Helping train RDM service providers through our upcoming MOOC

As part of a coordinated effort between the DCC and Research Data Netherlands (RDNL), a MOOC is in its early stages of development with a working title of “Delivering RDM services”. Our aim is to give some pointers to research support staff such as libraries, IT departments, research offices, ethics departments and so forth, as opposed to the data generators, in what to look out for when delivering services. It will not be the same as some other online learning resources that you may have seen which are more researcher-centric, e.g. MANTRA, RDMSmooc, the forthcoming FOSTER toolkit and the Open Science MOOC. In contrast, this MOOC builds on Essentials 4 Data Support and DCC training materials and tools focussed on supporting data creators through the provision of services.


The skeleton of this MOOC can be found here and comments are welcome if there is anything in particular that you, the research support staff community, may want us to cover while we’re still in this early phase. As you can see, there are five modules that have been proposed, but for now we’ll be happy just to get Module 1 completed - making a MOOC is a learning experience for us after all! The five proposed modules are:

  1. The business of RDM services: the drivers, players & what needs to be done
  2. Quick wins and starting points for data support
  3. Services during the active research phase
  4. Data publishing and sharing services
  5. Refining and improving services

If you were at IDCC18, and had a chance to peruse the posters, you may have seen a poster for this MOOC too – if not, don’t fret – you can see it here. Speaking of IDCC18, I guess I should introduce myself since (a) I was there (as well as my colleagues from the DCC also making this MOOC, Sarah Jones and Magdalena Getler), but (b) I’m new at the DCC and you may have missed me. I’m Venkat, and I’m the new training lead and research data specialist. I come from a biology background and used to work in a project that produced and handled a lot of digital data, mainly images, but I have no formal background in RDM. Although IDCC was slightly a baptism of fire for me (I hadn’t even started my new role at that point), the conference was a great experience and I got to meet many new people and hope to make many more contacts.

Anyway, back to this MOOC: one topic in Module 1 that we aim to cover is how one should start with self-assessment of where their institution stands in terms of RDM infrastructure. If you are part of an institution that has poor RDM services you may find yourself playing catch-up with the requirements of funding bodies, for instance. On the other hand, you may be very up to speed with RDM services but simply want to check to what degree. There are a number of ways to go about this at the moment with different tools available from various groups internationally.

One such tool is the research infrastructure self-evaluation framework (RISE), developed at the DCC by Jonathan Rans and Angus Whyte, and is available freely to implement. Initially, RISE was tested with 16 UK institutions and since has been deployed by many others sometimes without DCC support. Unlike other evaluations that were already available, RISE aims to give a health check on an institution’s level of capability regarding how well it is placed at delivering the services needed by researchers for their data and the RDM lifecycle. What are the checkpoints set out by RISE? The first implementation of the framework consisted of a 10-point plan: 10 service areas, subdivided into 20 capabilities, and each of these defined by 4 statements: Level 0 (no action); Level 1 (reactive); Level 2 (proactive); and Level 3 (sector-leading).

So…an example of how RISE has been used can be found at TU Delft (4TU) from June 2017. The research data services (RDS) department undertook the survey by enlisting ten staff members spanning various stages in the lifecycle of data, including four members from RDS/4TU.

Together with such a tool as RISE and other evaluation tools out there, our “Delivering RDM services” MOOC hopes it can show the research services staff community some useful information to better tailor their infrastructures.

In each section of the toolkit we’ll be introducing support staff to activities they need to address, such as doing a health check on their current institutional infrastructure, providing storage and tools to help researchers create and analyse data, or the role of data stewards in managing data and ensuring it is FAIR. We will explain concepts and introduce tools and methodologies that can be used, as well as profiling examples of practice from elsewhere, such as the 4TU use of RISE. These case studies will help others implement RDM services at their own institution.

We have some ideas of people to approach, but would also welcome input from you. What examples can you share from your practice? Do you have blog articles we could include as reading exercises or would you be willing to be on video? Please review the outline and – get involved!