IMPLEMENTING TRADITIONAL LIBRARY CLASSIFICATION SYSTEMS WITHIN LINKED DATA ENVIRONMENTS: PRACTICAL CHALLENGES FROM ACADEMIC LIBRARIES

Abstract

This study examines the application of traditional library classification systems within Linked Data environments in academic libraries, emphasing on conceptual importance, thematic standardisation, application difficulties, and integration procedures. The swift shift from print-based and physically ordered collections to digitally interconnected information systems has enhanced the demand for academic libraries to adapt traditional knowledge organisation mechanism to semantic web innovations. Traditional classification schemes such as the Dewey Decimal Classification (DDC), Library of Congress Classification (LCC), and Universal Decimal Classification (UDC) continues to be fundamental for subject organisation, bibliographic control, and information retrieval, regardless the increasing complication of digital information environments. The research uses a qualitative exploratory design based on a methodical analysis of scholarly literature published between 2021 and 2025. Appropriate data were collected from databases including Scopus, Web of Science, Google Scholar, Emerald Insight, and ScienceDirect. The study is rooted on Classification Theory, Semantic Web Theory, and the Technology Organisation System (TOE) framework. The results reveal that Linked Data technologies such as RDF, SKOS, OWL, and BIBFRAME enhance interoperability, semantic consistency, and discoverability of library resources. However, problems including insufficient infrastructure, metadata conversion challenges, paucity of professional expertise, meager funding, and weakly institutional support remain an hindrance to implementation, especially in third-world countries. The study recommends gradual implementation, semantic standardisation, staff training, and continuous funding in digital infrastructure.