Compliance Culture or Culture Change? The role of funders in improving data management and sharing practice amongst researchers

Abstract

There is a wide and growing interest in promoting Research Data Management (RDM) and Research Data Sharing (RDS) from many stakeholders in the research enterprise. Funders are under pressure from activists, from government, and from the wider public agenda towards greater transparency and access to encourage, require, and deliver improved data practices from the researchers they fund.Funders are responding to this, and to their own interest in improved practice, by developing and implementing policies on RDM and RDS. In this review we examine the state of funder policies, the process of implementation and available guidance to identify the challenges and opportunities for funders in developing policy and delivering on the aspirations for improved community practice, greater transparency and engagement, and enhanced impact.The review is divided into three parts. The first two components are based on desk research: a survey of existing policy statements drawing in part on existing surveys and a brief review of available guidance on policy development for funders. The third part addresses the experience of policy implementation through interviews with funders, policy developers, and infrastructure providers. ‡ © Neylon C. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.In our review we identify, in common with other surveys, that RDM and RDS policies are increasingly common. The most developed are found amongst funders in the United States, United Kingdom, Australia, and European Union. However many other funders and nations have aspirational statements or are developing policy. There is a broad pattern of policy development moving from aspiration, to recommendations, to requirements, and finally reporting and auditing of data management practice.There are strong similarities across policies: a requirement for data management planning, often in grant submissions, expectations that data supporting published articles will be made available, and in many cases requirements for data archiving and availability over extended periods beyond grants. However there are also important differences in implementation.There is essentially no information available on the uptake and success of different policies in terms of compliance rates, or degrees of data availability. Many policies require a Data Management Plan as part of grant submission. This requirement can be enforced but there is disagreement on the value of this. One view is that requirements such as DMPs are the only way to force researchers to pay attention to these issues. The other is that such requirements lead to a culture of compliance in which the minimal effort is made and planning is seen as a "tick-box" exercise that has no further value. In this view requirements such as DMPs may actually be damaging the effort to effect culture change towards improved co...

Motivating participation in open science by examining researcher incentives

“…Our analysis revealed that MNI researchers were generally favorable toward the notion of open science, reporting that they already engage in significant sharing. Nevertheless, almost half our interviewees noted that the concept is vague ( Fecher and Friesike, 2014 ; Grubb and Easterbrook, 2011 ; OECD, 2015 ) and expressed uncertainty about what precisely open science would require of them ( Open Research Data Task Force, 2017 ; Neylon, 2017 ; Ferguson, 2014 ). Based on our data, this uncertainty can discourage participation in two ways.…”

“…Recent evidence suggests that providing incentives for individual researchers to participate is the key rate-limiting step ( Kidwell et al, 2016 ; Longo and Drazen, 2016 ; Fecher et al, 2015 ). This has stimulated many to think more deeply about how cultural factors, policies and metrics may affect the uptake of open practices by researchers ( European Commission, 2017 ; Wilsdon, 2015 ; Harley, 2013 ; Neylon, 2017 ). This study builds on this work by providing insight into the perspectives of researchers in the lead up to the adoption of an open science policy within their institution.…”

Why Won’t They Just Adopt Good Research Data Management Practices? An Exploration of Research Teams and Librarians’ Role in Facilitating RDM Adoption

“…Requirements from funding agencies and publishers can have a strong influence on the decision to adopt data sharing behaviors, as founder and publisher requirements can directly affect ultimate behaviors without affecting the direct determinants. It is still unclear how much policy is affecting practice (Neylon, 2017), but in the 2019 State of Open Data Report, journal or publisher requirements were found to be the fourth highest motivator for data sharing and funder requirements was ranked sixth (Digital Science). Funders with highly specific requirements could negatively affect the effort expectancy because of the work required to adopt sharing behaviors.…”