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

Sheng Gao, Harold Boley, Darka Mioc, François Anton, Xialoun Yi

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review


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.
Original languageEnglish
Title of host publicationThird International RuleML Symposium on Rule Interchange and Applications (RuleML-2009)
Publication date2009
ISBN (Print)978-3-642-04984-2
Publication statusPublished - 2009
SeriesLecture Notes in Computer Science


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