European Research Data Landscape

22 February 2023

FAIR Data is an important element of Open Science. In Europe we are several years down the road and there are a lot of initiatives and fundings. What has this brought us so far? What is the status of the FAIR practices of researchers and the FAIRness of research data? The European Research Data Landscape study, which DANS was a partner in, dives into this. We summarise the most important and noticeable outcomes.

About the European Landscape study

The European Research Data Landscape study looks at researchers’ practices in producing, reusing and depositing data, and in making it FAIR, as well as examining the research data repository landscape. During the study, two surveys were carried out – one among researchers (over 15,000 responses), and the other among research data repositories (over 300 responses) – as well as an automated assessment of the FAIRness of research datasets, using the tool F-UJI. The findings of the study show that while certain FAIR practices are being adopted, and researchers are motivated by the ideals of Open Science, obstacles still remain to making data FAIR. These include limited local support, the actual implementation of FAIR in practice, lack of awareness, and the lack of progress monitoring at various levels.

Outcomes

The drive to manage and store data

There are a number of obvious outcomes, such as that policies of funding bodies, institutions and publishers are most influential for the respondents when it comes to research data management (RDM) and data sharing. Respondents store data in several places: local storage is slightly more popular than institutional cloud storage, and personal physical data storage is preferred to personal cloud storage. 40% of the respondents used a research data repository at least once to store their data.

The strongest drives to store data in a research data repository are first with 65%, to accelerate scientific research and the public benefit, second, to disseminate and continue the impact research, and third, to support Open Science (58%). Remarkably, with around 30% the storage requirements of the publishers, funders or institutions score lower than their policies for managing and sharing data.

How well known is FAIR

Over 60% of the respondents are familiar with the FAIR principles on a certain level, and almost two-thirds of them indicate that they put the principles into practice. Of course, researchers can also show “FAIR behaviour” without knowing the principles, as the following diagram indicates (N=10,889):

Almost one-third of the respondents always use community standards for data and metadata, make use of a researcher identifier like ORCID, develop a data management plan and look for existing data to reuse. On the downside, many respondents never acquire a persistent identifier for their software data.

Research institutions are mentioned as being the first place to go to for support in managing, sharing and/or making data FAIR. They are followed by the discipline and the national levels.

Reuse of data

Although many respondents have not heard of FAIR or do not store data, the concepts behind the principles appear to resonate with the respondents (N = 10,900):

Respondents who have reused data, mostly reused data referenced in academic publications or data they had already used in the past. It was also quite common to find relevant data while engaging in an open search. Out of the 7,738 respondents who reused existing data, 68% had reused data that was publically available without restrictions.

How FAIR are datasets in repositories?

For the study nearly 8,000 datasets in 31 repositories all over Europe were automatically assessed with the F-UJI FAIR metrics assessment tool. The overall average score of these datasets was 54,6%. In and of itself this percentage does not tell much, because different assessment tools test and score different aspects in different ways. Moreover, the architecture of repositories varies as well, which can make it tricky for automated tools to find specific information. Therefore the DANS team presented and explained the findings not only in the report, but also in a workshop with representatives of the repositories involved.

Conclusion

There is still a lot to establish to create FAIR and Open Science. DANS is working hard to accomplish this, both on the national and international level. For example with our Data Stations for long-term preservation and access, the TDCC-SSH program to support researchers and institutions in Social Sciences and Humanities and FAIR-IMPACT to implement the FAIR principles and solutions.

The study was commissioned by the Directorate-General for Research and Innovation (DG RTD) of the European Commission, with the general objective to provide a detailed characterisation of the research data ecosystem in the European context, covering the EU Member States, Horizon 2020 Associated Countries (AC) and the UK. The study was carried out by Visionary Analytics, DANS, the Digital Curation Centre (DCC) and the European Future Innovation System (EFIS) centre. The full report with recommendations for the European Commission and all underlying data are available from Zenodo: https://zenodo.org/communities/erdl21/?page=1&size=20