Development of A Framework Using Findable, Accessible, Interoperable, and Reusable Model for Data Management Practices in Nigerian Universities

The era of digitalization has made data-driven discovery a new paradigm, creating an urgent need for proper data management. While Nigerian universities generate vast amounts of data through diverse academic and research activities, they suffer from fragmented and inefficient data practices that hinder data reusability, interoperability, and collaboration. Recognizing the critical gap of lacking a standardized, empirically tested framework tailored to the Nigerian context, this study developed and validated a FAIR-compliant framework based on the Findable, Accessible, Interoperable, and Reusable (FAIR) principles. This was achieved by designing a formal, scalable blueprint using the semantically rich OntoUML modeling, which integrates a centralized repository, metadata management, an interoperability layer, and a formal governance structure. The framework's adherence was confirmed via a two-stage validation: first, through objective FAIR-Checking adherence testing, which yielded a perfect score across all core FAIR metrics (F1, F2, F4, A1, I1, I2, R1.1, R1.2), and second, through expert reviews, which validated its practical usability and compliance with local regulations like the Nigerian Data Protection Regulation (NDPR). Consequently, the research bridges the gap between theory and application, providing a viable, actionable solution that makes significant contributions to improved data governance, enhanced research collaboration, and the development of trustworthy, efficient data systems in Nigeria and beyond.