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 privacydriven EA meta-model is developed that is capable of answering key concerns resulting from the GDPR.

Businesses today are increasingly dependent on how they transform information into economic value, while simultaneously being compliant with intensified privacy requirements, resulting from legal acts like the General Data Protection Regulation (GDPR). As a consequence, realizing information governance has become a topic more important than ever to balance the beneficial use and protection of information. This paper argues that enterprise architecture management (EAM) can be a key to GDPR implementation as one important domain of information governance by providing transparency on information integration throughout an organization. Based on 24 interviews with 29 enterprise architects, we identified a multiplicity of benefits and barriers within the interplay of EAM and GDPR implementation and derived seven design principles that should foster EAM to enhance information governance.

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With the ubiquitous use of mobile devices, locationbased services (LBS) have rapidly pervaded daily life. By providing context-and location-specific information, LBS enable a myriad of opportunities for individuals and organizations. However, the manifold advantages come along with a radical increase in location privacy concerns and non-transparent data flows between the various actors involved. While research often focuses on protecting the dyadic relation between the user and LBS provider, the entirety of dark sides constituting privacy violations remains hidden. In this paper, we follow the paradigm of architectural thinking to shed light on the diverse dark sides emerging in today's LBS. By drawing on a multiple case study and developing a notation for architectural maps that help understand LBS from a socio-technical and privacy-oriented perspective, we reveal six dark side archetypes of LBS.

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