Étiquette : research data

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EN

Data Availability Statements in Mega Journals: A Comparative Analysis of Global and Korea-Affiliated Publications in Health and Medical Research

Authors : Sanghee Oh, Yunseo Park, Seyun Sim

Data Availability Statements (DAS) have become a standard mechanism for promoting transparency and reproducibility in open-access mega journals, yet questions remain about how effectively they support meaningful data sharing in practice and how these practices vary across national research contexts.

This study examines data-sharing practices in the medical and health sciences through a comparative analysis of global publications and Korea-affiliated articles in three mega journals indexed in PubMed Central: PLOS ONE, Scientific Reports and BMJ Open (2020–2024). DAS from 176,145 articles were collected from PubMed Central using an automated pipeline with manual validation and classified into a seven-category typology reflecting levels of data accessibility and reuse.

Results indicate that although DAS inclusion increased over time, repository-based data sharing remains limited, while ‘data available upon request’ continues to be prevalent. Clear differences are observed across journals: PLOS ONE shows greater use of repository-based and in-article sharing, whereas Scientific Reports and BMJ Open rely more heavily on ‘data available upon request’. Korea-affiliated articles largely follow global trends, with slightly greater reliance on national public data repositories.

Repository use is concentrated among a small number of international multidisciplinary platforms and selected national biomedical databases. The findings reveal a persistent gap between formal DAS compliance and effective data accessibility, indicating the need for clearer, more actionable data-sharing guidance.

URL : Data Availability Statements in Mega Journals: A Comparative Analysis of Global and Korea-Affiliated Publications in Health and Medical Research

DOI : https://doi.org/10.1002/leap.2083

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FR

Pratiques de gestion et de partage des données de recherche. Retour d’expérience de quatre projets SHS lauréats du Prix Science Ouverte 2025

Auteur/Author : Joachim Schöpfel

Cet article propose une étude comparative de quatre projets de recherche lauréats du Prix Science Ouverte 2025 issus des sciences humaines et sociales (humanités numériques, linguistique, sociologie quantitative et longitudinale), en se concentrant sur leurs pratiques de gestion des données de recherche.

À partir d’entretiens qualitatifs, l’étude examine les types de données produites, les modalités de gestion, les responsabilités, ainsi que les stratégies de partage et de valorisation. L’analyse est structurée selon les principes FAIR (Findable, Accessible, Interoperable, Reusable). Les résultats mettent en évidence une forte hétérogénéité des pratiques, mais aussi une convergence vers une professionnalisation accrue de la gestion des données et une intégration progressive des exigences de la science ouverte.

Une attention particulière est accordée à l’impact du Prix Science Ouverte des Données de la Recherche, dont les effets se manifestent principalement en termes de reconnaissance, de visibilité et de consolidation des pratiques.

URL : https://lilloa.hal.science/hal-05634994v2

Catégories
EN

Modeling the impact of research data unavailability on science

Authors : Jorge Chamorro-Padial, Francisco-Javier Rodrigo-Ginés, Rosa Rodrí­guez-Sánchez, R.M. Gil, Roberto García

Scientific progress depends on the accessibility and reproducibility of research outputs. Unfortunately, datasets and other referenced resources in academic publications frequently become unavailable over time, limiting reproducibility and reuse.

In this work, we quantitatively analyze the potential impact of research data unavailability by applying economic, probabilistic, and network based models to scientific citation networks. Rather than measuring knowledge directly, we use citation based network metrics as proxies for the dissemination and potential reuse of scientific results, and study how the absence of data-linked resources affects impact propagation and productivity-related indicators.

We further examine the resilience of citation networks under different modeling assumptions and analyze the role of highly influential nodes, or superpropagators, in amplifying the effects of dataset loss.

Our results reveal structural dependencies on vulnerable data sources and show that the magnitude of the impact depends strongly on network position and model assumptions.

These findings provide quantitative evidence of the systemic consequences of data unavailability and underline the importance of long-term data preservation and accessibility policies in scientific research.

URL : Modeling the impact of research data unavailability on science

DOI : https://doi.org/10.1016/j.joi.2026.101813

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EN

PreprintToPaper dataset: connecting bioRxiv preprints with journal publications

Autors : Fidan Badalova, Julian Sienkiewicz, Philipp Mayr

The PreprintToPaper dataset connects bioRxiv preprints with their corresponding journal publications, enabling large-scale analysis of the preprint-to-publication process. It comprises metadata for 145,517 preprints from two periods, 2016–2018 (pre-pandemic) and 2020–2022 (pandemic), retrieved via the bioRxiv and Crossref APIs.

