Open Science – DigitalKoans

“Open Research Data Integration in Universities: How Data Stewards Adapt Global Policies to Local Contexts”

Global research policies, often driven by political agendas rather than academic expertise, generate pressure on local entities to conform to global standards. This is particularly the case for universities seeking international relevance, which must address Open Research Data (ORD) principles. Our study examines the strategic decisions that university boards must make in adopting ORD, and explores the developing role of data stewards as key facilitators in day-to-day data governance. Drawing on the first-hand experience of a professional data steward at a research-intensive Swiss university, we illustrate in four situations how power dynamics and knowledge gaps complicate the reconciliation of ORD ideals with local operational realities. In response, we advocate a strategic shift to an integrated data stewardship model. We also propose strategies to empower data stewards by increasing the visibility of ORD in research projects, promoting task flexibility, reducing bureaucratic constraints, and setting realistic, incremental goals. We further recommend adapting global terminology to local contexts, harmonizing processes, and proactively promoting ORD. Ultimately, our efforts emphasize the specificity of universities as expert organizations and complement traditional education and training initiatives. In this way, we aim to pave the way for a more effective and holistic implementation of ORD and ultimately other global policies.

https://doi.org/10.1002/asi.70034

“Adoption of Open Research Practices Exceeding Expectations”

New analysis of open research practices suggests that researchers are increasingly motivated to share their data by factors beyond policy mandates, such as enhanced visibility, impact, and collaboration. The investigation by Taylor & Francis and DataSeer found that over half of authors included a Data Availability Statement (DAS) in their journal article, explaining whether and how readers can access data, and a third of researchers in some disciplines openly shared their data. . . .

A key finding is that researchers are going beyond the minimum open research requirements of the journal they publish in. Given that not all journals currently mandate the inclusion of a DAS, the team expected around a third of articles would include one. In fact, they found that just over half of researchers (52%) had done so. Similarly, a third of researchers in some disciplines chose to openly share their research data regardless of the journal’s policy.

https://tinyurl.com/87sxrp9p

Paywall: “Strengthening Research Support: Scholarly Communication Training for Liaison Librarians”

The study involved creating 16 OARs tailored to specific academic disciplines, utilizing a combination of free and subscription resources to compile data on publishing practices and citation insights. Surveys conducted before and after the dissemination of the reports evaluated the impact on librarians’ knowledge and confidence levels. The findings suggest that developing scholarly communication literacy among liaison librarians can improve their confidence and effectiveness in supporting faculty publishing practices. The collaboration between liaison librarians and the Scholarly Communications Librarian is essential for fostering partnerships with faculty and enhancing the library’s role in research support.

https://tinyurl.com/2ufwxxre

"An Exploration of the Functionality and Usability of Open Research Platforms to Support Open Science "

This paper examines the user experience and functionality of four open research platforms – Zenodo, Figshare, OSF, and Authorea – to assess their utility in disseminating research outputs that are varied in form as well as academic discipline, and in facilitating collaboration on larger projects by multi-institutional groups. The researchers analysed the platforms’ community features, record creation processes (including metadata fields), search functionality, and analytics capabilities.

https://doi.org/10.5281/zenodo.111656135

| Research Data Publication and Citation Bibliography | Research Data Sharing and Reuse Bibliography | Research Data Curation and Management Bibliography | Digital Scholarship |

“A Comprehensive Review of Data Sharing Practices in Addiction Research: Trends, Challenges, and Future Directions”

Only 22.75 % of articles included a DSS [Data Sharing Statement], though this rose to 52 % by 2023. DSS inclusion was higher in clinical trials than cohort studies (24.49 % vs. 16.59 %), and more common in open access articles (24.36 %) than non-open access ones (19.55 %). Journals with both journal and publisher “Requires” policies had the highest inclusion rate (43.07 %). Logistic regression confirmed policy alignment as the strongest predictor of DSS presence.

https://doi.org/10.1016/j.drugalcdep.2025.112794

“Finding Common Ground: When Commercial and Non-Commercial Meet in Open Science”

At the Open Science FAIR 2025 at CERN, we convened a panel that many would have previously considered unlikely: bringing together voices from commercial publishing, open source foundations, research infrastructure organizations, and libraries to explore how seemingly opposing interests can find common ground. What emerged was a nuanced conversation about the reality of building sustainable open science ecosystems, one that requires us to move beyond simplistic “us versus them” narratives.

https://tinyurl.com/mzvt2n6s

“From Policy to Practice: Progress Towards Data- And Code-Sharing in Ecology and Evolution”

