Safeguarding the nation's digital memory: towards a Bayesian model of digital preservation risk. Issue 1 (2nd January 2021)

• Record Type: Journal Article
• Authors: Barons, Martine; Bhatia, Sidhant; Double, Jodie; Fonseca, Thais; Green, Alex; Krol, Stephen; Merwood, Hannah; Mulinder, Alec; Ranade, Sonia; Smith, Jim Q; Thornhill, Tamara; Underdown, David H
• Is Part Of: Archives and records. Volume 42:Issue 1(2021)
• Page Start: 58
• Page End: 78
• Publication Date: 2021-01-02
• Subjects: Digital preservation -- risk -- collaboration -- Bayesian network -- decision-support system; Archives -- Great Britain -- Periodicals; Archives -- Ireland -- Periodicals; Public records -- Great Britain -- Periodicals; Public records -- Ireland -- Periodicals; 025.1714094105
• DOI: 10.1080/23257962.2021.1873121
• Languages: English
• ISSNs: 2325-7962

Abstract

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.