We selected the two periods to capture preprint-publication dynamics before and during the COVID-19 pandemic while avoiding transitional years. Each record includes bibliographic information such as titles, abstracts, authors, institutions, submission dates, licenses, and subject categories, alongside enriched publication metadata including journal names, publication dates, author lists, and further information.

In addition to the main dataset, a version-history subset provides all available versions of preprints within the two selected periods, enabling analysis of how preprints evolve over time. Preprints are categorized into three groups: Published (formally linked to a journal article), Preprint Only (posted on a preprint server), and Gray Zone (potentially published in a journal but unlinked).

To enhance reliability, title and author similarity scores were computed, and a human-annotated subset of 299 records was created to evaluate Gray Zone cases. The dataset supports diverse applications, including studies of scholarly communication, open science policies, bibliometric tool development, and natural language processing research on textual changes between preprints and their corresponding journal articles.

URL : PreprintToPaper dataset: connecting bioRxiv preprints with journal publications

DOI : https://doi.org/10.1038/s41597-026-06867-3

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EN

Evaluating the efficacy and impact of a pilot programme for FAIR data stewardship at a UK university

Authors : Zuzanna Zagrodzka, Jenni Adam, Richard Campbell, Helen Foster

Increasingly, funders, publishers, and institutions expect researchers to comply with the FAIR principles to ensure that data is findable, accessible, interoperable, and reusable. In an institutional context, however, questions remain as to how organisations can move beyond a broad commitment to FAIR, coupled with support for researchers to comply nominally with related grant conditions, to a more embedded and sustainable approach with a meaningful and pervasive impact on the FAIRness of research outputs.

A data stewardship model offers one way to achieve this, yet in contrast to universities in mainland Europe and especially in the Netherlands, the UK is substantially lacking in such infrastructure at an institutional level, hampering efforts to evidence its potential impact within UK institutions and thereby advocate for its adoption.

This article examines efforts to address this challenge via a recent project at the University of Sheffield to establish a pilot support service around FAIR data stewardship. It also provides a case study of how the benefits and impact of such an intervention might be identified and articulated through an evidence-led evaluation.

URL : Evaluating the efficacy and impact of a pilot programme for FAIR data stewardship at a UK university 

DOI : https://doi.org/10.2218/ijdc.v19i1.1035

Catégories
EN

Research Data: A Public Good or a Private Asset?

Authors : Tadeu Fernando Nogueira, Trude Eikebrokk, Laila Økdal Aksetøy

This article is concerned with the issue of how Research Performing Organizations can balance the market and non-market values of the research data they hold. To address this issue, we adopt the lenses of the Resource Based View and Open Science and explore the interplay between them.

In doing so, this article addresses the question of whether it is possible to achieve a balance between research data as a public good and as a private asset and if so, how. Of particular interest are Research Performing Organizations in the institute sector that operate under both market and non-market logics, which have implications for how they govern their research data.

From the discussions undertaken in the article, one of the main conclusions is that Research Performing Organizations may benefit from adopting a research data governance model that captures both the economic and societal values of research data.

They could do so, for instance, by developing an integrative institutional policy and by actively using data management plans to evaluate the value of the data produced in research projects.

URL : Research Data: A Public Good or a Private Asset?

DOI : https://doi.org/10.53377/lq.22604

 

Catégories
EN

Making Reproducibility a Reality by 2035? Enabling Publisher Collaboration for Enhanced Data Policy Enforcement

Authors : Rebecca Taylor-Grant, Matthew Cannon, Allyson Lister, Susanna-Assunta Sansone

This paper describes a project which identified practical and pragmatic ways to increase the FAIRness and reproducibility of published research. Academic journals have supported Open Science through the implementation of data sharing policies for over ten years; some evidence has since emerged on the additional time, resources and expertise that policy enforcement requires as part of an editorial workflow.

A series of publisher workshops facilitated by the EC-funded TIER2 project aimed to identify the key checks needed to enforce strengthened journal data sharing policies and to understand which editorial roles have the capacity to undertake such enforcement. The intended outcome of this work was to establish the workflows and resourcing which can support academic journals to enforce stronger data sharing policies in future.

URL : Making Reproducibility a Reality by 2035? Enabling Publisher Collaboration for Enhanced Data Policy Enforcement

DOI : https://doi.org/10.2218/ijdc.v19i1.1064