Weise, M., Kovacevic, F., Popper, N., & Rauber, A. (2022). OSSDIP: Open Source Secure Data Infrastructure and Processes Supporting Data Visiting. Data Science Journal, 21(1), 1–18. https://doi.org/10.5334/dsj-2022-004
E194-04 - Forschungsbereich Data Science E194-01 - Forschungsbereich Software Engineering
Data Science Journal
Number of Pages:
Data Visiting; Data Leakage; FAIR Data; Isolated Nodes; Secure Data Infrastructure
Meeting the conflicting goals of protecting and maintaining control over sensitive data while also allowing access by third parties constitutes a significant challenge. Secure data infrastructures support data visiting in a highly controlled and monitored environment which, if properly set-up and operated, provide high security guarantees through a combination of technical, legal and procedural mechanisms. To ease the process of deploying such a secure data infrastructure, we present a detailed documentation of the architecture and processes of such an infrastructure and provide a pre-configured reference implementation based entirely on open source software that can be flexibly configured to meet differing security requirements and deployment scenarios.
We combine mechanisms for data visiting on secured infrastructure components with optional components of data anonymization and fingerprinting, covered by extensive logging and monitoring functions and embedded in defined processes and contractual frameworks. The set-up is based upon the experience of operating such a secure infrastructure in the medical domain for almost ten years, addressing the emerging need to make such a solution available to a larger set of stakeholders. We show that our system significantly enhances data visiting, offers a higher level of data isolation and present our open source reference implementation thereof.
Computer Engineering and Software-Intensive Systems: 50% Information Systems Engineering: 50%