The State of Open Data survey has been capturing researchers’ attitudes and experiences with open data since 2016. The 2025 report celebrates its tenth year, with more insights and findings. Understanding how researchers feel about data sharing and open data mandates helps institutions design services, training and infrastructure that genuinely match researchers’ needs and behaviours. By grounding policy and support in these insights, institutions can promote stronger adoption and compliance. They can create an environment that empowers, rather than pressures, their researchers. In a special blog contribution, ϳԹ’s Ed Gerstner, Director, Research Environment Alliances, Academic Affairs, shares his thoughts on the 2025 report, and why he is (cautiously) hopeful that technology could push openness forward.
With the 2025 State of Open Data report, titled 'A decade of progress and challenges,' we mark 10 years of tracking how researchers think about and engage with open data. The annual reports on the survey results have become a key reference point for understanding the open data landscape. The 2025 report shows that we’ve come a long way in ten years, but we’ve still got a way to go.
The 10th anniversary report examines the current state of open data as reflected in the 2025 survey results, as well as how attitudes and practices have evolved over the past decade. It provides valuable insight into experiences of researchers with data sharing, their attitudes and practices. You’ll also find input from experts on related topics, from funder mandates to data sharing challenges and from recognition to reproducibility
“Looking back, data sharing is still woefully unrecognised by funders and institutions. Looking forward, technology has finally reached a point where it might be able to help.”
For institutions, this long-term view of researchers’ motivations and the challenges they face offers insights that help them better design the essential services they offer to their researchers. With evidence-based support and advocacy, institutional stakeholders are invaluable partners in fostering open, transparent and reproducible research.
Making data FAIR, without sufficient credit for time and effort
The 2025 State of Open Data report shows that researchers’ familiarity with the idea of FAIR data has dramatically improved (ensuring data are findable, accessible, interoperable, and reusable).
But while the proportion of researchers who are now familiar with the FAIR principles has increased substantially, the 2025 report finds that recognition for researchers who make their data FAIR, or even just open, has not. Two-thirds of respondents told us that they feel researchers still don’t receive sufficient credit for making their research data open. This misalignment between efforts and recognition is one of the most significant barriers to widespread adoption of data sharing.
Date sharing mandates: Compliance burden with no support?
This in itself isn’t news, and has been discussed often, including in previous State of Open Data reports. What is striking to see is the corresponding drop-in net support for national open data mandates.
In the first report in 2016, a clear majority of respondents told us that they strongly supported open data mandates. In 2025, that strong support has fallen to around 40%, and to less than a third in the United States. National or funder mandates can be powerful drivers of data sharing, by setting clear standards of the practice. But without resources, tools, and guidance to researchers, these mandates may be seen as burdening researchers with compliance without enough support.
Even so, support for mandates outweighs opposition when comparing the two groups, which is encouraging to see. Institutional stakeholders, from libraries and research offices to data support units, play a central role in helping researchers understand and meet data sharing mandates. Understanding the challenges researchers face when implementing these mandates enables institutional stakeholders to better support them, design relevant services, and advocate for meaningful institutional change.
The challenges of sharing data and doing it right
But even with the strongest will in the world, researchers have precious little time to share their data (which is why it is so important to understand what drives successful data sharing). Data sharing competes with the need to manage labs, write papers, chase research funds, teach undergrads, and much more besides doing actual research.
What’s more, . If research data is released without sufficient metadata, it has little value. Metadata is the information that tells others not just when, where, and by whom it was collected, but what it represents. Without metadata, the potential of shared data to be found and reused (the F and the R in FAIR) is limited.
The curation of data and the creation of metadata that enables it to be FAIR are specialist skills. If we require all researchers to be data scientists, it will cost much more than merely the investment in the construction and maintenance of digital infrastructure. The more time researchers spend making their data open, the less time they will have to spend doing research.
“How do you guide people to structure data in a way that others can use it? There is enormous capability, for example, in the academic librarian community that knows how to do these sorts of things well.” - Brian Nosek, Co-founder and Executive Director of the Center for Open Science and Psychology Professor at the University of Virginia, from the 2025 State of Open Data Report
Institutions can make the difference in supporting researchers with preparing high-quality datasets. The report identifies librarians as enablers of metadata, standards and licensing. Such institutional support can help researchers make their data available and accessible, thus promoting data sharing adoption and compliance.
AI supporting data sharing: The importance of maintaining trust
Recognition of researchers’ efforts to share data would be a first step. The support of data specialists would be even better. Short of both, it seems that technology might soon fill some of the gaps.
In the 2025 State of Open Data survey, a quarter of respondents told us that they were using artificial intelligence to help them create metadata. That’s a promising sign, but with a warning. Although AI can be used to help researchers manage data, it can also help dishonest actors generate fake data. Any incentives to share data need to be developed in a way that they don’t reward bad behaviour.
“AI empowers researchers to make their data FAIR, but it also allows for the generation of fraudulent data. Credit systems should promote the former and deter the latter.”
One of the greatest benefits of open data is the insight that can be gained by combining many datasets together. If the authenticity of any one of these data cannot be trusted, the value of the whole is lost. It’s critical then, that we develop ways to validate trust in the data that are shared.
Explore the full State of Open Data 2025 report to learn more about researchers’ views on data sharing and for expert insights on related topics, from funder mandates to data sharing challenges, and from recognition to reproducibility.
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