Paula Martinez Lavanchy, the Research Data officer coordinating RDM training initiatives at TU Delft and 4TU.ResearchData co-organized the ‘First meeting of National Research Data & Software training coordination’ together with Mateusz Kuzak from the Netherlands eScienceCenter and Carlos Teijeiro Barjas from SURFsara.
This is her report about the event that took place on 3 March 2020 at SURF in Utrecht.
How did this initiative start?
In October 2019, TU Delft published its Vision for Research Data and Software Management Training. This ambitious plan aims at covering the different training needs that we consider relevant for researchers (including PhD candidates) at different stages of their research. This is a live document that needs constant evaluation and adjustment. So, since its publication, my task as the coordinator of RDM training activities has been to implement this vision and to investigate the challenges that can be encountered and possible solutions.
One of the first evident challenges is, how can we ensure that we are able to provide all the training we think is relevant for researchers in a sustainable way?
At the end of 2019, in a meeting with Mateusz Kuzak from the Netherlands eScienceCenter and Carlos Teijeiro from SURFsara, we discussed all our ideas for developing and organizing training at our respective institutions and already found some ways to collaborate. But, we also thought that the sustainability issue of RDM (including software) training is probably common at different institutions and that there are other challenges that we could be solving collaboratively within the training coordinators community. So, we decided to go national!
What was the meeting about?
We contacted everybody that we knew was involved in providing or coordinating training in the field of Research Data and Software skills at the Dutch Universities and other organizations and call for a meeting to:
- Network and exchange knowledge about the training activities at different research institutions around the Netherlands
- Identify the challenges and the needs for training
- Identify collaboration opportunities
The session took place on 3 March 2020 and 18 participants (including us – the three hosts) from 12 institutions joined for a whole afternoon to discuss training.
Here you can see the introduction slides of the meeting: https://doi.org/10.5281/zenodo.3712254
We initiated the session with 5 min pitches from each institution to know what type of training is in place. After that, we collected challenges encountered in RDM-generic training, Software-related training and Discipline-specific training.
This first part of the discussion provided useful information about the different approaches towards training for RDM-related topics. Sometimes training on RDM is provided under a broad topic like Research Reproducibility or Open Science, and sometimes it is split to focus on specific RDM-related tasks such as Data Management Planning or Data Publication.
At this point, I already identified with whom I should be exchanging experiences more in-depth about similar courses organized at TU Delft. It is in my to-do list to discuss with colleagues from the Centre for Digital Scholarship Leiden if and how to join forces to provide Data Carpentries for Social Sciences, which demonstrated to be very relevant for researchers at TU Delft Faculty of Architecture. I am also hoping to exchange knowledge with colleagues from VU Amsterdam about their approach to training on versioning control (training on Git). And, I could also get some more colleagues engaged in participating in our Code Refinery Train-the-Trainer event planned after the summer.
When discussing challenges, it was easy to identify commonalities such as lack of trainers and helpers for the training sessions, the low motivation of researchers to attend the generic RDM courses if they are not mandatory, the lack of practical exercises and applied material, or the the lack of awareness about innovative ways to provide RDM training.
Then, the most exciting part came: Is there room for collaboration to approach the challenges? Are we interested in collaborating? If yes, how can we collaborate?
A collaborative future
In the last part of the meeting, we brainstormed about ideas to work collaboratively on training. Everybody agreed that there is a lot of potential to work we could collaborate on in different areas.
Some example of collaborative efforts that were mentioned:
- National pool of trainers for domain-specific, data type-specific and/or software to exchange between institutions.
- Database of trainers profiles – in case institutions want to hire trainers or facilitate the exchange of trainers within institutions.
- Coordination of The Carpentries efforts – having a national coordinator of The Carpentries (or training in general) that can support people in creating a community around training, certifying instructors, and the development of training materials.
- Exchange of course materials from the different institutions in The Netherlands – focus on making them FAIR, exchange course description, modules, visual material and exercises (especially practical exercises).
- Training in developing open training materials in a collaborative manner (using The Carpentries framework)
- Train-the-Trainers programme – support staff providing training needs pedagogical skills and to learn creative ways of providing the content/exercises. In addition, there is also a need to learn about tools that researchers use for RDM in order to be able to teach about them.
