Enterprise Modelling and Information Systems Architectures (EMISAJ)

Call for Papers - Special Issue

Towards Privacy Preservation and Data Protection in Information System Design

Editors

• Agnes Koschmider, University of Kiel, Germany
• Judith Michael, RWTH Aachen, Germany
• Nathalie Baracaldo, IBM Research - Almaden, USA

Scope
This special issue seeks research articles, industry or experience reports related to all aspects of privacy and data protection in the design of information systems. Data breaches and data misuse continuously increase the uncertainty in the use of devices and systems that process personal data. Apart from this, declarations of consent are given by users without a clear understanding of it. Sensitive information, such as personal data must be given special attention when designing information systems. Personal data protection is of paramount importance to ensure compliance with the General Data Protection Regulation (GDPR), which obliges organizations to consider privacy throughout the complete development process. This requires an interplay between technical solutions related to privacy engineering techniques and user-friendly interfaces allowing to protect data and to configure privacy preferences by users. This is also critical to build information systems that users can trust. This special issue invites submissions that address privacy-by-design, privacy engineering, privacy enhancing technologies, privacy architectures, the integration of privacy into software engineering lifecycle phases, user experience with privacy mechanisms, data protection in analytics and mining or investigating privacy concerns within agile (or) model-based system engineering methods.

Possible topics include but are not limited to:

• User-centered access control in IS design
• The relationship between security, privacy and trust in IS design
• Privacy compliant reuse of software
• Conceptual modeling, privacy and trust
• Privacy and trust by design in process-aware information systems
• Model-based approaches for privacy preserving IS
• Agile development methods and privacy guarantee
• User acceptance of privacy-related features and applications
• Best-practices for privacy regulations in various application domains
• Privacy preservation and machine learning
• Privacy engineering for (event) logs

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