1. Drivers for the development of an Animal Health Surveillance Ontology (AHSO).
- Author
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Dórea FC, Vial F, Hammar K, Lindberg A, Lambrix P, Blomqvist E, and Revie CW
- Subjects
- Animals, Population Surveillance methods, Biological Ontologies, Sentinel Surveillance veterinary
- Abstract
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., (Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.)
- Published
- 2019
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