6.2. Arriving at FAIR institutional policies
Adopting an institutional research data policy that embraces the FAIR principles can result in recognition, energy and resources for the implementation of good practices since FAIR implementation requires reshaping and alignment of existing policies.
This section looks at key stakeholders and ways to cultivate an institution-wide FAIR research data environment.
Research data in the institutional policy framework
Institutional policies underpin staffing and resource allocation, approaches and workflows, and can enable and support (or hinder) new practices. Therefore, implementing the FAIR principles for research data at the institutional level needs a review of existing policies to remove potential stumbling blocks and adoption of research data policies with the aim of embracing FAIR.
An institutional policy commitment to the FAIR principles can strengthen policies and efforts in safeguarding research integrity , and should thus be included in policies related to institutional research data. Moreover, institutional commitments to Open Access or Open Research in general can also be bolstered by references to FAIR principles.
A great push for adopting FAIR principles at the institutional level stems from the fact that more and more funders are embracing FAIR as a requirement for their grants. Institutional policies can help to navigate conflicting interests in collaborative research projects. One such example would be to point out the benefits of FAIR data management to (potentially) sceptical industry partners in showing that the principles can be aligned with the need to protect commercially sensitive data. Some institutions may already have dedicated research policies in place for particular areas of research, e.g. for clinical research practices, either at the institutional or the departmental level. These existing policies should be checked for alignment with the FAIR principles as well.
Institutional policies regarding data protection , research ethics , commercialisation and intellectual property rights (IP) are sometimes seen to contradict or impede the implementation of FAIR for some research projects. Striving for FAIR data management can make the task of protecting personally identifiable data and any other sensitive data easier while maintaining the possibility to validate research results. Good (FAIR) data management enables greater control over data and supports a more targeted approach to achieve the aim of making research data 'as open as possible, as closed as necessary' (as outlined in the Programme Guidelines on FAIR Data Management in Horizon 2020). Institutional policies that need to restrict access to data for ethical, legal and commercial reasons can and should embrace the commitment to FAIR data management at the same time.
Research data might also be implicated in policies on technical services, e.g. cloud storage or repositories, IT security (or cybersecurity), or in retention schedules of record management. It is important to engage with different policy owners from different units, e.g. IT or ethics, to develop a cohesive FAIR research data framework at the institutional level which also complies with applicable laws and regulations.
Influencing policymaking
Writing and implementing institutional policies is a collaborative effort. Integrating FAIR principles into existing institutional policies, or developing a dedicated research data policy at an institution requires effective communication and networking with relevant stakeholders.
Understanding policy-making processes and workflows at the institution is the first step towards integrating FAIR in an institutional policy framework. Most institutions maintain a central policy hub and will have someone (an individual or a group of people) tasked with maintaining coherence between all institutional policies and ensuring currentness of all policies. Every individual policy will then have a primary owner tasked with maintaining the policy, supervising compliance and organising periodic reviews and a consultative approach for necessary updates. Ownership of a policy is tied to a function. The owner of a Research Data Policy, for instance, could be the Data Steward, regardless of which individual currently holds the position. Each policy will also have a number of affected stakeholders whose interests need to be taken into account when proposing policy changes.
Typical steps to implement new or updated policies will involve:
identifying the relevant policy documents, their owners and relevant stakeholders;
understanding the interdependencies between policies and the procedures in place to implement or update them;
informal discussions with relevant stakeholders about the needs and benefits of new or updated policies. Understanding requirements and potential roadblocks;
proposing new policy statements (in new or updated policy documents);
consultations and discussions to reach a consensus with all stakeholders; and
policy owners forwarding the proposed changes (or new policies) for approval by senior management, such as the school council or senate.
Institutional setups vary widely and relevant stakeholders will go by various names. The following list therefore only provides a rough overview of potential stakeholders who might be involved in the policy implementation or update process:
Research offices monitor compliance with funder requirements and can be a key driver of institutional adoption of FAIR principles. Other involvements could include the provision of training and the enforcement of policies about research integrity.
IT departments offer a variety of support services relevant for research data that are governed by relevant policies and applicable laws and regulations. IT support services may include, but are not limited to, the provision of computers, servers and cloud storage, institutional repository hosting, and cyber and IT security maintenance.
Libraries often provide services supporting research data management. Sharing and publishing data are important aspects of Open Research. Other services libraries may provide include Open Access, repository support, DMP reviews, as well as RDM training and consultations.
Ethics boards need to approve a wide range of research proposals. Processes and procedures surrounding research data are key to gaining ethics clearance. Policies and procedures need to be aligned and integrated with the FAIR principles.
Data protection offices are concerned with implementing and safeguarding provisions laid down by applicable privacy laws and regulations, such as the EU General Data Protection Regulation (GDPR) and Canada's Personal Information Protection and Electronic Documents Act (PIPEDA). Data protection practices can and should be aligned with FAIR principles.
Technology transfer offices encourage and support researchers and their institutions with the commercialisation of research results by safeguarding intellectual property rights. Policies and procedures are in place to safeguard intellectual property rights. These policies can and should be aligned with FAIR principles to make data as open as possible and as closed as necessary.
Departments, research centres and units, and individual researchers are stakeholders in all research data-related policies. They might be the owners of some policies governing specific areas of research. It is a strategic advantage to have them as close allies for implementing or updating FAIR research data policies (Association of American Universities and Association of Public and Land-grant Universities 2021).
Senior management needs to formally put policies into effect and is ultimately responsible for maintaining alignment of all policies and organising review and update processes. In order to move towards institutional implementation of FAIR, senior management will need to recognise that research data are valuable assets of an institution, and that it is important to endorse FAIR principles to harness the ultimate value of research data.
Resources:
Sample guides and perspectives on institutional approaches:
Open Science and its role in universities: A roadmap for cultural change – Discussion and analyses on Open Research approaches at the university level, with recommendations on what universities can do to embrace Open Science principles, policies and practices.
LEARN Toolkit of Best Practices for Research Data Management – 23 Best-Practice Case Studies from institutions around the world, drawn from issues in the original LERU (12) Roadmap.
Association of American University's Guide to Accelerate Public Access to Research Data – Discussions and recommendations on institutional strategies to advance public access to research data.
Institutional policies are registered by FAIRsharing, making them discoverable and citable (see this example from the University of Oxford).
Learn more:
Lesson Plan 16: Data management and governance in industry and research
(12) LERU: League of European Ressearch Universities
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