Scalable OWL 2 Reasoning for Linked Data

  • Aidan Hogan
  • Jeff Z. Pan
  • Axel Polleres
  • Yuan Ren
Chapter
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6848)

Abstract

The goal of the Scalable OWL 2 Reasoning for Linked Data lecture is twofold: first, to introduce scalable reasoning and querying techniques to Semantic Web researchers as powerful tools to make use of Linked Data and large-scale ontologies, and second, to present interesting research problems for the Semantic Web that arise in dealing with TBox and ABox reasoning in OWL 2. The lecture consists of three parts. The first part will begin with an introduction and motivation for reasoning over Linked Data, including a survey of the use of RDFS and OWL on the Web. The second part will present a scalable, distributed reasoning service for instance data, applying a custom subset of OWL 2 RL/RDF rules (based on a tractable fragment of OWL 2). The third part will present recent work on faithful approximate reasoning for OWL 2 DL. The lecture will include our implementation of the mentioned techniques as well as their evaluations. These notes provide complimentary reference material for the lecture, and follow the three-part structure and content of the lecture.

Keywords

Link Data Description Logic Partial Evaluation Rule Application Negation Normal Form 
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 2011

Authors and Affiliations

  • Aidan Hogan
    • 1
  • Jeff Z. Pan
    • 2
  • Axel Polleres
    • 1
    • 3
  • Yuan Ren
    • 2
  1. 1.Digital Enterprise Research InstituteNational University of IrelandGalwayIreland
  2. 2.Department of Computing ScienceUniversity of AberdeenUK
  3. 3.Siemens AG ÖsterreichViennaAustria

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