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European Semantic Web Conference

ESWC 2018: The Semantic Web pp 481–495Cite as

GDPRtEXT - GDPR as a Linked Data Resource

Part of the Lecture Notes in Computer Science book series (LNISA,volume 10843)

Abstract

The General Data Protection Regulation (GDPR) is the new European data protection law whose compliance affects organisations in several aspects related to the use of consent and personal data. With emerging research and innovation in data management solutions claiming assistance with various provisions of the GDPR, the task of comparing the degree and scope of such solutions is a challenge without a way to consolidate them. With GDPR as a linked data resource, it is possible to link together information and approaches addressing specific articles and thereby compare them. Organisations can take advantage of this by linking queries and results directly to the relevant text, thereby making it possible to record and measure their solutions for compliance towards specific obligations. GDPR text extensions (GDPRtEXT) uses the European Legislation Identifier (ELI) ontology published by the European Publications Office for exposing the GDPR as linked data. The dataset is published using DCAT and includes an online webpage with HTML id attributes for each article and its subpoints. A SKOS vocabulary is provided that links concepts with the relevant text in GDPR. To demonstrate how related legislations can be linked to highlight changes between them for reusing existing approaches, we provide a mapping from Data Protection Directive (DPD), which was the previous data protection law, to GDPR showing the nature of changes between the two legislations. We also discuss in brief the existing corpora of research that can benefit from the adoption of this resource.

Keywords

  • GDPR
  • DPD
  • Linked resource
  • Regulatory technology
  • Legal compliance
  • SKOS
  • DCAT
  • e-governance

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Fig. 1.
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Fig. 3.

Notes

  1. 1.

    https://openscience.adaptcentre.ie/projects/GDPRtEXT/.

  2. 2.

    https://creativecommons.org/licenses/by/4.0/.

  3. 3.

    http://publications.europa.eu/mdr/eli/index.html.

  4. 4.

    http://eur-lex.europa.eu/eli/reg/2016/679/oj.

  5. 5.

    https://opengogs.adaptcentre.ie/harsh/GDPRtEXT/.

  6. 6.

    https://rdflib.readthedocs.io/en/stable/.

  7. 7.

    https://www.w3.org/TR/vocab-dcat/.

  8. 8.

    https://www.w3.org/TR/void/.

  9. 9.

    https://virtuoso.openlinksw.com/.

  10. 10.

    http://wifo5-03.informatik.uni-mannheim.de/pubby/.

  11. 11.

    https://www.w3.org/TR/skos-reference/.

  12. 12.

    https://protege.stanford.edu/.

  13. 13.

    https://www.dataprotection.ie/.

  14. 14.

    https://ico.org.uk/.

  15. 15.

    https://www.nymity.com/.

  16. 16.

    https://doi.org/10.5281/zenodo.591294.

  17. 17.

    http://www.essepuntato.it/lode.

  18. 18.

    http://vowl.visualdataweb.org/webvowl.html.

  19. 19.

    http://purl.org/adaptcentre/openscience/ontologies/GDPRtEXT/docs.

  20. 20.

    https://dgarijo.github.io/Widoco/doc/bestPractices/index-en.html.

  21. 21.

    https://www.w3.org/TR/EARL10-Schema/.

  22. 22.

    https://www.w3.org/TR/odrl-model/.

  23. 23.

    https://doi.org/10.5281/zenodo.1146351.

  24. 24.

    https://datahub.ckan.io/dataset/gdprtext.

  25. 25.

    https://data.gov.ie/dataset/suggest/a5f365f6-719f-4eab-9bfe-4d494aeb31ee.

  26. 26.

    http://data.europa.eu/euodp/.

  27. 27.

    https://opengogs.adaptcentre.ie/harsh/GDPRtEXT/issues.

  28. 28.

    https://www.w3.org/TR/annotation-model/.

  29. 29.

    https://www.european-privacy-seal.eu.

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Acknowledgement

This paper is supported by the ADAPT Centre for Digital Content Technology, which is funded under the SFI Research Centres Programme (Grant 13/RC/2106) and is co-funded under the European Regional Development Fund.

Author information

Authors and Affiliations

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

    Harshvardhan J. Pandit, Declan O’Sullivan & Dave Lewis

  2. University of Derby, Derby, United Kingdom

    Kaniz Fatema

Authors
  1. Harshvardhan J. Pandit
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  2. Kaniz Fatema
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  3. Declan O’Sullivan
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  4. Dave Lewis
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Correspondence to Harshvardhan J. Pandit .

Editor information

Editors and Affiliations

  1. University of Bologna, Bologna, Italy

    Dr. Aldo Gangemi

  2. Sapienza University of Rome, Rome, Italy

    Prof. Roberto Navigli

  3. Universidad Simón Bolívar, Caracas, Venezuela

    Maria-Esther Vidal

  4. Wright State University, Dayton, Ohio, USA

    Prof. Dr. Pascal Hitzler

  5. EURECOM, Biot, France

    Raphaël Troncy

  6. CWI, Amsterdam, The Netherlands

    Laura Hollink

  7. Elsevier B.V., Amsterdam, The Netherlands

    Anna Tordai

  8. CNR-ISTC, Rome, Italy

    Mehwish Alam

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Pandit, H.J., Fatema, K., O’Sullivan, D., Lewis, D. (2018). GDPRtEXT - GDPR as a Linked Data Resource. In: , et al. The Semantic Web. ESWC 2018. Lecture Notes in Computer Science(), vol 10843. Springer, Cham. https://doi.org/10.1007/978-3-319-93417-4_31

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  • DOI: https://doi.org/10.1007/978-3-319-93417-4_31

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