TY - CHAP

T1 - A Privacy-driven Enterprise Architecture Meta-Model for Supporting Compliance with the General Data Protection Regulation

AU - Burmeister, Fabian

AU - Drews, Paul

AU - Schirmer, Ingrid

N1 - Conference code: 52

PY - 2019/1/1

Y1 - 2019/1/1

N2 - The 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.

AB - The 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.

KW - Business informatics

KW - Enterprise Architecture and Business Process Analysis

KW - Organizational Systems and Technology

KW - Enterprise architecture

KW - GDPR

KW - Meta-Model

KW - Privacy

KW - Security

UR - http://www.scopus.com/inward/record.url?scp=85073507425&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/5ddd5736-84c8-32b8-aa0f-57f88425ff56/

U2 - 10.24251/HICSS.2019.729

DO - 10.24251/HICSS.2019.729

M3 - Article in conference proceedings

T3 - Proceedings of the Annual Hawaii International Conference on System Sciences

SP - 6052

EP - 6061

BT - Proceedings of the 52nd Annual Hawaii International Conference on System Sciences, HICSS 2019

A2 - Bui, Tung X.

PB - University of Hawaiʻi at Mānoa

CY - Honolulu

T2 - 52nd Annual Hawaii International Conference on System Sciences - HICSS 2019

Y2 - 8 January 2019 through 11 January 2019

ER -