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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.
| selected citations These citations are derived from selected sources. 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). | 0 | |
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| 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. | Average |
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