Collaborative Curation & Collection Science
Leveraging the complementary capabilities of human and machine intelligence to collaboratively facilitate direct connections between digitisation, curation and data integration and management.
The broader vision for the collections of the future is to fully leverage the complementary capabilities of human and machine intelligence to collaboratively facilitate direct connections between digitisation, curation and data integration and management. Building a flexible interactive two-way interface between curators, researchers and machines is a long-term goal. A critical first step is to improve the ability to manage and curate the specimens. While there will always be a need for humans in the system there are many tasks that could be assisted by “digital curators”.
This project aims to identify and evaluate the first practical steps towards a broader concept of what a ‘digital curator’ could do and provide a ‘proof-of-concept’ demonstration of the value of integrating machine and human intelligence to assist with collection management. The first step of this project involves identifying which types of activities where a digital curator could provide substantial assistance to human collection staff. This includes explicit identification of tasks where machine-human interaction and collaboration is a critical element. The design of the AI and the associated collaborative workflows will improve data quality and assist users to extract the most relevant and accurate information from the databases.
This collaborative digital curation capability will be built with the flexibility to ultimately be deployed across collections.
Pete Thrall, Alan Stenhouse, Brendan Lepschi, Federica Turco, Juanita Rodriguez Arrieta, Alexander Schmidt-Lebuhn, Nicole Fisher, Emma Toms