O’Sullivan, KatherineMarkovic, MilanDymiter, JaroslawScheliga, BernhardOdo, ChinasaWilde, Katie2025-02-072025-02-072025-02-06O’Sullivan, K, Markovic, M, Dymiter, J, Scheliga, B, Odo, C & Wilde, K 2025, 'Semi-automated data provenance tracking for transparent data production and linkage to enhance auditing and quality assurance in Trusted Research Environments', International Journal of Population Data Science, vol. 10, no. 2, 18. https://doi.org/10.23889/ijpds.v10i2.24642399-4908ORCID: /0000-0001-5024-8846/work/177758938https://hdl.handle.net/2164/25014We would like to acknowledge the DaSH Team in delivering and evaluating the PE-TRE (Adrian Martin, Helen Rowlands, Joanne Lumsden, Vicky Munro, Amal Sebastian and Michael Gent) and the support and contributions from researchers at the University of Aberdeen Centre for Health Data Science and NHS Grampian (Jessica Butler, Simon Sawheny, Dimitra Blana) and University of Aberdeen and NHS Grampian Information Governance teams (Jody McKenzie, Fiona Stuart and Alan Bell), and University of Aberdeen’s Department of Natural and Computing Science (Ana Ciocarlan). Further acknowledgement to contributors to the DARE UK Semi-Automated Risk Assessment project (PI: Arlene Casey), with contributions from DataLoch (Stuart Dunbar, Amy Tilbrook), West of Scotland Safe Haven (Charlie Mayor), eDRIS (Scottish National Safe Haven) (Jackie Caldwell) and University of Sussex (Liz Ford).217313249engdata provenancesemi-automationtrusted research environmentssecure data environmentssafe havendata linkagetransparancyinformation governanceauditQA75 Electronic computers. Computer scienceQ Science (General)Supplementary DataDASLinkQA75Q1Journal article10.23889/ijpds.v10i2.2464102