Exploring Motivations, Challenges, and Practices in Research Data Sharing Across Disciplines

Research data sharing and management are vital for transparency and innovation in science. Despite its importance, challenges like privacy concerns, intellectual property issues, and lack of standardized practices vary across disciplines. Health sciences face privacy barriers, while digital humanities in Thailand struggle with copyright issues. STEM fields show higher data reuse than humanities and social sciences. Although frameworks like the FAIR principles exist, comprehensive investigations into data-sharing behaviors and effective strategies are needed. This Research Topic explores motivations, challenges, and practices in data sharing across disciplines, focusing on institutional policies and their impact on scientific progress.As data becomes increasingly central to research practice, understanding how and why researchers share, or withhold, their data is essential to advancing open, collaborative, and impactful science. Despite the existence of frameworks like FAIR (Findable, Accessible, Interoperable, Reusable), actual practices remain fragmented, with significant variation between disciplines, institutions, and regions.In many STEM fields, open data is encouraged through well-established norms and infrastructure. In contrast, researchers in the humanities, social sciences, and digital humanities often face distinct obstacles, including concerns over copyright, lack of repositories suited to qualitative data, and ethical sensitivities tied to cultural or contextual materials. These differences call for nuanced, evidence-based studies into the motivations, incentives, and barriers that shape data-sharing practices across fields.This Research Topic aims to explore:• Why researchers choose to share or withhold data• What institutional, cultural, or disciplinary factors influence those decisions• How policies, infrastructure, and research evaluation systems support or constrain data sharing• What practices, tools, or frameworks improve responsible and effective data management• How cross-disciplinary comparisons can reveal transferable lessons and scalable strategiesWe particularly welcome submissions that offer:• Empirical studies of data-sharing behavior within or across disciplines• Policy analyses that evaluate institutional or national strategies for data openness• Case studies exploring successful (or failed) implementation of open data initiatives• Conceptual contributions that advance our understanding of strategic data governance• Insights into the evolving role of data in team science, interdisciplinary research, and R&D program managementWe invite original research articles, reviews, and policy-focused papers that critically engage with the evolving landscape of research data sharing. Topic editors: Sanhong Deng, Chongwu Bi, Chenglong Li Source: https://www.frontiersin.org/research-topics/76317/exploring-motivations-challenges-and-practices-in-research-data-sharing-across-disciplines