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modelling provenance for gdpr compliance using linked open data vocabularies

descriptionPublicationkeyboard_double_arrow_right Other literature type , Conference object 01 Jan 2017Publisher:ZenodoPublicly fundedFunded by:SFI | ADAPT: Centre for Digital...

Authors: Pandit, Harshvardhan J.; Lewis, Dave;

doi: 10.5281/zenodo.3246474 , 10.5281/zenodo.3246475

modelling provenance for gdpr compliance using linked open data vocabularies

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Abstract

The upcoming General Data Protection Regulation (GDPR)requires justification of data activities to acquire, use, share, and store data using consent obtained from the user. Failure to comply may result in significant heavy fines which incentivises creation and maintenance of records for all activities involving consent and data. Compliance documentation therefore requires provenance information outlining consent and data life cycles to demonstrate correct usage of data in accordance with the related consent provided and updated by the user. In this paper,we present GDPRov, a linked data ontology for expressing provenance of consent and data lifecycles with a view towards documenting compliance.GDPRov is an OWL ontology that extends PROV-O and P-Plan to model the provenance, and uses SPARQL to express compliance related queries.

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Trinity College Dublin
Ireland

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Augmenting PROV with Plans in P-PLAN: Scientific Processes as Linked Data
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