Establishing RDM Consultancy Services in Universities: A Roadmap

1 Establishing RDM Consultancy Services in Universities: A Roadmap by Özgün Ünver, Ph.D., Data Steward: Social Sciences & Humanities, Vrije Universiteit Brussel (Disclaimer: ChatGPT 5 was used during the drafting stage of this document, and the text was thoroughly revised and edited by the author afterwards.) Introduction Universities across Europe face growing challenges in supporting effective, compliant, and sustainable Research Data Management (RDM). While many institutions already provide training, templates, and guidance, these services may fall short for large and complex research groups or projects funded through ERC, Horizon, or other major grants. To address this gap, a structured RDM Consultancy provides tailored, hands-on, and collaborative support that embeds RDM practices directly within the workflows of researchers. This document provides a detailed framework for designing, implementing, and evaluating such a programme. It is based on the practical experience of piloting the RDM Consultancy service at Vrije Universiteit Brussel (VUB) and can serve as a blueprint for other universities wishing to replicate this approach. The core idea is to combine expertise from data stewards (and, in this case, consultants) with the active participation of research groups. The consultancy provides practical outputs, such as operational electronic lab notebooks (ELNs), structured data storage systems, and tailored metadata templates, while simultaneously building capacity within research groups to sustain these practices independently. This document outlines the programme’s scope, processes, governance, evaluation mechanisms, and success factors, offering universities a clear path toward establishing and continuously improving their own RDM consultancy offers. Rationale and Objectives Modern research environments demand rigorous RDM due to funder requirements, institutional policies, the growing complexity and amount of (digital) data, and the growing importance of reproducibility and data sharing in the wider academic milieu. Yet researchers often lack the expertise, resources, or time to implement these practices effectively on their own. Traditional support services – training sessions, online resources, or generic 2 templates – are valuable but insufficient for research project consortia and research groups with complex data workflows and large numbers of researchers. The RDM Consultancy service aims to fill this gap by offering: 1. Tailored and hands-on support aligned with the specific needs of each group or project 2. Collaborative engagement with researchers to co-develop solutions (also known as a done-with-you approach) 3. Sustainable capacity building that ensures independence after consultancy ends In short, the programme bridges the gap between knowledge and implementation, making good data management both achievable and longlasting. Scope of Services In the pilot phase, RDM Consultancy at VUB was designed as an extension of the university’s core RDM services, provided free of charge, offered only to the largest research groups, and capped at a defined workload (i.e., 10 working days per consultancy). This ensured the service is both impactful and scalable. Once the pilot phase was concluded and the need for the RDM Consultancy was established, it was decided that the service would be offered on a continuous and “first-come-first-served" basis and to all research groups (not only the large ones) as well as large project consortia (such as those funded by ERC or Horizon Europe). At VUB, typical consultancy topics include:  Configuring approved storage solutions with structured folders, permissions, and access controls  Migrating data from non-approved or legacy storage systems to institutional storage  Writing or refining Data Management Plans (DMPs)  Implementing specific elements of DMPs into daily workflows  Designing research-specific metadata templates and README documentation  Selecting discipline-specific data repositories and providing hands-on guidance for data deposition  Supporting applications for access to third-party data (e.g., governmental, industrial, or hospital data)  Organising workshops tailored to the group’s specific workflows and tools 3  Setting up fully operational Electronic Lab Notebooks (ELNs) for the research/project group These examples demonstrate the consultancy’s breadth: from technical infrastructure to compliance and documentation. The goal is not only to deliver solutions but to embed them effectively within the group’s practices. Process Framework The consultancy follows a structured process to ensure consistency and accountability. Step 1. Request and Intake Research groups apply through a simple request form on the university’s RDM portal. The form collects key information such as applicant details, research group name, specific needs, and expected outcomes. After submission, an intake meeting is arranged with the assigned data steward. The aim of this meeting is to collect information on:  Research context and type of data produced  Specific RDM challenges and needs  Desired outcomes and how success will be measured  Preferred working method: done-with-you (capacity building) or donefor-you (faster delivery, in case of urgency) - the preference is always the former to enable independent RDM practices after the consultancy is finished  Required input from researchers: beyond the working method, the consultants often need specific administrative or data-related information from the research group in order to deliver on the requests  Timeline and availability of core group members (a small number of researchers who will be closely involved in the consultancy process – often including the chair of the research/project group and a project/data manager)  Whether any trainings or workshops are foreseen for the larger group of researchers (beyond the core group)  Any specific deadlines that need to be met to prioritise certain actions over others An agreement email is then sent to the research group, summarising the intake discussion, outlining a plan of action, restating the deadlines, and clarifying responsibilities. Importantly, it establishes expectations that the group must actively contribute to ensure success. 4 Step 2. Execution Execution is iterative and collaborative. The process typically includes: 1. Discussion with the group to refine understanding of needs 2. Design and development of proposed solutions 3. Presentation and refinement, where feedback from the group is incorporated 4. Implementation, if included in the scope 5. Workshops or training sessions to embed knowledge across the group This approach ensures the solution is fit-for-purpose and that the group is equipped to sustain it beyond the consultancy. Step 3. Sign-Off Once it is confirmed that the consultancy is finalised, the data steward also sends an evaluation form which would be filled out by the client. Once the evaluation is received, the data steward sends a final email to the group summarising the outcomes, confirming project closure, and clarifying that new consultancies can be requested for additional needs. This avoids openended commitments and reinforces the time-bound nature of the service. Evaluation and Continuous Improvement Evaluation is critical for measuring the impact of the consultancy and refining the service. Structured feedback is gathered through an online survey distributed to research group chairs or data managers after consultancy completion. The survey questions cover (see Appendix for the full questionnaire):  Clarity and organisation of the consultancy process  Relevance and usability of delivered solutions  Effectiveness of the done-with-you approach  Impact on the independence of the research group regarding RDM practices  Value of workshops and training  Additional support needs The survey may be complemented by an optional follow-up meeting to clarify responses. As a result of such structured evaluation, the consultants can: 5  Produce annual evaluation report with key insights and recommendations  Refine processes and materials continuously  Strengthen trust and engagement with researchers Governance and Resourcing A successful consultancy programme requires clear governance and careful resource management:  Assignment of consultants (data stewards): Projects are allocated based on research domain and expertise, with additional support available for specialist topics.  