task OntoDM_510989s OntoDM_510989 OntoDM_510989 a parameter setting is a data item that is a quality specification of some algorithm parameter and denotes its configuration when an algorithm implementation is used as a data mining operator in the process of algorithm execution. parameter setting OntoDM_512674s OntoDM_512674 OntoDM_512674 LCN tree-based hierarchical classification algorithm for single path prediction is a data mining algorithm that solves a tree-based hierarchical classification task with single label paths and as a result produces a hierarchical classification model using a local classifier per node (LCN) approach. LCN tree based HC algorithm for single path prediction OntoDM_516954s OntoDM_516954 OntoDM_516954 output sequence specification is an output structured datatype specification that denotes a sequence datatype on the output part of the data. output:sequence OntoDM_519526s OntoDM_519526 OntoDM_519526 GC tree based HC algorithm for single path and mandatory leaf node prediction OntoDM_528443s OntoDM_528443 OntoDM_528443 LCL tree-based hierarchical classification algorithm for multiple path and non-mandatory leaf node prediction is a data mining algorithm that solves a tree-based hierarchical classification task with multiple label paths and partial depth labeling and as a result produces a hierarchical classification model using a local classifier per level (LCL) approach. LCL tree based HC algorithm for multiple path and non-mandatory leaf node prediction OntoDM_530819s OntoDM_530819 OntoDM_530819 A ensemble algorithm is a data mining algorithm that solves a data mining task and as a result produces an ensemble of generalizations. ensemble algorithm OntoDM_532190s OntoDM_532190 OntoDM_532190 language of neural nets OntoDM_535716s OntoDM_535716 OntoDM_535716 Probability distributions specification is a ensemble specification and denotes a type of generalization that is produced by a probability distribution estimation ensemble algorithm. This algorithm produces a set of probability distributions at its output. probability distributions ensemble specification OntoDM_537602s OntoDM_537602 OntoDM_537602 labeled feature-based dataset with primitive output is a dataset specification of a labeled dataset with tuple of primitives datatype (specified with the feature set specification) on the descriptive part and a primitive datatype on the output part of the data (specified with the output feature specification). feature-based completely labeled dataset with primitive output OntoDM_540049s OntoDM_540049 OntoDM_540049 LC tree-based hierarchical classification algorithm is a data mining algorithm that solves a tree-based hierarchical classification task and as a result produces a hierarchical classification model using a local classifier (LC) approach. LC tree based HC algorithm OntoDM_541005s OntoDM_541005 OntoDM_541005 multi-label classification dataset is a dataset specification of a labeled dataset with tuple of primitives datatype (specified with the feature set specification) on the descriptive part and a set of discrete datatype on the output part of the data. multi-label classification dataset OntoDM_542264s OntoDM_542264 OntoDM_542264 Tree based hierarchical classification task is a hierarchical classification task where the objective is to predict a set of labels organized in a tree (represented with a output tree with boolean edges and discrete nodes) from a set of features (represented by a descriptive tuple of primitives datatype). supervised tree-based hierarchical classification task OntoDM_544234s OntoDM_544234 OntoDM_544234 data mining software toolkit OntoDM_548678s OntoDM_548678 OntoDM_548678 A data mining task description is-a specifcation entity that denotes a specific data mining task applied on a specific dataset, having in mind the specific type of generalization produced by the task (generalization specifcation) data mining task description OntoDM_548720s OntoDM_548720 OntoDM_548720 data mining source code module OntoDM_549140s OntoDM_549140 OntoDM_549140 LCPN tree-based hierarchical classification algorithm is a data mining algorithm that solves a tree-based hierarchical classification task and as a result produces a hierarchical classification model using a local classifier per parent node (LCPN) approach. LCPN tree based HC algorithm OntoDM_555011s OntoDM_555011 OntoDM_555011 LCN DAG-based hierarchical classification algorithm for multiple path and non-mandatory leaf node prediction is a data mining algorithm that solves a DAG-based hierarchical classification task with multiple label paths and partial depth labeling and as a result produces a hierarchical classification model using a local classifier per node (LCN) approach. LCN DAG based HC algorithm for single path and non-mandatory leaf node prediction OntoDM_559103s OntoDM_559103 OntoDM_559103 Tree based hierarchical classification task with single label paths is a tree based hierarchical classification task where the objective is to predict a set of labels organized in a tree (represented with a output tree with boolean edges and discrete nodes) from a set of features (represented by a descriptive tuple of primitives datatype), where the data instances are allowed to have a single paths of labels. tree-based hierarchical classification task with single label paths OntoDM_565974s OntoDM_565974 OntoDM_565974 multi-target regression dataset is a dataset specification of a labeled dataset with tuple of primitives datatype (specified with the feature set specification) on the descriptive part and a tuple of reals (specified with the feature set specification) on the output part of the data. multi-target regression dataset OntoDM_570767s OntoDM_570767 OntoDM_570767 Multi-label classification algorithm is a data mining algorithm that solves a multi-label classification task and as a result produces a multi-label classification model. multi-label classification algorithm OntoDM_572839s OntoDM_572839 OntoDM_572839 LCL tree-based hierarchical classification algorithm for single path and mandatory leaf node prediction is a data mining algorithm that solves a tree-based hierarchical classification task with single label paths and full depth labeling and as a result produces a hierarchical classification model using a local classifier per level (LCL) approach. LCL tree based HC algorithm for single path and mandatory leaf node prediction OntoDM_577929s OntoDM_577929 OntoDM_577929 A predictive model for structured output is a predictive model specification and denotes predictive models that are built on data having a structured datatype on the output part. predictive model for structured output OntoDM_583334s OntoDM_583334 OntoDM_583334 Multi-target regression model is a multi-target prediction model and denotes predictive models that are built on data having a tuple of reals (set of output features) on the output part, and set of features (represented by a descriptive tuple of primitives) on the descriptive part. multi-target regression model OntoDM_585235s OntoDM_585235 OntoDM_585235 LCL DAG-based hierarchical classification algorithm for multiple path and non-mandatory leaf node prediction is a data mining algorithm that solves a DAG-based hierarchical classification task with multiple label paths and partial depth labeling and as a result produces a hierarchical classification model using a local classifier per level (LCL) approach. LCL DAG based HC algorithm for multiple path and non-mandatory leaf node prediction OntoDM_600958s OntoDM_600958 OntoDM_600958 predicting structured output task is a predictive modeling task where the objective is to predict a structured output (represented with a structured datatype). supervised structured output prediction task OntoDM_603253s OntoDM_603253 OntoDM_603253 scenario OntoDM_608558s OntoDM_608558 OntoDM_608558 unlabeled feature-based dataset is a dataset specification of unlabeled dataset with tuple of primitives as a descriptive datatype specification and descriptive feature set specification. feature-based unlabeled dataset OntoDM_609184s OntoDM_609184 OntoDM_609184 binary classification dataset is a dataset specification of a labeled dataset with tuple of primitives datatype (specified with the feature set specification) on the descriptive part and a boolean datatype on the output part of the data (specified with the feature specification). binary classification dataset OntoDM_611937s OntoDM_611937 OntoDM_611937 GC tree based HC algorithm for single path and non-mandatory leaf node prediction OntoDM_613600s OntoDM_613600 OntoDM_613600 clustering evaluation OntoDM_613675s OntoDM_613675 OntoDM_613675 LCPN DAG-based hierarchical classification algorithm for single path prediction is a data mining algorithm that solves a DAG-based hierarchical classification task with single label paths and as a result produces a hierarchical classification model using a local classifier per parent node (LCPN) approach. LCPN DAG based HC algorithm for single path prediction OntoDM_613950s OntoDM_613950 OntoDM_613950 language of graphical models OntoDM_616457s OntoDM_616457 OntoDM_616457 language of decision rules OntoDM_616614s OntoDM_616614 OntoDM_616614 software toolkit OntoDM_620805s OntoDM_620805 OntoDM_620805 DAG based hierarchical classification task with single label paths and full depth labeling is a DAG based hierarchical classification task where the objective is to predict a set of labels organized in a DAG (represented with a output DAG with boolean edges and discrete nodes) from a set of features (represented by a descriptive tuple of primitives datatype), where the data instances are allowed to have single paths of labels and all instances have full depth of labeling. DAG based hierarchical classification task with single label paths and full depth labeling OntoDM_622093s OntoDM_622093 OntoDM_622093 LCL tree-based hierarchical classification algorithm for multiple path and mandatory leaf node prediction is a data mining algorithm that solves a tree-based hierarchical classification task with multiple label paths and full depth labeling and as a result produces a hierarchical classification model using a local classifier per level (LCL) approach. LCL tree based HC algorithm for multiple path and mandatory leaf node prediction OntoDM_622428s OntoDM_622428 OntoDM_622428 Tree based hierarchical classification task with single label paths and full depth labeling is a tree based hierarchical classification task where the objective is to predict a set of labels organized in a tree (represented with a output tree with boolean edges and discrete nodes) from a set of features (represented by a descriptive tuple of primitives datatype), where the data instances are allowed to have single paths of labels and all instances have full depth of labeling. tree-based hierarchical classification task with single label paths and full depth labeling OntoDM_625176s OntoDM_625176 OntoDM_625176 evaluation algorithm implementation OntoDM_627978s OntoDM_627978 OntoDM_627978 Multi-target binary decision tree is a multi-target binary classification model and denotes predictive models that are built on data having a tuple of boolean (set of output features) on the output part, set of features (represented by a descriptive tuple of primitives) on the descriptive part, and is expressed in the language of decision trees. multi-target binary decision tree OntoDM_629944s OntoDM_629944 OntoDM_629944 labeled dataset with structured output is a dataset specification of a labeled dataset with structured output datatype specification. completely labeled dataset with structured output OntoDM_636213s OntoDM_636213 OntoDM_636213 multi-target multi-class classification dataset is a dataset specification of a labeled dataset with tuple of primitives datatype (specified with the feature set specification) on the descriptive part and a tuple of discrete (specified with the feature set specification) on the output part of the data. multi-target multi-class classification dataset OntoDM_636747s OntoDM_636747 OntoDM_636747 multi-class classification dataset is a dataset specification of a labeled dataset with tuple of primitives datatype (specified with the feature set specification) on the descriptive part, and a discrete datatype on the output part of the data (specified with the feature specification). multi-class classification dataset OntoDM_640624s OntoDM_640624 OntoDM_640624 Hierarchical classification decision tree is a hierarchical classification model and denotes predictive models that are built on data having a labeled graph datatype on the output part, set of features (represented by a descriptive tuple of primitives) on the descriptive part, and it is expressed in the language of decision trees. hierarchical classification decision tree OntoDM_642324s OntoDM_642324 OntoDM_642324 language of decision trees OntoDM_651414s OntoDM_651414 OntoDM_651414 a predicted dataset is a dataset that is an output of a predictive model execution process. predicted dataset OntoDM_661861s OntoDM_661861 OntoDM_661861 structure based structured output prediction task is a predicting structured output task where the objective is to predict a structured output (represented with a outputstructured datatype) from a structure (represented by a descriptive structured datatype). supervised structure based structured output prediction task OntoDM_666475s OntoDM_666475 OntoDM_666475 labeled feature-based dataset with structured output is a