OSSDIP: Open Source Secure Data Infrastructure and Processes Supporting Data Visiting

Abstract

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.

PHIRI: lessons for an extensive reuse of sensitive data in federated health research

“…humans or machine learning algorithms) are allowed to implement federated research solutions. 16 , 17 …”

“Be sustainable”: EOSC‐Life recommendations for implementation of FAIR principles in life science data handling

“…With regard to Access and Benefit‐sharing (Appendix Supplementary Information S7), and as sharing may be perceived as a risk, EOSC‐Life has developed a prototype toolbox (Ohmann et al , 2022) allowing researchers to find existing, reliable resources relevant for sharing sensitive data across all participating RIs (Appendix Supplementary Information S8), supported by an interdisciplinary categorisation system [R9] (David et al , 2022) for which sustainability is increased by iterative building, validated by iterative consensus (Fig 3). Another example, the Open‐Source Secure Data Infrastructure and Processes Platform (https://www.ifs.tuwien.ac.at/infrastructures/ossdip/; OSSDIP – Weise et al , 2021) was developed as a blueprint that can be deployed, e.g. for educational purposes [R11] .…”

Harmonising knowledge for safer materials via the “NanoCommons” Knowledge Base

“…Furthermore, NanoCommons pushed for data management to be considered much earlier in the data life cycle, indeed at the point of experimental planning and design, as a means to identify at the outset the metadata and data needs. This could help develop meta (data) capture tools to support the researchers in their day-to-day data generation and processing [11]. Thus, based on the experiences from data shepherding, the nanosafety community needs and requirements guided and informed the design and implementation of the technical solutions developed and integrated into the NanoCommons Knowledge Base.…”