Collections data has been slowly appearing online, as museums computerise their collections management systems and focus on the huge effort to digitise. However, so much of this data is unstandardised and written in chunks of text that make it difficult to search and sort through.
Most museums will never find the resources to fully catalogue their collections, but that doesn’t mean we can’t make the most of the data that already exists. This is where the potential of computational techniques such as artificial intelligence (AI) come in.
The use of AI is being explored through initiatives such as the Science Museum Group’s two Arts and Humanities Research Council-funded Towards a National Collection projects, Heritage Connector and Congruence Engine, to better understand how specific digital techniques can help. The idea is that we can use tools such as AI to do a lot of automated connecting work without having to re-catalogue collections.
AI has many problems, not least the potential to reinforce biases in our collections data. But it can help identify gaps in our knowledge and pinpoint new and previously hidden connections.
It may sound daunting, but AI’s potential uses for the sector are only just being understood.
Arran Rees is a research associate at the University of Leeds, working with the Science Museum Group on Congruence Engine