First conceptualised in 2014, the FAIR data principles have been highly influential in bringing research data to the forefront of the open science movement. This year we celebrate five years since the formal publication of the FAIR data principles, and to mark this milestone Springer Nature has launched its latest white paper ‘The Future of FAIR’. In the Future of FAIR we brought together an international cohort of research data professionals, and asked them to share their opinions on the impact to date of the FAIR principles, and their views on what needs to be considered next in research data management.
The burgeoning open science (or open research) movement aims to make public and charity funded research as transparent and accessible as possible, and available for use to all to use, extend and build on. Research data is central to this vision, and to many policies and initiatives launched in recent years encouraging the adoption of open science practices. The impact of the FAIR data concept on open science advocates, position statements, policies and funding opportunities is unmistakable.
We know that implementing open science practices can be beneficial for individual researchers, and as might be hoped, the flurry of open science activity has resulted in researcher awareness of the FAIR data principles steadily increasing. In the State of Open Data 2018 we found that 15% of the respondents were familiar with FAIR, increasing to 18% and 20% in 2019 and 2020 respectively. However, familiarity does not necessarily translate to understanding and in our State of Open Data surveys we also observed a rise in the proportion of researchers who had heard of FAIR but did not consider themselves familiar with the principles; 25% in 2018, 28% in 2019 and 31% in 2020. This demonstrates a persistent gap in researchers' understanding of how to implement the FAIR principles for their own work, which can mean that even when researchers do share their data it’s not necessarily in a usable form.
With this context in mind and working closely with the Better Research for Better Data programme committee, we asked our group of international data experts to provide their views on the five key topics summarized here.
Ensuring that primary research data on covid-19 can be found, accessed, understood and built upon has been a cornerstone of the global response to the pandemic. Governments and policy makers at all levels have been required to understand emerging research data in real time in order to make informed decisions which directly impact the health and well-being of their citizens. The FAIR data principles have been an essential framework for many policy makers in their thinking about data sharing. Implementation challenges, especially around interoperability, remain for researchers and policy makers alike. The research data community has an important opportunity to use this hard won knowledge on the impact of FAIR in a pandemic, and accordingly shape the future of how we share data and research outputs.
Data sharing has been embedded into practice for decades in some disciplines, notably structural biology, genetics and genomics. As we increase our understanding of these areas and improve our ability to share data, good research data management must include consideration of study participants, in addition to the needs of potential data reusers. Building public trust in research outputs is a responsibility to be shared by researchers, peer reviewers, publishers and all stakeholders in the research enterprise.
Over recent years we have seen a huge increase in the use of devices such as smart watches to gather and store data; data which could feed into clinical medicine. This Real World Data (RWD) has the potential to bring huge benefits, to healthcare companies by reducing the cost of gathering data, and to patients by reducing the burden of clinical trials. At the same time, the use of RWD raises ethical and practical issues around bias, privacy and consent, all of which need to be proactively addressed in order to maximize the potential for improving patient outcomes.
Data professionals play an important role in supporting researchers to understand and implement the FAIR data principles. However the skills and capability requirements for these support roles are not universally defined, making it complex for research institutions to establish these types of positions. Building capacity for research data support roles will help to embed the FAIR data principles into research education and practice.
Ensuring equitable access to sustainable research data infrastructure is vital for wider implementation of the FAIR data principles. The capacity of research institutions, funders and governments to build and maintain such infrastructure varies considerably across the globe. Understanding and addressing these challenges will require a cultural shift in the conversation around data sharing, in order to ensure that open science practices are implemented for the benefit of all researchers.
The importance of global access to quality and reliable research has never been as transparently clear as over the past 18 months.The challenges identified and discussed by our international data experts in the ‘Future of FAIR’ are complex and in many cases require the engagement of multiple stakeholders at several levels of governance. Springer Nature is proud to play its part in working directly with the research community; from initiatives that help individual researchers, to projects enabling entire disciplines to implement changes on important aspects such as data sharing and research reporting. As Springer Nature CEO Frank Vrancken Peeters noted earlier this year, partnerships are key for advancing open science, and we look forward to continuing to work with the global research community in this important endeavour.