German funders' data sharing policies-A qualitative interview study.

BACKGROUND: Data sharing is commonly seen as beneficial for science but is not yet common practice. Research funding agencies are known to play a key role in promoting data sharing, but German funders' data sharing policies appear to lag behind in international comparison. This study aims to answer the question of how German data sharing experts inside and outside funding agencies perceive and evaluate German funders' data sharing policies and overall efforts to promote data sharing. METHODS: This study is based on sixteen guided expert interviews with representatives of German funders and German research data experts from stakeholder organisations, who shared their perceptions of German' funders efforts to promote data sharing. By applying the method of qualitative content analysis to our interview data, we categorise and describe noteworthy aspects of the German data sharing policy landscape and illustrate our findings with interview passages. RESULTS: We present our findings in five sections to distinguish our interviewees' perceptions on a) the status quo of German funders' data sharing policies, b) the role of funders in promoting data sharing, c) current and potential measures by funders to promote data sharing, d) general barriers to those measures, and e) the implementation of more binding data sharing requirements. DISCUSSION AND CONCLUSION: Although funders are perceived to be important promoters and facilitators of data sharing throughout our interviews, only few German funding agencies have data sharing policies in place. Several interviewees stated that funders could do more, for example by providing incentives for data sharing or by introducing more concrete policies. Our interviews suggest the academic freedom of grantees is widely perceived as an obstacle for German funders in introducing mandatory data sharing requirements. However, some interviewees stated that stricter data sharing requirements could be justified if data sharing is a part of good scientific practice.

What is data stewardship? Towards a comprehensive understanding.

Data stewardship is a term that is understood in heterogenous ways. In recent organisational developments and efforts to build infrastructures and hire professional staff for research data management in various scientific fields in Europe, data stewardship is understood as mainly aiming at optimising data management in line with the FAIR principles (findability, accessibility, interoperability, reusability) forpurposes of reuse in the interests of the scientific community and the public. In addition, especially in the health and biomedical sciences some understandings of data stewardship mainly focus on the responsibility to respect the informational rights of data subjects. Following on from these different understandings and from recent developments to include ever more stakeholders in data stewardship, we propose a comprehensive understanding of data stewardship. According to this comprehensive understanding, data stewardship includes responsibilities towards all pertinent stakeholders and to equally consider and respect their legitimate rights and interests in order to build and maintain an efficient, trusted and fair data ecosystem. We also point out some of the practical challenges implied in such a comprehensive understanding.

Neither carrots nor sticks? Challenges surrounding data sharing from the perspective of research funding agencies-A qualitative expert interview study.

BACKGROUND: Data Sharing is widely recognised as crucial for accelerating scientific research and improving its quality. However, data sharing is still not a common practice. Funding agencies tend to facilitate the sharing of research data by both providing incentives and requiring data sharing as part of their policies and conditions for awarding grants. The goal of our article is to answer the following question: What challenges do international funding agencies see when it comes to their own efforts to foster and implement data sharing through their policies? METHODS: We conducted a series of sixteen guideline-based expert interviews with representatives of leading international funding agencies. As contact persons for open science at their respective agencies, they offered their perspectives and experiences concerning their organisations' data sharing policies. We performed a qualitative content analysis of the interviews and categorised the challenges perceived by funding agencies. RESULTS: We identify and illustrate six challenges surrounding data sharing policies as perceived by leading funding agencies: The design of clear policies, monitoring of compliance, sanctions for non-compliance, incentives, support, and limitations for funders' own capabilities. However, our interviews also show how funders approach potential solutions to overcome these challenges, for example by coordinating with other agencies or adjusting grant evaluation metrics to incentivise data sharing. DISCUSSION AND CONCLUSION: Our interviews point to existing flaws in funders' data sharing policies, such as a lack of clarity, a lack of monitoring of funded researchers' data sharing behaviour, and a lack of incentives. A number of agencies could suggest potential solutions but often struggle with the overall complexity of data sharing and the implementation of these measures. Funders cannot solve each challenge by themselves, but they can play an active role and lead joint efforts towards a culture of data sharing.