Note: An Excel export of the full program will be available at the end of August.
Enhancing Serials Metadata with Artificial Intelligence: A Case Study Using ChatGPT and Alma Cloud Apps
Event part
Conference
Abstract
In the rapidly evolving technological landscape, the integration of Artificial Intelligence (AI) into library practices offers significant potential for enhancing metadata quality. In this session, the presenters will showcase a project undertaken by the University of Toronto Libraries (UTL) to leverage ChatGPT and Alma cloud apps to standardize and improve serials metadata. The initiative employs AI-driven techniques to identify discrepancies in item metadata, automate the correction process, and reload the metadata using Alma's cloud apps. The project also highlights how these technologies can enable the retrospective itemization of serials and the regeneration of serial summary holding statements. By empowering librarians with artificial intelligence and advanced API tools, this project showcases a scalable and innovative approach to metadata remediation, enabling large-scale enhancements that significantly improve the accessibility and utility of library collections.
Track
Development / Initiative
Products or Areas of Focus
Alma
Presenters
![[photo]](https://secure.gravatar.com/avatar/c3c1474d0cc2809bb8a3026581d5d3c1.png?d=https://proposalspace.com/images/no_photo.png&r=PG&s=50 "Marlene van Ballegooie, Metadata Technologies Manager, University of Toronto Libraries")
Marlene van Ballegooie, Metadata Technologies Manager, University of Toronto Libraries
LinkedIn URL
![[photo]](https://secure.gravatar.com/avatar/806c3ea8199f026be6b6d4df78ccee44.png?d=https://proposalspace.com/images/no_photo.png&r=PG&s=50 "Juliya Borie, Librarian, Metadata Services, University of Toronto Libraries")