Geospatial-Enabled RuleML in a Study on Querying Respiratory Disease Information

Authors:
Sheng Gao;Harold Boley;Darka Mioc;Francois Anton;Xiaolun Yi
Affiliations:
GGE, University of New Brunswick, Fredericton, Canada;NRC, Institute for Information Technology, Fredericton, Canada;GGE, University of New Brunswick, Fredericton, Canada and National Space Institute, Technical University of Denmark, Denmark;Department of Informatics and Mathematical Modelling, Technical University of Denmark,;Service New Brunswick, Fredericton, Canada
Venue:
RuleML '09 Proceedings of the 2009 International Symposium on Rule Interchange and Applications
Year:
2009

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Abstract

A spatial component for health data can support spatial analysis and visualization in the investigation of health phenomena. Therefore, the utilization of spatial information in a Semantic Web environment will enhance the ability to query and to represent health data. In this paper, a semantic health data query and representation framework is proposed through the formalization of spatial information. We include the geometric representation in RuleML deduction, and apply ontologies and rules for querying and representing health information. Corresponding geospatial built-ins were implemented as an extension to OO jDREW. Case studies were carried out using geospatial-enabled RuleML queries for respiratory disease information. The paper thus demonstrates the use of RuleML for geospatial-semantic querying and representing of health information.