We want researchers to share data and one incentive would be to recognize it with academic merits, which would mean that data sharing needs to be measured and rewarded to a higher degree than today. During the recent IASSIST conference, SND and Elsevier hosted a workshop on merits and metrics.
The workshop began with a review of statistics from the publishing company Elsevier. They have indexed research data from more than 2,000 European databases and repositories.
Guillaume Warnan from Elsevier presented statistics with a particular focus on trends in Sweden and the Netherlands. Both countries have over the past decade sought to actively promote open data by, for instance, politically decided strategies and action plans to achieve open science. These efforts now appear to be visible in the statistics.
‘We can see the same trends for both countries. Between the years 2012 and 2020, there is a consistent development where data sharing increases by approximately 25 to 29 percent every year’, said Guillaume Warnan.
However, there are some differences between research disciplines. Most data, in both Sweden and the Netherlands, are being shared in medicine, chemistry, and biology, whereas economics, technology and the humanities share the least amounts of research data.
Elsevier has also compared the impact for publications with and without linked research data. Metrics show that publications with linked data are more frequently cited. This is the case not only for Sweden and the Netherlands, but throughout the EU.
‘We can see that we get a very positive effect from sharing the data together with a publication. This is the type of statistics that we will keep measuring, and hopefully it can help promote open data even more’, said Guillaume Warnan.
Difficult to decide which metrics to measure
It’s increasingly common to share data, but there’s still not a system for academic recognition of data sharing comparable to that for publication of articles. To create that system, it must be possible to evaluate data, such as by various metrics.
‘If we want open science to become a reality, we have to find a way to regard published data as an academic merit, and to do that we must have a way to measure and quantify them’, said Merlijn de Smit from the Research Data Management Team at Stockholm University.
Which metrics that are the most favourable to measure, and how to measure them, is still up for discussion. Gustav Nilsonne, Domain Specialist at SND and Associate Professor of Neuroscience at Karolinska Institutet, introduced the national activities at SUHF (the Association of Swedish Higher Education Institutions). He stated that we must make the most of the digital development to create new, less static systems for academic recognition.
‘We think it’s necessary to develop new measurement methods that can be used to evaluate and link academic merits to various types of research projects, such as research data, code, and data management plans.’
Nynke de Groot from Erasmus University in the Netherlands called for thoughtful consideration. The most fundamental questions have to be addressed first. We must know what we want to measure and what our goal is. Then we must ask which metrics that are useful to get us there.
Guillaume Warnan agreed that we should take it slow.
‘We should choose metrics very carefully, as they’ll create certain behaviours among researchers. We also need to ask what we want to achieve with open data’, he said.