Animal Health Surveillance Ontological Framework (AHSO)
Animal health data are collected for different primary purposes by different institutions, e.g. clinical data are stored by veterinarians to have history on their patients; laboratory data are recorded mainly to allow proper billing. These data are then used for surveillance secondarily - we build automated systems that try to make sense of these data to detect patterns of diseases in real-time.
Project Goal: To develop a framework of interconnected ontological modules which can promote the secondary use of animal health data for surveillance (data-driven surveillance, or syndromic surveillance).
Visit the AHSO open book for detailed information about the project
Background information and resources about ontologies
Visit the AHSO open book. This is an open-book initiative, and everyone is welcome to add discussions or suggest materials that can enrich the repository for those of us trying to understand what ontologies are all about and how they can contribute to animal health surveillance.
Communication and Involvement
- Submit an issue on GitHub (Form)
- Contact us via the project’s community discussion forum (you don't need a Google account for that).
- Contact us writing to email@example.com.
Project management and structure
Current core AHSO members (2016-2017)
- Fernanda Dórea, project leader: National Veterinary Institute, Sweden
- Crawford Revie: University of Prince Edward Island, Canada
- Ann Lindberg: National Veterinary Institute, Sweden
- Flavie Vial: Epi-Connect, Sweden
- Eva Blomqvist: Linköping University, Sweden
- Patrick Lambrix: Linköping University, Sweden
- Karl Hammar: Jönköping University, Sweden
Note that AHSO is under early stages of development.