Our Heritage, Our Stories: developing AI tools to link and support community-generated digital cultural heritage

Ewan d. Hannaford, Viktor Schlegel, Rhiannon Lewis, Stefan Ramsden, Jenny Bunn, John Moore, Marc Alexander, Hannah Barker, Riza Batista-Navarro, Lorna Hughes, Goran Nenadic

Research output: Contribution to journalArticlepeer-review

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Abstract

Purpose: Community-generated digital content (CGDC) is one of the UK’s prime cultural assets. However, CGDC is currently “critically endangered” (Digital Preservation Coalition, 2021) due to technological and organisational barriers and has proven resistant to traditional methods of linking and integration. The challenge of integrating CGDC into larger archives has effectively silenced diverse community voices within our national collection. Our Heritage, Our Stories (OHOS), funded by the UK’s AHRC programme Towards a National Collection, responds to these urgent challenges by bringing together cutting-edge approaches from cultural heritage, humanities and computer science. Design/methodology/approach: Existing solutions to CGDC integration, involving bespoke interventionist activities, are expensive, time-consuming and unsustainable at scale, while unsophisticated computational integration erases the meaning and purpose of both CGDC and its creators. Using innovative multidisciplinary methods, AI tools and a co-design process, previously unfindable and unlinkable CGDC will be made discoverable in our virtual national collection. Findings: There currently exists a range of disconnected, fragile and under-represented community-generated heritage which is at increasing risk of loss. Therefore, OHOS will work to ensure the survival and preservation of these nationally important resources, for the future and for our shared national collection. Originality/value: As we dissolve barriers to create meaningful new links across CGDC collections and develop new methods of engagement, OHOS will also make this content accessible to new and diverse audiences. This will facilitate a wealth of fresh research while also embedding new strategies for future management of CGDC into heritage practice and training and fostering newly enriching, robust connections between communities and archival institutions.

Original languageEnglish
Pages (from-to)1133-1147
Number of pages15
JournalJournal of Documentation
Volume80
Issue number5
Early online date4 Jun 2024
DOIs
Publication statusPublished - 3 Sept 2024

Keywords

  • AI
  • CGDC
  • Community archives
  • Digital heritage
  • NLP
  • National collection
  • Natural language processing

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