A RuleML Study on Integrating Geographical and Health Information

Authors:
Sheng Gao;Darka Mioc;Harold Boley;Francois Anton;Xiaolun Yi
Affiliations:
Department of Geodesy and Geomatics Engineering, University of New Brunswick, Fredericton, Canada;Department of Geodesy and Geomatics Engineering, University of New Brunswick, Fredericton, Canada;Institute for Information Technology, NRC, Fredericton, Canada;Department of Informatics and Mathematical Modelling, Technical University of Denmark,;Service New Brunswick, Fredericton, Canada
Venue:
RuleML '08 Proceedings of the International Symposium on Rule Representation, Interchange and Reasoning on the Web
Year:
2008

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Abstract

To facilitate health surveillance, flexible ways to represent, integrate, and deduce health information become increasingly important. In this paper, an ontology is used to support the semantic definition of spatial, temporal and thematic factors of health information. The ontology is realized as an interchangeable RuleML knowledge base, consisting of facts and rules. Rules are also used for integrating geographical and health information. The implemented eHealthGeo system uses the OO jDREW reasoning engine to deduce implicit information such as spatial relationships. The system combines this with spatial operations and supports health information roll-up and visualization. The eHealthGeo study demonstrates a RuleML approach to supporting semantic health information integration and management.