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Semi-automated data provenance tracking for transparent data production and linkage to enhance auditing and quality assurance in Trusted Research Environments

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dc.contributor.authorO’Sullivan, Katherine
dc.contributor.authorMarkovic, Milan
dc.contributor.authorDymiter, Jaroslaw
dc.contributor.authorScheliga, Bernhard
dc.contributor.authorOdo, Chinasa
dc.contributor.authorWilde, Katie
dc.contributor.institutionUniversity of Aberdeen.Trusted Things and Communitiesen
dc.contributor.institutionUniversity of Aberdeen.Computing Scienceen
dc.contributor.institutionUniversity of Aberdeen.Relationship Managementen
dc.date.accessioned2025-02-07T11:33:01Z
dc.date.available2025-02-07T11:33:01Z
dc.date.issued2025-02-06
dc.descriptionWe 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).en
dc.description.statusPeer revieweden
dc.format.extent21
dc.format.extent7313249
dc.identifier301234414
dc.identifier3bbd1a3f-5d95-41e1-b4b8-fd14cfc7f90e
dc.identifier85217797947
dc.identifier.citationO’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.v10i2.2464en
dc.identifier.doi10.23889/ijpds.v10i2.2464
dc.identifier.iss2en
dc.identifier.issn2399-4908
dc.identifier.otherORCID: /0000-0001-5024-8846/work/177758938
dc.identifier.urihttps://hdl.handle.net/2164/25014
dc.identifier.vol10en
dc.language.isoeng
dc.relation.ispartofInternational Journal of Population Data Scienceen
dc.subjectdata provenanceen
dc.subjectsemi-automationen
dc.subjecttrusted research environmentsen
dc.subjectsecure data environmentsen
dc.subjectsafe havenen
dc.subjectdata linkageen
dc.subjecttransparancyen
dc.subjectinformation governanceen
dc.subjectauditen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectQ Science (General)en
dc.subjectSupplementary Dataen
dc.subjectDASen
dc.subjectLinken
dc.subject.lccQA75en
dc.subject.lccQ1en
dc.titleSemi-automated data provenance tracking for transparent data production and linkage to enhance auditing and quality assurance in Trusted Research Environmentsen
dc.typeJournal articleen

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