A systematic review and conceptual framework for cloud-based ontology-driven knowledge management systems in higher education institutions

Universities nowadays rely on digital platforms for organizing and sharing their institutional courses data. However, institutional information is scattered across different learning management systems, administrative databases, and research repositories, and there is no common system connecting them. Data were extracted from the relevant major academic database Springer Link, Scopus and IEEE for the year ranging from 2015 to 2025. Initially, 248 researches were observed out of which 30 studies review by expert were selected after filtering. The studies were analyzed for the cloud technologies in system design, the ontologies for the structured representation of knowledge and the knowledge graphs for the connected data systems. 22 out of 30 studies reported measurable improvements in knowledge accessibility. However, 78% of the reviewed systems lacked scalable reasoning mechanisms to handle large datasets, and fewer than 30% provided practical implementation guidance. Our research has three contributions: (i) literature synthesis of ontology-driven systems and cloud-based knowledge management in higher education; (ii) a system architecture that integrates cloud service models (IaaS, PaaS, SaaS), SPARQL-based knowledge graphs, and semantic technologies (OWL, RDF ontologies), grounded in a deployment scenario at Jazan University, Saudi Arabia; and (iii) a step-by-step implementation framework.