The risks of not sharing data are greater than the costs
Research data represent a new currency. Traditionally, publishers did not publish or curate research data, they were interested only in publications. Now, research data and publications are at least equally important.
Data aren’t just good for science. They are also good for driving the kind of innovation needed to solve some of the biggest issues facing the world today. The outbreak of the coronavirus is a perfect example of how open data can help tackle a major global issue.
The spread of the virus sparked discussion in Paris last month where nine global university networks signed the Sorbonne Declaration vowing to develop appropriate reward systems for scholars who made their data open and accessible. It was a major milestone in advancing the cause of research data management in an open science/scholarship world.
But, without investment and culture change for managing and sharing data, the risk could be bigger than the return.
A recent European Commission Report found that sharing and better managing research data would save €10.2 billion per year in Europe, with an additional potential of €16 billion of added value by the innovation generated.
Research data that are FAIR (findable, accessible, interoperable and reusable) and open for sharing and reuse mean that researchers have easy access to experimentation by others, thus avoiding the need for costly duplication.
They also enable research groups to look at research methodology, to test the results produced by others, and to detect mistaken, even fraudulent, use of data. This is an important part of research integrity which, in the UK, is being promoted by the UK Reproducibility Network.
Not all research data can be open, because much – such as patient data – contains personal information that would be inappropriate to share. In this sense, open data are different from open access publications, where current debates centre on making the whole of a publisher’s output open, rather than a part of it.
These are the kinds of challenges for universities in embracing FAIR, open data.
Universities have to create institutional research data repositories in which data can be curated and stored for the long term, as “open as possible, as closed as necessary”. In turn, there need to be data specialists to run and manage the service, and these salary costs need to be met.
So new is the concept of research data management that the first report on the European Open Science Cloud stressed that Europe needed half a million research data stewards within a decade.
