Abstract Despite the increasing availability of Open Science (OS) infrastructure and the rise in policies to change behaviour, OS practices are not yet the norm. While pioneering researchers are developing OS practices, the majority sticks to status quo. To transition to common practice, we must engage a critical proportion of the academic community. In this transition, OS Communities (OSCs) play a key role. OSCs are bottom-up learning groups of scholars that discuss OS within and across disciplines. They make OS knowledge more accessible and facilitate communication among scholars and policymakers. Over the past two years, eleven OSCs were founded at several Dutch university cities. In other countries, similar OSCs are starting up. In this article, we discuss the pivotal role OSCs play in the large-scale transition to OS. We emphasize that, despite the grassroot character of OSCs, support from universities is critical for OSCs to be viable, effective, and sustainable.

The biological sciences community is increasingly recognizing the value of open, reproducible and transparent research practices for science and society at large. Despite this recognition, many researchers fail to share their data and code publicly. This pattern may arise from knowledge barriers about how to archive data and code, concerns about its reuse, and misaligned career incentives. Here, we define, categorize and discuss barriers to data and code sharing that are relevant to many research fields. We explore how real and perceived barriers might be overcome or reframed in the light of the benefits relative to costs. By elucidating these barriers and the contexts in which they arise, we can take steps to mitigate them and align our actions with the goals of open science, both as individual scientists and as a scientific community.

Several movements have emerged related to the general idea of promoting ‘openness’ in science. Research councils are key institutions in bringing about changes proposed by these movements, as sponsors and facilitators of research. In this paper we identify the approaches used in Canada, the US and the UK to advance open science, as a step towards understanding how policy in this area is evolving. The findings highlight three broad patterns across the countries, showing that open science is supported not only be the activities of individual research councils, but also through government mandates and inter-council cooperation. These patterns involve efforts to create a digital infrastructure for open science, to foster open access, and to support open data initiatives.

Grand challenges related to the environment, human health, and sustainability confront science and society. Understanding and mitigating these challenges in a rapidly changing environment require data[1] to be FAIR (Findable, Accessible, Interoperable, and Reusable) and as open as possible on a global basis. Scientific discovery must not be impeded unnecessarily by fragmented and closed systems, and the stewardship of research data should avoid defaulting to the traditional, proprietary approach of scholarly publishing. Therefore, the adoption of new policies and principles, coordinated and implemented globally, is necessary for research data and the associated infrastructures, tools, services, and practices. The time to act on the basis of solid policies for research data is now. The Beijing Declaration is intended as a timely statement of core principles to encourage global cooperation, especially for public research data. It builds on and acknowledges the many national and international efforts that have been undertaken in the policy and technical spheres on a worldwide basis. These major contributions are listed in the Appendix. Several emergent global trends justify and precipitate this declaration of principles: Massive global challenges require multilateral and cross-disciplinary cooperation and the broad reuse of data to improve coherence concerning recent UN landmark agreements, such as the Paris Climate Agreement, the Sendai Framework for Disaster Risk Reduction, the Sustainable Development Goals (SDGs), the Convention on Biological Diversity, the Plant Treaty, the World Humanitarian Summit, and others. The comprehensive agendas for action provided by these agreements requires access to and reuse of all kinds of data. Research and problem-solving, especially addressing the SDG challenges, are increasingly complex and driven by ‘big data’, resulting in the need to combine and reuse very diverse data resources across multiple fields. This poses an enormous challenge in the interoperability of data and responsible stewardship, with full respect for privacy. Rapid advances in the technologies that generate and analyze data pose major challenges concerning data volume, harmonization, management, sharing, and reuse. At the same time, emerging technologies (including machine learning) offer new opportunities that require access to reusable data available in distributed, yet interoperable, international data resources. Changing norms and ethics encourage high-quality research through greater transparency, promote the reuse of data, and improve trustworthiness through the production of verifiable and reproducible research results. Increasing the openness of research data is efficient, improving the public return on investment, and generating positive externalities. Open Science initiatives are emerging globally, including in less economically developed countries. There consequently are opportunities for these countries to take advantage of technological developments to develop a greater share in scientific production. Without determined action, there is also a risk that the divide in scientific production will widen. In September 2019, CODATA and its Data Policy Committee convened in Beijing to discuss current data policy issues and developed a set of data policies adapted to the new Open Science paradigm. The Declaration proposed below is the result of that meeting and is now put forward for public review. [1] In the attached document we deliberately use the word data very broadly, to comprise data (stricto sensu) and the ecosystem of digital things that relate to data, including metadata, software and algorithms, as well as physical samples and analogue artefacts (and the digital representations and metadata relating to these things).

"We see a diverse, interconnected, open, professional and viable, developing OS ecosystem in Europe on solid ground; one that is worth investing in. At the same time, this developing ecosystem faces a range of issues that challenge its path to a more open and sustainable future." This is a core conclusion of this new SPARC Europe report; the work is a result of a recent in-depth survey of infrastructure and/or services that are part of the European Open Science infrastructure (OSI) landscape. Find the dataset here: 10.5281/zenodo.4153742