| dc.contributor.author | Lewis, David | en |
| dc.contributor.author | PANDIT, HARSHVARDHAN JITENDRA | en |
| dc.date.accessioned | 2018-03-08T12:21:45Z | |
| dc.date.available | 2018-03-08T12:21:45Z | |
| dc.date.created | 22 Oct 2017 | en |
| dc.date.issued | 2017 | en |
| dc.date.submitted | 2017 | en |
| dc.identifier.citation | Harshvardhan J Pandit, Dave Lewis, Modelling Provenance for GDPR Compliance using Linked Open Data Vocabularies, 5th Society, Privacy and the Semantic Web - Policy and Technology workshop (PrivOn 2017).co-located with ISWC 2017, Vienna, Austria, 22 Oct 2017, 2017 | en |
| dc.identifier.other | Y | en |
| dc.identifier.uri | http://hdl.handle.net/2262/82660 | |
| dc.description | PUBLISHED | en |
| dc.description | Vienna, Austria | en |
| dc.description.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 | en |
| dc.description.sponsorship | 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. | en |
| dc.language.iso | en | en |
| dc.rights | Y | en |
| dc.subject | GDPR, Data Protection, Linked Open Data, Data Provenance | en |
| dc.title | Modelling Provenance for GDPR Compliance using Linked Open Data Vocabularies | en |
| dc.title.alternative | 5th Society, Privacy and the Semantic Web - Policy and Technology workshop (PrivOn 2017).co-located with ISWC 2017 | en |
| dc.type | Conference Paper | en |
| dc.type.supercollection | scholarly_publications | en |
| dc.type.supercollection | refereed_publications | en |
| dc.identifier.peoplefinderurl | http://people.tcd.ie/delewis | en |
| dc.identifier.peoplefinderurl | http://people.tcd.ie/pandith | en |
| dc.identifier.rssinternalid | 184782 | en |
| dc.rights.ecaccessrights | openAccess | |
| dc.subject.TCDTheme | Digital Engagement | en |
| dc.identifier.rssuri | http://ceur-ws.org/Vol-1951/PrivOn2017_paper_6.pdf | en |
| dc.identifier.orcid_id | 0000-0002-3503-4644 | en |
| dc.status.accessible | N | en |
| dc.contributor.sponsor | Science Foundation Ireland (SFI) | en |
| dc.contributor.sponsorGrantNumber | 13/RC/2106 | en |
