Auteur/Author : Agnès Robin
Les données de la recherche scientifique sont actuellement soumises à un programme de standardisation technique (FAIR) dont l’objectif est d’en permettre la diffusion aux fins de réutilisation par le public (entreprises privées ou autre).
Cette politique, qui sans se confondre avec elle, converge avec celle dite de « science ouverte », s’articule autour d’un principe normatif conflictuel, selon lequel le résultats de la recherche (et donc les données) doivent être « aussi ouverts que possibles et pas plus fermés que nécessaire », obligeant alors les chercheurs, ingénieurs et documentalistes, éventuellement chargés de la gestion des données de la recherche, à procéder à une qualification juridique délicate des données.
URL : http://intelligibilite-numerique.numerev.com/index.php/numeros/n-1-2020/9-le-principe-d-ouverture-des-donnees-de-la-recherche-scientifique
Authors : Antti M. Rousi, Mikael Laakso
The practices for if and how scholarly journals instruct research data for published research to be shared is an area where a lot of changes have been happening as science policy moves towards facilitating open science, and subject-specific repositories and practices are established.
This study provides an analysis of the research data sharing policies of highly-cited journals in the fields of neuroscience, physics, and operations research as of May 2019. For these 120 journals, 40 journals per subject category, a unified policy coding framework was developed to capture the most central elements of each policy, i.e. what, when, and where research data is instructed to be shared.
The results affirm that considerable differences between research fields remain when it comes to policy existence, strength, and specificity. The findings revealed that one of the most important factors influencing the dimensions of what, where and when of research data policies was whether the journal’s scope included specific data types related to life sciences which have established methods of sharing through community-endorsed public repositories.
The findings surface the future research potential of approaching policy analysis on the publisher-level as well as on the journal-level. The collected data and coding framework is provided as open data to facilitate future research and journal policy monitoring.
DOI : https://doi.org/10.1007/s11192-020-03467-9
Authors : Maximilian Siebert, Jeanne Fabiola Gaba, Laura Caquelin, Henri Gouraud, Alain Dupuy, David Moher, Florian Naudet
To explore the implementation of the International Committee of Medical Journal Editors (ICMJE) data-sharing policy which came into force on 1 July 2018 by ICMJE-member journals and by ICMJE-affiliated journals declaring they follow the ICMJE recommendations.
A cross-sectional survey of data-sharing policies in 2018 on journal websites and in data-sharing statements in randomised controlled trials (RCTs).
ICMJE website; PubMed/Medline.
ICMJE-member journals and 489 ICMJE-affiliated journals that published an RCT in 2018, had an accessible online website and were not considered as predatory journals according to Beall’s list. One hundred RCTs for member journals and 100 RCTs for affiliated journals with a data-sharing policy, submitted after 1 July 2018.
Main outcome measures
The primary outcome for the policies was the existence of a data-sharing policy (explicit data-sharing policy, no data-sharing policy, policy merely referring to ICMJE recommendations) as reported on the journal website, especially in the instructions for authors.
For RCTs, our primary outcome was the intention to share individual participant data set out in the data-sharing statement.
Eight (out of 14; 57%) member journals had an explicit data-sharing policy on their website (three were more stringent than the ICMJE requirements, one was less demanding and four were compliant), five (35%) additional journals stated that they followed the ICMJE requirements, and one (8%) had no policy online. In RCTs published in these journals, there were data-sharing statements in 98 out of 100, with expressed intention to share individual patient data reaching 77 out of 100 (77%; 95% CI 67% to 85%).
One hundred and forty-five (out of 489) ICMJE-affiliated journals (30%; 26% to 34%) had an explicit data-sharing policy on their website (11 were more stringent than the ICMJE requirements, 85 were less demanding and 49 were compliant) and 276 (56%; 52% to 61%) merely referred to the ICMJE requirements.
In RCTs published in affiliated journals with an explicit data-sharing policy, data-sharing statements were rare (25%), and expressed intentions to share data were found in 22% (15% to 32%).
Authors : Thu-Mai Christian, Amanda Gooch, Todd Vision, Elizabeth Hull
Despite the increase in the number of journals issuing data policies requiring authors to make data underlying reporting findings publicly available, authors do not always do so, and when they do, the data do not always meet standards of quality that allow others to verify or extend published results.
