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Safeguarding the nation’s digital memory : Bayesian network modelling of digital preservation risks
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Barons, Martine J., Fonseca, Thaís C. O., Merwood, Hannah and Underdown, David H. (2022) Safeguarding the nation’s digital memory : Bayesian network modelling of digital preservation risks. In: Progress in Industrial Mathematics at ECMI 2021. ECMI 2021. Mathematics in Industry, 39 . Springer, Cham, pp. 501-508. ISBN 9783031118173
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WRAP-safeguarding-nation’s-digital-memory-Bayesian-network-modelling-digital-preservation-risks-Barons-2022.pdf - Accepted Version Embargoed item. Restricted access to Repository staff only until 25 November 2023. Contact author directly, specifying your specific needs. - Requires a PDF viewer. Download (332Kb) |
Official URL: https://link.springer.com/chapter/10.1007/978-3-03...
Abstract
Archives comprise primary sources which may be physical, born digital or digitised. Digital records have a limited lifespan, through carrier degradation, software and hardware obsolescence and storage frailties. It is important that the original bitstream of these primary sources is preserved and can be demonstrated to have been preserved. Soft elicitation with experienced archivists was used to identify the most likely elements contributing to digital preservation success and failure and the relationships between these elements. A Bayesian Network representation of an integrating decision support system provided a compact representation of reality, enabling the risk scores for various scenarios to be compared using a linear utility function. Thus, the effect on risk of various actions and interventions can be quantified. This tool, DiAGRAM, is now in use.
| Item Type: | Book Item | ||||||||||||
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| Subjects: | C Auxiliary Sciences of History > CD Diplomatics. Archives. Seals > CD921 Archives Q Science > QA Mathematics |
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| Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||||||||||
| Library of Congress Subject Headings (LCSH): | Digital preservation, Digital preservation -- Mathematical models , Preservation of materials -- Mathematical models | ||||||||||||
| Series Name: | Mathematics in Industry | ||||||||||||
| Publisher: | Springer, Cham | ||||||||||||
| ISBN: | 9783031118173 | ||||||||||||
| ISSN: | 1612-3956 | ||||||||||||
| Book Title: | Progress in Industrial Mathematics at ECMI 2021. ECMI 2021. | ||||||||||||
| Official Date: | 25 November 2022 | ||||||||||||
| Dates: |
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| Volume: | 39 | ||||||||||||
| Page Range: | pp. 501-508 | ||||||||||||
| DOI: | 10.1007/978-3-031-11818-0_65 | ||||||||||||
| Status: | Peer Reviewed | ||||||||||||
| Publication Status: | Published | ||||||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||||||
| Date of first compliant deposit: | 17 March 2023 | ||||||||||||
| RIOXX Funder/Project Grant: |
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