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Safeguarding the nation’s digital memory : towards a Bayesian model of digital preservation risk
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Barons, Martine J., Bhatia, Sidhant, Double, Jodie, Fonseca, Thaís C. O., Green, Alex, Krol, Stephen, Merwood, Hannah, Mulinder, Alec, Ranade, Sonia, Smith, Jim Q., Thornhill, Tamara and Underdown, David H. (2021) Safeguarding the nation’s digital memory : towards a Bayesian model of digital preservation risk. Archives and Records, 42 (1). pp. 58-78. doi:10.1080/23257962.2021.1873121 ISSN 2325-7962.
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WRAP-Safeguarding-nations-digital-memory-Bayesian-digital-risk-21.pdf - Published Version - Requires a PDF viewer. Available under License Open Government Licence: OGL (v3.0). Download (3114Kb) | Preview |
Official URL: https://doi.org/10.1080/23257962.2021.1873121
Abstract
Preservation of digital material is a challenge for which many archives feel underprepared and ill equipped. The National Archives (UK) has been working in collaboration with statisticians from the University of Warwick and partners from across the UK archives sector to develop a decision-support system which quantifies the risks involved in digital preservation. Through interdisciplinary collaboration, this partnership has developed an interactive tool for managing risks to digital material, based on a Bayesian statistical network. The tool provides archivists with a different way of thinking about digital preservation, supported by an evidence base they can use to advocate for action. The project illustrates the potential benefit of a collaborative approach, combining insight from different disciplines.
| Item Type: | Journal Article | ||||||||||||
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| Subjects: | Q Science > QA Mathematics Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science |
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| Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||||||||||
| Library of Congress Subject Headings (LCSH): | Digital preservation -- Great Britain, Data protection, Archival materials -- Conservation and restoration, Risk management -- Mathematical models, Digital preservation -- Management | ||||||||||||
| Journal or Publication Title: | Archives and Records | ||||||||||||
| Publisher: | Taylor & Francis | ||||||||||||
| ISSN: | 2325-7962 | ||||||||||||
| Official Date: | 28 May 2021 | ||||||||||||
| Dates: |
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| Volume: | 42 | ||||||||||||
| Number: | 1 | ||||||||||||
| Page Range: | pp. 58-78 | ||||||||||||
| DOI: | 10.1080/23257962.2021.1873121 | ||||||||||||
| Status: | Peer Reviewed | ||||||||||||
| Publication Status: | Published | ||||||||||||
| Reuse Statement (publisher, data, author rights): | Published under an Open Government Licence https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/ | ||||||||||||
| Access rights to Published version: | Open Access (Creative Commons) | ||||||||||||
| Copyright Holders: | Archives and Records Association | ||||||||||||
| Date of first compliant deposit: | 5 August 2021 | ||||||||||||
| Date of first compliant Open Access: | 14 February 2023 | ||||||||||||
| RIOXX Funder/Project Grant: |
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