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.

 

The development of a research data policy at Wageningen University & Research: best practices as a framework

Authors: Hilde van Zeeland, Jacquelijn Ringersma

The current case study describes the development of a Research Data Management policy at Wageningen University & Research, the Netherlands. To develop this policy, an analysis was carried out of existing frameworks and principles on data management (such as the FAIR principles), as well as of the data management practices in the organisation.

These practices were defined through interviews with research groups. Using criteria drawn from the existing frameworks and principles, certain research groups were identified as ‘best-practices’: cases where data management was meeting the most important data management criteria.

These best-practices were then used to inform the RDM policy. This approach shows how engagement with researchers can not only provide insight into their data management practices and needs, but directly inform new policy guidelines.

URL : The development of a research data policy at Wageningen University & Research: best practices as a framework

DOI : http://doi.org/10.18352/lq.10215

Standardising and harmonising research data policy in scholarly publishing

Authors : Iain Hrynaszkiewicz, Aliaksandr Birukou, Mathias Astell, Sowmya Swaminathan, Amye Kenall, Varsha Khodiyar

To address the complexities researchers face during publication, and the potential community-wide benefits of wider adoption of clear data policies, the publisher Springer Nature has developed a standardised, common framework for the research data policies of all its journals. An expert working group was convened to audit and identify common features of research data policies of the journals published by Springer Nature, where policies were present.

The group then consulted with approximately 30 editors, covering all research disciplines, within the organisation. The group also consulted with academic editors and librarians and funders, which informed development of the framework and the creation of supporting resources.

Four types of data policy were defined in recognition that some journals and research communities are more ready than others to adopt strong data policies. As of January 2017 more than 700 journals have adopted a standard policy and this number is growing weekly. To potentially enable standardisation and harmonisation of data policy across funders, institutions, repositories, societies and other publishers the policy framework was made available under a Creative Commons license.

However, the framework requires wider debate with these stakeholders and an Interest Group within the Research Data Alliance (RDA) has been formed to initiate this process.

This paper was presented at the 12th International Digital Curation Conference, Edinburgh, UK on 22 February 2017 and will be submitted to International Journal of Digital Curation.

URL : Standardising and harmonising research data policy in scholarly publishing

DOI : https://doi.org/10.1101/122929