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EvoPat – Pattern-Based Evolution and Refactoring of RDF Knowledge Bases

  • Christoph Rieß
  • Norman Heino
  • Sebastian Tramp
  • Sören Auer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6496)

Abstract

Facilitating the seamless evolution of RDF knowledge bases on the Semantic Web presents still a major challenge. In this work we devise EvoPat – a pattern-based approach for the evolution and refactoring of knowledge bases. The approach is based on the definition of basic evolution patterns, which are represented declaratively and can capture simple evolution and refactoring operations on both data and schema levels. For more advanced and domain-specific evolution and refactorings, several simple evolution patterns can be combined into a compound one. We performed a comprehensive survey of possible evolution patterns with a combinatorial analysis of all possible before/after combinations, resulting in an extensive catalog of usable evolution patterns. Our approach was implemented as an extension for the OntoWiki semantic collaboration platform and framework.

Keywords

Evolution Pattern Link Data SPARQL Query Ontology Evolution Triple Store 
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 2010

Authors and Affiliations

  • Christoph Rieß
    • 1
  • Norman Heino
    • 1
  • Sebastian Tramp
    • 1
  • Sören Auer
    • 1
  1. 1.AKSW, Institut für InformatikUniversität LeipzigLeipzigGermany

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