Using Generative AI Tools for Research Data Management: Questions and Answers

Date of Live Webinar: Thursday, March 27, 2025, 1:00 p.m.–2:30 p.m., Central Time

A generative AI tool can be used to evaluate a data management plan in tandem with human oversight/expertise. Librarian expertise in RDM is essential for ensuring researchers use these tools in alignment with data literacy and ethical best practices.

If you support research data management (RDM), you know that demands on researchers to meet RDM requirements and mandates are increasing just as the use of generative artificial intelligence (AI) tools is becoming ubiquitous.

Alisa Beth Rod and Sandy Hervieux, librarians with expertise in RDM and AI, will be your guides toward understanding of how (and whether) generative AI tools can assist in activities related to RDM. They’ll show that generative AI tools can be used now in assisting in explaining file naming conventions, directory structures, and other tasks in the RDM workflow. They will show that libraries are well-positioned to offer services, support, and guidance to researchers in using generative AI tools according to best practices and in alignment with data literacy principles.

Learning Outcomes

By the end of this course, you will be able to:

Explain how to use a generative AI tool to evaluate a data management plan and apply this knowledge to disciplinary use cases in health science/medicine
Describe the ways in which generative AI tools may be integrated effectively into research data management workflows for researchers and librarians/information professionals
Describe the ethical and privacy concerns of applying generative AI to research data management practices
Participate in the discourse on the use of generative AI technologies in the context of research data management

Audience

Health sciences librarians and other information professionals who support research data management or who have at least an introductory-level understanding of research data management (e.g., what is RDM, what activities are involved in supporting RDM, etc.)

Presenters

Alisa Beth Rod, MIS, PhD is the Research Data Management Specialist at McGill University Libraries. Prior to joining McGill, Alisa was the Survey Methodologist at Ithaka S+R and then the Associate Director of the Empirical Reasoning Center at Barnard College. Her research interests include data-related librarianship, research data management, and data culture in academic libraries.

Sandy Hervieux, MLIS is the Head Librarian of the Nahum Gelber Law Library at McGill University in Montreal, Quebec, Canada. She co-edited, The Rise of AI: Implications and Applications of Artificial Intelligence in Academic Libraries and has authored several articles and presentations on AI in libraries. Her research interests include reference services, information literacy, and the impact of artificial intelligence on user services.

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