Normalizing Data (sharing)
Introducing Five Essential Factors, our latest white paper. Over the past two years, we’ve heard from more than 11,000 researchers about their views on data sharing, what they do in practice and the challenges they face. Building on that understanding, today we have released a whitepaper which proposes five key factors to make data management and sharing “business as usual” for all researchers.
This week, my colleague Iain Hrynaszkiewicz has been at the Research Data Alliance Plenary 13 meeting in Philadelphia, representing Springer Nature and chairing an interest group on standardising data policies. At RDA, we also shared hot off-the-press copies of our new whitepaper, Five Essential Factors for Data Sharing, published this week and openly available on figshare. All of the underlying source data is also available on figshare (links provided in the report).
It’s hard to believe it has been a year since my first RDA meeting in Berlin, and the publication of our first white paper Practical Challenges for Researchers in Data Sharing in March 2018. It’s been a busy year for the research data team at Springer Nature and personally, I have learned a lot through our continued research and conversations with funders, researchers and institutions.
Since our last report, we have followed up with research in China and Japan, to complement the picture of North America and Europe in Practical Challenges. In all, we now have survey data from over 11,000 researchers from around the world. We’ve built on and synthesised the research we have done, which pinpoints challenges researchers face when sharing data.
While researchers are sharing their data more often, most researchers are not yet managing or sharing data in ways that make it findable, accessible interoperable and reusable (FAIR). Our learnings over the past twelve months have cemented for me how much needs to be done to make good research data practice as routine and commonplace as the publication of research articles and monographs. Our thinking on this has crystallised into the “five essential factors” we set out in this report:
- Clear policy: from funders, institutions, journals, publishers, and research communities. Setting unambiguous and specific requirements for data management and sharing to lead to a shift in researcher behaviour.
- Better credit: to make data sharing worth a researcher’s time. With more formal recognition through data citations, authorship, inclusion in research assessments, and career advancement, data sharing will increase.
- Explicit funding: for data management and data sharing, as well as data publishing. Policy without access to dedicated funding to enable compliance is unlikely to result in increased data sharing.
- Practical help: for organizing data, finding appropriate repositories and provision of faster, easier routes to share data. The majority of researchers don’t know how or where to make their research data available.
- Training and education: to answer common questions from researchers on data sharing and help build skills and knowledge. Communicating the benefits of best data practice and addressing common areas of concern.
At Springer Nature, we have continued to develop the solutions we can offer to the research community to help make good data practice the norm. There is no learning like doing, and we continue to be heartened by enthusiasm from funders, foundations and institutions, and reality-checked by the early stages of allocated budgets for research data. We’ve seen that researchers may report that they see the value in sharing data, but in general they are not doing so with alacrity, even when support is offered. A reminder that we need to do more to make it easier for researchers to share, and more obvious why it is worth their time and effort.
Our work to better understand how to make a difference continues. We hope by understanding what is making researchers take action, we can better help more researchers to do so. We look forward to continuing to share our findings to help accelerate progress to make research data as open as possible.
You can read the full report here.
You can also watch a short video providing more insights into the whitepaper here.