AHO aims to support data interoperability in animal health - it focuses on modeling the structure of the animal population and the health data recorded about animals, such as clincial observations, laboratory tests, animal movement registries, etc.
Several terminology catalogues already exist in health and epidemiology. Ontologies can incorporate these existing resources and re-use all their knowledge. But we move beyond the listing of concepts and include also “relationships” between concepts (semantics), creating a knowledge model for health surveillance. A machine-interpretable version of the domain knowledge offers several advantages, in particular:
- Use of automated reasoners to make inferences and detect errors in the data.
- Flexibility to accommodate to knowledge growth and updates.
- Reuse. Ontologies are meant to model specific pieces of knowledge, in a way that allows linking to complementary pieces. As epidemiology is highly multi-disciplinary, the use of ontologies allows us to piece together expertise from many different domains.
- Interoperability. Terminologies allow humans to understand each other and agree on what things mean. Ontologies allow software to talk to each other.
Project management and structure
This project is managed by the Swedish National Veterinary Institute. This project started as the Animal Health Surveillance Ontology, funded by the Swedish Innovation Agency - Vinnova. It has evolved into an ontological framework composed of AHO, as well as a surveillance focused ontology which also incorporates other health domains (visit HSO).
Current core members:
- Fernanda Dórea, project leader: National Veterinary Institute, Sweden
- Crawford Revie: University of Prince Edward Island, Canada
- Ann Lindberg: National Veterinary Institute, Sweden
- Eva Blomqvist: Linköping University, Sweden
- Patrick Lambrix: Linköping University, Sweden
- Karl Hammar: Jönköping University, Sweden
Help and advice from https://genepio.org/
Note that AHO is under early stages of development.