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Decision Provenance : Harnessing Data Flow for Accountable Systems

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dc.contributor.authorSingh , Jat
dc.contributor.authorCobbe, Jennifer
dc.contributor.authorNorval, Chris
dc.date.accessioned2024-03-12T14:48:00Z
dc.date.available2024-03-12T14:48:00Z
dc.date.issued2019-01-16
dc.descriptionFunding Information: This work was supported by the U.K. Engineering and Physical Sciences Research Council (EPSRC) under Grant EP/P024394/1 and Grant EP/R033501/1 and Microsoft through the Microsoft Cloud Computing Research Centre.en
dc.description.statusPeer revieweden
dc.format.extent13
dc.format.extent3477630
dc.identifier284250698
dc.identifierad03cb5c-fd21-46fc-97ca-63376eeda870
dc.identifier85058884047
dc.identifier.citationSingh , J, Cobbe, J & Norval, C 2019, 'Decision Provenance : Harnessing Data Flow for Accountable Systems', IEEE Access, vol. 7, pp. 6562-6574. https://doi.org/10.1109/ACCESS.2018.2887201en
dc.identifier.doi10.1109/ACCESS.2018.2887201
dc.identifier.issn2169-3536
dc.identifier.otherORCID: /0000-0002-4331-7863/work/153542297
dc.identifier.urihttps://hdl.handle.net/2164/22985
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85058884047&partnerID=8YFLogxKen
dc.identifier.vol7en
dc.language.isoeng
dc.relation.ispartofIEEE Accessen
dc.subjectAccountabilityen
dc.subjectAIen
dc.subjectalgorithmic & automated decision-makingen
dc.subjectdata managementen
dc.subjectGDPRen
dc.subjectgovernanceen
dc.subjectIoTen
dc.subjectlawen
dc.subjectmachine learningen
dc.subjectprivacyen
dc.subjectprovenanceen
dc.subjectsecurityen
dc.subjectsystems of systemsen
dc.subjecttransparencyen
dc.subjectTK Electrical engineering. Electronics Nuclear engineeringen
dc.subjectGeneral Computer Scienceen
dc.subjectGeneral Materials Scienceen
dc.subjectGeneral Engineeringen
dc.subjectEngineering and Physical Sciences Research Council (EPSRC)en
dc.subjectEP/P024394/1en
dc.subjectEP/R033501/1en
dc.subject.lccTKen
dc.titleDecision Provenance : Harnessing Data Flow for Accountable Systemsen
dc.typeJournal articleen

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