Étiquette : research data policies

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

DOI : http://doi.org/10.18352/lq.10272

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

Alternative location : https://figshare.com/articles/Developing_a_research_data_policy_framework_for_all_journals_and_publishers/8223365/1

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?

DOI : https://doi.org/10.2478/ijicte-2018-0008

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

DOI : https://doi.org/10.1101/443499

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

DOI : http://dx.doi.org/10.12688/f1000research.16523.1

The Changing Influence of Journal Data Sharing Policies on Local RDM Practices

Authors : Dylanne Dearborn, Steve Marks, Leanne Trimble

The purpose of this study was to examine changes in research data deposit policies of highly ranked journals in the physical and applied sciences between 2014 and 2016, as well as to develop an approach to examining the institutional impact of deposit requirements.

Policies from the top ten journals (ranked by impact factor from the Journal Citation Reports) were examined in 2014 and again in 2016 in order to determine if data deposits were required or recommended, and which methods of deposit were listed as options.

For all 2016 journals with a required data deposit policy, publication information (2009-2015) for the University of Toronto was pulled from Scopus and departmental affiliation was determined for each article.

The results showed that the number of high-impact journals in the physical and applied sciences requiring data deposit is growing. In 2014, 71.2% of journals had no policy, 14.7% had a recommended policy, and 13.9% had a required policy (n=836).

In contrast, in 2016, there were 58.5% with no policy, 19.4% with a recommended policy, and 22.0% with a required policy (n=880). It was also evident that U of T chemistry researchers are by far the most heavily affected by these journal data deposit requirements, having published 543 publications, representing 32.7% of all publications in the titles requiring data deposit in 2016.

The Python scripts used to retrieve institutional publications based on a list of ISSNs have been released on GitHub so that other institutions can conduct similar research.

URL : The Changing Influence of Journal Data Sharing Policies on Local RDM Practices

DOI : https://doi.org/10.2218/ijdc.v12i2.583

Data sharing and reanalysis of randomized controlled trials in leading biomedical journals with a full data sharing policy: survey of studies published in The BMJ and PLOS Medicine

Authors : Florian Naudet, Charlotte Sakarovitch, Perrine Janiaud, Ioana Cristea, Daniele Fanelli, David Moher, John P A Ioannidis

Objectives

To explore the effectiveness of data sharing by randomized controlled trials (RCTs) in journals with a full data sharing policy and to describe potential difficulties encountered in the process of performing reanalyses of the primary outcomes.

Design

Survey of published RCTs.

Setting

PubMed/Medline.

Eligibility criteria

RCTs that had been submitted and published by The BMJ and PLOS Medicine subsequent to the adoption of data sharing policies by these journals.

Main outcome measure

The primary outcome was data availability, defined as the eventual receipt of complete data with clear labelling. Primary outcomes were reanalyzed to assess to what extent studies were reproduced. Difficulties encountered were described.

Results

37 RCTs (21 from The BMJ and 16 from PLOS Medicine) published between 2013 and 2016 met the eligibility criteria. 17/37 (46%, 95% confidence interval 30% to 62%) satisfied the definition of data availability and 14 of the 17 (82%, 59% to 94%) were fully reproduced on all their primary outcomes. Of the remaining RCTs, errors were identified in two but reached similar conclusions and one paper did not provide enough information in the Methods section to reproduce the analyses. Difficulties identified included problems in contacting corresponding authors and lack of resources on their behalf in preparing the datasets. In addition, there was a range of different data sharing practices across study groups.

Conclusions

Data availability was not optimal in two journals with a strong policy for data sharing. When investigators shared data, most reanalyses largely reproduced the original results. Data sharing practices need to become more widespread and streamlined to allow meaningful reanalyses and reuse of data.