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Conference object . 2018
License: CC BY
Data sources: ZENODO
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Conference object . 2018
License: CC BY
Data sources: Datacite
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Exploring GDPR Compliance Over ProvenanceGraphs Using SHACL

Authors: Pandit, Harshvardhan J.;

Exploring GDPR Compliance Over ProvenanceGraphs Using SHACL

Abstract

Semantic web technologies provide an open and adaptable framework for compliance regarding the General Data Protection Regulation (GDPR). Our previous work in this regard demonstrates the use of SPARQL for querying provenance of consent and personal data lifecycles for compliance. We extend this work through our model for evaluation of GDPR compliance using SHACL to validate the correctness and completeness of information. The model describes the creation of a compliance graph consisting of information required to document and demonstrate compliance linked to specific articles and obligations within the GDPR using the GDPRtEXT vocabulary.

Related Organizations

1. Agarwal, S., Steyskal, S., Antunovic, F., Kirrane, S.: Legislative Compliance Assessment: Framework, Model and GDPR Instantiation. Annual Privacy Forum (APF 2018) (in-press) (2018)

2. Kirrane, S., Ferna┬┤ndez, J.D., Dullaert, W., Milosevic, U., Polleres, A., Bonatti, P., Wenning, R., Drozd, O., Raschke, P.: A Scalable Consent, Transparency and Compliance Architecture. In: Proceedings of the Posters and Demos Track of the Extended Semantic Web Conference (ESWC 2018) (in-press) (2018) [OpenAIRE]

3. Pandit, H.J., Fatema, K., O'Sullivan, D., Lewis, D.: GDPRtEXT - GDPR as a Linked Data Resource. In: The Semantic Web. Lecture Notes in Computer Science, Springer, Cham (Jun 2018). https://doi.org/10.1007/978-3-319-93417-4 31

4. 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), http://ceur-ws.org/Vol-1951/#paper-06

5. Pandit, H.J., O'Sullivan, D., Lewis, D.: Queryable Provenance Metadata For GDPR Compliance. In: SEMANTiCS 2018 - 14th International Conference on Semantic Systems (in-press). Vienna, Austria (2018), https://s3-eu-west-1.amazonaws.com/harshp-media/research/publications/ 2018_conference_queryable_provenance_metadata_for_GDPR_compliance.pdf

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  • citations
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    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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visibility
download
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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0
Average
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35
15
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SFI| ADAPT: Centre for Digital Content Platform Research
Project
  • Funder: Science Foundation Ireland (SFI)
  • Project Code: 13/RC/2106
  • Funding stream: SFI Research Centres ; SFI Research Centres Programme | Phase 1
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