This phenomenon suggests the need to consider the effectiveness of journal data policies to present and articulate transparency requirements, and how well they facilitate (or hinder) authors’ ability to produce and provide access to data, code, and associated materials that meet quality standards for computational reproducibility.
This article describes the results of a research study that examined the ability of journal-based data policies to: 1) effectively communicate transparency requirements to authors, and 2) enable authors to successfully meet policy requirements.
To do this, we conducted a mixed-methods study that examined individual data policies alongside editors’ and authors’ interpretation of policy requirements to answer the following research questions.
Survey responses from authors and editors along with results from a content analysis of data policies found discrepancies among editors’ assertion of data policy requirements, authors’ understanding of policy requirements, and the requirements stated in the policy language as written.
We offer explanations for these discrepancies and offer recommendations for improving authors’ understanding of policies and increasing the likelihood of policy compliance.
URL : Journal data policies: Exploring how the understanding of editors and authors corresponds to the policies themselves
DOI : https://doi.org/10.1371/journal.pone.0230281
Auteur/Author : Joachim Schöpfel
Dans le cadre du Plan national pour la science ouverte, la structuration et le partage des données de recherche font désormais partie des priorités de la politique scientifique de la France.
Chaque établissement et chaque organisme scientifique doit se doter d’une politique de la science ouverte et mettre en place un ensemble de services et dispositifs pour la gestion des données de la recherche.
A partir d’enquêtes sur le terrain, l’article propose une feuille de route pour la mise en œuvre d’une telle politique sur un campus universitaire en sciences humaines et sociales.
Dix principes indiquent des pistes pour la gouvernance et le pilotage de cette politique, pour déterminer les priorités de développement et d’investissements, et pour faire le lien avec les infrastructures de recherche, dont notamment Huma-Num.
Il s’agit d’une démarche bottom-up, qui met l’accent sur les pratiques et besoins des chercheurs et qui place les chercheurs au cœur d’une politique institutionnelle dans le domaine des données de recherche.
URL : https://www.openscience.fr/Penser-local
Authors : Tom Willaert, Jacob Cottyn, Ulrike Kenens, Thomas Vandendriessche, Demmy Verbeke, Roxanne Wyns
This case study critically examines ongoing developments in contemporary scholarship through the lens of research data management support at KU Leuven, and KU Leuven Libraries in particular.
By means of case-based examples, current initiatives for fostering sound scientific work and scholarship are considered in three associated domains: support for policy-making, the development of research infrastructures, and digital literacy training for students, scientists and scholars.
It is outlined how KU Leuven Libraries collaborates with partner services in order to contribute to KU Leuven’s research data management support network. Particular attention is devoted to the innovations that facilitate such collaborations.
These accounts of initial experiences form the basis for a reflection on best practices and pitfalls, and foreground a number of pertinent challenges facing the domain of research data management, including matters of scalability, technology acceptance and adoption, and methods for effectively gauging and communicating the manifold transformations of science and scholarship.
URL : Research data management and the evolutions of scholarship: policy, infrastructure and data literacy at KU Leuven
DOI : http://doi.org/10.18352/lq.10272
Authors : Iain Hrynaszkiewicz, Natasha Simons, Azhar Hussain, Simon Goudie
More journals and publishers – and funding agencies and institutions – are introducing research data policies. But as the prevalence of policies increases, there is potential to confuse researchers and support staff with numerous or conflicting policy requirements.
We define and describe 14 features of journal research data policies and arrange these into a set of six standard policy types or tiers, which can be adopted by journals and publishers to promote data sharing in a way that encourages good practice and is appropriate for their audience’s perceived needs.
Policy features include coverage of topics such as data citation, data repositories, data availability statements, data standards and formats, and peer review of research data.
These policy features and types have been created by reviewing the policies of multiple scholarly publishers, which collectively publish more than 10,000 journals, and through discussions and consensus building with multiple stakeholders in research data policy via the Data Policy Standardisation and Implementation Interest Group of the Research Data Alliance.
Implementation guidelines for the standard research data policies for journals and publishers are also provided, along with template policy texts which can be implemented by journals in their Information for Authors and publishing workflows.
We conclude with a call for collaboration across the scholarly publishing and wider research community to drive further implementation and adoption of consistent research data policies.
URL : Developing a research data policy framework for all journals and publishers
Alternative location : https://figshare.com/articles/Developing_a_research_data_policy_framework_for_all_journals_and_publishers/8223365/1