Governing information privacy in data ecosystems with architectural thinking

This study addresses the challenge of governing privacy within data ecosystems by integrating architectural thinking (AT) into the discourse. Organizations are increasingly embarking on complex data-sharing initiatives, often encompassing personal data, raising heightened privacy concerns and regulatory obligations. With transparency obscured by complexity, there is a pressing need for systematic approaches to decompose data ecosystems. Leveraging AT, traditionally applied in intra-organizational contexts, this article proposes extending its application to the ecosystem level. By triangulating qualitative data from case studies and expert interviews, key privacy concerns of both business and regulatory stakeholders in data ecosystems are unveiled. Based on these concerns, the study develops and demonstrates a comprehensive data ecosystem architecture meta-model as a foundation for AT to govern privacy from both a business and regulatory perspective. The contributions bridge existing gaps in understanding and addressing privacy concerns within data ecosystems, offering stakeholders a systematic approach for analysis and mitigation.