Train-the-Supporter:Becoming a Strategic RDM Partner

Research data management is no longer just about knowing the right tools, standards, or policies. In many institutions, the real challenge lies elsewhere: in translating this knowledge into meaningful support, in navigating complex stakeholder environments, and in making RDM actually work in practice.

This workshop is designed for those who operate in exactly this space.

It is aimed at research support professionals who are already familiar with RDM and want to move beyond explaining concepts towards actively shaping how research data management is implemented in their institution. Whether you work as a data steward, in a library, in IT, or in administration, the focus is on your role as someone who enables, guides, and increasingly influences research processes.

At its core, the workshop is about a shift in perspective.

Instead of approaching RDM primarily as a set of topics to be taught, it frames it as a service that needs to be designed, communicated, and embedded into institutional structures. This includes understanding the research ecosystem you are part of, clarifying your own role within it, and developing strategies to work effectively with different stakeholders.

Participants will explore how to move from reactive support—answering questions as they arise—towards a more structured and proactive approach. This involves learning how to conduct consultations in a way that uncovers underlying needs, how to deal with resistance or uncertainty, and how to guide conversations even in situations where formal authority is limited.

A look into the workshop

The workshop is structured into a series of interconnected modules that gradually shift the perspective from understanding RDM support to actively shaping it in practice.

You will work on:

  • Understanding your role in the research ecosystem
    You will map your institutional RDM landscape, identify key stakeholders, and reflect on how support, services, and training interact. This creates the foundation for positioning yourself beyond a purely reactive role.
  • Developing consultation and communication skills
    Moving from answering questions to guiding processes.
    You will develop practical consultation skills, including needs assessment, structuring conversations, and handling resistance. Through interactive formats, you will experience how small interventions can significantly change outcomes—even without formal authority.
  • Translating RDM concepts into practice
    FAIR is not treated as an abstract concept, but as something that needs to work in practice. You will engage with repositories, persistent identifiers (DOI, ORCID, ROR, RAiD), and infrastructure landscapes, and explore how they connect into a broader system. Hands-on exercises include evaluating datasets (e.g. with F-UJI) and identifying suitable repositories.
  • Navigating legal and ethical complexity
    You will work through real-world scenarios involving GDPR, consent, anonymisation, and licensing. The workshop also introduces CARE principles and places them in relation to FAIR, highlighting that good data management is not only technical—but also ethical, contextual, and often political.
  • Designing RDM support as a service
    A central part of the workshop is moving from knowledge to service design. You will explore how RDM can be embedded into institutional processes, how to structure workflows, and how to collaborate across roles. This includes working with tools such as service canvases, reflecting on trade-offs (e.g. ELN vs. Excel vs. Git), and designing a minimal viable RDM setup for your context.
  • Positioning yourself as a strategic partner
    You will reflect on your role as a data steward or support professional, define boundaries, and explore how to increase your visibility and impact within your institution. This includes reporting, stakeholder alignment, and building trust over time.
  • Looking ahead: trends and developments
    The workshop concludes with a forward-looking perspective on current initiatives, open science developments, EOSC, and the role of AI in data governance. These discussions are used to reflect on how your role may evolve—and where strategic opportunities lie.

The goal is not only to gain new perspectives, but to develop concrete approaches that can be directly applied in practice.