dataset specification of a labeled dataset with tuple of primitives datatype (specified with the feature set specification) on the descriptive part and a structured datatype on the output part of the data. feature-based completely labeled dataset with structured output OntoDM_669483s OntoDM_669483 OntoDM_669483 LCL tree-based hierarchical classification algorithm for single path prediction is a data mining algorithm that solves a tree-based hierarchical classification task with single label paths and as a result produces a hierarchical classification model using a local classifier per level (LCL) approach. LCL tree based HC algorithm for single path prediction OntoDM_674255s OntoDM_674255 OntoDM_674255 Multi-target regression algorithm is a data mining algorithm that solves a multi-target regression task and as a result produces a multi-target regression model. multi-target regression algorithm OntoDM_675141s OntoDM_675141 OntoDM_675141 descriptive set of discrete is a descriptive structured datatype specification that denotes a set of discrete datatype on the descriptive part of the data. descriptive:set of discrete OntoDM_686944s OntoDM_686944 OntoDM_686944 regression dataset is a dataset specification of a labeled dataset with tuple of primitives datatype (specified with the feature set specification) on the descriptive part and a real datatype on the output part of the data (specified with the output specification). regression dataset OntoDM_688833s OntoDM_688833 OntoDM_688833 A regression model is a feature-based predictive model for primitive output and denotes predictive models that are built on data having a real datatype on the output part, and set of features (represented by a descriptive tuple of primitives) on the descriptive part. regression model OntoDM_689658s OntoDM_689658 OntoDM_689658 Multi-target multi-class decision tree is a multi-target multi-class classification model and denotes predictive models that are built on data having a tuple of discrete (set of output features) on the output part, set of features (represented by a descriptive tuple of primitives) on the descriptive part, and are expressed in the language of decision trees. multi-target multi-class decison tree OntoDM_692551s OntoDM_692551 OntoDM_692551 LCL DAG-based hierarchical classification algorithm for multiple path and non-mandatory leaf node prediction is a data mining algorithm that solves a DAG-based hierarchical classification task with multiple label paths and partial depth labeling and as a result produces a hierarchical classification model using a local classifier per level (LCL) approach. LCL DAG based HC algorithm for single path and non-mandatory leaf node prediction OntoDM_692808s OntoDM_692808 OntoDM_692808 labeled dataset with structured output is a dataset specification of a labeled dataset with structured datatype on the descriptive part and a structured datatype on the output part of the data. structure-based completely labeled dataset with structured output OntoDM_693227s OntoDM_693227 OntoDM_693227 description OntoDM_694510s OntoDM_694510 OntoDM_694510 GC tree-based hierarchical classification algorithm for multiple path prediction is a data mining algorithm that solves a tree-based hierarchical classification task with multiple label paths and as a result produces a hierarchical classification model using a global classifier (GC) approach. GC tree-based HC algorithm for multiple path prediction OntoDM_708865s OntoDM_708865 OntoDM_708865 representational medium specification OntoDM_716122s OntoDM_716122 OntoDM_716122 output boolean specification is an output primitive datatype specification that denotes a boolean datatype on the output part of the data. output:boolean OntoDM_718392s OntoDM_718392 OntoDM_718392 DAG based hierarchical classification task with multiple label paths and partial depth labeling is a DAG based hierarchical classification task where the objective is to predict a set of labels organized in a DAG (represented with a output DAG with boolean edges and discrete nodes) from a set of features (represented by a descriptive tuple of primitives datatype), where the data instances are allowed to have multiple paths of labels and at least one instance has a partial depth of labeling. DAG based hierarchical classification task with multiple label paths and partial depth labeling OntoDM_718446s OntoDM_718446 OntoDM_718446 Structure-based predictive modeling algorithm for primitive output is a data mining algorithm that solves a structure-based primitive output prediction task and as a result produces a structure-based predictive model for primitive output. structure-based prectictive modeling algorithm for primitive output OntoDM_721008s OntoDM_721008 OntoDM_721008 Random Forest OntoDM_722523s OntoDM_722523 OntoDM_722523 Multi-target classification algorithm is a data mining algorithm that solves a multi-target classification task and as a result produces a multi-target classification model. multi-target classification algorithm OntoDM_726490s OntoDM_726490 OntoDM_726490 Mapping specification is a information content entity that denotes a part of a data example on which a concrete datatype applies to. mapping specification OntoDM_727807s OntoDM_727807 OntoDM_727807 multi-target binary classification dataset is a dataset specification of a labeled dataset with tuple of primitives datatype (specified with the feature set specification) on the descriptive part and a tuple of booleans (specified with the feature set specification) on the output part of the data. multi-target binary classification dataset OntoDM_728533s OntoDM_728533 OntoDM_728533 Multi-target binary classification algorithm is a data mining algorithm that solves a multi-target binary classification task and as a result produces a multi-target binarty classification model. multi-target binary classification algorithm OntoDM_730046s OntoDM_730046 OntoDM_730046 LCN tree-based hierarchical classification algorithm for multiple path and non-mandatory leaf node prediction is a data mining algorithm that solves a tree-based hierarchical classification task with multiple label paths and partial depth labeling and as a result produces a hierarchical classification model using a local classifier per node (LCN) approach. LCN tree based HC algorithm for multiple path and non-mandatory leaf node prediction OntoDM_730934s OntoDM_730934 OntoDM_730934 evaluation algorithm OntoDM_731692s OntoDM_731692 OntoDM_731692 A single generalization algorithm is a data mining algorithm that solves a data mining task and as a result produces a single generalization. single generalization algorithm OntoDM_733255s OntoDM_733255 OntoDM_733255 Multi-target classification task is a multi-target prediction task where the objective is to predict a set of binary/discrete features (represented with a output tuple of booleans or discrete) from a set of features (represented by a descriptive tuple of primitives datatype). supervised multi-target classification task OntoDM_741571s OntoDM_741571 OntoDM_741571 output primitive is an output datatype specification that denotes a primitive datatype on the output part of the data. primitive-based output data specification OntoDM_746568s OntoDM_746568 OntoDM_746568 multi-target prediction dataset is a dataset specification of a labeled dataset with tuple of primitives datatype (specified with the feature set specification) on the descriptive part and a tuple of primitives (specified with the feature set specification) on the output part of the data. multi-target prediction dataset OntoDM_748173s OntoDM_748173 OntoDM_748173 operator OntoDM_754841s OntoDM_754841 OntoDM_754841 GC tree based HC algorithm for multiple path and mandatory leaf node prediction OntoDM_757135s OntoDM_757135 OntoDM_757135 information processing objective is objective specification of the end point that an information processing process needs to achieve at its end. information processing objective OntoDM_757640s OntoDM_757640 OntoDM_757640 Multi-target multi-class classification algorithm is a data mining algorithm that solves a multi-target multi-class classification task and as a result produces a multi-target multi-class classification model. multi-target multi-class classification algorithm OntoDM_771971s OntoDM_771971 OntoDM_771971 GC tree based HC algorithm for multiple path and non-mandatory leaf node prediction OntoDM_776589s OntoDM_776589 OntoDM_776589 OntoDM_776589 pattern discovery evaluation OntoDM_782155s OntoDM_782155 OntoDM_782155 LCN DAG-based hierarchical classification algorithm for multiple path and mandatory leaf node prediction is a data mining algorithm that solves a DAG-based hierarchical classification task with multiple label paths and full depth labeling and as a result produces a hierarchical classification model using a local classifier per node (LCN) approach. LCN DAG based HC algorithm for multiple path and mandatory leaf node prediction OntoDM_783954s OntoDM_783954 OntoDM_783954 multi-target classification dataset is a dataset specification of a labeled dataset with tuple of primitives datatype (specified with the feature set specification) on the descriptive part and a tuple of booleans or discrete (specified with the feature set specification) on the output part of the data. multi-target classification dataset OntoDM_785336s OntoDM_785336 OntoDM_785336 Structure-based primitive output prediction task is a predicting primitive output task where the objective is to predict a primitive output (represented with a primitive datatype) from a structure (represented by a descriptive structured datatype). supervised structure based primitive output prediction task OntoDM_793930s OntoDM_793930 OntoDM_793930 LCL tree-based hierarchical classification algorithm is a data mining algorithm that solves a tree-based hierarchical classification task and as a result produces a hierarchical classification model using a local classifier per level (LCL) approach. LCL tree based HC algorithm OntoDM_794067s OntoDM_794067 OntoDM_794067 feature-based time series predicton dataset is a dataset specification of a labeled dataset with tuple of primitives datatype (specified with the feature set specification) on the descriptive part and a sequence of reals datatype on the output part of the data. feature-based time-series prediction dataset OntoDM_813772s OntoDM_813772 OntoDM_813772 language of bayesian nets OntoDM_815320s OntoDM_815320 OntoDM_815320 Multi-target multi-class classification task is a multi-target classification task where the objective is to predict a set of discrete features (represented with a output tuple of discrete ) from a set of features (represented by a descriptive tuple of primitives datatype). supervised multi-target multi-class classification task OntoDM_817028s OntoDM_817028 OntoDM_817028 Multi-target predictive modeling algorithm is a data mining algorithm that solves a multi-target prediction task and as a result produces a multi-target predictive model. multi-target predictive modelling algorithm OntoDM_817888s OntoDM_817888 OntoDM_817888 data mining workflow OntoDM_818411s OntoDM_818411 OntoDM_818411 GC DAG based HC algorithm for single path and mandatory leaf node prediction OntoDM_826903s OntoDM_826903 OntoDM_826903 Tree based hierarchical classification task with multiple label paths is a tree based hierarchical classification task where the objective is to predict a set of labels organized in a tree (represented with a output tree with boolean edges and discrete nodes) from a set of features (represented by a descriptive tuple of primitives datatype), where the data instances are allowed to have multiple paths of labels. tree-based hierarchical classification task with multiple label paths OntoDM_829270s OntoDM_829270 OntoDM_829270 LCPN DAG-based hierarchical classification algorithm for multiple path and non-mandatory leaf node prediction is a data mining algorithm that solves a DAG-based hierarchical classification task with multiple label paths and partial depth labeling and as a result produces a hierarchical classification model using a local classifier per parent node (LCPN) approach. LCPN DAG based HC algorithm for single path and non-mandatory leaf node prediction OntoDM_831808s OntoDM_831808 OntoDM_831808 Feature-based predictive modeling algorithm for structured output is a data mining algorithm that solves a feature-based primitive structured prediction task and as a result produces a feature-based predictive model for structured output. feature-based predictive modeling algorithm for structured output OntoDM_835948s OntoDM_835948 OntoDM_835948 output structured specification is an output datatype specification that denotes a structured datatype on the output part of the data. structure-based output data specification OntoDM_837886s OntoDM_837886 OntoDM_837886 regression classification task is a feature-based primitive output task where the objective is to predict a real output (represented with a real datatype) from a set of features (represented by a descriptive tuple of primitives datatype). supervised regression task OntoDM_838789s OntoDM_838789 OntoDM_838789 LCL DAG-based hierarchical classification algorithm for single path prediction is a data mining algorithm that solves a DAG-based hierarchical classification task with single label paths and as a result produces a hierarchical classification model using a local classifier per level (LCL) approach. LCL DAG based HC algorithm for single path