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 journalArticle

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.

LanguageEnglish
Pages39-48
Number of pages10
JournalPreventive Veterinary Medicine
Volume166
Early online date9 Mar 2019
DOIs
Publication statusPublished - 1 May 2019

Fingerprint

animal health
monitoring
Health
Information Management
information management
Information Storage and Retrieval
Semantics
Information Systems
public health
Language
Public Health

Keywords

  • classification
  • standards
  • syndromic surveillance
  • terminology
  • vocabulary

Cite this

Dórea, Fernanda C. ; Vial, Flavie ; Hammar, Karl ; Lindberg, Ann ; Lambrix, Patrick ; Blomqvist, Eva ; Revie, Crawford W. / Drivers for the development of an Animal Health Surveillance Ontology (AHSO). In: Preventive Veterinary Medicine. 2019 ; Vol. 166. pp. 39-48.
@article{4bae3a1ecdb7425d8078aef6313690f5,
title = "Drivers for the development of an Animal Health Surveillance Ontology (AHSO)",
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.",
keywords = "classification, standards, syndromic surveillance, terminology, vocabulary",
author = "D{\'o}rea, {Fernanda C.} and Flavie Vial and Karl Hammar and Ann Lindberg and Patrick Lambrix and Eva Blomqvist and Revie, {Crawford W.}",
year = "2019",
month = "5",
day = "1",
doi = "10.1016/j.prevetmed.2019.03.002",
language = "English",
volume = "166",
pages = "39--48",
journal = "Preventive Veterinary Medicine",
issn = "0167-5877",

}

Drivers for the development of an Animal Health Surveillance Ontology (AHSO). / Dórea, Fernanda C.; Vial, Flavie; Hammar, Karl; Lindberg, Ann; Lambrix, Patrick; Blomqvist, Eva; Revie, Crawford W.

In: Preventive Veterinary Medicine, Vol. 166, 01.05.2019, p. 39-48.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Drivers for the development of an Animal Health Surveillance Ontology (AHSO)

AU - Dórea, Fernanda C.

AU - Vial, Flavie

AU - Hammar, Karl

AU - Lindberg, Ann

AU - Lambrix, Patrick

AU - Blomqvist, Eva

AU - Revie, Crawford W.

PY - 2019/5/1

Y1 - 2019/5/1

N2 - 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.

AB - 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.

KW - classification

KW - standards

KW - syndromic surveillance

KW - terminology

KW - vocabulary

UR - http://www.scopus.com/inward/record.url?scp=85062891881&partnerID=8YFLogxK

UR - https://www.sciencedirect.com/journal/preventive-veterinary-medicine

U2 - 10.1016/j.prevetmed.2019.03.002

DO - 10.1016/j.prevetmed.2019.03.002

M3 - Article

VL - 166

SP - 39

EP - 48

JO - Preventive Veterinary Medicine

T2 - Preventive Veterinary Medicine

JF - Preventive Veterinary Medicine

SN - 0167-5877

ER -