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Ontology-Based Integration of Occupational Health Data: Method and Case Studies

Authors:
Cassandra Barbey
Malika Smaïl-Tabbone
Nathalie Bonvallot
Frédéric Clerc

Keywords: ontologies; integration data; heterogeneous data; occupational health.

Abstract:
The data related to occupational health exhibit diverse characteristics and are not inherently designed to interoperate; however, they contain complementary information. The integration of such data has the potential to enhance the current understanding of occupational health risks. Therefore, the objective of this study is to analyse heterogeneous data derived from 10 French occupational databases provided by 6 French institutes. An Ontology-Based Data Integration (OBDI) approach was employed, involving the mapping of data sources to a domain-specific ontology, namely the Occupational Exposure Ontology (OExO). In addition to OExO, four other ontologies were utilised: the Occupational Exposure Thesaurus (TEP) for occupational nuisances or hazards, the International Classification of Diseases (ICD-10) for medical conditions, the French Nomenclature of Activities (NAF) for industry sectors, and the Professions and Socio-professional Categories (PCS) for occupational classifications. The integration of these data is primarily achieved through the concept of the "occupational group", defined as a cohort of individuals of the same gender, engaged in the same occupation, and employed within the same industry sector. The study presents two case studies derived from the integrated knowledge base: a quantitative analysis identifying occupational groups with the highest exposure to nuisances and disease prevalence, and a qualitative analysis evaluating the consistency of information associated with each nuisance and disease.

Pages: 7 to 12

Copyright: Copyright (c) IARIA, 2024

Publication date: September 29, 2024

Published in: conference

ISSN: 2308-4464

ISBN: 978-1-68558-187-9

Location: Venice, Italy

Dates: from September 29, 2024 to October 3, 2024