prediction OntoDM_843203s OntoDM_843203 OntoDM_843203 labeled structure-based dataset with primitive output is a dataset specification of a labeled dataset with a structure datatype on the descriptive part and a primitive datatype on the output part of the data (specified with the output feature specification). structure-based completely labeled dataset with primitive output OntoDM_843647s OntoDM_843647 OntoDM_843647 output sequence of real specification is an output sequence datatype specification that denotes a sequence of reals datatype on the output part of the data. output:sequence of reals OntoDM_849533s OntoDM_849533 OntoDM_849533 labeled dataset with primitive output is a dataset specification of labeled dataset with primitive output datatype specification. completely labeled dataset with primitive output OntoDM_849657s OntoDM_849657 OntoDM_849657 GC DAG based HC algorithm for single path and non-mandatory leaf node prediction OntoDM_860244s OntoDM_860244 OntoDM_860244 dataset quality OntoDM_860584s OntoDM_860584 OntoDM_860584 Pattern discovery ensemble algorithm is a data mining algorithm that solves a pattern discovery task and as a result produces a ensemble of set of patterns. pattern discovery ensemble algorithm OntoDM_865023s OntoDM_865023 OntoDM_865023 A multi-class classification model is a classification model and denotes predictive models that are built on data having a discrete datatype on the output part, and set of features (represented by a descriptive tuple of primitives) on the descriptive part. multi-class classification model OntoDM_871327s OntoDM_871327 OntoDM_871327 Predictive modeling algorithm for structured output is a data mining algorithm that solves a predicting structured output task and as a result produces a predictive model for structured output. predictive modeling algorithm for structured output OntoDM_874928s OntoDM_874928 OntoDM_874928 LCN DAG-based hierarchical classification algorithm for single path and mandatory leaf node prediction is a data mining algorithm that solves a DAG-based hierarchical classification task with single label paths and full depth labeling and as a result produces a hierarchical classification model using a local classifier per node (LCN) approach. LCN DAG based HC algorithm for single path and mandatory leaf node prediction OntoDM_879928s OntoDM_879928 OntoDM_879928 unlabeled dataset is a dataset specification for datasets that have only descriptive datatype specification of the data examples contained in the dataset. unlabeled dataset OntoDM_882801s OntoDM_882801 OntoDM_882801 LCPN DAG-based hierarchical classification algorithm for multiple path and mandatory leaf node prediction is a data mining algorithm that solves a DAG-based hierarchical classification task with multiple label paths and full depth labeling and as a result produces a hierarchical classification model using a local classifier per parent node (LCPN) approach. LCPN DAG based HC algorithm for multiple path and mandatory leaf node prediction OntoDM_892395s OntoDM_892395 OntoDM_892395 A data example is a data item that represents one unit of data and it is a part of a dataset. It is a synonim with a case or example or observation in statistics. data example OntoDM_895197s OntoDM_895197 OntoDM_895197 output set of discrete specification is an output set specification that denotes a set of discrete datatype on the output part of the data. output:set of discrete OntoDM_900172s OntoDM_900172 OntoDM_900172 GC DAG based HC algorithm for multiple path and non-mandatory leaf node prediction OntoDM_901970s OntoDM_901970 OntoDM_901970 LCN tree-based hierarchical classification algorithm for multiple path and mandatory leaf node prediction is a data mining algorithm that solves a tree-based hierarchical classification task with multiple label paths and full depth labeling and as a result produces a hierarchical classification model using a local classifier per node (LCN) approach. LCN tree based HC algorithm for multiple path and mandatory leaf node prediction OntoDM_908131s OntoDM_908131 OntoDM_908131 output labeled graph specification is an output structured datatype specification that denotes a labeled graph datatype on the output part of the data. labeled graph output specification OntoDM_910828s OntoDM_910828 OntoDM_910828 Boosting OntoDM_913132s OntoDM_913132 OntoDM_913132 multi class classification task is a flat classification task where the objective is to predict a discrete output (represented with a boolean or discrete datatype) from a set of features (represented by a descriptive tuple of primitives datatype). supervised multi-class classification task OntoDM_917475s OntoDM_917475 OntoDM_917475 evaluation algorithm execution OntoDM_918795s OntoDM_918795 OntoDM_918795 probability distribution evaliuation OntoDM_919659s OntoDM_919659 OntoDM_919659 LCPN tree-based hierarchical classification algorithm for multiple path and mandatory leaf node prediction is a data mining algorithm that solves a tree-based hierarchical classification task with multiple label paths and full depth labeling and as a result produces a hierarchical classification model using a local classifier per parent node (LCPN) approach. LPCN tree based HC algorithm for multiple path and non-mandatory leaf node prediction OntoDM_930862s OntoDM_930862 OntoDM_930862 Tree based hierarchical classification task with multiple label paths and partial depth labeling is a tree based hierarchical classification task where the objective is to predict a set of labels organized in a tree (represented with a output tree with boolean edges and discrete nodes) from a set of features (represented by a descriptive tuple of primitives datatype), where the data instances are allowed to have multiple paths of labels and at least one instance has a partial depth of labeling. tree-based hierarchical classification task with multiple label paths and partial depth labeling OntoDM_931732s OntoDM_931732 OntoDM_931732 Hierarchical classification task is a feature-based structured output prediction task where the objective is to predict a hierarchical output (represented with a output labeled graph datatype) from a set of features (represented by a descriptive tuple of primitives datatype). supervised hierarchical classification task OntoDM_936293s OntoDM_936293 OntoDM_936293 output tuple of real specification is an output tuple of primitives specification that denotes a tuple of reals datatype on the output part of the data. output:tuple of real OntoDM_938471s OntoDM_938471 OntoDM_938471 a data example specification is a data item specification entity that is about a data example. data example specification OntoDM_941659s OntoDM_941659 OntoDM_941659 constraint based data mining task OntoDM_941793s OntoDM_941793 OntoDM_941793 Feature-based predictive modeling algorithm for primitive output is a data mining algorithm that solves a feature-based primitive output prediction task and as a result produces a feature-based predictive model for primitive output. feature-based predictive modeling algorithm for primitive output OntoDM_942569s OntoDM_942569 OntoDM_942569 A structure-based predictive model for primitive output is a predictive model specification and denotes predictive models that are built on data having primitive datatype on the output part, and a structured datatype on the descriptive part. structure-based predictive model for primitive output OntoDM_942737s OntoDM_942737 OntoDM_942737 LC DAG-based hierarchical classification algorithm is a data mining algorithm that solves a DAG-based hierarchical classification task and as a result produces a hierarchical classification model using a local classifier (LC) approach. LC DAG based HC algorithm OntoDM_944653s OntoDM_944653 OntoDM_944653 data mining software OntoDM_960431s OntoDM_960431 OntoDM_960431 hierarchical classification dataset is a dataset specification of a labeled dataset with tuple of primitives datatype (specified with the feature set specification) on the descriptive part and a labeled graph datatype on the output part of the data. hierarchical classification dataset OntoDM_970232s OntoDM_970232 OntoDM_970232 Stacking OntoDM_975727s OntoDM_975727 OntoDM_975727 LCL DAG-based hierarchical classification algorithm for multiple path and mandatory leaf node prediction is a data mining algorithm that solves a DAG-based hierarchical classification task with multiple label paths and full depth labeling and as a result produces a hierarchical classification model using a local classifier per level (LCL) approach. LCL DAG based HC algorithm for multiple path and mandatory leaf node prediction OntoDM_982352s OntoDM_982352 OntoDM_982352 data mining workflow execution OntoDM_997152s OntoDM_997152 OntoDM_997152 generalization processing algorithm OntoDM_U1_059913s OntoDM_U1_059913 OntoDM_U1_059913 evaluation workflow execution OntoDM_U1_858511s OntoDM_U1_858511 OntoDM_U1_858511 evaluation workflow OntoDT_10000000000 completely labeled dataset OntoDT_10000000001 semi-labeled dataset OntoDT_10000000002 partially labeled dataset OntoDT_10000000003 supervised predictive modelling task OntoDT_10000000004 semi-supervised predictive modelling task OntoDT_10000000005 semi-supervised structured output prediction task OntoDT_10000000006 semi-supervised feature-based structured output prediction task OntoDT_10000000007 semi-supervised hierarchical classification task OntoDT_10000000008 semi-supervised DAG based hierarchical classification task OntoDT_10000000009 semi-supervised tree-based hierarchical classification task OntoDT_10000000010 semi-supervised multi-label classification task OntoDT_10000000011 semi-supervised multi-target prediction task OntoDT_10000000012 semi-supervised multi-target classification task OntoDT_10000000013 semi-supervised multi-target binary classification task OntoDT_10000000014 semi-supervised multi-target multi-class classification task OntoDT_10000000015 semi-supervised multi-target regression task OntoDT_10000000016 semi-supervised time-series prediction task OntoDT_10000000017 semi-supervised structure-based structured output prediction task OntoDT_10000000018 semi-supervised primitive output prediction task OntoDT_10000000019 semi-supervised feature-based primitive output prediction task OntoDT_10000000020 semi-supervised flat classification task OntoDT_10000000021 semi-supervised binary classification task OntoDT_10000000022 semi-supervised multi-class classification task OntoDT_10000000023 semi-supervised regression task OntoDT_10000000024 semi-supervised structure-based primitive output prediction task OntoDT_10000000025 online predictive modeling task OntoDT_10000000026 batch predictive modeling task OntoDT_10000000027 online supervised predictive modeling task OntoDT_10000000028 online semi-supervised predictive modeling task OntoDT_10000000029 online semi-supervised structured output prediction task OntoDT_10000000030 online semi-supervised feature-based structured output prediction task OntoDT_10000000031 online semi-supervised hierarchical classification task OntoDT_10000000032 online semi-supervised DAG based hierarchical classification task OntoDT_10000000033 online semi-supervised tree based hierarchical classification task OntoDT_10000000034 online semi-supervised multi-label classification task OntoDT_10000000035 online semi-supervised multi-target prediction task OntoDT_10000000036 online semi-supervised multi-target classification task OntoDT_10000000037 online semi-supervised multi-target binary classification task OntoDT_10000000038 online semi-supervised multi-target multi-class classification task OntoDT_10000000039 online semi-supervised multi-target regression task OntoDT_10000000040 online semi-supervised time-series prediction task OntoDT_10000000041 online semi-supervised structure-based structured output prediction task OntoDT_10000000042 online semi-supervised primitive output prediction task OntoDT_10000000043 online semi-supervised feature-based primitive output prediction task OntoDT_10000000044 online semi-supervised flat classification task OntoDT_10000000045 online semi-supervised binary classification task OntoDT_10000000046 online semi-supervised multi-class classification task OntoDT_10000000047 online semi-supervised regression task OntoDT_10000000048 online semi-supervised structure-based primitive output prediction task OntoDT_10000000049 online supervised structured output prediction task OntoDT_10000000050 online supervised feature-based structured output prediction task OntoDT_10000000051 online supervised hierarchical classification task OntoDT_10000000052 online supervised DAG based hierarchical classification task OntoDT_10000000053 online supervised tree-based hierarchical classification task OntoDT_10000000054 online supervised multi-label classification task OntoDT_10000000055 online supervised multi-target prediction task OntoDT_10000000056 online supervised multi-target classification task OntoDT_10000000057 online supervised multi-target binary classification task OntoDT_10000000058 online supervised multi-target multi-class classification task OntoDT_10000000059 online supervised multi-target regression task OntoDT_10000000060 online supervised time-series prediction task OntoDT_10000000061 online supervised structure-based structured output prediction task OntoDT_10000000062 online supervised primitive output prediction task OntoDT_10000000063 online supervised feature-based primitive output prediction task