Data and code are essential for ensuring the credibility of scientific results and facilitating reproducibility, areas in which journal sharing policies play a crucial role. However, in ecology and evolution, we still do not know how widespread data- and code-sharing policies are, how accessible they are, and whether journals support data and code peer review. Here, we first assessed the clarity, strictness and timing of data- and code-sharing policies across 275 journals in ecology and evolution. Second, we assessed initial compliance to journal policies using submissions from two journals: Proceedings of the Royal Society B (Mar 2023–Feb 2024: n = 2340) and Ecology Letters (Jun 2021–Nov 2023: n = 571). Our results indicate the need for improvement: across 275 journals, 22.5% encouraged and 38.2% mandated data-sharing, while 26.6% encouraged and 26.9% mandated code-sharing. Journals that mandated data- or code-sharing typically required it for peer review (59.0% and 77.0%, respectively), which decreased when journals only encouraged sharing (40.3% and 24.7%, respectively). Our evaluation of policy compliance confirmed the important role of journals in increasing data- and code-sharing but also indicated the need for meaningful changes to enhance reproducibility. We provide seven recommendations to help improve data- and code-sharing, and policy compliance.

https://doi.org/10.1098/rspb.2025.1394

| Artificial Intelligence |
| Research Data Curation and Management Works |
| Digital Curation and Digital Preservation Works |
| Open Access Works |
| Digital Scholarship |

“What Is the Impact of Open Science Practice?”

For the first time, an international research team has conducted a comprehensive study covering an entire country and all disciplines. The authors, Giovanni Colavizza (Denmark), Lauren Cadwallader (United States) and Iain Hrynaszkiewicz (United States), chose to study France, a leading country in monitoring Open Science, and to use data from the French Open Science Monitor, that covers the entire country since 2018.

The study covers a considerable corpus of over 500,000 scientific articles. It reveals that each open science practice seems to be associated with an increase of the number of citations of the articles concerned. The results show that:

An article published in open access is linked to 8.6% increase in citations compared to an article that is not open access.

An article sharing source code is linked to 13.5% increase in citations.

An article sharing data is linked to 14.3% increase in citations.

An article published as a preprint is linked to 19% increase in citations.

These results vary considerably across disciplines and represent the average of diverse specific situations. For example, in medical research, data sharing is associated with a 34.9% increase in citations. In basic biology, publishing a preprint is associated with a 25.3% increase in citations. In the social sciences, sharing code related to a publication is associated with a 38% increase in citations.

https://tinyurl.com/2ernabx5

An Analysis of the Effects of Open Science Indicators on Citations in the French Open Science Monitor

“Causal Evidence of Racial and Institutional Biases in Accessing Paywalled Articles and Scientific Data”

Scientific progress fundamentally depends on researchers’ ability to access and build upon the work of others. Yet, a majority of published work remains behind expensive paywalls, limiting access to universities that can afford subscriptions. Furthermore, even when articles are accessible, the underlying datasets could be restricted, available only through a “reasonable request” to the authors. One way researchers could overcome these barriers is by relying on informal channels, such as emailing authors directly, to obtain paywalled articles or restricted datasets. However, whether these informal channels are hindered by racial and/or institutional biases remains unknown. Here, we combine qualitative semi-structured interviews, large-scale observational analysis, and two randomized audit experiments to examine racial and institutional disparities in access to scientific knowledge. Our analysis of 250 million articles reveals that researchers in the Global South cite paywalled papers and upon-request datasets at significantly lower rates than their Global North counterparts, and that these access gaps are associated with reduced knowledge breadth and scholarly impact. To interrogate the mechanisms underlying this phenomenon, we conduct two randomized email audit studies in which fictional PhD students differing in racial background and institutional affiliation request access to paywalled articles (N = 18,000) and datasets (N = 11,840). We find that racial identity more strongly predicts response rate to paywalled article requests compared to institutional affiliation, whereas institutional affiliation played a larger role in shaping access to datasets. These findings reveal how informal gatekeeping can perpetuate structural inequities in science, highlighting the need for stronger data-sharing mandates and more equitable open access policies.

https://arxiv.org/abs/2509.08299

“How a New Data Platform Sheds Light on Open Science Funding”

TSOSI is a data platform designed to make visible which organizations have financially supported which open infrastructures. In the current beta version, it includes data provided by five infrastructures—Directory of Open Access Journals (DOAJ), Directory of Open Access Books (DOAB), SciPost, PeerCommunityIn, and Open Scholarly Communication in the European Research Area for the Social Sciences and Humanities (OPERAS)—revealing a small segment of the open science funding landscape. Information about the financial support these infrastructures have received was already partly available on their websites—see, for example, the supporters’ webpage of the DOAJ—but TSOSI represents an important step forward. Instead of appearing fragmented on websites, encapsulated into webpages, and without identifiers, this information is now collected on a centralized data platform where it is structured and enriched with the two key identifiers—Research Organization Registry (ROR) and Wikidata. These identifiers then permit the collection of information about organizations, such as country, geographical location, Wikipedia description, and logos.

