Research funders have increasingly required a data management and sharing plan as part of their application processes. They tend to encourage maximal sharing, sometimes requiring it. Funders allow inclusion of the resources required to implement a DMS plan in grant budgets. Submitted plans are typically reviewed by agency staff and occasionally peer-reviewers. Grant awardees are expected to demonstrate compliance at regular reporting periods.
The Open Research Funders Group (ORFG) is a partnership of funding organizations committed to the open sharing of research outputs. This will benefit society by accelerating the pace of discovery, reducing information-sharing gaps, encouraging innovation, and promoting reproducibility. The ORFG speaks in an amplified voice, and engages a range of stakeholders to develop actionable principles and policies that enable sharing and collaboration across the global research enterprise.
Journals and journal editors increasingly recognize their role in good data management and sharing practices. Biomedical journals are more likely to have data quality and sharing policies than other disciplines. The largest and most prestigious journals have the most robust policies.
Journals' work in this area is ongoing. For example, nearly 33% of the journals in a 2017 study by Vasilevsky et al. explicitly encouraged data sharing, and 12% required it as a condition of publication.
Figure 1: Percentage of journals per each data sharing mark (DSM).
(A) shows the percentage of all journals for each data sharing mark. (B) shows the percentage of citable items from each journal (including PLOS ONE) for each data sharing mark. (C) shows the percentage of citable items for each journal (excluding PLOS ONE) for each data sharing mark. Because of the journal PLOS ONE's high publishing activity, we analyzed the percentage of citable items for each data sharing mark including and excluding PLOS ONE.
Ad-hoc and formal disciplinary communities have been some of the strongest advocates of data management and sharing. For example, the FAIR data principles were created by members of FORCE11, a multi-disciplinary community interested in improving research communication. Multiple domain communities have issued and advocated for data and experiment specific DMS guidelines.
