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Geospatial and Temporal Semantic Analytics
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Author(s): Matthew Perry (University of Georgia, USA), Amit Sheth (University of Georgia, USA), Ismailcem Budak Arpinar (University of Georgia, USA)and Farshad Hakimpour (University of Georgia, USA)
Copyright: 2009
Pages: 10
Source title:
Handbook of Research on Geoinformatics
Source Author(s)/Editor(s): Hassan A. Karimi (University of Pittsburgh, USA)
DOI: 10.4018/978-1-59140-995-3.ch021
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Abstract
The amount of digital data available to researchers and knowledge workers has grown tremendously in recent years. This is especially true in the geography domain. As the amount of data grows, problems of data relevance and information overload become more severe. The use of semantics has been proposed to combat these problems (Berners-Lee et al., 2001; Egenhofer, 2002). Semantics refer to the meaning of data rather than its syntax or structure. Systems which can understand and process data at a semantic level can achieve a higher level of automation, integration, and interoperability. Applications generally use semantic technology for three basic purposes: (1) semantic integration, (2) semantic search and contextual browsing, and (3) semantic analytics and knowledge discovery (Sheth & Ramakrishnan, 2003).
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