https://tinyurl.com/2fmdee54

AI Openness: A Primer for Policymakers

This paper explores the concept of openness in artificial intelligence (AI), including relevant terminology and how different degrees of openness can exist. It explains why the term “open source” – a term rooted in software – does not fully capture the complexities specific to AI. This paper analyses current trends in open-weight foundation models using experimental data, illustrating both their potential benefits and associated risks. It incorporates the concept of marginality to further inform this discussion. By presenting information clearly and concisely, the paper seeks to support policy discussions on how to balance the openness of generative AI foundation models with responsible governance.

https://tinyurl.com/mpva5s47

“Open Data in Social Sciences: Growth, Impact, and Equity in Data Paper Publishing ”

The rapid growth of data-driven research has elevated the prominence of data papers as a specialised scholarly publication format, which enhances data accessibility, transparency, and reproducibility in scientific research. This study provides a comprehensive analysis of peer-reviewed data papers in social science, examining their growth, scholarly impact, adoption trends, mandates, policies, and funding landscape across the globe. Results show a 36 % annual growth rate (R² = 0.865), with 83 % of data papers published after 2021, driven by open-access mandates, funding agency requirements, digital repositories and growing emphasis on open science. The United States and China dominate publication volume, while Switzerland and the UK lead in citation impact. Despite a weak but significant open-access citation advantage (r = 0.052, p < 0.001), 22.7 % of data papers remain uncited, reflecting a “citation paradox.” Altmetric data highlights societal impact through media mentions (46 %), policy influence (36 %), patents (9 %) and engagement across social media platforms (X, Facebook, etc). Collaboration and funding patterns reveal entrenched Global North-South disparities, with 75 % of publications and 78 % of collaborative strength concentrated in the Global North. Only 42.5 % of journals enforce FAIR principles, and 35 % address CARE compliance, highlighting policy inconsistencies. To advance equitable open science, the study recommends standardised ethical frameworks, equitable funding models, and institutional support for global south scholars.

https://tinyurl.com/bdhsu57t

“Open Science Falling Behind in the Era of Artificial Intelligence”

Generative Artificial Intelligence (AI) refers to a new generation of content generation technologies that emerged after the rise of Transformer architecture in 2017, characterized by its core technical features of “compute-intensive architecture, model-driven paradigm, and data closed-loop system” (Table 1). AI is accelerating scientific discoveries and reshaping the research process, propelling AI for science toward becoming a novel research paradigm. There is a pressing demand for open science due to these advancements, yet the development of open science lags considerably behind the AI era. This disparity arises from the loss of academic leadership and insufficient motivation to pursue openness within the industrial sector, which could hinder AI empowerment and scientific innovation. Effective intervention by the public sector and policymakers becomes crucial when the “invisible hand” fails.

https://doi.org/10.3389/frma.2025.1595824

“Research Data Management Services in Academic Libraries to Support the Research Data Life Cycle: A Systematic Review”

Academic libraries play an increasingly crucial role in providing services, information, education, and infrastructure support related to research data management (RDM). This systematic review aims to provide a comprehensive and critical analysis of the state of RDM services offered by academic libraries worldwide. Utilizing the systematic review methodology, the paper examines 89 empirical studies to answer four research questions: (1) the types of RDM services implemented by academic libraries; (2) what are the infrastructure, workflow, and resources used to support these services; (3) what are the reasons for implementing these RDM services; and (4) the effectiveness of these RDM services in supporting the research data life cycle, if any. This review highlights the critical reasons academic libraries provide RDM services and how they implemented these services through partnerships, infrastructure, and systems, and adapting to new workflows within the library. These findings also examine the balance between institutional contexts, researchers’ needs, and library resources required to provide these RDM services. By investigating these questions, the results will provide recommendations and guidance for academic libraries interested in implementing RDM services in their own library and institutional contexts.

https://doi.org/10.1002/asi.70008

“Bridging the Gap: Improving Data Sharing Practices in Surgical Research”

Of the 1094 articles, only 141 (12.89%) included DSS, with higher rates in clinical trials (18.05%) compared to cohort studies (5.20%). Studies funded by government or industry and open-access articles (18.95%) were more likely to include DSS. Journals with higher impact factors were more likely to comply. Thematic analysis revealed recurring issues of gatekeeping, conditional data access, and privacy concerns. Out of 96 corresponding authors contacted, only 18 shared data.

https://doi.org/10.1016/j.jss.2025.04.036

Paywall: “NIH-Funded Science Must Now Be Free to Read Instantly: What You Should Know”

From 1 July, researchers funded by the US National Institutes of Health (NIH) will be required to make their scientific papers available to read for free as soon as they are published in a peer-reviewed journal. . . .

