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- Safeguarding National Digital Memory: Bayesian Network modelling of digital preservation risks
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- Home
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Postgraduate research
- Info for new students
- Current research students
- Postgraduate conference
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- Michael Tallis PhD Research Travel Award
- Information about research theses
- Past research students
- Resources
- Entry requirements
- PhD projects
- Obtaining funding
- Application & fee information
Student services
- Help for postgraduate students
- Thesis guidelines
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- Mathematics Drop-in Centre
- Consultation
- Statistics Consultation Service
- Academic advice
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Abstract
The National Archives, UK, identified a need to be able to assess risks to archives held digitally in order to ensure their longevity. Working with the Applied Statistics & Risk Unit at the University of Warwick, UK, a decision-support tool was developed. 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 the risk of various actions and interventions can be quantified. This tool, DiAGRAM, is now in use.
Bio: Dr Martine J Barons is the Director of the Applied Statistics and Risk Unit at the University of Warwick. The remit of AS&RU is to encourage and co-ordinate external partnerships which enable the early applications of theoretical, methodological and algorithmic developments made in the department, university and mathematical sciences community. After a career in business, Martine completed her PhD in 2013 in Complexity Science and Health Sciences, switching to from frequentist to Bayesian Statistics in her postdoc with Prof. Jim Smith.
Martine was a speaker at COP26 in 2021, launching Communicating Climate Risk: A Toolkit (bit.ly/CommunicatingClimateRisk ) and has research collaborations with a number of organisations form business, government and industry as well as with Melbourne, Monash and Imperial Universities. Her work with The National Archive, UK, recently received the 2022 Decision Analysis Practice Award, sponsored jointly by the Decision Analysis Society and the Society of Decision Professionals (https://www.informs.org/Recognizing-Excellence/Community-Prizes/Decision-Analysis-Society/Decision-Analysis-Practice-Award).
The recording of the talk is available on Stat Across Campuses playlist.