Generative AI for Born-Digital Collections: A Case Study of Metadata Management in an Institutional Repository
Abstract
This case study examines the application of generative artificial intelligence (AI) tools, specifically ChatGPT-4o, ChatGPT-5, and Google Gemini 2.5 Flash, to streamline metadata extraction and creation for a born-digital collection within a digital repository environment. Testing four descriptive metadata elements—titles, abstracts, keywords, and full-text URLs—the study shows that AI improves efficiency in structured tasks but remains limited in semantic ones such as keyword matching. Results demonstrate that AI can streamline metadata workflows for small or resource-constrained institutions while emphasizing the continuing importance of human oversight and ethical responsibility in AI-assisted metadata workflows.
Fields of Study & Subjects
Research Data Management Practices
Information Retrieval and Search Behavior
Digital and Traditional Archives Management
Publication details
- Journal / source
- Cataloging & Classification Quarterly
- Publisher
- Informa UK Limited
- Volume
- 64
- Issue
- 3-4
- Pages
- 123–147
- Publication date
- 8 May 2026
- Language
- EN