Several publishers, including Elsevier and Springer Nature, require that papers published in closed-access journals remain available only to subscribers for an embargo period — 6 or 12 months, for instance — before they can be placed in repositories such as PubMed Central. . . .

These publishers might steer authors towards their OA journals (or the OA parts of their hybrid journals) to comply with the policy. .. .

“Authors should know that in advance, and if they don’t want to pay the APC, but still want to comply with the NIH policy, then they have to go somewhere else,” [Peter] Suber says.

https://tinyurl.com/5dbwzw9n

“How Are Us Institutions Putting Public Access Into Practice? Insights from Our ‘Reasonable Costs’ Institutional Research”

Today, we [Invest in Open Infrastructure] are releasing the results of this collaboration in three documents:

“Between the Memo and the Mandate: Institutional Perspectives on Public Access Readiness”: a summary of the survey responses, including which policies and practices institutions already have in place, and what units are responsible for different actions.

A packet of workflows, constructed in collaboration with colleagues at each institution, illustrating a variety of approaches to sponsored project administration for different institution sizes and types. . . .

“Preparing for Public Access: Mapping Institutional Workflows for Sponsored Research Success”: a full methodology and results summary from conducting the surveys and interviews and constructing the workflows. . . . This document also contains four appendices containing the text of each of the two surveys and two interviews.

https://tinyurl.com/bdzptfkk

Open Licensing Models in the Cultural Heritage Sector

This document reports on a study of open licensing practices among cultural heritage institutions (CHIs) carried out by researchers in the CREATe Centre at the University of Glasgow and the Centre for Archive Studies at the University of Liverpool. The purpose of this study – funded by Creative Commons – is to advance understanding of how open licensing is being used in CHIs in practice and to enable information sharing about potential strategies. The authors do not endorse any singular approach – the findings reflect responses by a wide range of institutions in their own local contexts

https://tinyurl.com/yck7necz

“‘It’s Messy and It’s Massive’: How Has the Open Science Debate Developed in the Post-COVID Era?”

he COVID-19 pandemic accelerated the global adoption of open science (OS) practices. However, as the pandemic subsides, the debate around OS continues to evolve. This study investigates how the pandemic has shaped the OS discourse and identifies key issues and challenges. Interviews were conducted with influential stakeholders across the research and publishing communities. The findings show that while many areas of debate remained constant, the ways in which they were discussed exposed underlying systemic challenges, which must be addressed if OS is to progress. These issues included the scope and definition of OS; regional variations in its implementation; the relationship between OS and fundamental questions of the purpose and practice of science; and the need to reform incentives and reward structures within the research system. A more complex understanding of OS is required, which takes into account the importance of equity and diversity and the challenges of implementing OS in different cultural and geographical contexts. The study emphasises the importance of shifting scientific culture to prioritise values such as quality, integrity, and openness, and reforming rewards structures to incentivise open practices.

https://doi.org/10.12688/f1000research.162577.1

“A Case Study: The Savings Potential Thanks to Fair Data in One Materials Science PhD Project”

The FAIR (Findable, Accessible, Interoperable, and Reusable) data principles have gained significant attention as a means to enhance data sharing, collaboration, and reuse across various domains. Here, we explore the potential benefits of implementing FAIR data practices within engineering projects, with a monetary focus in the German context, but by considering aspects which are relatively universal. By examining the FAIR-data aspect of a Materials Science and Engineering PhD project, it becomes evident that substantial cost savings can be achieved. The estimated savings are 2,600 Euros per year from the PhD project considered. This study underscores the importance of implementing FAIR data practices in engineering projects and highlights some significant economic benefits that can be derived from such initiatives. By embracing FAIR principles, organizations in the engineering sector can unlock the full potential of their data, optimize resource allocation, and drive innovation in a cost-effective manner.

https://arxiv.org/abs/2506.12043

“What Does ‘Open Research’ Mean for Qualitative Research?”

