This event will be held on
08 February 2024
- 15:00 – 16:15
Following on from our successful November webinar, Making your collections AI ready, Peter Findlay will chair a further discussion, to encourage the library community to be bold in providing machine ready collections, in support of research, and to feel more confident with the impending introduction of AI into the community.
This time Peter will be joined by colleagues from the University of Manchester Library. The library has a wealth of digitised collection content and a very active researcher base. In their talk, Ian Gifford, head of digital development, and Jane Gallagher, head of digital special collections and services, will explore the opportunities, risks and challenges inherent in curating these collections as data. Using digital collections data case studies and focusing on special collections, they will consider practical responses to the Vancouver statement on collections-as-Data and our thoughts for sector-wide progress to AI readiness.
We will then go on to discuss how machine ready collections can be described. Significant work in web archives scholarship focuses on the description and provenance of collections and their data. Looking beyond the worlds of libraries, archives and cultural heritage can provide valuable alternative approaches, which we can experiment with and use. Datasheets for datasets is a method for describing large datasets from the field of machine learning, which uses a standard set of questions arranged by stages of the data lifecycle.
This presentation reports back on the findings of a collaborative project between Emily Maemura, assistant professor, school of information sciences, University of Illinois at Urbana Champaign and Helena Byrne, curator of web archives at the British Library UK Web Archive. The project explored if the Datasheets for datasets framework, originally developed by Timnit Gebru, could be applied to UK Web Archive collections published as data sets.
Who should attend
Librarians who have strategic oversight of special collections including archives and those who simply want to respond to the demand for more data and how they might make their collections AI ready.
For further information, please contact email@example.com.