A Privacy-driven Enterprise Architecture Meta-Model for Supporting Compliance with the General Data Protection Regulation

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dc.contributor.authorBurmeister, Fabian
dc.contributor.authorDrews, Paul
dc.contributor.authorSchirmer, Ingrid
dc.date.accessioned2019-01-03T00:45:06Z
dc.date.available2019-01-03T00:45:06Z
dc.date.issued2019-01-08
dc.description.abstractThe processing of personal data has evolved into an integral component of businesses by providing several data-driven opportunities. Simultaneously, businesses struggle with the associated responsibility for privacy, as recent data scandals have shown. As a consequence, the European Commission has passed the General Data Protection Regulation (GDPR) to enhance the rights of citizens and the requirements on data protection. This paper argues that enterprise architecture (EA) models can be a key to compliance with the GDPR. Following an incremental research approach, we categorize the major obligations resulting from the GDPR, derive essential stakeholder concerns and outline necessary EA elements for capturing aspects of analytics, security and privacy in EA models. On this basis, a privacy-driven EA meta-model is developed that is capable of answering key concerns resulting from the GDPR.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2019.729
dc.identifier.isbn978-0-9981331-2-6
dc.identifier.urihttp://hdl.handle.net/10125/60040
dc.language.isoeng
dc.relation.ispartofProceedings of the 52nd Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectEnterprise Architecture and Business Process Analysis
dc.subjectOrganizational Systems and Technology
dc.subjectEnterprise Architecture, GDPR, Meta-Model, Privacy, Security
dc.titleA Privacy-driven Enterprise Architecture Meta-Model for Supporting Compliance with the General Data Protection Regulation
dc.typeConference Paper
dc.type.dcmiText

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