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.
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See DiAGRAM’s ‘Glossary’ tab here: https://nationalarchives.shinyapps.io/DiAGRAM/.
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The authors acknowledge with gratitude valuable contributions to the project by staff from partner institutions,Footnote 2 and by the additional experts who participated in the elicitation. This work was supported by: the National Lottery Heritage Fund under project reference number OM-19-01060; The Engineering and Physical Sciences Research Council under grant EP/R511808/1; and The National Archives (UK).
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Barons, M.J., Fonseca, T.C.O., Merwood, H., Underdown, D.H. (2022). Safeguarding the Nation’s Digital Memory: Bayesian Network Modelling of Digital Preservation Risks. In: Ehrhardt, M., Günther, M. (eds) Progress in Industrial Mathematics at ECMI 2021. ECMI 2021. Mathematics in Industry(), vol 39. Springer, Cham. https://doi.org/10.1007/978-3-031-11818-0_65
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Online ISBN: 978-3-031-11818-0