Transforming Library Services with Metadata Lakes: Leveraging Big Data and AI for Enhanced Resource Management

Abstract

This study explores the transformative role of metadata in the management of library resources and services, particularly within the context of big data. Metadata enhances data discoverability, indexing, and automation, which, in turn, improves searchability, analytics, and decision-making processes. Libraries are facing an explosion of big data, diverse formats, and evolving user expectations, necessitating a shift in how metadata is managed. In response, this paper proposes a theoretical framework for implementing a “metadata lake” within libraries operating in a big data environment. The concept of a metadata lake is a novel approach to metadata management, and this study aligns it with the characteristics of big data to demonstrate its potential in library systems. Metadata management in libraries has evolved to fit into the big data ecosystem, creating opportunities for knowledge discovery, AI-driven automation, and predictive analytics. By adopting big data technologies, libraries can enhance access, efficiency, data transfer and research impact. The metadata lake concept offers scalability, AI-driven enrichment, and interoperability, allowing libraries to leverage big data and semantic technologies to improve the storage, processing, and retrieval of metadata. The integration of AI-driven recommendations will further enhance content discovery and user engagement. This paper highlights the importance of adopting advanced analytics, linked open data, and semantic technologies in library metadata management. It presents the metadata lake as the future of library metadata, ensuring libraries remain adaptable and capable of contributing to the big data landscape. Furthermore, future research could explore the use of machine learning (ML) and natural language processing (NLP) to automate metadata creation, enrich bibliographic records, and improve classification accuracy, ensuring that libraries continue to evolve in line with technological advancements.