Journal data policies: Exploring how the understanding of editors and authors corresponds to the policies themselves

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


Penser local. Développer une politique de données sur un campus SHS

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.


Research data management and the evolutions of scholarship: policy, infrastructure and data literacy at KU Leuven

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


Developing a research data policy framework for all journals and publishers

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

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Is Open Access to Research Data a Strategic Priority of Czech Universities?

Author : Jakub Novotný

Open access to research data is one of the key themes of current science development concepts and relevant R & D strategies at least in Europe. A systemic change in the modus operandi of science and research should lead to so-called Open Science.

The presented paper questions the extent to which the Open Science concept is reflected in the strategies of Czech universities. The paper first describes basic idea of Open Access to Research Data including principles of „FAIR data” as one of the key assumption of it.

After a brief characterization of the Czech university sector, the results of the empirical analysis of the inclusion of the Open Access to Research Data concept in the current strategic plans of the Czech universities are presented.

The conclusion of the paper is then an evaluation of the results, which reveal an underestimation of the Open Science concept in the current strategic plans of the Czech universities.

URL : Is Open Access to Research Data a Strategic Priority of Czech Universities?


The History, Advocacy and Efficacy of Data Management Plans

Authors : Nicholas Smale, Kathryn Unsworth, Gareth Denyer, Daniel Barr

Data management plans (DMPs) have increasingly been encouraged as a key component of institutional and funding body policy. Although DMPs necessarily place administrative burden on researchers, proponents claim that DMPs have myriad benefits, including enhanced research data quality, increased rates of data sharing, and institutional planning and compliance benefits.

In this manuscript, we explore the international history of DMPs and describe institutional and funding body DMP policy. We find that economic and societal benefits from presumed increased rates of data sharing was the original driver of mandating DMPs by funding bodies.

Today, 86% of UK Research Councils and 63% of US funding bodies require submission of a DMP with funding applications. Given that no major Australian funding bodies require DMP submission, it is of note that 37% of Australian universities have taken the initiative to internally mandate DMPs.

Institutions both within Australia and internationally frequently promote the professional benefits of DMP use, and endorse DMPs as ‘best practice’. We analyse one such typical DMP implementation at a major Australian institution, finding that DMPs have low levels of apparent translational value.

Indeed, an extensive literature review suggests there is very limited published systematic evidence that DMP use has any tangible benefit for researchers, institutions or funding bodies.

We are therefore led to question why DMPs have become the go-to tool for research data professionals and advocates of good data practice. By delineating multiple use-cases and highlighting the need for DMPs to be fit for intended purpose, we question the view that a good DMP is necessarily that which encompasses the entire data lifecycle of a project.

Finally, we summarise recent developments in the DMP landscape, and note a positive shift towards evidence-based research management through more researcher-centric, educative, and integrated DMP services.

URL : The History, Advocacy and Efficacy of Data Management Plans


Sharing health research data – the role of funders in improving the impact

Authors : Robert F. Terry, Katherine Littler, Piero L. Olliaro

Recent public health emergencies with outbreaks of influenza, Ebola and Zika revealed that the mechanisms for sharing research data are neither being used, or adequate for the purpose, particularly where data needs to be shared rapidly.

A review of research papers, including completed clinical trials related to priority pathogens, found only 31% (98 out of 319 published papers, excluding case studies) provided access to all the data underlying the paper – 65% of these papers give no information on how to find or access the data.

Only two clinical trials out of 58 on interventions for WHO priority pathogens provided any link in their registry entry to the background data.

Interviews with researchers revealed a reluctance to share data included a lack of confidence in the utility of the data; an absence of academic-incentives for rapid dissemination that prevents subsequent publication and a disconnect between those who are collecting the data and those who wish to use it quickly.

The role of the funders of research needs to change to address this. Funders need to engage early with the researchers and related stakeholders to understand their concerns and work harder to define the more explicitly the benefits to all stakeholders.

Secondly, there needs to be a direct benefit to sharing data that is directly relevant to those people that collect and curate the data.

Thirdly more work needs to be done to realise the intent of making data sharing resources more equitable, ethical and efficient.

Finally, a checklist of the issues that need to be addressed when designing new or revising existing data sharing resources should be created. This checklist would highlight the technical, cultural and ethical issues that need to be considered and point to examples of emerging good practice that can be used to address them.

URL : Sharing health research data – the role of funders in improving the impact