Data access management system for relational accountability orchestration (pre-print)
As we enter the next decade of FAIR with advanced artificial intelligence to analyse and interpret valuable data, we must have interoperable authorisation processes to ensure proper data management practice. In this article, we describe the Resource Entitlement Management System (REMS) software. REMS provides a generic workflow engine that translates ethical, legal, and cultural requirements into actionable permissions. REMS manages the relational accountability for data protection between data applicants, authorisation bodies, and data holders. REMS introduces configurable levels of automation while keeping human oversight intact. Once a Data Access Committee (DAC) approves a request, REMS issues a permission in a standard format (e.g. GA4GH Visa) and logs the entire process for auditing. REMS operates across diverse regulatory and federated landscapes, utilizing global standards and metadata (e.g., OIDC, GA4GH, W3.org) to programmatically enforce controlled access. It facilitates sensitive data management aligned with FAIR principles, supporting initiatives including the European Genomic Data Infrastructure (GDI), Genome of Europe, CADRE, the ZERO childhood cancer portal, and various national biobanks and language repositories. Crucially, streamlining access must respect cultural safety and data sovereignty. The Rakeiora platform (Aotearoa New Zealand) exemplifies how technical standards can uphold indigenous governance; by integrating Māori values, the project demonstrates that community-led oversight is essential for building trust in digital infrastructure.
Authors
- Markku Rontu
- Andrew Patterson (ORCID: https://orcid.org/0000-0002-1163-8558)
- Claire E. Rye (ORCID: https://orcid.org/0000-0003-4630-7836)
- Dylan Spalding (ORCID: https://orcid.org/0000-0002-4285-2493)
- Heikki Lehväslaiho (ORCID: https://orcid.org/0000-0002-6263-1356)
- Conrad Leonard (ORCID: https://orcid.org/0000-0002-4131-2065)
- Ilkka Lappalainen (ORCID: https://orcid.org/0000-0001-5762-893X)
- Juha Törnroos (ORCID: https://orcid.org/0000-0001-9216-0455)
- Bernard J. Pope (ORCID: https://orcid.org/0000-0002-4840-1095)
- Martin Matthiesen
- Martin Kuba (ORCID: https://orcid.org/0000-0002-0305-7446)
- Jarno Laitinen (ORCID: https://orcid.org/0000-0002-7952-9024)
- Tommi Nyrönen (ORCID: https://orcid.org/0000-0002-5569-5183)
- Tiina Wahlfors (ORCID: https://orcid.org/0000-0002-3910-796X)
- Oliver Hofmann (ORCID: https://orcid.org/0000-0002-7738-1513)
- Melissa Konopko (ORCID: https://orcid.org/0000-0001-9515-398X)
- Tommi Jalkanen
- Minttu Sauramo
- Jaakko Leinonen (ORCID: https://orcid.org/0000-0001-6537-8520)
- Tracey Godfery (ORCID: https://orcid.org/0000-0002-0955-3563)
- Matt Pestle
- Miska Husgafvel
- Miikka Kallberg (ORCID: https://orcid.org/0000-0002-1457-3999)
- Mikael Linden (ORCID: https://orcid.org/0000-0002-3634-3756)
- Bruno Pacheco (ORCID: https://orcid.org/0009-0007-9791-2506)
- Meeri Hakala (ORCID: https://orcid.org/0009-0004-5990-8512)
- Janne Lauros
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-09-01
- DOI
- https://doi.org/10.5281/zenodo.22207241
- Primary Topic
- Research Data Management Practices
- Type
- preprint