OntoDT_10000000064 online supervised flat classification task OntoDT_10000000065 online supervised binary classification task OntoDT_10000000066 online supervised multi-class classification task OntoDT_10000000067 online supervised regression task OntoDT_10000000068 online supervised structure-based primitive output prediction task OntoDT_10000000069 data stream specification OntoDT_10000000070 labeled data stream OntoDT_10000000071 completely labeled data stream OntoDT_10000000072 semi-labeled data stream OntoDT_10000000073 partially labeled data stream OntoDT_10000000074 unlabeled data stream OntoDT_10000000075 semi-labeled dataset with structured output OntoDT_10000000076 feature-based semi-labeled dataset with structured output OntoDT_10000000077 feature-based time-series semi-labeled prediction dataset OntoDT_10000000078 hierarchical semi-labeled classification dataset OntoDT_10000000079 DAG-based hierarchical semi-labeled classification dataset OntoDT_10000000080 tree-based hierarchical semi-labeled classification dataset OntoDT_10000000081 multi-label semi-labeled classification dataset OntoDT_10000000082 multi-target semi-labeled prediction dataset OntoDT_10000000083 multi-target semi-labeled binary classification dataset OntoDT_10000000084 multi-target semi-labeled multi-class classification dataset OntoDT_10000000085 multi-target semi-labeled regression dataset OntoDT_10000000086 structure-based semi-labeled dataset with structured output OntoDT_10000000087 semi-labeled dataset with primitive output OntoDT_10000000088 feature-based semi-labeled dataset with primitive output OntoDT_10000000089 flat semi-labeled classification dataset OntoDT_10000000090 binary semi-labeled classification dataset OntoDT_10000000091 multi-class semi-labeled classification dataset OntoDT_10000000092 semi-labeled regression dataset OntoDT_10000000093 structure-based semi-labeled dataset with primitive output OntoDT_10000000094 semi-labeled data stream with structured output OntoDT_10000000095 feature-based semi-labeled data stream with structured output OntoDT_10000000096 feature-based time-series semi-labeled prediction data stream OntoDT_10000000097 hierarchical semi-labeled classification data stream OntoDT_10000000098 DAG-based hierarchical semi-labeled classification data stream OntoDT_10000000099 tree-based hierarchical semi-labeled classification data stream OntoDT_10000000100 multi-label semi-labeled classification data stream OntoDT_10000000101 multi-target semi-labeled prediction data stream OntoDT_10000000102 multi-target semi-labeled binary classification data stream OntoDT_10000000103 multi-target semi-labeled multi-class classification data stream OntoDT_10000000104 multi-target semi-labeled regression data stream OntoDT_10000000105 structure-based semi-labeled data stream with structured output OntoDT_10000000106 semi-labeled data stream with primitive output OntoDT_10000000107 feature-based semi-labeled data stream with primitive output OntoDT_10000000108 flat semi-labeled classification data stream OntoDT_10000000109 binary semi-labeled classification data stream OntoDT_10000000110 multi-class semi-labeled classification data stream OntoDT_10000000111 semi-labeled regression data stream OntoDT_10000000112 structure-based semi-labeled data stream with primitive output OntoDT_10000000113 multi-target semi-labeled classification data stream OntoDT_10000000114 multi-target semi-labeled classification dataset OntoDT_10000000115 completely labeled data stream with structured output OntoDT_10000000116 feature-based completely labeled data stream with structured output OntoDT_10000000117 feature-based time-series prediction data stream OntoDT_10000000118 hierarchical classification data stream OntoDT_10000000119 DAG-based hierarchical classification data stream OntoDT_10000000120 tree-based hierarchical classification data stream OntoDT_10000000121 multi-label classification data stream OntoDT_10000000122 multi-target prediction data stream OntoDT_10000000123 multi-target classification data stream OntoDT_10000000124 multi-target binary classification data stream OntoDT_10000000125 multi-target multi-class classification data stream OntoDT_10000000126 multi-target regression data stream OntoDT_10000000127 structure-based completely labeled data stream with structured output OntoDT_10000000128 completely labeled data stream with primitive output OntoDT_10000000129 feature-based completely labeled data stream with primitive output OntoDT_10000000130 flat classification data stream OntoDT_10000000131 binary classification data stream OntoDT_10000000132 multi-class classification data stream OntoDT_10000000133 regression data stream OntoDT_10000000134 structure-based completely labeled data stream with primitive output OntoDM-Viz_00000s OntoDM-Viz_00000 OntoDM-Viz_00000 Void is the datatype representing an object whose presence is syntactically or semantically required, but carries no information in a given instance. void datatype OntoDT_0000001s OntoDT_0000001 OntoDT_0000001 ordinal datatype OntoDT_0000002s OntoDT_0000002 OntoDT_0000002 boolean is the mathematical datatype associated with two-valued logic. boolean datatype OntoDT_0000003s OntoDT_0000003 OntoDT_0000003 integer is the mathematical datatype comprising the exact integral values. integer datatype OntoDT_0000004s OntoDT_0000004 OntoDT_0000004 Rational is the mathematical datatype comprising the “rational numbers”. rational datatype OntoDT_0000203s OntoDT_0000203 OntoDT_0000203 synonym: subtype extended datatype OntoDT_0000204s OntoDT_0000204 OntoDT_0000204 dimensionality OntoDT_0000208s OntoDT_0000208 OntoDT_0000208 homogenous aggregate generator OntoDT_0000209s OntoDT_0000209 OntoDT_0000209 heterogenous aggregate generator OntoDT_0000210s OntoDT_0000210 OntoDT_0000210 homogenous aggregate generator with variable size OntoDT_0000211s OntoDT_0000211 OntoDT_0000211 homogenous unordered aggregate generator with variable size OntoDT_0000212s OntoDT_0000212 OntoDT_0000212 non-numeric primitive datatype OntoDT_0000213s OntoDT_0000213 OntoDT_0000213 numeric primitive datatype OntoDT_0000214s OntoDT_0000214 OntoDT_0000214 numeric ordered primitive datatype OntoDT_0000215s OntoDT_0000215 OntoDT_0000215 non-numeric unordered primitive datatype OntoDT_0000216s OntoDT_0000216 OntoDT_0000216 non-numeric ordered primitive datatype OntoDT_0000217s OntoDT_0000217 OntoDT_0000217 homogenous aggregate datatype OntoDT_0000218s OntoDT_0000218 OntoDT_0000218 heterogenous aggregate datatype OntoDT_0000219s OntoDT_0000219 OntoDT_0000219 homogenous aggregate datatype with variable size OntoDT_0000220s OntoDT_0000220 OntoDT_0000220 homogenous unordered aggregate datatype with variable size OntoDT_0000221s OntoDT_0000221 OntoDT_0000221 direct access property OntoDT_0000222s OntoDT_0000222 OntoDT_0000222 indirect acess property OntoDT_0000223s OntoDT_0000223 OntoDT_0000223 add operation OntoDT_0000224s OntoDT_0000224 OntoDT_0000224 delete operation OntoDT_0000225s OntoDT_0000225 OntoDT_0000225 difference operation OntoDT_0000226s OntoDT_0000226 OntoDT_0000226 equal operation OntoDT_0000227s OntoDT_0000227 OntoDT_0000227 in order operation OntoDT_0000228s OntoDT_0000228 OntoDT_0000228 insert operation OntoDT_0000229s OntoDT_0000229 OntoDT_0000229 multiply operation OntoDT_0000230s OntoDT_0000230 OntoDT_0000230 dyadic select operation OntoDT_0000231s OntoDT_0000231 OntoDT_0000231 isEmpty operation OntoDT_0000232s OntoDT_0000232 OntoDT_0000232 negate operation OntoDT_0000233s OntoDT_0000233 OntoDT_0000233 nonNegative operation OntoDT_0000234s OntoDT_0000234 OntoDT_0000234 promote operation OntoDT_0000235s OntoDT_0000235 OntoDT_0000235 reciprocial operation OntoDT_0000236s OntoDT_0000236 OntoDT_0000236 round operation OntoDT_0000237s OntoDT_0000237 OntoDT_0000237 monadic select operation OntoDT_0000238s OntoDT_0000238 OntoDT_0000238 serialize operation OntoDT_0000239s OntoDT_0000239 OntoDT_0000239 successor operation OntoDT_0000241s OntoDT_0000241 OntoDT_0000241 countable OntoDT_0000242s OntoDT_0000242 OntoDT_0000242 finite OntoDT_0000243s OntoDT_0000243 OntoDT_0000243 uncountable OntoDT_0000244s OntoDT_0000244 OntoDT_0000244 bounded above OntoDT_0000245s OntoDT_0000245 OntoDT_0000245 bounded below OntoDT_0000246s OntoDT_0000246 OntoDT_0000246 unbounded above OntoDT_0000247s OntoDT_0000247 OntoDT_0000247 unbounded below OntoDT_0000248s OntoDT_0000248 OntoDT_0000248 bounded OntoDT_0000249s OntoDT_0000249 OntoDT_0000249 unbounded OntoDT_0000250s OntoDT_0000250 OntoDT_0000250 approximate OntoDT_0000251s OntoDT_0000251 OntoDT_0000251 exact OntoDT_0000252s OntoDT_0000252 OntoDT_0000252 numeric OntoDT_0000253s OntoDT_0000253 OntoDT_0000253 non-numeric OntoDT_0000254s OntoDT_0000254 OntoDT_0000254 ordered OntoDT_0000255s OntoDT_0000255 OntoDT_0000255 non-ordered OntoDT_0000256s OntoDT_0000256 OntoDT_0000256 Add:complex OntoDT_0000257s OntoDT_0000257 OntoDT_0000257 Add:integer OntoDT_0000258s OntoDT_0000258 OntoDT_0000258 Add:rational OntoDT_0000259s OntoDT_0000259 OntoDT_0000259 Add:real OntoDT_0000260s OntoDT_0000260 OntoDT_0000260 Add:scaled OntoDT_0000261s OntoDT_0000261 OntoDT_0000261 Delete:bag OntoDT_0000262s OntoDT_0000262 OntoDT_0000262 Delete:table OntoDT_0000263s OntoDT_0000263 OntoDT_0000263 Difference:set OntoDT_0000264s OntoDT_0000264 OntoDT_0000264 Difference:time&date OntoDT_0000265s OntoDT_0000265 OntoDT_0000265 Select:array OntoDT_0000266s OntoDT_0000266 OntoDT_0000266 Select:table OntoDT_0000267s OntoDT_0000267 OntoDT_0000267 Equal:array OntoDT_0000268s OntoDT_0000268 OntoDT_0000268 Equal:bag OntoDT_0000269s OntoDT_0000269 OntoDT_0000269 Equal:boolean OntoDT_0000270s OntoDT_0000270 OntoDT_0000270 Equal:character OntoDT_0000271s OntoDT_0000271 OntoDT_0000271 Equal:choice OntoDT_0000272s OntoDT_0000272 OntoDT_0000272 Equal:class OntoDT_0000273s OntoDT_0000273 OntoDT_0000273 Equal:complex OntoDT_0000274s OntoDT_0000274 OntoDT_0000274 Equal:enumerated OntoDT_0000275s OntoDT_0000275 OntoDT_0000275 Equal:integer OntoDT_0000276s OntoDT_0000276 OntoDT_0000276 Equal:ordinal OntoDT_0000277s OntoDT_0000277 OntoDT_0000277 Equal:pointer OntoDT_0000278s OntoDT_0000278 OntoDT_0000278 Equal:procedure OntoDT_0000279s OntoDT_0000279 OntoDT_0000279 Equal:rational OntoDT_0000280s OntoDT_0000280 OntoDT_0000280 Equal:real OntoDT_0000281s OntoDT_0000281 OntoDT_0000281 Equal:record OntoDT_0000282s OntoDT_0000282 OntoDT_0000282 Equal:scaled OntoDT_0000283s OntoDT_0000283 OntoDT_0000283 Equal:sequence OntoDT_0000284s OntoDT_0000284 OntoDT_0000284 Equal:set OntoDT_0000285s OntoDT_0000285 OntoDT_0000285 Equal:discrete OntoDT_0000286s OntoDT_0000286 OntoDT_0000286 Equal:table OntoDT_0000287s OntoDT_0000287 OntoDT_0000287 Equal:time&date OntoDT_0000288s OntoDT_0000288 OntoDT_0000288 Equal:void OntoDT_0000289s OntoDT_0000289 OntoDT_0000289 InOrder:enumerated OntoDT_0000290s OntoDT_0000290 OntoDT_0000290 InOrder:interger OntoDT_0000291s OntoDT_0000291 OntoDT_0000291 InOrder:ordinal OntoDT_0000292s OntoDT_0000292 OntoDT_0000292 InOrder:rational OntoDT_0000293s OntoDT_0000293 OntoDT_0000293 InOrder:real OntoDT_0000294s OntoDT_0000294 OntoDT_0000294 InOrder:scaled OntoDT_0000295s OntoDT_0000295 OntoDT_0000295 InOrder:time&date OntoDT_0000296s OntoDT_0000296 OntoDT_0000296 Insert:bag OntoDT_0000297s OntoDT_0000297 OntoDT_0000297 Insert:table OntoDT_0000298s OntoDT_0000298 OntoDT_0000298 Multiply:complex OntoDT_0000299s OntoDT_0000299 OntoDT_0000299 Multiply:integer OntoDT_0000300s OntoDT_0000300 OntoDT_0000300 Multiply:rational OntoDT_0000301s OntoDT_0000301 OntoDT_0000301 Multiply:real OntoDT_0000302s OntoDT_0000302 OntoDT_0000302 Multiply:scaled OntoDT_0000303s OntoDT_0000303 OntoDT_0000303 And:boolean OntoDT_0000304s OntoDT_0000304 OntoDT_0000304 Append:sequence OntoDT_0000305s OntoDT_0000305 OntoDT_0000305 AttributeFunctionOverride:class OntoDT_0000306s OntoDT_0000306 OntoDT_0000306 AttributeReplace:class OntoDT_0000307s OntoDT_0000307 OntoDT_0000307 Divide:scaled OntoDT_0000308s OntoDT_0000308 OntoDT_0000308 Fetch:table OntoDT_0000309s OntoDT_0000309 OntoDT_0000309 FieldReplace:record OntoDT_0000310s OntoDT_0000310 OntoDT_0000310 Intersection:set OntoDT_0000311s OntoDT_0000311 OntoDT_0000311 Lsln:set OntoDT_0000312s OntoDT_0000312 OntoDT_0000312 Or:boolean OntoDT_0000313s OntoDT_0000313 OntoDT_0000313 Subset:set OntoDT_0000314s OntoDT_0000314 OntoDT_0000314 Tag:choice OntoDT_0000315s OntoDT_0000315 OntoDT_0000315 Union:set OntoDT_0000316s OntoDT_0000316 OntoDT_0000316 dyadic aritmetic operation OntoDT_0000317s OntoDT_0000317 OntoDT_0000317 dyadic logical operation OntoDT_0000318s OntoDT_0000318 OntoDT_0000318 dyadic set operation OntoDT_0000319s OntoDT_0000319 OntoDT_0000319 dyadic updating operation OntoDT_0000320s OntoDT_0000320 OntoDT_0000320 dyadic comparison operation OntoDT_0000321s OntoDT_0000321 OntoDT_0000321 dyadic retrieve operation OntoDT_0000322s OntoDT_0000322 OntoDT_0000322 IsEmpty:bag OntoDT_0000323s OntoDT_0000323 OntoDT_0000323 IsEmpty:sequence OntoDT_0000324s OntoDT_0000324 OntoDT_0000324 IsEmpty:table OntoDT_0000325s OntoDT_0000325 OntoDT_0000325 Select:bag OntoDT_0000326s OntoDT_0000326 OntoDT_0000326 Select:set OntoDT_0000327s OntoDT_0000327 OntoDT_0000327 Negate:complex OntoDT_0000328s OntoDT_0000328 OntoDT_0000328 Negate:integer OntoDT_0000329s OntoDT_0000329 OntoDT_0000329 Negate:rational OntoDT_0000330s OntoDT_0000330 OntoDT_0000330 Negate:real OntoDT_0000331s OntoDT_0000331 OntoDT_0000331 Negate:scaled OntoDT_0000332s OntoDT_0000332 OntoDT_0000332 NonNegative:integer