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GeoCosm: A Semantics-Based Approach for Information Integration of Geospatial Data

  • Sudha Ram
  • Vijay Khatri
  • Limin Zhang
  • Daniel Dajun Zeng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2465)

Abstract

Information integration implies access to distributed information sources without interfering with the autonomy of the underlying data sources. Integration of distributed geospatial data requires a mechanism for selecting the data sources and performing data processing operations on the selected sources efficiently. We describe a semantics-based information integration approach that uses a spatio-temporal semantic model to define the geospatial information content of the sources, employs a conflict resolution ontology to resolve semantic heterogeneity, and uses geospatial metadata to help the users evaluate usefulness of the available data sources. We show how the captured metadata can be used for efficient query planning. Based on our proposed approach, we are developing GeoCosm, a web-based prototype that would help integrate autonomous distributed heterogeneous geospatial data.

Keywords

Information Integration Snow Water Equivalent Geospatial Data Plan Execution Query Plan 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Sudha Ram
    • 1
  • Vijay Khatri
    • 1
  • Limin Zhang
    • 1
  • Daniel Dajun Zeng
    • 1
  1. 1.Department of MISUniversity of ArizonaTucsonUSA

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