November 2021

FAIRsFAIR started a series of training activities to mapping data science programmes at universities and integrating FAIR data skills into them. Creating synergies with existing competence frameworks for data scientists, data stewards and other relevant professions, developing a FAIR data competence framework which can be integrated into those on different education levels, developing education and training material (e.g. model courses and curricula) for university programmes, and capacity building for universities to apply the material (e.g. for instance in doctoral education) are some of the expected outcomes of the FAIRsFAIR task force on creating a FAIR and harmonised Competence Centre for the EOSC.

Through her role in EOSC Pillar, Paula Oset Garcia collaborated with FAIRsFAIR to  deliver two  three day train-the-trainer workshops in June and September 2021 to promote and empower national networks of Data Stewards with awareness of good practices, concepts and techniques. (here the Ghent event, and the blogpost)


What’s a Data Steward? Is there a shared, common definition across organisations in Belgium?

Data Steward is a very recent and emerging role in Belgium. Ghent University was one of the first institutions to establish a data steward team, and it has only been in place for two years. Other RPOs have set up RDM support teams in the meantime, although the setting varies significantly from institution to institution, depending on the local context. In most institutions the role sits within the generic & advisory tasks and policy & coordination tasks. In some cases, there is an infrastructure component, and the title might vary (e.g. “technical data steward”). The name of the role varies as well (“Data steward”, “Information specialist”, “Data manager”). In some cases, people with previous support roles (i.e. librarians), have taken up some RDM support tasks. 
In summary, there is not a common definition or approach as to what exactly a data steward does or where in the organisation sits
During the training co-organised with FAIRsFAIR we asked the audience about the set up of their job:
“50% had been in their data steward role for less than 6 months, 18% between 6 and 12 months, and only the remaining 32% had been working as a data steward for longer than a year. Most of the participants (55%) work in smaller teams of less than 5 people, or work on their own (25%). Only 20% was part of a team of more than 5 members.”


What’s the level of awareness about FAIR and Open Access in data stewardship roles in Belgian HEI, Universities, RPO and Research Organisations? 

In Flanders, there is a significant awareness within data stewards, specially in those cases where the team or the position has been active for a longer period. For those cases where the role is more recent, this can be less developed. Open Access (if understood as OA to publications), may fall outside the scope of the role of a data steward. This is typically done by other library staff. 
I am less familiar with the situation in Wallonia, the French speaking region of Belgium.


Are support measures offered at the national and/or institutional levels to facilitate the uptake of data-intensive skills to practice FAIR RDM?

At the Flemish level, the Flemish government established an Open Science policy plan in 2019 with the objective to align with European OS policies, the Open Data Directive, EOSC etc. The Flemish Open Science Board (FOSB) was founded, to advise the government on and give shape to OS policy in Flanders , e.g. by identifying priorities, by deciding on how the government’s open science subsidies should be allocated, by setting a series of task forces, etc. There is a dedicated budget of 5 million euro per year to support RPOs transition to OS, including dedicated funds to hire data stewards. Progress within institutions will be monitored by means of key performance indicators and associated targets, including for  DMPs for research projects, open and FAIR data, etc. 


Is there a need for a national network of data stewards in Belgium and/or more broadly across Europe?

Such networks are very valuable at this stage. Most data stewards in Belgium are quite new to the role and work in small teams, in a rapidly evolving policy landscape. Many provide a generic/central type of support and sometimes lack the domain specific expertise required for specific situations. Therefore, having access to an additional pool of expertise within a network of colleagues can be very helpful. In Flanders, a knowledge hub has been set up as part of a Flemish Research Data Network within FOSB; it organises monthly meetings around specific topics to exchange knowledge and practices within institutions. It is still in the early phases of development and due to the pandemic we have not been able to meet in person yet. However, there are valuable opportunities to set up specific task forces or working groups to address common challenges. 


What do you think is needed to help HEIs and RPOs to implement and optimise RDM support services to advance the production and use of FAIR data within their organisations?

Dedicated long-term funding for professional support, establishment of clear and harmonised policies, access to appropriate infrastructure, (being able to) monitor progress, access to (formal) training and professional development opportunities for data stewards, as well as greater understanding  and recognition of the data steward role.


What can be done to improve even more the situation related to the uptake of FAIR data skills and practices in your institution?

Harmonisation of policies. At the moment there are different requirements (e.g. whether OA to data is required or not, whether FAIR is an expected outcome or not) depending on the funding organisation. The stricter requirements tend to come from European funding, but the majority of the funding at Ghent University comes from other sources.
Keep professional support (data stewards). Include FAIR principles and RDM basics as part of curriculum at earlier stages. More incentives for researchers to share data and manage them in line with FAIR principles.