In the next few weeks, we need to identify if some of these ideas could be organized within established initiatives already existing in the Netherlands e.g. LCRDM, NPOS, RDNL, etc. It is also necessary to discuss how the resources can be organized to continue the coordination of the Research Data & Software training at a national level.
The ideas will be shared with the initial group we contacted and we can decide as a community the best way to move forward.
Over 300 participants gathered to talk on:
Collective Curation: the many hands that make data work.
The programme focused on the community: the various stakeholders that play a role in ensuring digital objects are properly created, managed and shared.
The 2day conference started with a very interesting keynote on the Internet of Things (IoT) from Francine Berman, Professor in Computer Science at Rensselaer Polytechnic Institute (RPI) and this year based at Harvard. The main message was: IoT can be Utopia or Dystopia, it is all up to us. The IoT will generate TBs of data. How do we cope with that? How do we prevent devices for being hacked? Where is the privacy when you drive in an automated vehicle? The car knows which music you listen to!!
I spoke with people engaged in the training of people and had the chance to promote the courses Essentials 4 Data Support course and the MOOC Delivering Research Data Services. We ran this MOOC last year Autumn and we rerun the MOOC, starting February 24. Last year we had over 1600 participants!! The poster was presented in a poster:
One of the session was on a risk catalogue that can be used to review data management plans. There are legal, privacy, ethical and technical risks. It makes the data management plan more a working document, knowing the risks and how to manage them.
Second day, February 18
The second day started with a keynote from Kostas Glinos, Head of Unit for Open Science at European Commission, in the directorate-general for Research & Innovation since 1 June 2019. He spoke on how responsible research data management will be key in mainstreaming Open Science policies under the next framework programme, Horizon Europe. In that programme mandatory data management plans for all projects that generate or collect research data, and by introducing data management considerations as an element on which applicants can be evaluated. One of the reasons is that the EU wants to improve trust between science and society by engaging citizens in co-designing and co-creating research.
Another presentation I liked was on gaming: Lego; Metadata for reproducibility. In short:
Build a vehicle with 13 bricks, document what you have built and take it apart again. Another group will then build the car again using the documentation. After building the cars are compared with another. This generates lots of discussions and can be used for talking on the importance of metadata.
I attended a session on the Privacy Impact Assessment (PIA) from the ICPSR. The PIA investigates the privacy issues concerning data. The ICPSR trains researchers to acquire a passport that approves access ta various databases, based on their training and credentials. Researchers acquire a passport where the level of access is mentioned.
An impression of the conference:
Sandra Collins (Director of the National Library of Ireland) on Collecting and Curating the National Memory was the last keynote speaker.
The Irish National Library collects memories to share the culture and story of a nation. In the past that were ‘physical’ memories: newspapers, books and also lottery tickets! But in the digital age, our life is more and more open and our personal memories are digital-born. The National Library collects nowadays more and more digital items, already more than 300.000 Irish websites! The National Library works together RDA and DCC in curating their collection. And many volunteers to provide metadata to all kind of items.
Some conclusions of this iDCC:
– There is a strong focus on FAIR, and on how to put these principles into practice
– Reliability is becoming more and more an issue
– More and more data are generated, as more and more devices are connected. We as a society need to take care of that, in good collaboration with government and academia.
The next iDCC will be organised in collaboration with the RDA Plenary, Edinburgh, UK, from 20th to 22nd April 2021.
By Paula Martinez-Lavanchy
On the 19th of November I joined the meeting of the EUA-FAIRsFAIR focus “Teaching (FAIR) data management and stewardship” at the University of Amsterdam. In this post I summarized my key reflections of what happened during the meeting.
For those who are not yet familiar with FAIRsFAIR, it is an European project that started in March 2019 with the aim “to supply practical solutions for the use of the FAIR data principles throughout the research data life cycle. Emphasis is on fostering FAIR data culture and the uptake of good practices in making data FAIR.” The project has four main areas of work: ‘Data Practices’, ‘Data Policy’, ‘Certification’ (repositories) and ‘Training, Education and Support’. The meeting in Amsterdam was part of the activities of this last area, and specifically part of Work Package 7 of the project “FAIR Data Science and Professionalisation”. The main organizer of the event was the European University Association (EUA).
