Using Generative AI to Reduce Manual Burden in Research Data Management
Scientists want to do science. Some things they don’t want to spend time doing include: - Making a plan for managing their data - Creating README files for their materials - Filling out and updating metadata for research outputs Our team provides tools and services to help make research data FAIR - Findable, Accessible, Interoperable, and Reusable. In this panel, we’ll discuss recent efforts to use Generative AI to help in data curation tasks, and the challenges and opportunities we’ve discovered. Projects include using AI for: - Drafting and giving feedback on data management plans - Reviewing datasets prior to repository submission to suggest improvements that help others re-use them - Streamlining metadata curation by automating validation and enrichment workflows By reducing burden on the researcher, while still keeping them as the final authority, we can continue to support making data FAIR and let scientists spend more time on the science itself.
Speaker/Host
Primary/Host Speaker
Becky Hofstein Grady
Senior Product Manager at UC Office of the President
Becky Hofstein Grady joined UC O6ice of the President in 2024 to be the Senior Product Manager for Data Management Planning at the California Digital Library. She works as the service manager for the DMP Tool, a free, open-source online tool that helps researchers write data management plans (DMPs) for grant applications. Currently, her team is working on rebuilding the tool to o6er more machine-actionable functionality and new features. Together with other institutions and partners, they are exploring innovative functions like using generative AI to help review and draft DMPs, interfacing with local research systems to re-use information, and promoting connections of DMPs to the broader scholarly ecosystem. Before joining UCOP, she received her PhD in social psychology from UC Irvine (Zot!) and then worked as both a user experience researcher and a product manager in the video game industry.
Co-speaker(s)
Additional Speakers
Adam Buttrick
Senior Product Manager at UC Office of the President
Adam Buttrick is the Senior Product Manager for Persistent Identifiers at the California Digital Library (CDL). A librarian and developer based in Los Angeles, USA, Adam previously worked on the research team at Crossref, as a developer for the Getty Conservation Institute, an implementation manager for OCLC’s Metadata Services, and for the University of Michigan Library.
Scott Fisher
Lead Programmer at UC Office of the President
Scott Fisher is Technical Lead at the UC Curation Center, California Digital Library, where he builds data-publication tools that help researchers make their work findable, accessible, interoperable, and reusable. He co-developed the Dryad repository and the CDL Web Archiving Service and has presented at Open Repositories and Code4lib. Scott is passionate about using AI to streamline data-sharing workflows and reducing friction so researchers can more easily preserve and publish their results.
Steve Diggs
Research Data Specialist at UC Office of the President
Steve Diggs is a Research Data Specialist with the University of California Office of the President (UCOP), serving as the Senior Product Manager for the data publishing portfolio at the University of California Curation Center (UC3). He previously was the Technical Director for the Hydrographic Data Office at Scripps Institution of Oceanography, UC San Diego. With decades of experience in designing and operating full-stack information systems, Steve focuses on making data more valuable, discoverable, and accessible to the research community. He is also active in international data and science teams, serving on the Board on Research Data and Information (BRDI) under the National Academies of Sciences, Engineering, and Medicine (NASEM) and the UN Ocean Decade Data Coordination Committee. Steve’s extensive work with researchers in the field and lab gives him a deep understanding of the challenges and opportunities in managing scholarly data.
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