OntoDT_0000333s OntoDT_0000333 OntoDT_0000333 NonNegative:rational OntoDT_0000334s OntoDT_0000334 OntoDT_0000334 Promote:complex OntoDT_0000335s OntoDT_0000335 OntoDT_0000335 Promote:rational OntoDT_0000336s OntoDT_0000336 OntoDT_0000336 Promote:real OntoDT_0000337s OntoDT_0000337 OntoDT_0000337 Reciprocal:rational OntoDT_0000338s OntoDT_0000338 OntoDT_0000338 Reciprocal:real OntoDT_0000339s OntoDT_0000339 OntoDT_0000339 Reciprocal:complex OntoDT_0000340s OntoDT_0000340 OntoDT_0000340 Round:scaled OntoDT_0000341s OntoDT_0000341 OntoDT_0000341 Round:time&date OntoDT_0000342s OntoDT_0000342 OntoDT_0000342 Serialize:bag OntoDT_0000343s OntoDT_0000343 OntoDT_0000343 Serialize:table OntoDT_0000344s OntoDT_0000344 OntoDT_0000344 Successor:enumerated OntoDT_0000345s OntoDT_0000345 OntoDT_0000345 Successor:ordinal OntoDT_0000346s OntoDT_0000346 OntoDT_0000346 AttributeFunctionInvocation:class OntoDT_0000347s OntoDT_0000347 OntoDT_0000347 AttributeSelect:class OntoDT_0000348s OntoDT_0000348 OntoDT_0000348 Cast:choice OntoDT_0000349s OntoDT_0000349 OntoDT_0000349 Dereference:pointer OntoDT_0000350s OntoDT_0000350 OntoDT_0000350 Discriminant:choice OntoDT_0000351s OntoDT_0000351 OntoDT_0000351 Extend:time&date OntoDT_0000352s OntoDT_0000352 OntoDT_0000352 FieldSelect:record OntoDT_0000353s OntoDT_0000353 OntoDT_0000353 Head:sequence OntoDT_0000354s OntoDT_0000354 OntoDT_0000354 Invoke:procedure OntoDT_0000355s OntoDT_0000355 OntoDT_0000355 MapToBag:table OntoDT_0000356s OntoDT_0000356 OntoDT_0000356 MapToTable:table OntoDT_0000357s OntoDT_0000357 OntoDT_0000357 Not:boolean OntoDT_0000358s OntoDT_0000358 OntoDT_0000358 SetOf:set OntoDT_0000359s OntoDT_0000359 OntoDT_0000359 SquareRoot:complex OntoDT_0000360s OntoDT_0000360 OntoDT_0000360 Tail:sequence OntoDT_0000361s OntoDT_0000361 OntoDT_0000361 monadic aritmetic operation OntoDT_0000362s OntoDT_0000362 OntoDT_0000362 monadic retrive operation OntoDT_0000363s OntoDT_0000363 OntoDT_0000363 map operation OntoDT_0000364s OntoDT_0000364 OntoDT_0000364 boolean operation OntoDT_0000365s OntoDT_0000365 OntoDT_0000365 Replace:array OntoDT_0000366s OntoDT_0000366 OntoDT_0000366 Empty:bag OntoDT_0000367s OntoDT_0000367 OntoDT_0000367 Empty:sequence OntoDT_0000368s OntoDT_0000368 OntoDT_0000368 Empty:set OntoDT_0000369s OntoDT_0000369 OntoDT_0000369 Empty:table OntoDT_0000370s OntoDT_0000370 OntoDT_0000370 index access OntoDT_0000371s OntoDT_0000371 OntoDT_0000371 key access OntoDT_0000372s OntoDT_0000372 OntoDT_0000372 access by value OntoDT_0000373s OntoDT_0000373 OntoDT_0000373 implementation dependent access OntoDT_0000374s OntoDT_0000374 OntoDT_0000374 position access OntoDT_0000375s OntoDT_0000375 OntoDT_0000375 ordered aggregate OntoDT_0000376s OntoDT_0000376 OntoDT_0000376 unordered aggregate OntoDT_0000377s OntoDT_0000377 OntoDT_0000377 identifier not unique OntoDT_0000378s OntoDT_0000378 OntoDT_0000378 identifier unique OntoDT_0000379s OntoDT_0000379 OntoDT_0000379 fixed size OntoDT_0000380s OntoDT_0000380 OntoDT_0000380 variable size OntoDT_0000381s OntoDT_0000381 OntoDT_0000381 component mandatory OntoDT_0000382s OntoDT_0000382 OntoDT_0000382 component non-mandatory OntoDT_0000383s OntoDT_0000383 OntoDT_0000383 one dimensional OntoDT_0000384s OntoDT_0000384 OntoDT_0000384 two dimensional OntoDT_0000385s OntoDT_0000385 OntoDT_0000385 multi dimensional OntoDT_0000386s OntoDT_0000386 OntoDT_0000386 homogenous OntoDT_0000387s OntoDT_0000387 OntoDT_0000387 heterogenous OntoDT_0000388s OntoDT_0000388 OntoDT_0000388 recursive OntoDT_0000389s OntoDT_0000389 OntoDT_0000389 non-recursive OntoDT_0000390s OntoDT_0000390 OntoDT_0000390 structured OntoDT_0000391s OntoDT_0000391 OntoDT_0000391 unstructured OntoDT_0000392s OntoDT_0000392 OntoDT_0000392 semi-structured OntoDT_0000393s OntoDT_0000393 OntoDT_0000393 non-unique values OntoDT_0000394s OntoDT_0000394 OntoDT_0000394 unique values OntoDT_0000396s OntoDT_0000396 descriptive data without missing values field component OntoDT_0000397s OntoDT_0000397 completely labeled target data field component OntoDT_0000408s OntoDT_0000408 OntoDT_0000408 bound OntoDT_004c390e_eaf3_4960_9918_c02cbd396ea4 tree with named nodes datatype OntoDT_47a7dfda_6531_4182_b5e7_c275c9861f34 descriptive field component OntoDT_5512ddf7_aa51_42f2_881c_36d79b91175a DAG named node component OntoDT_8c7ab50e_e725_47f8_be3e_b14b257f8bbe target field component OntoDT_UC_0000006s OntoDT_UC_0000006 completely labeled target primitive field component OntoDT_UC_0000007s OntoDT_UC_0000007 completely labeled target boolean field component OntoDT_UC_0000008s OntoDT_UC_0000008 completely labeled target discrete field component OntoDT_UC_0000009s OntoDT_UC_0000009 completely labeled target real field component OntoDT_UC_0000010s OntoDT_UC_0000010 completely labeled target sequence of real field component OntoDT_UC_0000011s OntoDT_UC_0000011 completely labeled target hierarchical field component OntoDT_UC_0000012s OntoDT_UC_0000012 completely labeled target DAG field component OntoDT_UC_0000013s OntoDT_UC_0000013 completely labeled target tree field component OntoDT_UC_0000014s OntoDT_UC_0000014 completely labeled target set of discrete field component OntoDT_UC_0000015s OntoDT_UC_0000015 completely labeled target record of primitives field component OntoDT_UC_0000016s OntoDT_UC_0000016 completely labeled target record of boolean field component OntoDT_UC_0000017s OntoDT_UC_0000017 completely labeled target record of discrete field component OntoDT_UC_0000018s OntoDT_UC_0000018 completely labeled target record of reals field component OntoDT_UC_0000019s OntoDT_UC_0000019 completely labeled target structured field component OntoDT_UC_0000020s OntoDT_UC_0000020 descriptive record of primitives without missing values field component OntoDT_UC_0000021s OntoDT_UC_0000021 descriptive record of reals without missing values field component OntoDT_UC_0000022s OntoDT_UC_0000022 descriptive record of boolean without missing values field component OntoDT_UC_0000023s OntoDT_UC_0000023 descriptive record of discrete without missing values field component OntoDT_UC_0000024s OntoDT_UC_0000024 descriptive set of integer without missing values field component OntoDT_UC_0000025s OntoDT_UC_0000025 descriptive strucured without missing values field component OntoDT_UC_0000026s OntoDT_UC_0000026 OntoDT_UC_0000026 set of integer datatype OntoDT_UC_0000027s OntoDT_UC_0000027 OntoDT_UC_0000027 integer base datatype OntoDT_UC_0000030s OntoDT_UC_0000030 OntoDT_UC_0000030 positive integer OntoDT_UC_0000031s OntoDT_UC_0000031 OntoDT_UC_0000031 positive integer range generator 1 OntoDT_ca96378e_c421_454c_9ba6_db5010ce068a tree named node component 1 OntoDT_cfe27088_b275_4c80_aa9b_76031276226c tree node component OntoDT_e2caaa71_5d5b_45bf_b571_5a88c6dbd6c7 DAG node component OntoDT_fdc29bbe_5fe1_4d0c_87dd_2414b82a13f7 DAG with named nodes datatype DMType_053b0c7b_d8cc_40ac_aa56_aa068c0cf830 real unlabeled data with missing values base type DMType_32857f39_cadc_4079_82a2_e59df0ccf930 transactional unlabeled data without missing values base type DMType_3673e47d_b822_40ed_b8e7_a928f20832d2 record with one component base type DMType_3fed3c83_ae4d_4036_92fc_041e571c451c record with two components base type DMType_48b3005d_3bfe_41e0_a314_63ac5ec40912 unlabeled data with missing values base type DMType_52eb5123_0162_4fc0_90b3_acfc56e77561 sequence of records with two components DMType_582a2f8d_5fd1_432c_9c6b_4a59787a28e0 discrete unlabeled data with missing values base type DMType_5cecd5b2_d7f3_4d55_a131_8a9a6d5c17cc unlabeled data base type DMType_5f451bb8_3e2b_4cb9_8028_29a52bbb687f sequence of records with one component DMType_6c8717e4_dbc9_4d67_bb44_1fea01fe15c0 boolean unlabeled data without missing values base type DMType_6ead9e09_853c_4b1c_bd33_96454b02a80c real unlabeled data without missing values base type DMType_86256372_9b32_4299_bed0_210543ffacaa feature-based unlabeled data with missing values base type DMType_b5af437a_5ac8_4498_8e07_952d4b9f9a96 feature-based unlabeled data without missing values base type DMType_bf8552c1_2b4b_4f14_822d_d0ab9ebeb878 boolean unlabeled data with missing values base type DMType_e2185a56_8925_48a1_a587_8ae14eedb7cc unlabeled data without missing values base type DMType_e6389935_bf31_468d_a781_ff79bab1ec50 transactional unlabeled data with missing values base type DMType_e701b657_8da6_406e_93b6_c0e8cc09c798 discrete unlabeled data without missing values base type unlabeled data with missing values semi-labeled stream data without missing values semi-labeled data with missing values primitive alternative component unlabeled data with missing values base type directed information network with labeled homogenous nodes and labeled homogenous edges feature-based semi-labeled data with missing values and with tree with named nodes output base type completely labeled stream data with missing values feature-based semi-labeled data without missing values and with DAG with named nodes output base type feature-based semi-labeled data without missing values and with tree with named nodes output undirected information network with unlabeled heterogenous nodes and labeled homogenous edges semi-labeled data semi-labeled target sequence of reals field component partially labeled data without missing values base type directed information network with homogenous nodes and homogenous edges choice(record of boolean,void) datatype semi-labeled target tree field component undirected information network with homogenous nodes and heterogenous edges choice(primitive,void) datatype directed information network with unlabeled heterogenous nodes and labeled homogenous edges choice(hierarchical,void) datatype undirected information network with homogenous nodes and homogenous edges feature-based semi-labeled data without missing values and with tree with named nodes output base type feature-based completely labeled data with missing values and with DAG with named nodes output base type record of choice(boolean,void) directed information network with labeled heterogenous nodes and unlabeled homogenous edges directed information network with labeled homogenous nodes and labeled heterogenous edges undirected information network with heterogenous nodes and homogenous edges directed information network with unlabeled heterogenous nodes and unlabeled homogenous edges sequence of choice(discrete,void) choice(record of reals,void) datatype undirected information network with labeled heterogenous nodes and labeled heterogenous edges choice(discrete,void) field component feature-based semi-labeled stream data with missing values and with tree with named nodes output feature-based completely labeled stream data with missing values and with tree with named nodes output undirected information network with labeled heterogenous nodes and labeled homogenous edges edge specification directed information network with homogenous nodes and heterogenous edges undirected information network with labeled heterogenous nodes and unlabeled heterogenous edges choice(real,void) base type feature-based completely labeled data with missing values and with tree with named nodes output semi-labeled stream data choice(record of primitive,void) datatype descriptive record of discrete with missing values field component semi-labeled target hierarchical field component undirected information network with heterogenous nodes undirected information network with labeled homogenous nodes and unlabeled heterogenous edges directed information network with labeled heterogenous nodes and unlabeled heterogenous edges undirected information network with labeled homogenous nodes and unlabeled homogenous edges semi-labeled target record of primitives field component undirected information network with labeled heterogenous nodes and unlabeled homogenous edges completely labeled target DAG with named nodes field component void alternative component unlabeled data without missing values base type feature-based semi-labeled data without missing values and with DAG with named nodes output feature-based semi-labeled stream data with missing values and with DAG with named nodes output semi-labeled target discrete field component directed information network with unlabeled homogenous nodes and unlabeled heterogenous edges directed information network with heterogenous nodes and heterogenous edges completely labeled data semi-labeled target DAG with named nodes field component undirected information network with unlabeled heterogenous nodes and labeled heterogenous edges hierarchical alternative component descriptive record of primitives with missing values field component directed information network with heterogenous nodes undirected information network with unlabeled homogenous nodes and labeled heterogenous edges directed information network with unlabeled heterogenous nodes and labeled heterogenous edges feature-based completely labeled stream data with missing values and with DAG with named nodes output choice(sequence of reals,void) datatype directed information network with unlabeled heterogenous nodes and unlabeled heterogenous edges semi-labeled target real field component feature-based completely labeled stream data without missing values and with DAG with named nodes output completelly labeled data with missing values base type partially labeled data with missing values base type tree with named nodes alternative component choice(boolean,void) field component descriptive record of boolean with missing values field component semi-labeled target