Workload management: Each consultancy is capped at ~10 working days on a first-come-first-served basis to maintain service sustainability.  Tracking and monitoring: Internal systems record request dates, intake details, time spent, project status, and responsible staff.  Oversight and quality assurance: Regular internal reviews ensure consistency across consultancies and provide opportunities for knowledge exchange among data stewards. This structure balances flexibility for research groups with accountability for the data steward team. Communication and Outreach To ensure uptake, the consultancy must be actively promoted. Key strategies include:  Announcements on the university’s intranet, newsletters, and RDM portals  Presentations at faculty boards and research council meetings  Sharing success stories from early projects to demonstrate tangible benefits  Emphasising the programme’s defining features: free, collaborative, practical, and time-limited Effective communication frames consultancy as a trusted extension of core RDM services rather than a replacement. Key Success Indicators Several elements underpin the success of an RDM consultancy programme: 6 Voluntariness: A clear demand for consultancy should come from the researchers, as this is the basis for active participation during the consultancy period. Clear boundaries with sufficient flexibility: Scope, workload, and deliverables must be well-defined from the outset, but enough flexibility is also built in to make it possible to pivot and/or add other tasks if needed. Researcher engagement: Active participation is essential; consultancy is not a passive service and aims for RDM capacity building amongst researchers. Expertise pooling: Data stewards collaborate internally to share knowledge and skills. Feedback loops: Systematic evaluation ensures continuous improvement. Scalability: Services must be designed to accommodate demand, starting with large groups before potential expansion to smaller ones Conclusion The RDM Consultancy Programme offers universities a powerful way to strengthen research practices, meet compliance requirements, and foster a culture of sustainable data management. By combining tailored, hands-on support with structured processes and robust evaluation, the programme addresses the limitations of traditional services while building long-term researcher independence. The VUB experience demonstrates that such a model is feasible, impactful, and scalable. Other universities can adapt this blueprint by aligning the consultancy framework with their own resources, infrastructure, and institutional culture. Implemented thoughtfully, the consultancy can transform RDM support from a peripheral service into an embedded, collaborative partner in the research lifecycle, thereby improving both the quality and impact of academic research. 7 Appendix: Evaluation Questionnaire One response per Research Group or project. All open-ended text questions are optional except for the last section on value and outcomes. Section A: General Information 1. Name of the Research Group (and the Project, if applicable): ___________ 2. Name(s) of the respondent(s): ________________________________________ 3. The role(s) of the respondent(s) within the Research Group: □ Chair or co-chair □ Data Manager □ Project Manager/Coordinator □ Other (e.g., professor, postdoc, PhD researcher): _______________________ 4. Type of consultancy received (select all that apply): □ ELN setup □ Internal storage solution setup (with folder structure) □ Data migration □ DMP writing □ Metadata template development □ Data repository selection and data preservation □ DMP implementation support □ Access to third-party data □ Other: _____________________________________________ Section B: Consultancy Process Rate on a scale from 1 (Strongly Disagree) to 5 (Strongly Agree): 5. The consultancy objectives were clearly defined. 6. The consultancy process was well-structured and organised. 8 7. The hands-on approach effectively involved our research group in developing RDM solutions. 8. Any further comments regarding the consultancy process? (Open Text) _____________________________________________________________________________ _____________________________________________________________________________ _____________________________________________________________________________ Section C: Quality of the Consultancy Rate on a scale from 1 (Strongly Disagree) to 5 (Strongly Agree): 9. The Data Steward(s) understood our specific needs and research context. 10. Communication frequency, timing of meetings, and responsiveness of the Data Steward(s) were appropriate. 11. The delivered RDM solutions and materials (ELN, folder structures, templates, etc.) were clear, relevant, and usable. 12. Any further comments concerning the quality of the consultancy? (Open Text) _____________________________________________________________________________ _____________________________________________________________________________ _____________________________________________________________________________ Section D: Impact of the Consultancy Rate on a scale from 1 (Strongly Disagree) to 5 (Strongly Agree): 13. The consultancy has improved our research group's RDM practices. 14. The time invested in the consultancy was worth the benefits we gained. 9 15. We implemented the suggested solutions, and they are in active use in our RDM workflow. 16. The consultancy equipped our research group to manage RDM solutions independently. 17. Were there any difficulties or barriers (technical, organisational, etc.) to implementing the recommendations? If so, what were they and were they resolved? (Open Text) _____________________________________________________________________________ _____________________________________________________________________________ _____________________________________________________________________________ 18. Any further comments concerning the impact of the consultancy on your research group? (Open Text) _____________________________________________________________________________ _____________________________________________________________________________ _____________________________________________________________________________ Section E: Workshop & Training Effectiveness (optional section, only if applicable) If there were any workshops organised for your research group, rate on a scale from 1 (Strongly Disagree) to 5 (Strongly Agree): 19. The workshop(s) were relevant to our research needs. 20. The workshop(s) were well-structured and interactive. 21. The workshop(s) enhanced our understanding of the developed RDM solutions. 22. Any further comments concerning the effectiveness of the training(s) or workshop(s) that were organized for your research group? (Open Text) _____________________________________________________________________________ _____________________________________________________________________________ _____________________________________________________________________________