Supporting GDPR Compliance through effectively governing Data Lineage and Data Provenance

General Data Protection Regulation (GDPR) is a new set of EU guidelines governing how organisations handle personal data replacing the current Data Protection Act (DPA) and has been enforced since May 2018. With GDPR in place organizations need to process personal data lawfully, maintain this accurately for no longer than necessary, and in a secure way.

They should be able to report on the purposes of processing, the categories of personal data they control, and be able to demonstrate compliance with regards to GDPR policies. The challenge organizations face with regards to GDPR, being able to record every point where processing activities of personal data takes place and to showcase accountability with regards to this activity, has made data governance even more critical on the data lineage and data provenance aspects.

Governing data lineage enables the understanding of the organization’s data flow activities and to identify and document the legal justification for each type of activity. In addition GDPR requires evidence of records for the processing of personal data which implies the need to effectively record and govern data provenance.

In the current talk we are going to showcase how effectively governing data lineage and data provenance gives us the ability to verify that the processing of private data within an organization is compliant with GDPR regulatory requirements.

Paraskevi Zerva
Cognition & Knowledge Representation Lead, Elsevier

Paraskevi Zerva is an Information Architect at JP Morgan Chase & Co Corporate Technology in Glasgow and has over eight years of work and research experience in ontology modelling and formal languages for data and web/cloud-based services, Semantic Web technologies, and AI using rule-based reasoning and ontology inferencing.


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