Semi-automated data provenance tracking for transparent data production and linkage to enhance auditing and quality assurance in Trusted Research Environments
This project demonstrates the next stage in advancing transparency and quality assurance within TREs by semi-automating and systematising data tracking in a single tool throughout the data processing lifecycle, improving transparency, openness and quality assurance.
Authors
- Milan Marković (ORCID: https://orcid.org/0000-0002-5477-287X)
- Chinasa Odo (ORCID: https://orcid.org/0000-0002-0770-0806)
- Bernhard Scheliga (ORCID: https://orcid.org/0000-0003-2764-6605)
- Katie Wilde (ORCID: https://orcid.org/0000-0001-5024-8846)
- Katherine O’Sullivan (ORCID: https://orcid.org/0000-0002-9225-4942)
- Jaroslaw Dymiter
Institutions
- University of Bradford (GB)
- University of Aberdeen (GB)
- University of Sheffield (GB)
Publication Details
- Journal
- International Journal for Population Data Science
- Published
- 2025-02-06
- DOI
- https://doi.org/10.23889/ijpds.v10i2.2464
- Citations
- 2
- Primary Topic
- Data Quality and Management
- Type
- article
- Field-Weighted Citation Impact
- 4.21
Funders
- Wellcome Trust
- University of Sussex
- University of Aberdeen