The university of michigan school of information and the inter-university consortium for political and social research (icpsr) will study how generative artificial intelligence (genai) might enhance…

The University of Michigan School of Information and the Inter-University Consortium for Political and Social Research (ICPSR) received a $749,965 Project Grant award from the Institute of Museum and Library Services (IMLS) through the National Leadership Grants for Museums (CFDA 45.312) program. The award will fund a study on how generative artificial intelligence (GenAI) can enhance data curation processes, including drafting and evaluating metadata as well as identifying and managing sensitive data elements. The project aims to improve efficiency for data curators, increase detailed metadata access for data reusers, and enhance data privacy protections for research participants. Evaluation will involve curator feedback, user studies, text analytics, and comparisons with ICPSR's current metadata curation and search capabilities. The grant period runs from Aug 1, 2024 to Jul 31, 2027.

The university of michigan school of information and the inter-university consortium for political and social research (icpsr) will study how generative artificial intelligence (genai) might enhance data curation. A prior imls-funded study revealed that nationally, the data curation field is challenged with the time-intensive nature of generating expert-crafted, detailed metadata and addressing potential disclosure risks when sharing data for reuse. This research project will pursue both how genai can aid in drafting and evaluating metadata, as well as how computational tools can assist in identifying and managing sensitive data elements. Evaluation of genai tools' effectiveness will involve curator feedback, user studies, text analytics, and comparisons with icpsr's current metadata curation and search indices. Project beneficiaries across the nation will include data curators gaining efficiency in their roles; data reusers enjoying better data access and variable-level, detailed metadata; and research participants benefiting from enhanced data privacy through reduced disclosure risks.