Linking open spatiotemporal data in the data clouds

  • Authors:

  • He Hu;Xiaoyong Du

  • Affiliations:

  • School of Information, Renmin University of China, Beijing, China and Key Laboratory of Data Engineering and Knowledge Engineering, MOE, Beijing, China;School of Information, Renmin University of China, Beijing, China and Key Laboratory of Data Engineering and Knowledge Engineering, MOE, Beijing, China

  • Venue:
  • RSKT'10 Proceedings of the 5th international conference on Rough set and knowledge technology
  • Year:
  • 2010

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Abstract

The Linked Data Clouds are the best expression and realization of the Semantic Web vision to date. The Data Clouds can significantly benefit both the AI and Semantic Web communities by enabling new classes of tasks and enhancing reasoning, data mining and knowledge discovery applications. There are various forms of spatiotemporal data in the Linked Data Clouds. To efficiently utilize these spatiotemporal data, schema heterogeneity problem must be resolved. A hierarchical spatiotemporal model is proposed to give a conceptual description of different spatiotemporal dataset of Linked Data Clouds. The model can support schema level mappings and convey relationships between concepts of different datasets at the schema level. The hierarchical spatiotemporal model contains three layers: an meta level for abstract level spacetime knowledge; an schema level for well-known models in spatial and temporal reasoning - Allen's Interval Algebra in temporal reasoning and the RCC model in spatial reasoning; and an instantiations level to provide systematic mapping and formal descriptions of the various ground spatiotemporal statements.