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The preprint movement, once seen as a pragmatic, low-cost, researcher-driven route to openness, now faces its own moment of uncertainty.
As AI systems increasingly reason from the scientific literature, the integrity signals that make research trustworthy - open data, structured metadata, robust retraction processes - matter more than ever.
Advances in agentic AI combined with increasingly large reserves of openly accessibly and machine-readable data are creating a perfect storm for the mass-production of AI authored research papers.
Executive summary of an independent study on the economic benefits of open science, showing how sharing research outputs enables reuse, improves efficiency, and supports innovation.
The 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.
Is open scholarship an honest signal of researcher integrity? Preliminary evidence suggests that data and code sharing, preprinting, and other open behaviors are indeed less common in papermill articles.
It’s hard to measure social and economic impacts of making papers and data free, researchers say.
This year’s Open Science Conference was dedicated entirely to Open Science and AI. Participants examined both the opportunities and the challenges at this intersection, exploring how to responsibly integrate AI into research processes and, conversely, how to build trustworthy AI on trustworthy data.
The current relationship between researchers, funders and commercial publishers has created a “drain” – depriving the research system of money, time, trust and control.
While Open Science infrastructures are used a lot, their funding is precarious. TSOSI is a project that aims to improve this situation by making financial support for open infrastructure more visible.
Academic freedom and the autonomy of science require protection not only against direct state interference, but also against the more subtle colonisation of research by political and economic systems.
What does Open Access promise and what does it cost? How can the crucial importance of open infrastructures be embedded as a collective core task? What could a new concept for financing Diamond Open Access look like? At the Open Access Days 2025, these and other questions were answered in lectures and workshops.
Experts call for African-led platforms and pooled funding to protect scientific visibility.
Responding to early-career researchers' honest questions with accusations of misconduct is a travesty of open science.
In this interview with Peter Suber, the Senior Advisor on Open Access at Harvard Library and Director of the Harvard Open Access Project at the Berkman Klein Center discusses the current alarming developments taking place in the US research landscape – and offers valuable advice to colleagues from abroad.
To create a research culture that makes the best use of available data, the FAIR principles need to be extended
Measures intended to encourage openness are clashing with efforts to reform assessment
As more of the research process is exposed, the readiness and resources of researchers and their institutions must be considered
As a recent consultation on how to monitor open science practices draws to a close, it is argued that if monitoring frameworks aim to capture the widest dimensions of open science as a practice they should include case studies.
A recent work outlines seven kinds of research data misuse and provide recommendations.
