Development of a FAIR Data Point Repository for Academic Projects
Abstract
An enormous amount of data is associated with academic projects scattered across different locations and in different formats, making it difficult for researchers to find and access the data. Without a centralized repository, researchers may end up duplicating existing data, wasting time and resources. Also, researchers are less likely to share their data with others when no platform readily facilitates it, this impedes collaboration and hinders the progress of science. Therefore, this study aimed to develop a FAIR (Findable, Accessible, Interoperable, and Reusable) data point repository for academic projects. The requirement specifications for the system were identified and modelled using the Unified Modelling Language (UML), the required database schemas were thoughtfully designed, and the repository was implemented using web technologies such as PHP, MySQL, HTML, CSS, and jQuery. The performance of the developed FAIR data point was evaluated based on the essential, important, and useful FAIRness indicators for the FAIR data maturity model. A 95% pass was obtained for the measure of essential indicator of FAIRness, the measure of the important indicators resulted in an 85.71% pass and the measure of useful indicator of FAIRness resulted in a 57.14%. The performance evaluation result demonstrated a high-level compliance with the essential and important indicators. The findings of this study imply that an adaptable community-wide compliant FAIR data repository with the potential to catalyze collaboration, enhance data sharing, and contribute to the progress of scientific research on a global scale is deployable.
Keywords
Data managementFAIR principlesFAIR data pointFAIR data repositoryOpen
Science
References
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