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Evaluating and Enhancing FAIR Compliance in Data Resource Portal DevelopmentYiqing Qu (18437745) 01 May 2024 (has links)
<p dir="ltr">There is a critical need for improvement in scientific data management when the big-data era arrives. Motivated by the evolution and significance of FAIR principles in contemporary research, the study focuses on the development and evaluation of a FAIR-compliant data resource portal. The challenge lies in translating the abstract FAIR principles into actionable, technological implementations and the evaluation. After baseline selection, the study aims to benchmark standards and outperform existing FAIR compliant data resource portals. The proposed approach includes an assessment of existing portals, the interpretation of FAIR principles into practical considerations, and the integration of modern technologies for the implementation. With a FAIR-ness evaluation framework designed and applied to the implementation, this study evaluated and improved the FAIR-compliance of data resource portal. Specifically, the study identified the need for improved persistent identifiers, comprehensive descriptive metadata, enhanced metadata access methods and adherence to community standards and formats. The evaluation of the FAIR-compliant data resource portal with FAIR implementation, showed a significant improvement in FAIR compliance, and eventually enhanced data discoverability, usability, and overall management in academic research.</p>
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