Open research methods are sweeping Higher Education institutions with promises of greater transparency, rigour and trustworthiness in research. However, as many of these methods (such as preregistration, data sharing and reproducible code) are derived from quantitative scientific methodologies and concerns, this creates dilemmas for qualitative researchers, especially those working with marginalised communities. Data sharing may not be possible where it endangers oppressed people, or where even storing such data places the researcher in danger. There are also questions about how relevant concepts like replicability are for research methods that focus on particular contexts, or whether preregistration is useful for ethnographic researchers whose “sample” and research questions change in the course of fieldwork.

https://tinyurl.com/45z29p9a

“Understanding and Improving Data Repurposing”

We live in an age of unprecedented opportunities to use existing data for tasks not anticipated when those data were collected, resulting in widespread data repurposing. This commentary defines and maps the scope of data repurposing to highlight its importance for organizations and society and the need to study data repurposing as a frontier of data management. We explain how repurposing differs from original data use and data reuse and then develop a framework for data repurposing consisting of concepts and activities for adapting existing data to new tasks. The framework and its implications are illustrated using two examples of repurposing, one in healthcare and one in citizen science. We conclude by suggesting opportunities for research to better understand data repurposing and enable more effective data repurposing practices.

https://www.arxiv.org/abs/2506.09073

“Data Curation: Introducing a Competency Framework for the Social Sciences”

Research data management includes more than the question how researchers handle their data. In the sense of the FAIR principles, it is also about the sustainable safeguarding and organized reusability of research data. For social science, data-intensive research, research data centers and their data curating staff are therefore becoming increasingly important: data curators usually take on curation-specific tasks such as data preparation, securing research data in suitable archival environments, ensuring data accessibility, and the related control of the conditions of data re-use by third parties. Hence, they are specialized in the entire data curation process and, in particular, take on tasks of archiving and providing research data for reuse. Although the standards of comprehensive research data management are becoming more and more specific, this trend has not yet arrived in the corresponding training and further education measures. As a result, there is a gap between the growing demands on data curators and the development of competencies in the field of research data management with a focus on data curation. The competency framework presented in this article is intended to help close this gap: based on a Data Curation Lifecycle Model, a competency framework has been developed to support the development of targeted training and continuing education programs in the field of data curation, the formulation of learning objectives, and the evaluation of the corresponding trainings. The article points out the necessity to advance the development of competencies for this field, illustrates the schematic substructure of the data curation lifecycle, describes the development as well as the central core elements of the presented competency framework and discusses its perspectives. Overall, this competence framework is aimed in particular at (future) data curators, or as a schematic basis for the training of the relevant personnel. The focus is primarily on the data-intensive discipline of social sciences, although large parts can certainly be adapted for other disciplines and the corresponding data curation. The competency framework and this companion article are thereby intended to assist in advancing the sustainable professionalization of the previously understudied competency field of data curation.

https://doi.org/10.2218/ijdc.v19i1.889

“Linking Data Citation to Repository Visibility: An Empirical Study”

In today’s data-driven research landscape, dataset visibility and accessibility play a crucial role in advancing scientific knowledge. At the same time, data citation is essential for maintaining academic integrity, acknowledging contributions, validating research outcomes, and fostering scientific reproducibility. As a critical link, it connects scholarly publications with the datasets that drive scientific progress. This study investigates whether repository visibility influences data citation rates. We hypothesize that repositories with higher visibility, as measured by search engine metrics, are associated with increased dataset citations. Using OpenAlex data and repository impact indicators (including the visibility index from Sistrix, the h-index of repositories, and citation metrics such as mean and median citations), we analyze datasets in Social Sciences and Economics to explore their relationship. Our findings suggest that datasets hosted on more visible web domains tend to receive more citations, with a positive correlation observed between web domain visibility and dataset citation counts, particularly for datasets with at least one citation. However, when analyzing domain-level citation metrics, such as the h-index, mean, and median citations, the correlations are inconsistent and weaker. While higher visibility domains tend to host datasets with greater citation impact, the distribution of citations across datasets varies significantly. These results suggest that while visibility plays a role in increasing citation counts, it is not the sole factor influencing dataset citation impact. Other elements, such as dataset quality, research trends, and disciplinary norms, also contribute significantly to citation patterns.

https://arxiv.org/abs/2506.09530

“A New Book From ACRL: The Open Science Cookbook; Open Access Edition Available”

“The Open Science Cookbook” provides a wide variety of lesson plans and learning activities for supporting collaborative, transparent, openly accessible, and reproducible research. In five sections, it has something for beginners to more advanced practitioners and for different audience sizes.

Program Development

Instruction

Outreach

Events

Collaborations and Partnerships . . . .

“The Open Science Cookbook” is available for purchase in print through the ALA Online Store and Amazon.com; by telephone order at (800) 621-2736 or (773) 702-7010; and as an open access edition.

https://tinyurl.com/569s7e46