Supporting Complex Thematic, Spatial and Temporal Queries over Semantic Web Data

  • Matthew Perry
  • Amit P. Sheth
  • Farshad Hakimpour
  • Prateek Jain
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4853)


Spatial and temporal data are critical components in many applications. This is especially true in analytical domains such as national security and criminal investigation. Often, the analytical process requires uncovering and analyzing complex thematic relationships between disparate people, places and events. Fundamentally new query operators based on the graph structure of Semantic Web data models, such as semantic associations, are proving useful for this purpose. However, these analysis mechanisms are primarily intended for thematic relationships. In this paper, we describe a framework built around the RDF metadata model for analysis of thematic, spatial and temporal relationships between named entities. We discuss modeling issues and present a set of semantic query operators. We also describe an efficient implementation in Oracle DBMS and demonstrate the scalability of our approach with a performance study using a large synthetic dataset from the national security domain.


Resource Description Framework Graph Pattern Query Operator Resource Description Framework Data Resource Description Framework Graph 
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 2007

Authors and Affiliations

  • Matthew Perry
    • 1
  • Amit P. Sheth
    • 1
  • Farshad Hakimpour
    • 2
  • Prateek Jain
    • 1
  1. 1.Kno.e.sis Center, Department of Computer Science and Engineering, Wright State University, Dayton, OHUSA
  2. 2.LSDIS Lab, Department of Computer Science, University of Georgia, Athens, GAUSA

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