Metadata Enrichment and Interoperability: Scoping Review of Artificial Intelligence Contexts in Metadata in Academic Libraries Experiences Across the Globe
Year: 2025
Type: article
Abstract: Artificial Intelligence (AI) offers significant opportunities but requires librarian upskilling, responsible implementation, and ongoing evaluation of its impact on metadata ecosystems.This review (2015-2025) analyzes how AI is reshaping metadata creation, enrichment, interoperability, and access in academic libraries.Early research (2015-2019) focused on AI in digital library search engines and metadata extraction, while recent studies emphasize automation, GPT-based cataloguing, and interoperability frameworks.Key themes include automated metadata generation), metadata enrichment and structured archival description, and AI-driven discovery tools.Benefits cited are efficiency, scalability, and improved accuracy, though limitations include opacity of black-box models and inconsistency in outputs.Beyond technology, studies stress librarian readiness, metadata literacy, and AI competencies.Ethical and policy challenges-bias, transparency, and preservation standards (remain underexplored)..
Author: Shiva Kanaujia Sukula
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4413988460