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GConsent - A Consent Ontology Based on the GDPR

Part of the Lecture Notes in Computer Science book series (LNISA,volume 11503)


Consent is an important legal basis for the processing of personal data under the General Data Protection Regulation (GDPR), which is the current European data protection law. GPDR provides constraints and obligations on the validity of consent, and provides data subjects with the right to withdraw their consent at any time. Determining and demonstrating compliance to these obligations require information on how the consent was obtained, used, and changed over time. Existing work demonstrates feasibility of semantic web technologies in modelling information and determining compliance for GDPR. Although these address consent, they currently do not model all the information associated with it. In this paper, we address this by first presenting our analysis of information associated with consent under the GDPR. We then present GConsent, an OWL2-DL ontology for representation of consent and its associated information such as provenance. The paper presents the methodology used in the creation and validation of the ontology as well as an example use-case demonstrating its applicability. The ontology and this paper can be accessed online at


  • Consent
  • GDPR
  • Regulatory compliance
  • OWL2-DL ontology

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  • DOI: 10.1007/978-3-030-21348-0_18
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Fig. 1.
Fig. 2.
Fig. 3.


  1. 1.

    This is a form of legal notation to denote Recitals (Rec) or Articles (Art) in legal text. These are hyperlinked to where they occur in GDPR using GDPRtEXT [14].

  2. 2.

    The recent decision by CNIL (Décision n\(^{\circ }\)MED-2018-042 du 30 octobre 2018) regarding validity of consent was particularly influential.

  3. 3.

    Although the legal basis for obtaining this data under the GDPR could be interpreted as legitimate interest or benefit of data subject, it highlights the recording of information associated with such consent. The example also highlights the potential applicability of GConsent to scenarios other than GDPR such medical consent where additional laws and guidelines apply regarding consent.

  4. 4.

    The nurse is the agent that assumes and collects the given consent of the patient, making it an implicit consent given by delegation.

  5. 5.

    Punning allows reuse of types. See

  6. 6.

    Example: privacy policies which mention consent for data categories such as “Account Information” rather than specific instances.


  1. Bartolini, C., Muthuri, R.: Reconciling data protection rights and obligations: an ontology of the forthcoming EU regulation. In: Workshop on Language and Semantic Technology for Legal Domain, p. 8 (2015)

    Google Scholar 

  2. Berrueta, D., Phipps, J., Miles, A., Baker, T., Swick, R.: Best practice recipes for publishing RDF vocabularies. Working draft, W3C (2008)

    Google Scholar 

  3. Cox, S., Little, C.: Time ontology in OWL. World Wide Web Consortium (2017).

  4. Falco, R., Gangemi, A., Peroni, S., Shotton, D., Vitali, F.: Modelling OWL ontologies with Graffoo. In: Presutti, V., Blomqvist, E., Troncy, R., Sack, H., Papadakis, I., Tordai, A. (eds.) ESWC 2014. LNCS, vol. 8798, pp. 320–325. Springer, Cham (2014).

    CrossRef  Google Scholar 

  5. Fatema, K., Hadziselimovic, E., Pandit, H.J., Debruyne, C., Lewis, D., O’Sullivan, D.: Compliance through informed consent: Semantic based consent permission and data management model. In: Proceedings of the 5th Workshop on Society, Privacy and the Semantic Web - Policy and Technology (PrivOn2017) (PrivOn) (2017).

  6. Garijo, D.: WIDOCO: a wizard for documenting ontologies. In: d’Amato, C., et al. (eds.) ISWC 2017. LNCS, vol. 10588, pp. 94–102. Springer, Cham (2017).

    CrossRef  Google Scholar 

  7. Gurk, S.M., Abela, C., Debattista, J.: Towards ontology quality assessment. In: Joint Proceedings of the MEPDaW, p. 12 (2017)

    Google Scholar 

  8. Kirrane, S., et al.: A scalable consent, transparency and compliance architecture. In: Gangemi, A., et al. (eds.) ESWC 2018. LNCS, vol. 11155, pp. 131–136. Springer, Cham (2018).

    CrossRef  Google Scholar 

  9. Lebo, T., et al.: PROV-O: the PROV ontology (2013)

    Google Scholar 

  10. Lizar, M., Turner, D.: Consent receipt specification (2017).

  11. Mittal, S., Sharma, P.P.: The role of consent in legitimising the processing of personal data under the current EU data protection framework. Asian J. Comput. Sci. Inf. Technol. 7, 76–78 (2017).

    Google Scholar 

  12. Noy, N.F., McGuinness, D.L., et al.: Ontology development 101: a guide to creating your first ontology. Stanford Knowledge Systems Laboratory Technical report KSL-01-05 and \(\ldots \) (2001)

    Google Scholar 

  13. Palmirani, M., Martoni, M., Rossi, A., Bartolini, C., Robaldo, L.: PrOnto: privacy ontology for legal reasoning. In: Kő, A., Francesconi, E. (eds.) EGOVIS 2018. LNCS, vol. 11032, pp. 139–152. Springer, Cham (2018).

    CrossRef  Google Scholar 

  14. Pandit, H.J., Fatema, K., O’Sullivan, D., Lewis, D.: GDPRtEXT - GDPR as a linked data resource. In: Gangemi, A., et al. (eds.) ESWC 2018. LNCS, vol. 10843, pp. 481–495. Springer, Cham (2018).

    CrossRef  Google Scholar 

  15. Pandit, H.J., Lewis, D.: Modelling provenance for GDPR compliance using linked open data vocabularies. In: Proceedings of the 5th Workshop on Society, Privacy and the Semantic Web - Policy and Technology (PrivOn2017) (PrivOn) (2017).

  16. Pandit, H.J., O’Sullivan, D., Lewis, D.: Queryable provenance metadata for GDPR compliance. Procedia Comput. Sci. 137, 262–268 (2018). Proceedings of the 14th International Conference on Semantic Systems 10th - 13th of September 2018 Vienna, Austria

  17. Party, A.W.: Guidelines on consent under regulation 2016/679 (wp259rev.01) (2018).

  18. Poveda-Villalón, M., Suárez-Figueroa, M.C., Gómez-Pérez, A.: Validating ontologies with OOPS! In: ten Teije, A., et al. (eds.) EKAW 2012. LNCS (LNAI), vol. 7603, pp. 267–281. Springer, Heidelberg (2012).

  19. Regulation (EU) 2016/679 of the European parliament and of the council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing directive 95/46/EC (general data protection regulation) (2016).

  20. Tikkinen-Piri, C., Rohunen, A., Markkula, J.: EU general data protection regulation: changes and implications for personal data collecting companies. Comput. Law Secur. Rev. 34(1), 134–153 (2018).

    CrossRef  Google Scholar 

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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.

The authors wish to thank the members of Data Protection Vocabularies and Controls Community Group (DPVCG) for their inputs in the discussion of consent and its related research. The authors also wish to thank Pat McBennett for their help in this work.

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Pandit, H.J., Debruyne, C., O’Sullivan, D., Lewis, D. (2019). GConsent - A Consent Ontology Based on the GDPR. In: , et al. The Semantic Web. ESWC 2019. Lecture Notes in Computer Science(), vol 11503. Springer, Cham.

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