record of discrete field component undirected information network with heterogenous nodes and heterogenous edges directed information network with labeled heterogenous nodes and labeled heterogenous edges choice(real,void) datatype feature-based semi-labeled stream data without missing values and with DAG with named nodes output undirected edge specification choice(DAG,void) datatype discrete alternative component feature-based semi-labeled stream data without missing values and with tree with named nodes output semi-labeled data without missing values directed information network with homogenous nodes semi-labeled target tree with named nodes field component undirected information network with unlabeled heterogenous nodes and unlabeled heterogenous edges feature-based completely labeled data without missing values and with DAG with named nodes output directed information network with labeled homogenous nodes and unlabeled homogenous edges feature-based completely labeled stream data without missing values and with tree with named nodes output choice(primitive,void) field component semi-labeled target record of reals field component completely labeled data with missing values real alternative component directed information network with unlabeled homogenous nodes and unlabeled homogenous edges unlabeled data stream with missing values directed information network with labeled heterogenous nodes and labeled homogenous edges directed information network with heterogenous nodes and homogenous edges descriptive set of integer with missing values field component node datatype record of primitives alternative component undirected information network with labeled homogenous nodes and labeled homogenous edges record of choice(real,void) directed edge specification directed information network with unlabeled homogenous nodes and labeled homogenous edges choice(discrete,void) datatype descriptive record of reals with missing values field component semi-labeled target record of boolean field component unlabeled data semi-labeled target primitive field component sequence of choice(real,void) record of reals alternative component undirected information network with unlabeled homogenous nodes and unlabeled homogenous edges graph datatype choice(discrete,void) base type choice(real,void) field component undirected information network descriptive data with missing values field component feature-based completely labeled data with missing values and with DAG with named nodes output feature-based semi-labeled data with missing values and with DAG with named nodes output base type undirected information network with unlabeled homogenous nodes and unlabeled heterogenous edges choice(DAG with named nodes,void) datatype completelly labeled data without missing values base type semi-labeled target DAG field component unlabeled data without missing values sequence of real alternative component feature-based semi-labeled data with missing values and with tree with named nodes output undirected information network with homogenous nodes choice(boolean,void) datatype semi-labeled target data field component completely labeled stream data undirected graph datatype record of choice(primitive,void) undirected information network with labeled homogenous nodes and labeled heterogenous edges directed information network record of boolean alternative component record of discrete alternative component node specification feature-based semi-labeled data with missing values and with DAG with named nodes output undirected information network with unlabeled heterogenous nodes and unlabeled homogenous edges DAG alternative component feature-based completely labeled data without missing values and with DAG with named nodes output base type unlabeled data stream feature-based completely labeled data with missing values and with tree with named nodes output base type choice(record of discrete,void) datatype feature-based completely labeled data without missing values and with tree with named nodes output base type semi-labeled target structured field component unlabeled data stream without missing values completely labeled data without missing values completely labeled stream data without missing values semi-labeled stream data with missing values tree alternative component descriptive structured data with missing values field component undirected information network with unlabeled homogenous nodes and labeled homogenous edges boolean alternative component choice(tree with named nodes,void) datatype completely labeled target tree with named nodes field component choice(tree,void) datatype semi-labeled target boolean field component record of choice(discrete,void) directed graph datatype DAG with named nodes alternative component feature-based completely labeled data without missing values and with tree with named nodes output choice field component directed information network with labeled homogenous nodes and unlabeled heterogenous edges edge datatype directed information network with unlabeled homogenous nodes and labeled heterogenous edges feature-based semi-labeled stream data with missing values and with DAG output feature-based completely labeled stream data with missing values and with DAG output feature-based semi-labeled stream data without missing values and with structured output feature-based semi-labeled stream data with missing values and with record of primitives output partially labeled data without missing values and with structured output feature-based semi-labeled data without missing values and with primitive output structure-based partially labeled data without missing values and with structured output feature-based completely labeled data without missing values and with tree output feature-based completely labeled data without missing values and with single boolean output partialy labeled data without missing values feature-based completely labeled stream data with missing values and with single discrete output feature-based completely labeled data with missing values and with single real output completely labeled data without missing values and with primitive output feature-based semi-labeled stream data without missing values and with DAG output structure-based completely labeled data with missing values and with structured output feature-based completely labeled data without missing values and with single real output feature-based completely labeled stream data without missing values and with single real output feature-based semi-labeled data with missing values and with sequence of reals output feature-based completely labeled data without missing values and with set of discrete output feature-based partialy labeled data with missing values and with record of reals output partialy labeled data stream feature-based semi-labeled stream data with missing values and with single real output feature-based completely labeled stream data with missing values and with record of reals output discrete unlabeled data stream without missing values feature-based completely labeled data without missing values and with record of primitives output descriptive set of discrete without missing values field component transactional unlabeled data stream without missing values feature-based completely labeled stream data with missing values and with primitive output descriptive set of discrete with missing values field component feature-based semi-labeled data with missing values and with tree output feature-based completely labeled data without missing values and with sequence of reals output feature-based completely labeled stream data with missing values and with set of discrete output choice(set of discrete,void) datatype feature-based partialy labeled data with missing values and with structured output real unlabeled data with missing values feature-based completely labeled data with missing values and with primitive output real unlabeled data stream with missing values feature-based completely labeled data without missing values and with single discrete output feature-based semi-labeled data without missing values and with record of primitives output discrete unlabeled data without missing values structure based semi-labeled stream data without missing values and with primitive output feature-based semi-labeled stream data with missing values and with set of discrete output feature-based completely labeled stream data without missing values and with primitive output feature-based completely labeled data without missing values and with DAG output feature-based partialy labeled data stream without missing values and with sequence of reals output feature-based partialy labeled data with missing values and with set of discrete output feature-based completely labeled data with missing values and with single boolean output partialy labeled data stream without missing values and with structured output feature-based semi-labeled data with missing values and with single discrete output structure-based partialy labeled data stream with missing values and with structured output feature-based completely labeled stream data without missing values and with single discrete output feature-based semi-labeled stream data without missing values and with record of booleans output feature-based completely labeled data with missing values and with single discrete output feature-based completely labeled data without missing values and with record of booleans output partialy labeled data stream with missing values feature-based completely labeled data with missing values and with tree output feature-based partialy labeled data with missing values and with DAG output feature-based partially labeled data without missing values and with tree output set of choice(discrete,void) datatype structure based completely labeled stream data without missing values and with primitive output completely labeled data without missing values and with structured output feature-based partialy labeled data stream with missing values and with structured output feature-based semi-labeled data with missing values and with record of primitives output structure based completely labeled data without missing values and with primitive output feature-based completely labeled data with missing values and with hieararchial output transactional unlabeled data with missing values feature-based semi-labeled data with missing values and with set of discrete output feature-based completely labeled data with missing values and with sequence of reals output semi-labeled stream data without missing values and with primitive output feature-based completely labeled stream data without missing values and with sequence of reals output feature-based completely labeled data with missing values and with record of discrete output feature-based semi-labeled stream data without missing values and with record of reals output feature-based partialy labeled data stream without missing values and with record of reals output structure-based partialy labeled data with missing values and with structured output feature-based partialy labeled data stream without missing values and with record of discrete output partially labeled data feature-based semi-labeled data with missing values and with DAG output feature-based completely labeled data without missing values and with structured output feature-based completely labeled data with missing values and with DAG output feature-based completely labeled stream data with missing values and with single boolean output feature-based partialy labeled data stream with missing values and with record of booleans output semi-labeled stream data without missing values and with structured output feature-based partialy labeled data stream with missing values and with hieararchial output feature-based completely labeled stream data with missing values and with record of discrete output feature-based partialy labeled data stream without missing values and with record of booleans output partialy labeled data with missing values feature-based semi-labeled data with missing values and with structured output feature-based completely labeled stream data with missing values and with record of primitives output feature-based semi-labeled stream data without missing values and with hieararchial output completely labeled data with missing values and with primitive output feature-based semi-labeled data without missing values and with single real output structure-based partialy labeled data stream without missing values and with structured output feature-based completely labeled stream data without missing values and with record of reals output feature-based completely labeled stream data with missing values and with single real output feature-based completely labeled stream data with missing values and with record of booleans output feature-based completely labeled stream data without missing values and with DAG output structure based semi-labeled stream data with missing values and with primitive output feature-based partialy labeled data with missing values and with record of discrete output feature-based partially labeled data without missing values and with set of discrete output feature-based completely labeled stream data without missing values and with single boolean output semi-labeled data with missing values and with structured output semi-labeled data without missing values and with primitive output feature-based partially labeled data without missing values and with hieararchial output