Drivers for the development of an Animal Health Surveillance Ontology (AHSO)

Fernanda C. Dórea, Flavie Vial, Karl Hammar, Ann Lindberg, Patrick Lambrix, Eva Blomqvist, Crawford W. Revie

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
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Comprehensive reviews of syndromic surveillance in animal health have highlighted the hindrances to integration and interoperability among systems when data emerge from different sources. Discussions with syndromic surveillance experts in the fields of animal and public health, as well as computer scientists from the field of information management, have led to the conclusion that a major component of any solution will involve the adoption of ontologies. Here we describe the advantages of such an approach, and the steps taken to set up the Animal Health Surveillance Ontological (AHSO) framework. The AHSO framework is modelled in OWL, the W3C standard Semantic Web language for representing rich and complex knowledge. We illustrate how the framework can incorporate knowledge directly from domain experts or from data-driven sources, as well as by integrating existing mature ontological components from related disciplines. The development and extent of AHSO will be community driven and the final products in the framework will be open-access.

Original languageEnglish
Pages (from-to)39-48
Number of pages10
JournalPreventive Veterinary Medicine
Early online date9 Mar 2019
Publication statusPublished - 1 May 2019


  • classification
  • standards
  • syndromic surveillance
  • terminology
  • vocabulary

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