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Efficient SPARQL to SQL Translation with User Defined Mapping

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Knowledge Engineering and Semantic Web (KESW 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 649))

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Abstract

The RDF framework is becoming popular for presenting data. It makes the data easily accessible and queryable. However, the most common way how to store structured data is to use a relational database system. It is essential to create a mapping between these two worlds, to publish the data stored in a relational database in the RDF format. That can be effectively achieved by a virtual SPARQL endpoint over relational data.

There are already existing tools providing virtual SPARQL endpoints, but as we will show in the paper there is still space for improvement. In this paper we propose an algorithm to query RDF data stored in a relational database with an user defined mapping. Our aim is to generate SQL queries which can be effectively executed on the relational engines. In comparison to existing approaches we do not rely only on the optimizations of the relational query, but the SPARQL query first.

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Notes

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    For a complete description see [7].

  2. 2.

    See http://www.sukl.eu/.

  3. 3.

    Available at http://virtuoso.openlinksw.com/.

  4. 4.

    Ontop failed to respond. Virtuoso returned a result but it was not complete.

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Acknowledgments

This work was supported in part by the Charles University in Prague, project GA UK No. #158215 and in part by the Czech Science Foundation (GACR), grant number 16-09713.

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Authors and Affiliations

  1. Faculty of Mathematics and Physics, Charles University in Prague, Malostranské nám. 25, 118 00, Prague, Czech Republic

    Miloš Chaloupka & Martin Nečaský

Authors
  1. Miloš Chaloupka
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  2. Martin Nečaský
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Correspondence to Miloš Chaloupka .

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Editors and Affiliations

  1. Leipzig University , Leipzig, Germany

    Axel-Cyrille Ngonga Ngomo

  2. Czech Technical University in Prague , Praha, Czech Republic

    Petr Křemen

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Chaloupka, M., Nečaský, M. (2016). Efficient SPARQL to SQL Translation with User Defined Mapping. In: Ngonga Ngomo, AC., Křemen, P. (eds) Knowledge Engineering and Semantic Web. KESW 2016. Communications in Computer and Information Science, vol 649. Springer, Cham. https://doi.org/10.1007/978-3-319-45880-9_17

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  • DOI: https://doi.org/10.1007/978-3-319-45880-9_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45879-3

  • Online ISBN: 978-3-319-45880-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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