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OTM Confederated International Conferences "On the Move to Meaningful Internet Systems"

OTM 2016: On the Move to Meaningful Internet Systems: OTM 2016 Conferences pp 654–672Cite as

Validating Interlinks Between Linked Data Datasets with the SUMMR Methodology

Part of the Lecture Notes in Computer Science book series (LNPSE,volume 10033)

Abstract

Linked Data datasets use interlinks to connect semantically similar resources across datasets. As datasets evolve, a resources locator can change which can cause interlinks that contain old resource locators, to no longer dereference and become invalid. Validating interlinks, through validating the resource locators within them, when a dataset has changed is important to ensure interlinks work as intended. In this paper we introduce the SPARQL Usage for Mapping Maintenance and Reuse (SUMMR) methodology. SUMMR is an approach for Mapping Maintenance and Reuse (MMR) that provides query templates which are based on standard SPARQL queries for MMR activities. This paper describes SUMMR and two experiments: a lab-based evaluation of SUMMR’s mapping maintenance query templates and a deployment of SUMMR in the DBpedia v.2015-10 release to detect invalid interlinks. The lab-based evaluation involved detecting interlinks that have become invalid, due to changes in resource locators and the repair of the invalid interlinks. The results show that the SUMMR templates and approach can be used to effectively detect and repair invalid interlinks. SUMMR’s query template for discovering invalid interlinks was applied to the DBpedia v.2015-10 release, which discovered 53,418 invalid interlinks in that release.

Keywords

  • Linked data
  • Interlinks
  • Mapping maintenance
  • Quality
  • DBpedia

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Notes

  1. 1.

    http://www.scss.tcd.ie/~meehanal/Experiment3/.

  2. 2.

    http://dbpedia.org/sparql.

  3. 3.

    https://github.com/dbpedia/dbpedia-links.

  4. 4.

    http://wiki.dbpedia.org/Downloads2015-04.

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Acknowledgements

This research is supported by Science Foundation Ireland through the CNGL Program (Grant 12/CE/I2267) in the ADAPT Centre (www.adaptcentre.ie) at Trinity College Dublin and funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 644055 (ALIGNED, http://www.aligned-project.eu).

Author information

Authors and Affiliations

  1. Knowledge and Data Engineering Group, School of Computer Science and Statistics, ADAPT Centre, Trinity College Dublin, Dublin, Ireland

    Alan Meehan, Rob Brennan & Declan O’Sullivan

  2. AKSW, University of Leipzig, Computer Science, Leipzig, Germany

    Dimitris Kontokostas & Markus Freudenberg

Authors
  1. Alan Meehan
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  2. Dimitris Kontokostas
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  3. Markus Freudenberg
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  4. Rob Brennan
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  5. Declan O’Sullivan
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Corresponding author

Correspondence to Alan Meehan .

Editor information

Editors and Affiliations

  1. ADAPT Centre, Trinity College Dublin, Dublin 2, Ireland

    Christophe Debruyne

  2. University of Lorraine, Vandoeuvre-les-Nancy, France

    Hervé Panetto

  3. TU Graz, Graz, Austria

    Robert Meersman

  4. La Trobe University, Melbourne, Australia

    Tharam Dillon

  5. Institute of Computer Languages, TU Wien, Vienna, Austria

    eva Kühn

  6. ADAPT Centre, Trinity College Dublin, Dublin 2, Ireland

    Declan O'Sullivan

  7. Università degli Studi di Milano Crema, Crema, Italy

    Claudio Agostino Ardagna

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Meehan, A., Kontokostas, D., Freudenberg, M., Brennan, R., O’Sullivan, D. (2016). Validating Interlinks Between Linked Data Datasets with the SUMMR Methodology. In: , et al. On the Move to Meaningful Internet Systems: OTM 2016 Conferences. OTM 2016. Lecture Notes in Computer Science(), vol 10033. Springer, Cham. https://doi.org/10.1007/978-3-319-48472-3_39

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  • DOI: https://doi.org/10.1007/978-3-319-48472-3_39

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