Connecting the dots in the FAIR data support ecosystem

Internship type: Communication & case study development
Institution(s): TU Delft, TU/Eindhoven and University of Twente
Duration: 3 months (minimum)
Hours/week: 20 (minimum)
Preferred start date: February/March, September 2022
Supervisor name & contact details: Yan Wang (Data Steward Coordinator, TU Delft)

Project description

Making data Findable, Accessible, Interoperable and Reusable (FAIR) requires a truly collaborative effort, not just involving researchers but also  research data management (RDM) support service teams across institutions. There are several essential support services that are core to FAIR data, such ase data repositories, data management plans (DMPs) and Open Access (OA) publishing platforms. Meanwhile, these services are also connected with many other existing research support teams, including ICT, privacy, legal and ethics teams, for example. 

Currently, these services are often provided to researchers in an ad-hoc way and as one service at a time. Data stewards, as professionals who provide RDM and FAIR data support for researchers, serve as one of the main communication channels between researchers and RDM  support services. It is often the role of the data steward to understand and liaise with the various research support teams respectively to advise and guide researchers on best practices for managing their research data. With so many diverse services available, navigating the RDM/FAIR data support ecosystem can be a daunting and challenging responsibility. 

It is, therefore, worth exploring the connections among RDM support services and presenting them in a more intuitive way for researchers and support professionals to comprehend. Knowledge of such connections could allow for the implementation of more efficient workflows to support researchers, and promote good RDM practice and FAIR data within research institutions. For instance, if a researcher publishes their data or software code in the 4TU.ResearchData data repository, it follows that they may also be interested in publishing an OA article about their research and can be assisted with this process Alternatively,  if a researcher describes their plan to collect sensitive data upon writing their DMP, they could be offered a customised path throughout their research lifecycle with guidance  provided at various stages,  relating to privacy/ethical checks, data licensing, and data publishing options.  

This internship aims to explore and clarify the FAIR data support ecosystem and establish a pragmatic workflow to better connect support services teams within research institutions. Furthermore, it will be interesting to compare these workflows across different research institutions, and evaluate the merits and shortcomings of each.. This novel workflow will be  different from the concept of ‘one-stop-shop’ by revealing  dynamic networks of diverse support services, and signposting  specific services when certain conditions are met or expert guidance is required during the research lifecycle. This workflow will help to align and avoid duplication of efforts across different RDM support services teams, and will . connect the dots in the FAIR data support system. 

The intern will liaise with data stewards, researchers and RDM service teams from the 4TU.ResearchData partner institutions (TU Delft, TU Eindhoven and the University of Twente) and develop case studies that: 

  • Describe the current support workflow of all relevant services supporting FAIR data at each partner institution.
  • Evaluate how each service is perceived/used by researchers, e.g. which services are frequently used, which services are important but less known and/or deserve more publicity, etc. 
  • Analyse the commonality and uniqueness of each institution’s workflow.
  • Identify gaps and opportunities in the current RDM support ecosystem and communication about the service teams.
  • Propose suggestions or help organise joint sessions to improve communication among researchers, data stewards and service teams. 

Case studies will be published as dedicated articles on the 4TU.ResearchData website and published within our social media channels (Slack, Twitter and LinkedIn) and newsletter. The intern will have an opportunity to present their work at meetings, conferences and as a peer-reviewed publication. Any work conducted during this internship should be published and shared under a CC-0/CC-BY license. 

Prerequisite skills

  • Good communication and writing skills are  essential, and experience of conducting interviews is desirable. 
  • A goal-oriented mindset is necessary. The intern is expected to be pragmatic and cooperative while thinking independently. 
  • Research experience or familiarity with the research lifecycle in science/engineering/design/social science disciplines is desirable. 
  • Familiarity with institutional research support in the above mentioned disciplines is desirable. 

Benefits for interns

The intern will:

  • Obtain holistic insights into RDM support from an institutional perspective.
  • Connect with various RDM support stakeholders and understand the complexity of a multi-actor environment.
  • Learn and practice stakeholder analysis, gap analysis and case study development which are fundamental skills for both research and practice.

How to apply

Please send your CV and cover letter (in English, 2 page max for each) to with the subject line ‘4TU.ResearchData Internship Programme’. In your cover letter please include your motivation for applying for this project. Please briefly explain what interests you the most in this project, and feel free to mention anything particular that you would like to explore/learn from this project. All applications will be subject to a review process. 

For questions about the project activities, please contact the supervisor, Yan Wang ( For more information about how to apply, contact the community manager, Connie Clare ( This internship can be arranged for remote working. Details will be discussed with the supervisor.