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A Source-to-Target Constraint Rewriting for Direct Mapping

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The Semantic Web – ISWC 2021 (ISWC 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12922))

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Abstract

Most of the existing structured digital information today is still stored in relational databases. That’s why it is important for the Semantic Web effort to expose the information in relational databases as RDF, or allow to query it using SPARQL. Direct mapping is a fully automated approach for converting well-structured relational data to RDF that does not require formulating explicit mapping rules [2, 8]. Along with the mapped RDF data, it is desirable to have a description of that data. Previous work [3, 8] has attempted to describe the RDF graph in terms of OWL axioms, which is problematic, partly due to the open world semantics of OWL. We start from the direct mapping suggested by Sequeda et al. [8], which integrates and extends the functionalities of proposal [10] and the W3C recommendation [2], and present a source-to-target semantics preserving rewriting of constraints in an SQL database schema to equivalent SHACL [7] constraints on the RDF graph. We thus provide a SHACL description of the RDF data generated by the direct mapping without the need to perform a costly validation of those constraints on the generated data. Following the approach of [8], we define the rewriting from SQL constraints to SHACL by a set of Datalog rules. We prove that our source-to-target rewriting of constraints is constraint preserving and weakly semantics preserving.

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Notes

  1. 1.

    https://www.w3.org/TR/shacl/#implicit-targetClass.

  2. 2.

    This identification of binary relations is the main technical difference between the direct mapping of Sequeda et al. [8] and the W3C recommendation [2].

  3. 3.

    For \(n=1\) the same requirement could be expressed using dash:uniqueValueForClass from http://datashapes.org/constraints.html, but not for larger n.

  4. 4.

    See https://www.w3.org/TR/shacl/#sparql-constraints-prebound.

  5. 5.

    e.g., using SPARQL-based Target Types in https://www.w3.org/TR/shacl-af/.

References

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Acknowledgements

This work was supported by the Norwegian Research Council via the SIRIUS Centre for Research Based Innovation, Grant Nr. 237898. We thank Evgeny Kharlamov and Egor Kostylev for many fruitful discussions, Holger Knublauch for help with SHACL-SPARQL, and Roman Kontchakov for invaluable assistance in preparing the final version.

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Authors and Affiliations

  1. Department of Informatics, University of Oslo, Oslo, Norway

    Ratan Bahadur Thapa & Martin Giese

Authors
  1. Ratan Bahadur Thapa
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  2. Martin Giese
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Corresponding author

Correspondence to Martin Giese .

Editor information

Editors and Affiliations

  1. University of Würzburg, Würzburg, Germany

    Andreas Hotho

  2. Linköping University, Linköping, Sweden

    Eva Blomqvist

  3. University of Düsseldorf, Düsseldorf, Germany

    Stefan Dietze

  4. IBM Research - Thomas J. Watson Research, Hawthorne, CA, USA

    Achille Fokoue

  5. University of Texas, Austin, TX, USA

    Ying Ding

  6. Imperial College, London, UK

    Payam Barnaghi

  7. Australian National University, Canberra, ACT, Australia

    Armin Haller

  8. Fondazione Bruno Kessler, Povo, Trento, Italy

    Mauro Dragoni

  9. The Open University Walton Hall, Milton Keynes, UK

    Harith Alani

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Thapa, R.B., Giese, M. (2021). A Source-to-Target Constraint Rewriting for Direct Mapping. In: Hotho, A., et al. The Semantic Web – ISWC 2021. ISWC 2021. Lecture Notes in Computer Science(), vol 12922. Springer, Cham. https://doi.org/10.1007/978-3-030-88361-4_2

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  • DOI: https://doi.org/10.1007/978-3-030-88361-4_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-88360-7

  • Online ISBN: 978-3-030-88361-4

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