2024 Volume 34 Issue 4 Pages 353-356
The global movement toward open science is accelerating, with a focus on worldwide knowledge sharing. Researchers receiving public funding must manage and utilize research data under funder policies and the "open-and-close" strategy. This strategy seeks to balance international contributions with national interests, ensuring that research outcomes benefit both the global community and the home country. The responsibilities of researchers regarding research outputs, including research data, are on the rise, such as creating and implementing Data Management Plans in publicly funded projects and immediate open access to papers and evidence data. Given these increasing demands, infrastructure is critical to support researchers in managing, analyzing, sharing, and publishing research data. Effective data management practices are essential for reducing researchers' workload, allowing them to focus on their scientific contributions. This research presents the Comprehensive Pre-symptomatic Database Project as a case study, which aims to share, analyze, and publish experimental data, clinical data, and mathematical analysis data derived from mathematical analysis based on these datasets used in medicalmathematical collaborative research. This research outlines the challenges related to metadata processing in managing, sharing, analyzing, and publishing research data and discusses the necessary functionalities.