feature-based semi-labeled stream data with missing values and with record of reals output feature-based semi-labeled stream data with missing values and with primitive output feature-based semi-labeled data without missing values and with record of reals output feature-based semi-labeled stream data without missing values and with single discrete output feature-based semi-labeled data without missing values and with sequence of reals output structure-based semi-labeled stream data without missing values and with structured output feature-based semi-labeled stream data without missing values and with single boolean output feature-based completely labeled data with missing values and with set of discrete output feature-based completely labeled stream data without missing values and with set of discrete output feature-based semi-labeled stream data with missing values and with tree output semi-labeled target set of discrete field component completely labeled stream data without missing values and with structured output 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base type feature-based semi-labeled data with missing values and with single real output base type feature-based semi-labeled data with missing values and with record of reals output base type feature-based completely labeled data without missing values and with primitive output base type structure based semi-labeled data without missing values and with primitive output base type feature-based completely labeled data with missing values and with sequence of reals output base type feature-based completely labeled data without missing values and with single real output base type feature-based semi-labeled data with missing values and with single boolean output base type feature-based completely labeled data with missing values and with record of discrete output base type feature-based completely labeled data with missing values and with record of reals output base type semi-labeled data without missing values and with structured output base type completely labeled data with missing values and with primitive output base type semi-labeled data without missing values base type OntoDM_714659s OntoDM_714659 generalization language specification owl:Thing OntoDT_991825 example to be eventually removed example to be eventually removed failed exploratory term The term was used in an attempt to structure part of the ontology but in retrospect failed to do a good job Person:Alan Ruttenberg failed exploratory term IAO_0000120 metadata complete Class has all its metadata, but is either not guaranteed to be in its final location in the asserted IS_A hierarchy or refers to another class that is not complete. metadata complete organizational term Term created to ease viewing/sort terms for development purpose, and will not be included in a release organizational term IAO_0000122 ready for release Class has undergone final review, is ready for use, and will be included in the next release. Any class lacking "ready_for_release" should be considered likely to change place in hierarchy, have its definition refined, or be obsoleted in the next release. Those classes deemed "ready_for_release" will also derived from a chain of ancestor classes that are also "ready_for_release." ready for release metadata incomplete Class is being worked on; however, the metadata (including definition) are not complete or sufficiently clear to the branch editors. metadata incomplete IAO_0000125 pending final vetting All definitions, placement in the asserted IS_A hierarchy and required minimal metadata are complete. The class is awaiting a final review by someone other than the term editor. pending final vetting Core is an instance of a grouping of terms from an ontology or ontologies. It is used by the ontology to identify main classes. PERSON: Alan Ruttenberg PERSON: Melanie Courtot obsolete_core true placeholder removed placeholder removed terms merged An editor note should explain what were the merged terms and the reason for the merge. terms merged term imported This is to be used when the original term has been replaced by a term imported from an other ontology. An editor note should indicate what is the URI of the new term to use. term imported term split This is to be used when a term has been split in two or more new terms. An editor note should indicate the reason for the split and indicate the URIs of the new terms created. term split This is to be used if none of the existing instances cover the reason for obsolescence. An editor note should indicate this new reason. We expect to be able to mine these new reasons and add instances as required. obsolete_other true universal Hard to give a definition for. Intuitively a "natural kind" rather than a collection of any old things, which a class is able to be, formally. At the meta level, universals are defined as positives, are disjoint with their siblings, have single asserted parents. Alan Ruttenberg A Formal Theory of Substances, Qualities, and Universals, http://ontology.buffalo.edu/bfo/SQU.pdf universal defined class A defined class is a class that is defined by a set of logically necessary and sufficient conditions but is not a universal "definitions", in some readings, always are given by necessary and sufficient conditions. So one must be careful (and this is difficult sometimes) to distinguish between defined classes and universal. Alan Ruttenberg defined class named class expression A named class expression is a logical expression that is given a name. The name can be used in place of the expression. named class expressions are used in order to have more concise logical definition but their extensions may not be interesting classes on their own. In languages such as OWL, with no provisions for macros, these show up as actuall classes. Tools may with to not show them as such, and to replace uses of the macros with their expansions Alan Ruttenberg named class expression to be replaced with external ontology term Terms with this status should eventually replaced with a term from another ontology. Alan Ruttenberg group:OBI to be replaced with external ontology term requires discussion A term that is metadata complete, has been reviewed, and problems have been identified that require discussion before release. Such a term requires editor note(s) to identify the outstanding issues. Alan Ruttenberg group:OBI requires discussion The term was added to the ontology on the assumption it was in scope, but it turned out later that it was not. This obsolesence reason should be used conservatively. Typical valid examples are: un-necessary grouping classes in disease ontologies, a phenotype term added on the assumption it was a disease. https://github.com/information-artifact-ontology/ontology-metadata/issues/77 https://orcid.org/0000-0001-5208-3432 out of scope OntoDM_171335 C OntoDM_206736 JAVA OntoDM_206736 OntoDM_397256 boolean datatype OntoDM_458780 C++ OntoDM_592921 HMC-ENS-Bagging algorithm OntoDM_800750 output specification OntoDM_804811 integer datatype OntoDM_947353 descriptive specification 2.0 constraints_set pre_processing_algorithm_specification numeric_datatype data_object In the case of learning probabilistic models, we need to find a mapping of the form m::Td-->(Tc-->R0+). In the more general formulation of the problem, the training examples can have probability distributions over the c values insdead having the c values by itself. probabilistic_predictive_modeling_task prototype_calculation_process search_function_specification distance_function_specification distance_calculation_process evaluation_method_parameter refinement_relation_generation primitive_feature_specification Probabilistic predictive model P for types Td and Tc is a function that takes an object of type Td and return a probabiliy distribution over type Tc, i.e. has the signature p::Tc-->(Td-->R0+) probabilistic_predictive_model refinement_operator_specification feature_generation_process data_values basic_data_mining_component_role post_processing_task generalization_role base_learners_specification post_processing_algorithm_specification have to specify the output here! kernel_calculation_process information_content_entity_agregate pre_processing_algorithm_implementation target_feature_set_specification kernel_representation post_processing_algorithm_implementation example_representation data_item_representation refinement_operator_representation assignment_process fold_specification feature_generation_role structured_feature_specification Describes set of parameters parameters_set_specification datatype_representation dataset_role parameter_role bag_specification function_representation data_role scenario_representation projection_objective assesement specification pre_processing_task stuctured_datatype_construction An interpreter takes as input the data part of a pattern and an example and returns the result of applying the function part of the pattern to the example. interpretation_process descriptive_feature_set_specification dataset_projection_process data_use_specification query_representation prototype_function_representation kernel_function_specification distance_representation unlabeled_example unlabeled_data_item dataset_projection OntoDM_251805 matematical function Pance Panov 06.05.2010 External classes to OntoDM: IAO complete ontology importing both BFO and RO plus OBI classes extracted via OntoFox service inported from external_OBI.owl file http://purl.obofoundry.org/obo/obi.owl specified_input_role http://purl.obofoundry.org/obo/obi.owl specified_output_role has part my body has part my brain (continuant parthood, two material entities) my stomach has part my stomach cavity (continuant parthood, material entity has part immaterial entity) this year has part this day (occurrent parthood) a core relation that holds between a whole and its part Everything has itself as a part. Any part of any part of a thing is itself part of that thing. Two distinct things cannot have each other as a part. Occurrents are not subject to change and so parthood between occurrents holds for all the times that the part exists. Many continuants are subject to change, so parthood between continuants will only hold at certain times, but this is difficult to specify in OWL. See http://purl.obolibrary.org/obo/ro/docs/temporal-semantics/ Parthood requires the part and the whole to have compatible classes: only an occurrent have an occurrent as part; only a process can have a process as part; only a continuant can have a continuant as part; only an independent continuant can have an independent continuant as part; only a specifically dependent continuant can have a specifically dependent continuant as part; only a generically dependent continuant can have a generically dependent continuant as part. (This list is not exhaustive.) A continuant cannot have an occurrent as part: use 'participates in'. An occurrent cannot have a continuant as part: use 'has participant'. An immaterial entity cannot have a material entity as part: use 'location of'. An independent continuant cannot have a specifically dependent continuant as part: use 'bearer of'. A specifically dependent continuant cannot have an independent continuant as part: use 'inheres in'. has_part has part has measurement unit label IAO_0000124s IAO_0000124 uncurated Nothing done yet beyond assigning a unique class ID and proposing a preferred term. uncurated IAO_0000136 IAO_0000136s IAO_0000136ed http://purl.obofoundry.org/obo/iao.owl This document is about information artifacts and their representations A (currently) primitive relation that relates an information artifact to an entity. 