Querying Distributed RDF Data Sources with SPARQL

  • Bastian Quilitz
  • Ulf Leser
Conference paper

DOI: 10.1007/978-3-540-68234-9_39

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5021)
Cite this paper as:
Quilitz B., Leser U. (2008) Querying Distributed RDF Data Sources with SPARQL. In: Bechhofer S., Hauswirth M., Hoffmann J., Koubarakis M. (eds) The Semantic Web: Research and Applications. ESWC 2008. Lecture Notes in Computer Science, vol 5021. Springer, Berlin, Heidelberg

Abstract

Integrated access to multiple distributed and autonomous RDF data sources is a key challenge for many semantic web applications. As a reaction to this challenge, SPARQL, the W3C Recommendation for an RDF query language, supports querying of multiple RDF graphs. However, the current standard does not provide transparent query federation, which makes query formulation hard and lengthy. Furthermore, current implementations of SPARQL load all RDF graphs mentioned in a query to the local machine. This usually incurs a large overhead in network traffic, and sometimes is simply impossible for technical or legal reasons. To overcome these problems we present DARQ, an engine for federated SPARQL queries. DARQ provides transparent query access to multiple SPARQL services, i.e., it gives the user the impression to query one single RDF graph despite the real data being distributed on the web. A service description language enables the query engine to decompose a query into sub-queries, each of which can be answered by an individual service. DARQ also uses query rewriting and cost-based query optimization to speed-up query execution. Experiments show that these optimizations significantly improve query performance even when only a very limited amount of statistical information is available. DARQ is available under GPL License at http://darq.sf.net/.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Bastian Quilitz
    • 1
  • Ulf Leser
    • 1
  1. 1.Humboldt-Universität zu Berlin 

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