Flavie Vial, Karl Hammar, Patrick Lambrix, Noel Kennedy Fernanda Dórea (nanda@datadrivensurveillance.org), Crawford Revie, Ann Lindberg, Eva Blomqvist An ontology to support the use of animal health data for data-driven surveillance ontology. Mode details at http://datadrivensurveillance.org. Animal Health Surveillance Ontology (AHSO) This is an ontology for health surveillance, assuming that surveillance data is recorded at three main levels: SAMPLE data - data about specific collected samples; OBSERVATIONS, which can aggregate several samples; and OBSERVATIONAL CONTEXT, which is the context in which the observations were made (for instance clinical observation, surveillance sampling, etc). HEALTH EVENT is the occurrence in the real World to be modeled. This occurrence is an abstract concept, as it generally cannot be determined what are its boundaries in time, space, or population units. We assume that several OBSERVATIONS are derived from each health event, and recorded in the same or different databases - for instance clinical journal, laboratory database, abattoir. At the same time or not. AHSO attempts to model these time specific observations. The ontology is focused on the modeling of the animal and health information connected to a single observation, made at a specific point on time. All the information recorded is relative to that specific point in time. For instance, an animal belongs to a herd, which belongs to an owner, AT THE TIME OF THE OBSERVATION. We do not attempt to model how that animal changed herds on time. Similarly, we do not model clinical progression. It is up to those using the data to create definitions of when two observations should be connected to the same event. 0.1.0 containsRecordsOf hasAgeCategory hasBreed hasGeographicInformation hasMember hasProductionType hasRecordInRegistry hasSex hasSpecies hasSubjectBreed hasSubjectProductionType hasSubjectSpecies hasSubject hasSubjectAnimal hasSubjectHerd isBreedOfSpecies isMemberOf isObservedBy isOwnedBy isOwnerOf isRecordedBy hasSubjectAgeCategory contains observation observed in observation context is member of system has member activity contains sample is sample of is a member of context has context member hasAgeValue hasDOB hasID occursOnDateTime isRecordedOnDateTime hasAgeInformation days months weeks years hasAgeUnit AHSO_0000_000001 Observation AHSO_0000_000002 Zoographical Information AHSO_0000_000003 Registry AHSO_0000_000004 Population unit AHSO_0000_000005 Health and surveillance actors AHSO_0000_000007 Geographical Information AHSO_0000_000008 Animal owner AHSO_0000_000009 Veterinarian AHSO_0000_000010 Individual AHSO_0000_000011 Herd AHSO_0000_000013 Age Category AHSO_0000_000019 Breed AHSO_0000_000020 Production Type AHSO_0000_000021 Sex AHSO_0000_000022 Female AHSO_0000_000023 Male AHSO_0000_000024 Castrated male AHSO_0000_000025 Species AHSO_0000_000026 Mapped terminologies AHSO_0001_000001 Birth AHSO_0001_000002 Death AHSO_0001_000003 Fallen stock AHSO_0001_000004 Fallen stock destroyed on farm AHSO_0001_000005 Fallen stock not destroyed on farm AHSO_0001_000006 Declared movement AHSO_0001_000007 Slaughter AHSO_0001_000008 Home slaughter AHSO_0001_000009 Stillbirth event AHSO_0001_000010 Movement Registry AHSO_0001_000011 Registered Animal Movement AHSO_0002_000001 Observation context AHSO_0002_000002 Necropsy AHSO_0002_000005 Pathological examination AHSO_0002_000006 Ante Mortem Pathological Examination AHSO_0002_000007 Post Mortem Pathological Examination AHSO_0003_000002 Surveillance system AHSO_0003_000003 Surveillance activity AHSO_0003_000004 Sample 0.1.0 Flavie Vial, Karl Hammar, Patrick Lambrix, Noel Kennedy Fernanda Dórea (nanda@datadrivensurveillance.org), Crawford Revie, Ann Lindberg, Eva Blomqvist An ontology to support the use of animal health data for data-driven surveillance ontology. Mode details at http://datadrivensurveillance.org. Animal Health Surveillance Ontology (AHSO) This is an ontology for health surveillance, assuming that surveillance data is recorded at three main levels: SAMPLE data - data about specific collected samples; OBSERVATIONS, which can aggregate several samples; and OBSERVATIONAL CONTEXT, which is the context in which the observations were made (for instance clinical observation, surveillance sampling, etc). HEALTH EVENT is the occurrence in the real World to be modeled. This occurrence is an abstract concept, as it generally cannot be determined what are its boundaries in time, space, or population units. We assume that several OBSERVATIONS are derived from each health event, and recorded in the same or different databases - for instance clinical journal, laboratory database, abattoir. At the same time or not. AHSO attempts to model these time specific observations. The ontology is focused on the modeling of the animal and health information connected to a single observation, made at a specific point on time. All the information recorded is relative to that specific point in time. For instance, an animal belongs to a herd, which belongs to an owner, AT THE TIME OF THE OBSERVATION. We do not attempt to model how that animal changed herds on time. Similarly, we do not model clinical progression. It is up to those using the data to create definitions of when two observations should be connected to the same event. 0.1.0