Speaker: Chris Royds, The National Archives
Abstract: The number of born-digital government records is already vast, and growing exponentially. Traditional paper-based approaches to managing these “digital heaps” are not viable at scale; some sort of machine assistance is needed. Furthermore, appraisal and selection decisions require an understanding of the context behind these records – which, in many cases, has been lost over time.
The MISO project explores how the archive can help government departments address these gaps in their organisational memory by providing machine-readable contextual data derived from TNA’s existing collections – the ‘memory of government’. We hypothesise that TNA’s digital collections contain rich insights into past organisational structures, business priorities, initiatives, and policy development. In a structured, AI-ready format, these insights can inform algorithms and AI tools to map a department’s legacy digital records, providing historical context to guide selection decisions. We call this resource the Machine-Interpretable Selection Outline (MISO).
In addition, several of the techniques used in gathering and summarising information from TNA’s digital collections may be useful in understanding the contents of government departments’ digital heaps themselves. Implemented in the right way, and placed in the hands of records managers, these techniques could significantly increase the pace of working through existing digital heaps.
Bio: Chris Royds is a Data Scientist at The National Archives. His work focuses on developing data-driven techniques, to assist government in dealing with large heaps of unstructured digital records. He has previously worked at HMRC, The Met Office, Birkbeck University, and KPMG. He even had a small speaking role in the 2016 horror film The Conjuring 2.