Beyond Data Citations: Linking Datasets to Articles for AI Readiness
Document Type
Presentation
Publication Title
Elsevier Impact Conference (EIC) 2026
Abstract
This session begins with a summary of research data management best practices — including current requirements, trends, and community advancements — and an overview of the NIH Generalist Repository Ecosystem Initiative (GREI). It also examines how institutions can better prepare for the future adoption of AI as it relates to dataset sharing and reuse.
Panelists and audience members explore current best practices on data citations alongside ideas and concerns about AI's impact on the research and data community — including the central question: "Who is using my data that I'm not even aware of, and how do I know?" The discussion considers what products or services may exist or are on the horizon to answer that question, and how funders, publishers, research institutions, and researchers can work together to focus on the usage, utility, and impact of data — using automation to prepare for the opportunities and challenges ahead.
Topics include: improving submission workflows for data citations; why focus must go beyond citations alone; automating the linking of publications and datasets; how consistent metadata, mapping, and interoperable linking prepares institutions for AI in data science; and bridging the gap between current practice and future readiness.
Especially valuable for Digital Commons users with research data management needs and Pure users looking to link research outputs to datasets within their research management environment.
Publication Date
4-15-2026
College or School
UAB Libraries
Supplemental Associated Link
Recommended Citation
Chandramouliswaran, Ishwar; Love, Randall; Reese, Amy; and Zdawczyk, Tina, "Beyond Data Citations: Linking Datasets to Articles for AI Readiness" (2026). Libraries Professional Work. 45.
https://digitalcommons.library.uab.edu/libraries-pw/45