7/6/2009 Alan Ruttenberg. Following discussion with Jonathan Rees, and introduction of "mentions" relation. Weaken the is_about relationship to be primitive. We will try to build it back up by elaborating the various subproperties that are more precisely defined. Some currently missing phenomena that should be considered "about" are predications - "The only person who knows the answer is sitting beside me" , Allegory, Satire, and other literary forms that can be topical without explicitly mentioning the topic. person:Alan Ruttenberg Smith, Ceusters, Ruttenberg, 2000 years of philosophy is about is-about is_about IAO_0000219 IAO_0000219s IAO_0000219ed A person's name denotes the person. A variable name in a computer program denotes some piece of memory. Lexically equivalent strings can denote different things, for instance "Alan" can denote different people. In each case of use, there is a case of the denotation relation obtaining, between "Alan" and the person that is being named. A primitive, instance-level, relation obtaining between an information content entity and some portion of reality. Denotation is what happens when someone creates an information content entity E in order to specifically refer to something. The only relation between E and the thing is that E can be used to 'pick out' the thing. This relation connects those two together. Freedictionary.com sense 3: To signify directly; refer to specifically 2009-11-10 Alan Ruttenberg. Old definition said the following to emphasize the generic nature of this relation. We no longer have 'specifically denotes', which would have been primitive, so make this relation primitive. g denotes r =def r is a portion of reality there is some c that is a concretization of g every c that is a concretization of g specifically denotes r person:Alan Ruttenberg Conversations with Barry Smith, Werner Ceusters, Bjoern Peters, Michel Dumontier, Melanie Courtot, James Malone, Bill Hogan denotes denotes m is a quality measurement of q at t. When q is a quality, there is a measurement process p that has specified output m, a measurement datum, that is about q 8/6/2009 Alan Ruttenberg: The strategy is to be rather specific with this relationship. There are other kinds of measurements that are not of qualities, such as those that measure time. We will add these as separate properties for the moment and see about generalizing later From the second IAO workshop [Alan Ruttenberg 8/6/2009: not completely current, though bringing in comparison is probably important] This one is the one we are struggling with at the moment. The issue is what a measurement measures. On the one hand saying that it measures the quality would include it "measuring" the bearer = referring to the bearer in the measurement. However this makes comparisons of two different things not possible. On the other hand not having it inhere in the bearer, on the face of it, breaks the audit trail. Werner suggests a solution based on "Magnitudes" a proposal for which we are awaiting details. -- From the second IAO workshop, various comments, [commented on by Alan Ruttenberg 8/6/2009] unit of measure is a quality, e.g. the length of a ruler. [We decided to hedge on what units of measure are, instead talking about measurement unit labels, which are the information content entities that are about whatever measurement units are. For IAO we need that information entity in any case. See the term measurement unit label] [Some struggling with the various subflavors of is_about. We subsequently removed the relation represents, and describes until and only when we have a better theory] a represents b means either a denotes b or a describes describe: a describes b means a is about b and a allows an inference of at least one quality of b We have had a long discussion about denotes versus describes. From the second IAO workshop: An attempt at tieing the quality to the measurement datum more carefully. a is a magnitude means a is a determinate quality particular inhering in some bearer b existing at a time t that can be represented/denoted by an information content entity e that has parts denoting a unit of measure, a number, and b. The unit of measure is an instance of the determinable quality. From the second meeting on IAO: An attempt at defining assay using Barry's "reliability" wording assay: process and has_input some material entity and has_output some information content entity and which is such that instances of this process type reliably generate outputs that describes the input. This one is the one we are struggling with at the moment. The issue is what a measurement measures. On the one hand saying that it measures the quality would include it "measuring" the bearer = referring to the bearer in the measurement. However this makes comparisons of two different things not possible. On the other hand not having it inhere in the bearer, on the face of it, breaks the audit trail. Werner suggests a solution based on "Magnitudes" a proposal for which we are awaiting details. Alan Ruttenberg is quality measurement of IAO_0000418 IAO_0000418s IAO_0000418ed A relation between a data item and a quality of a material entity where the material entity is the specified output of a material transformation which achieves an objective specification that indicates the intended value of the specified quality. Person:Alan Ruttenberg Person:Bjoern Peters is quality specification of OBI_0000293 OBI_0000293s OBI_0000293ed has_specified_input has_specified_input see is_input_of example_of_usage The inverse property of is_specified_input_of 8/17/09: specified inputs of one process are not necessarily specified inputs of a larger process that it is part of. This is in contrast to how 'has participant' works. PERSON: Alan Ruttenberg PERSON: Bjoern Peters PERSON: Larry Hunter PERSON: Melanie Coutot has_specified_input has_specified_input OBI_0000294 OBI_0000294s OBI_0000294ed http://purl.obofoundry.org/obo/obi.owl Is a relationship between a generically dependent continuant and a specifically dependent continuant. A generically dependent continuant may inhere in more than one entity. It does so by virtue of the fact that there is, for each entity that it inheres, a specifically dependent *concretization* of the generically dependent continuant that is specifically dependent. For instance, consider a story, which is an information artifact that inheres in some number of books. Each book bears some quality that carries the story. The relation between this quality and the generically dependent continuant is that the former is the concretization of the latter. is_concretization_of is_concretization_of OBI_0000298 OBI_0000298s OBI_0000298ed has_quality OBI_0000299 OBI_0000299s OBI_0000299ed has_specified_output has_specified_output The inverse property of is_specified_output_of PERSON: Alan Ruttenberg PERSON: Bjoern Peters PERSON: Larry Hunter PERSON: Melanie Courtot has_specified_output has_specified_output OBI_0000300 OBI_0000300s OBI_0000300ed http://purl.obofoundry.org/obo/obi.owl Relation between a realizable and a process. Reciprocal relation of realizes [GOC:cjm] is_realized_by OBI_0000304 OBI_0000304s OBI_0000304ed is_manufactured_by OBI_0000308 OBI_0000308s OBI_0000308ed http://purl.obofoundry.org/obo/obi.owl Relation between a process and a function, where the unfolding of the process requires the execution of the function. Class level: P realizes F iff: given any p that instantiates P, there exists some f, t such that f instantiates F at t and p *realizes* f. Here, *realizes* is the primitive instance level relation [GOC:cjm] realizes realizes OBI_0000312 OBI_0000312s OBI_0000312ed is_specified_output_of is_specified_output_of A relation between a planned process and a continuant participating in that process. The presence of the continuant at the end of the process is explicitly specified in the objective specification which the process realizes the concretization of. Alan Ruttenberg PERSON:Bjoern Peters is_specified_output_of is_specified_output_of OBI_0000417 OBI_0000417s OBI_0000417ed http://purl.obofoundry.org/obo/obi.owl achieves_planned_objective has participant this blood coagulation has participant this blood clot this investigation has participant this investigator this process has participant this input material (or this output material) a relation between a process and a continuant, in which the continuant is somehow involved in the process Has_participant is a primitive instance-level relation between a process, a continuant, and a time at which the continuant participates in some way in the process. The relation obtains, for example, when this particular process of oxygen exchange across this particular alveolar membrane has_participant this particular sample of hemoglobin at this particular time. has_participant http://www.obofoundry.org/ro/#OBO_REL:has_participant has participant en Adam Goldstein Alan Ruttenberg Albert Goldfain Barry Smith Bjoern Peters Carlo Torniai Chris Mungall Chris Stoeckert Christian A. Boelling Clint Dowland Darren Natale David Osumi-Sutherland Gwen Frishkoff Holger Stenzhorn James A. Overton James Malone Jennifer Fostel Jie Zheng Jonathan Rees Larisa Soldatova Lawrence Hunter Mathias Brochhausen Matt Brush Melanie Courtot Michel Dumontier Paolo Ciccarese Pat Hayes Philippe Rocca-Serra Randy Dipert Ron Rudnicki Satya Sahoo Sivaram Arabandi Werner Ceusters William Duncan William Hogan Yongqun (Oliver) He The Information Artifact Ontology (IAO) is an ontology of information entities, originally driven by work by the OBI digital entity and realizable information entity branch. Information Artifact Ontology (IAO) An information artifact is, loosely, a dependent continuant or its bearer that is created as the result of one or more intentional processes. Examples: uniprot, the english language, the contents of this document or a printout of it, the temperature measurements from a weather balloon. For more information, see the project home page at https://github.com/information-artifact-ontology/IAO IDs allocated to related efforts: PNO: IAO_0020000-IAO_0020999, D_ACTS: IAO_0021000-IAO_0021999 IDs allocated to subdomains of IAO. pno.owl: IAO_0020000-IAO_0020999, d-acts.owl: IAO_0021000-IAO_0021999 2022-11-07 role_of role_ofs role_ofed http://purl.org/obo/owl/OBO_REL role_of has_agent has_agents has_agented has_part has_parts has_parted has_part preceded_by preceded_bies preceded_bied Larisa Soldatova Pance Panov Saso Dzeroski Pance Panov 20.06.2018 This ontology contains entities such as: datatype, datatype generator, datatype qualiy and others giving the possibility to represent arbitrary complex datatypes. The OntoDT ontology is based on and ISO/IEC 11404 (http://www.iso.org/iso/catalogue_detail.htm?csnumber=39479) standard and can be reused used independently by any domain ontology that requires representation and reasoning about general purpose datatypes. Ontology of General Purpose Datatypes 2.0 true English Pance Panov Ana Kostovska Larisa Soldatova Pance Panov Saso Dzeroski Pance Panov OWL-DL OntoDM-core English Data Mining and Knowledge Discovery Ontology of Core Data Mining Entities OntoDM-core http://kt.ijs.si/panovp/OntoDM/OntoDM.owl 0.2 2.0 Data Mining Datatypes OntoDM_clus_00001 OntoDM_clus_00002 OntoDM_clus_00003 OntoDM_clus_00004 OntoDM_clus_00005 OntoDM_clus_00006 OntoDM_clus_00007 OntoDM_clus_00008 OntoDM_clus_00009 OntoDM_clus_00010 OntoDM_clus_00011 OntoDM_clus_00012 OntoDM_clus_00013 OntoDM_clus_00014 OntoDM_clus_00015 OntoDM_clus_00016 OntoDM_clus_00017 OntoDM_clus_00018 OntoDM_clus_00019 OntoDM_clus_00020 OntoDM_clus_00021 OntoDM_clus_00022 OntoDM_clus_00023 OntoDM_clus_00024 OntoDM_clus_00025 OntoDM_clus_00026 OntoDM_clus_00027 OntoDM_clus_00028 OntoDM_clus_00029 OntoDM_clus_00030 OntoDM_clus_00031 OntoDM_clus_00032 OntoDM_clus_00033 OntoDM_clus_00034 OntoDM_clus_00035 OntoDM_clus_00036 OntoDM_clus_00037 OntoDM_clus_00038 OntoDM_clus_00039 OntoDM_clus_00040 OntoDM_clus_00041 OntoDM_clus_00042 OntoDM_clus_00043 OntoDM_clus_00044 OntoDM_clus_00046 OntoDM_clus_00047 OntoDM_clus_00048 OntoDM_clus_00049 OntoDM_clus_00050 OntoDM_clus_00051 OntoDM_clus_00052 OntoDM_clus_00053 OntoDM_clus_00054 OntoDM_clus_00055 OntoDM_clus_00056 OntoDM_clus_00057 OntoDM_clus_00058 OntoDM_clus_00059 OntoDM_clus_00060 OntoDM_clus_00061 OntoDM_clus_00062 OntoDM_clus_00063 OntoDM_clus_00064 OntoDM_clus_00065 OntoDM_clus_00068 OntoDM_clus_00070 OntoDM_clus_00071 OntoDM_clus_00072 OntoDM_clus_00073 OntoDM_clus_00074 OntoDM_clus_00075 OntoDM_clus_00076 OntoDM_clus_00077 OntoDM_clus_00079 OntoDM_clus_00079s OntoDM_clus_00079ed OntoDM_clus_00080 OntoDM_clus_00082 OntoDM_clus_00083 OntoDM_clus_00084 OntoDM_clus_00085 OntoDM_clus_00086 OntoDM_clus_00087 OntoDM_clus_00088 OntoDM_clus_00089 OntoDM_clus_00090 OntoDM_clus_00091 OntoDM_clus_00092 OntoDM_clus_00093 OntoDM_clus_00094 OntoDM_clus_00095 OntoDM_clus_00096 OntoDM_clus_00097 OntoDM_clus_00098 OntoDM_clus_00099 OntoDM_clus_00100 OntoDM_clus_00101 OntoDM_clus_00102 OntoDM_clus_00103 OntoDM_clus_00104 OntoDM_clus_00105 OntoDM_clus_00106 OntoDM_clus_00107 OntoDM_clus_00108 OntoDM_clus_00109 OntoDM_clus_00110 OntoDM_clus_00111 OntoDM_clus_00112 OntoDM_clus_00113 OntoDM_clus_00114 OntoDM_clus_00115 OntoDM_clus_00116 OntoDM_clus_00117 OntoDM_clus_00118 OntoDM_clus_00119 OntoDM_clus_00120 OntoDM_clus_00121 OntoDM_clus_00122 OntoDM_clus_00123 OntoDM_clus_00129 OntoDM_clus_00130 OntoDM_clus_00131 OntoDM_clus_00132 OntoDM_clus_00133 OntoDM_clus_00134 OntoDM_clus_00135 OntoDM_clus_00136 OntoDM_clus_00137 OntoDM_clus_00138 OntoDM_clus_00139 OntoDM_clus_00140 OntoDM_clus_00141 OntoDM_clus_00142 OntoDM_clus_00143 OntoDM_clus_00144 OntoDM_clus_00145 OntoDM_clus_00146 OntoDM_clus_00147 OntoDM_clus_00148 OntoDM_clus_00149 OntoDM_clus_00150 OntoDM_clus_00151 OntoDM_clus_00152 OntoDM_clus_00153 OntoDM_clus_00154 OntoDM_clus_00155 OntoDM_clus_00156 OntoDM_clus_00157 OntoDM_clus_00158 OntoDM_clus_00159 OntoDM_clus_00160 OntoDM_clus_00161 OntoDM_clus_00162 OntoDM_clus_00163 OntoDM_clus_00164 OntoDM_clus_00165 OntoDM_clus_00166 OntoDM_clus_00167 OntoDM_clus_00168 OntoDM_clus_00169 OntoDM_clus_00170 OntoDM_clus_00171 OntoDM_clus_00172 OntoDM_clus_00173 OntoDM_clus_00174 OntoDM_clus_00175 OntoDM_clus_00176 OntoDM_clus_00177 OntoDM_clus_00178 OntoDM_clus_00179 OntoDM_clus_00180 OntoDM_clus_00181 OntoDM_clus_00182 OntoDM_clus_00183 OntoDM_clus_00184 OntoDM_clus_00185 OntoDM_clus_00186 OntoDM_clus_00187 OntoDM_clus_00188 OntoDM_clus_00189 OntoDM_clus_00190 OntoDM_clus_00191 OntoDM_clus_00192 OntoDM_clus_00193 OntoDM_clus_00194 OntoDM_clus_00195 OntoDM_clus_00196 OntoDM_clus_00197 OntoDM_clus_00198 OntoDM_clus_00200 OntoDM_clus_00201 OntoDM_clus_00202 OntoDM_clus_00203 OntoDM_clus_00204 OntoDM_clus_00205 OntoDM_clus_00206 OntoDM_clus_00207 OntoDM_clus_00208 OntoDM_clus_00209 OntoDM_clus_00210 OntoDM_clus_00211 OntoDM_clus_00212 OntoDM_clus_00213 OntoDM_clus_00214 OntoDM_clus_00215 OntoDM_clus_00216 OntoDM_clus_00217 OntoDM_clus_00218 OntoDM_clus_00219 OntoDM_clus_00220 OntoDM_clus_00221 OntoDM_clus_00222 OntoDM_clus_00223 OntoDM_clus_00224 OntoDM_clus_00225 OntoDM_clus_00226 OntoDM_clus_00227 OntoDM_clus_00228 OntoDM_clus_00229 OntoDM_clus_00230 OntoDM_clus_00231 OntoDM_clus_00232 OntoDM_clus_00233 OntoDM_clus_00234 OntoDM_clus_00235 OntoDM_clus_00236 OntoDM_clus_00237 OntoDM_clus_00238 OntoDM_clus_00240 OntoDT_991825