Research institutions refer to universities and higher education organizations engaged in primary or secondary research and to publicly and privately funded research institutes/centres. Research institutions hold a focal role in transitioning to open access practices, as the primary loci where researchers carry out and publish their work. In recent years, research institutions around the world have been promoting the uptake of open access practices, as shown in the steadily increasing number of relevant policies. Nonetheless, the main focus thus far has been on open access to publications rather than research data. Where relevant policies exist, open access to research data is addressed in the context of research data management policies rather than as a policy specifically addressing open access to research data. Motivation to develop policies derives from institutions’ need to safeguard their intellectual, financial, human and material investment, as well as the increasing pressure from research funders who require that the research data produced with their funding is properly managed and is, in principle, openly accessible. In some cases, the motivation for developing a sound institutional data strategy derives from researchers, who acknowledge the significance of research data and the need for better management.
The most consistent progress in research data management is observed in the UK, the USA and Australia. Rapid developments both in the UK and the USA are mostly the result of funder mandatory requirements: Research Councils UK and the National Science Foundation and the National Institutes of Health in the USA. In Australia, while the policy of the main funding agency is not mandatory for research data, universities have made significant progress in addressing research data management under the influence of the Australian Code for Responsible Conduct of Research, requiring an institutional data management policy.
An effective data policy sets the pace and the requirements by which the research community within the institution is to abide. Such policy should allocate in a clear way responsibilities and tasks to the different actors within the institution, with researchers carrying the obligation to manage their research data to specific standards and the institution assuming the obligation to provide the services (infrastructure, training etc.) that will in turn allow researchers to comply with the policy requirements. While the allocation of responsibilities for each stakeholder is important, policies should be flexible enough to accommodate for the changes in researchers’ needs and keep pace with technological developments. Institutional policies share a number of other common elements: they recognize the significance and value of research data and high standards for their management; they set open access to research data as the default, where this is appropriate and legally possible; they require researchers to develop a DMP; they render researchers responsible for the data management within their project; they acknowledge the need to respect funder requirements. Furthermore, they set requirements regarding where to deposit research data and outline broadly the data retention policy/strategy of the institution.
Developing and implementing a data management policy and developing relevant services is essentially a team effort requiring the collaboration of multiple actors. The main units involved are the research office, the IT departments, the academic units, the libraries and the researchers. When it comes to developing services, the university library and the IT department are those mostly involved in operationalizing policies: i.e. the development of the technical infrastructure and its services, the training for the researchers and advocacy services. It is common that IT departments undertake the software and infrastructure development, while the library supports archiving, training and advocacy activities. In developing data management services institutions need to consider which services should be developed in-house and which may be outsourced, on the basis of an assessment of their needs and resources. With respect to infrastructures, while in general they are more developed as compared to the associated policy frameworks, dedicated research data repositories are not widespread among research institutions.
Institutional policies for data management and open access to research data should be accompanied by relevant funds. In particular, funding is necessary both for data management during the life cycle as well as for the curation and preservation of data in the long term as in some cases research institutions are seen as the ‘obvious’ place to host data, while in others they might constitute the only viable option given the patchy coverage of subject-specific data repositories or other data services. Yet, as external funding is usually limited to the lifetime of research projects, research institutions must increasingly turn towards finding resources for the long-term management and preservation of their output in research data.
In terms of training, formal training is necessary for researchers, as well as for librarians and information professionals in order to transition to open access to research data and a culture of open science more generally. While researchers in some fields may require training because they lack the knowledge and the skills on how to make their research data available and accessible, or how to reuse data and incorporate data in their research process, librarians and information experts require training for providing research data services that are necessary in an increasingly data-intensive research environment. Thus, workshops, as well as more formal training programmes and curricula that enable data management skills, data-intensive research, and the gradual development of data-scientists are important activities for research institutions to engage in.
Finally, further progress is needed in terms of rewarding researchers for good data management and providing open access to research data. Currently there is little, if any, formal recognition for data outputs in academic promotion or other assessment processes, which inhibits progress towards open access to research data.