Open data sharing: What a decade of researcher insights tells us

Author: Christina Emery

Head of Thought Leadership Programmes

“Where’s the data?” is the official theme of the 2026 Love Data Week, which allows us the space to think about the role of sharing data in the research process. In honour of this important theme, this blog explores what we’ve learned over a decade of asking researchers about open data. Drawing on ten years of the annual State of Open Data survey, the anniversary report offers a unique window into researchers’ attitudes, practices, and experiences with open data sharing.   

Below, we unpack the key findings most relevant to you as a researcher: how the research culture has shifted, what hasn’t changed, and what it all means for your own research data practices (including tips for open data sharing!).

Research data are the files digital or physical outputs generated or analysed in your research, that are needed to understand and interpret your work. They can take many forms such as visualisations, notebooks, code, spreadsheets, and maps, amongst others. When you make your research data open, accessible, and reusable, they become ‘open data’.  

Whether your funder or institution has requested you share your data openly, or you’re preparing a data availability statement, choosing a repository, or wondering how AI fits into your workflow, the topic of open data has become part of the discourse and practice of academic research. 

Capturing researchers’ perspectives on open data, since 2016 

But data requirements alone don’t tell the whole story. The State of Open Data survey has been running annually since 2016, and has collected over 43,000 responses from more than 200 countries. It is one of the longest running surveys exploring how researchers themselves feel about making their research data open and what challenges they’re experiencing. These experiences reveal the real barriers, motivations, and cultural shifts shaping open science today. 

If you’ve ever wondered whether your peers are struggling with the same challenges, or whether your discipline or region is keeping pace, the State of Open Data 2025: A Decade of Progress and Challenges report offers clarity. 

Main insights from a decade of the State of Open Data survey  

Looking back across a decade of survey data, a few major trends stand out: 

• Awareness of open science principles has grown dramatically, especially around the FAIR principles (guidelines to improve the Findability, Accessibility, Interoperability, and Reuse of digital assets). 
• Support for open practices remains high, even as enthusiasm for mandates declines in some regions. 
• The “credit gap” persists, with most researchers still feeling under-recognised for sharing data. 
• AI has rapidly entered research workflows, aiding data collection, data processing, and metadata creation. 
• Disciplinary and regional differences remain significant, shaping how open data is adopted in practice. 

Together, these trends paint a picture of a research ecosystem that is maturing but is still uneven, and still grappling with structural and resources barriers. 

Key findings researchers should know in 2026 

1. Awareness is up but support alone isn’t enough 

One of the most striking long-term shifts is the rise in familiarity with the FAIR principles. When the survey first asked about FAIR in 2018, nearly 60% of researchers had never heard of them. By 2025, that number has dropped to just over 20%. 

This shift is visible across disciplines. Fields that once lagged behind such as Business, Chemistry, and Materials Science have seen some of the biggest gains. Engineering and Biology now report familiarity rates above 40%, signalling a move from passive awareness to active engagement. 

What this means for you: If you haven’t been already, now is the time for you to start exploring the FAIR principles and join your peers in following them. Whether you’re preparing a grant application, depositing data, or collaborating across teams, funders and institutions increasingly expect that you follow the FAIR principles in your research practice.  

2. Mandate fatigue is real 

Open data mandates are a requirement by a national body or research funder for researchers to make their data openly accessible. These mandates are expected to encourage data sharing. But support for national open data mandates has shifted unevenly across the globe. Whilst global support looks stable at first glance, regional patterns tell a more nuanced story. 

The countries with the steepest decline in support for national mandates were Australia (63.2% in 2016, to 27.4% in 2025) and Brazil (64.7% in 2016 and 39% in 2025). Meanwhile, India (59.8% in 2016 and 54.7% in 2025) remained stable. Why the divergence? The report suggests that early enthusiasm for mandates may fade when researchers encounter practical challenges, due to unclear guidance, inconsistent standards, or insufficient institutional support. 

What this means for you: If you feel overwhelmed by policy requirements, you’re not alone. Many researchers support openness in principle but struggle with the realities of compliance. This is a signal to institutions and funders: mandates must be paired with practical and discipline-specific support. 

