This case study is based on a presentation by Margreet Bloemers ZonMw during the Finland edition of the ELIXIR Node Data Management Strategy (NDMS) module in 2023. The original training materials and shared notes are available through the ELITMa Finland workshop materials.
The presentation explored how funders increasingly move from project based RDM requirements towards organising research communities and domain specific FAIR implementation approaches. For Nodes developing a data management strategy, this shift is relevant because FAIRification requires coordination beyond individual projects.
Why is this relevant?
Many Nodes already support researchers with DMP guidance, repositories, consultations, FAIR support and training. However, FAIRification often requires additional coordination around metadata standards, vocabularies, community agreements, FAIR expertise and support structures.
The presentation illustrates that FAIRification is not only technical. Different research domains use different metadata approaches and standards. FAIRification therefore depends on collaboration between researchers, domain experts, data stewards, infrastructures and funders.
This means that FAIRification cannot always be organised project by project. Nodes may need to coordinate approaches across institutes, projects and communities.
What can Nodes learn from this?
FAIRification requires coordination
FAIRification often depends on shared metadata approaches, community standards, collaboration between expertise areas, and reusable support and guidance. Nodes can play a role in connecting these activities.
FAIRification is community specific
Different research communities use different standards, vocabularies and FAIR approaches. Generic support alone is often not sufficient. Nodes may therefore need:
- Community engagement
- Domain expertise
- Collaboration with researchers and data stewards
FAIR support goes beyond compliance
The presentation distinguishes research data management from FAIRification. FAIRification is presented as a process rather than a single compliance step. This may influence training, support services, infrastructure choices and FAIR expertise within the Node.
Funders increasingly expect reusable data
From a funder perspective, FAIR data increases the value and reuse of research investments. This may effect:
- Priorities for FAIR support
- Collaboration with research communities
- Investments in metadata and standards
- Alignment between local and national initiatives
What can you do?
Nodes may reflect on whether current support focuses mainly on project level RDM or already includes broader FAIRification approaches. They may also assess which FAIRification activities already exist, which metadata standards are used by communities, where coordination is currently fragmented, which expertise is missing, and which collaborations are needed to support FAIRification.