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Report on the workshop for FAIR Incentives on 9.5.2022


The EOSC-Nordic project’s Work Package 4.3.1. organized a “FAIR Incentives stakeholder workshop” on Monday the 9th of May 2022, attracting 45 participants from various stakeholders. The following is a summary of the workshop.

Project and work-package information

EOSC-Nordic is a project sponsored by the European Union under the Horizon 2020 program. The project aims to make Nordic and Baltic repositories adhere to the FAIR Principles ( to increase the Findability, Accessibility, Interoperability and Reusability of data and metadata in scientific research and other data-intensive domains.

Within the EOSC-Nordic project, there are several different Work-Packages (WP’s) defined. The workshop on the 9th of May was organized by WP 4 / Task 4.3. with a focus on “FAIR incentives” and to provide input to a document titled: “D4.4 Report and recommendations on FAIR incentives and expected impacts in the Nordics, Baltics and EOSC “.

Approach and agenda of the workshop

During the workshop, we gathered valuable input on the following interesting question:

What incentives can we define and recommend that will help drive the different policymakers and stakeholders (researchers, institutes, funders, ministries) to faster uptake of a FAIR-based infrastructure and FAIR practices in the Nordic/Baltic countries?

Not a simple question, and we realized that a fundamental “cultural change” was most likely required for such a large and complex project. During the workshop, we, therefore, recorded valuable input from the different stakeholders along the lines of five (5) distinct levels of change.

Five levels of change (make it possible, make it easy, make it normative, make it rewarding, make it required)

Figure: Nosek B.’s Theory of change model (2019)

Following this model, we broke the group of participants up into five break-out sessions to study and discuss relevant aspects of the pyramid above.

Report on the outcomes of the workshop

The workshop consisted of two parts:

  • Presentations of the findings resulting from the qualitative study on FAIR incentives gathered from questionnaires that were produced in 2021.
  • Allowing participants to discuss and influence the required FAIR incentives via Mentimeter questions and virtual break-out sessions using a virtual Conceptboard.

Find more information on the input provided by all participants in the links below.


Most important components of research culture based on FAIR DM and OS


Extracts from the Mentimeter discussions from the FAIR incentives stakeholder workshop.

Summary of takeaways

The main highlights from the workshop, listed per stakeholder level:

General level:

  • Incentives can be an important driver of cultural change
  • FAIR awareness at all levels is crucial!
  • Change should happen at all levels (also from the top)
  • Avoid making the same mistakes as with measuring Open Access to publications

Funder’s level:

  • Funders can play an important role in driving FAIR through financial incentives.
  • Financial awards are important but not exclusive drivers.
  • Funds should also be there for support and technical resources.
  • Reward the reuse of FAIR data, rather than only the production of FAIR data
  • Pre-defined/Pre-populated maDMPs should be required by the funder and be shared within a community, driving “convergence by convenience.”

Ministries/National level:

  • Ministries and institutions should work on strict requirements, with gradual phasing regarding implementation
  • Data standards, qualifications, self-assessment options, and certifications to be developed for overall consistency
  • Requirements to make it happen could differ per country
  • Improve communication and platforms (National / Ministry)
  • Legal + ethical view should be taken into account (Ministry)

Communities level:

  • Communities are essential for discussing/defining FAIR Implementation Profiles, like the semantic models, ontologies, controlled vocabularies, etc.
  • Different communities may have different requirements based on average data file size, metadata schemas, and/or data sensitivity aspects.

Infrastructure/Service provider level:

  • Services should match the different aspects of the FAIR principles.
  • Systems and Infrastructure need to be supportive and as user-friendly as possible (comparable to Spotify).

Research Institute/University level:

  • Data-Stewards at the institutes are crucial to support the researchers.
  • Actively supporting/awarding proper FAIR data sharing should be on the agenda of institutes/universities.

Researcher level:

  • Researchers should become more aware of FAIR data management, not necessarily becoming an expert in data management (services like data stewards can assist in the process).
  • A 5 % grant surplus for data management services may be applicable as an average, but there is no average/common researcher.
  • Peer recognition among researchers is also seen as important.
  • Set up a feedback process to ensure proper working of data sharing.

The workshop recording can be found on our YouTube channel.