Type

Conference Proceedings

Authors

Harshvardhan J Pandit
David Lewis

Subjects

Computer Science

Topics
linked data data information data protection intelligent content communications gdpr data modelling data provenance open data

Modelling Provenance for GDPR Compliance using Linked Open Data Vocabularies (2017)

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 lifecycles 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 OWL2 ontology that extends PROV-O and P-Plan to model the provenance, and uses SPARQL to express compliance related queries
Collections Ireland -> Trinity College Dublin -> School of Computer Science and Statistics
Ireland -> Trinity College Dublin -> RSS Feeds
Ireland -> Trinity College Dublin -> Computer Science
Ireland -> Trinity College Dublin -> RSS Feeds
Ireland -> Trinity College Dublin -> Computer Science (Scholarly Publications)

Full list of authors on original publication

Harshvardhan J Pandit, David Lewis

Experts in our system

1
Harshvardhan Pandit
Trinity College Dublin
Total Publications: 5
 
2
David Lewis
Trinity College Dublin
Total Publications: 86