Publication: Research - peer-review › Article in proceedings – Annual report year: 2012
With the growing amount of health information and frequent outbreaks of diseases, the retrieval of health information is given more concern. Machine understanding of spatial information can improve the interpretation of health data semantics. Most of the current research focused on the non-spatial semantics of health data, using ontologies and rules. Utilizing the spatial component of health data can assist in the understanding of health phenomena. This research proposes a semantic health information query architecture that allows the incorporation of both non-spatial semantics and geospatial semantics in health information integration and retrieval.
|Title of host publication||International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences : XXII ISPRS Congress|
|Number of pages||6|
|Conference||The XXII Congress of the International Society for Photogrammetry and Remote Sensing|
|Period||25/08/12 → 01/09/12|
- Public health, Ontologies, Respiratory diseases, RuleML, Geospatical data, Semantic interoperability
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