3. Open practices are popular, but recognition is lagging 

Despite mixed feelings about mandates, researchers remained strongly supportive of open practices in 2025 (n=3,959): 

• 88% support open access 
• 81% support open data 
• 76% support open peer review 
• 59% support preprinting 

But enthusiasm doesn’t erase the biggest cultural barrier: the lack of recognition for data sharing. 

Since 2020, the survey has consistently shown that most researchers feel they receive too little credit for sharing data. While the gap has narrowed slightly, nearly 70% still said their efforts go unrecognised. 

This disconnect affects behaviour. When data sharing requires significant time, documentation, and expertise but yields little professional reward, it’s no surprise that uptake varies. 

What this means for you: If you’ve ever felt that preparing a dataset to share openly takes more effort than it’s worth, you’re in good company. But the landscape is shifting. More institutions are beginning to recognise datasets as research outputs, and community-driven initiatives are emerging to reward contributions more fairly. 

4. AI is becoming part of the data workflow 

AI adoption is one of the fastest-moving trends in this year’s report. Between 2024 and 2025: 

• Use of AI for data processing jumped from 22% to 32% 
• AI use for metadata creation rose from 16% to 25% 
• AI use for data collection increased from 17% to 24% 

At the same time, the proportion of researchers who were unaware of AI tools dropped sharply. 

AI is becoming a standard part of the research data landscape, but its impact depends on how it is combined with data expertise. When designed with clear intent and informed by disciplinary standards, AI can support FAIR data sharing by automating routine tasks like metadata creation and streamlining data preparation workflows. Rather than replacing expertise, well-designed AI tools embed it, pointing towards a future where data is more FAIR, more reusable, and more efficiently managed. 

What this means for you: AI is quickly becoming part of the standard research toolkit. Using AI can support you to share your data openly and make your data FAIR, by automating tasks like metadata creation and reducing time and effort needed to prepare data for sharing.  

What experts told us: Voices from the community 

Beyond the numbers, the report includes insights from researchers, librarians, and data experts around the world. Their perspectives shared the realities behind the trends. Several themes stand out: 

• Infrastructure matters but it must be localised 

Experts emphasised that global mandates don’t always translate into local practice. Regions like Africa and Asia are developing their own open infrastructure ecosystems, tailored to cultural and community needs. As Joy Owango, Founding Director of Training Centre in Communication (TCC Africa) states, “It's a good sign. We are now getting sovereignty of our research.” 

• Data quality is a growing concern 

As Melissa Haendel, PhD, FACMI, Sarah Graham Kenan Distinguished Professor at the University of North Carolina at Chapel Hill, shares, “data dumping grounds” have emerged in response to mandates: “People are sharing their data, but they're not necessarily making it reusable.” 

• Librarians and data stewards are essential 

Many researchers lack the time or expertise to prepare high-quality datasets. Brian Nosek, Co-founder and Executive Director of the Center for Open Science and Psychology Professor at the University of Virginia, stresses the importance of support: “The support that's really needed is: how does a researcher make it easy for another person to know their data as well as they do?” Librarians and data professionals can bridge this gap, but only if institutions invest in them.  

• Recognition must evolve 

From nano attributions to open research awards, experts highlighted creative ways to reward data contributions. These initiatives show what is possible when institutions take recognition seriously. However, without broader systemic support, cultural and behavioural change may remain limited. 

Five practical tips to improve your own data sharing 

To make your data more discoverable, reusable, and impactful: 

• Cite all data, used or generated, in your research correctly 
• Identify and share (where possible) the data that underpin your research  
• Process any sensitive data and share it appropriately 
• Write a Data Availability Statement  
• Consider publishing a data article 

Read the full report, State of Open Data 2025: A Decade of Progress and Challenges, and join the launch webinar on Wednesday, 11 February, at 3pm GMT.  

Related content

• Report: The State of Open Data 2025: A Decade  of Progress and Challenges 
• Supporting open science practices: Why share your research data? 
• Celebrating data: tips and suggestions to help you make the most of research data in Love Data Week

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