2025/01/20 by Claude Pellen, Nchangwi Syntia Munung, Anna Catharina Vieira Armond +4 · 1 voice
Computer Science · Medicine · #Artificial Intelligence in Healthcare and Education #Ethics in Clinical Research #Research Data Management Practices
paper · pdf · doi:10.1016/j.jclinepi.2025.111680
openalex publication_date 2025/01/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Guided by the FAIR principles (Findable, Accessible, Interoperable, Reusable), responsible data sharing requires well-organized, high-quality datasets. However, researchers often struggle with implementing Data Management and Sharing Plans due to lack of knowledge on how to do this, time constraints, and legal, technical, and financial challenges, particularly concerning data ownership and privacy. While patients support data sharing, researchers and funders may hesitate, fearing the loss of intellectual property or competitive advantage. Although some journals and institutions encourage or mandate data sharing, further progress is needed. Additionally, global solutions are vital to ensure equitable participation from low- and middle-income countries. Ultimately, responsible data sharing requires strategic planning, cultural shifts in research, and coordinated efforts from all stakeholders to become standard practice in biomedical research.