FAIRsFAIR project aims to be deeply connected with the European Open Science Cloud (EOSC) through a dedicated Synchronisation Force, which will offer coordination and interaction opportunities between various stakeholders, including the EOSC. It was not clear to me how exactly will the input of the project be used/adopted by EOSC in practice. However, the EOSCpilot work on skills was part of the presentations we saw, which suggest that the deliverables of FAIRsFAIR project are meant to become a building block of the EOSC, and not yet another layer of the cake of FAIR.
The various initiatives related to RDM training and FAIR data skills
The meeting started with five presentations that introduced the audience to different initiatives regarding or related to Research Data Management (RDM) training and/or FAIR data skills. Since we already talked about layers, I would divide the presentations in two: Framework initiatives and Implementation initiatives.
Framework initiatives: where the goal is to define the skills/competences that data scientists, data stewards and researchers should acquire around data management and to build up training curricula. There was a dedicated presentation about the EDISON project (Yuri Demchenko – University of Amsterdam) and FAIR4S (Angus Whyte – Digital Curation Centre – DCC). However, many other initiatives related to RDM skills and competences were mentioned: RDA Education & Training in Data Handling IG, Skills Framework for Information Age (SFIA), Competency Matrix for Data Management Skills (Sapp Nelson, M – Purdue), Open Science Careers Assessment Matrix, Towards FAIR Data Steward as a profession for the Lifesciences”. Kind of impressive and overwhelming to see the amount of groups working in the RDM training field.
Implementation initiatives: I call them implementation initiatives because these are initiatives already providing training or they are in the planning of creating an education program.
It was very interesting to hear about the work done by ELIXIR (Celia van Gelder – DTL/ELIXIR-NL), which is running training events for researchers, developers, infrastructure operators and trainers in the Life Sciences. ELIXIR also have a consolidated train-the-trainer- programme that provides training skills and have developed a really nice platform (TESS) where they announce training, make training materials available, but also provide guidance on how to build training.
We also had the opportunity to hear about the “National Coordination of Data Steward Education in Denmark” (Michael Svendsen – Danish Royal Library). They used a survey approach to investigate the landscape of expected skills that Data Stewards should have (results to be published soon). Based on this, the Danish Royal Library together with the University of Copenhagen, are planning to design a Data steward Education curriculum (launch 2021) and drafting a specific training module for the study program of librarians.
In summary, the terms ‘training’ and ‘education’ were used in the different presentations, but also many target groups and many types of skills with a different degree of relevance depending on the project or the initiative working on it. While this diversity was impressive, it felt somewhat difficult to understand the rationale for all these parallel projects and approaches, and how will they all lead to a coherent, agreed, pan-European framework for RDM skills and competences.
Advantages, disadvantages, challenges and opportunities
In the afternoon session we had break out discussions where 4 topics were proposed:
- Teaching RDM/FAIR at Bachelor/Master level
- Addressing RDM/FAIR at Doctoral/Early-career researcher level
- Generic Data Stewardship and FAIR data competences
- Disciplinary/Domain-specific Data Stewardship and FAIR data competences
We had two sessions of discussion, so each of us had the opportunity to join two different topics. For each topic we discussed advantages/disadvantages, good practices, missed opportunities, challenges, target audiences, possible synergies, etc. I joined topic 1 (Teaching RDM/FAIR at Bachelor/Master level) and 4 (Disciplinary/Domain-specific Data Stewardship and FAIR data competences). In both breakout groups we had rather broad discussions and exchange of knowledge, with more or less structure, but I found them very interesting and valuable. The organizers promised to report on the discussion results, so I will not duplicate their efforts. There will be a following post for sharing my own overall reflections about education and training on RDM. So to be continued.
What are the next steps for the FAIRsFAIR project with regards to skills and competences? The organizers intend to use the results of this meeting and the results collected in the “Consultation on EUA-FAIRsFAIR survey on research data and FAIR data principles”, a survey that they recently run, in order to define the activities of the project in the track of training and education. So hopefully more on this soon.
The organizers of this event have recently shared a Short summary of the Focus Group workshop at https://www.fairsfair.eu/articles-publications/fairsfair-focus-group-university-amsterdam.
TU Delft is delighted to publish its Vision for Research Data and Software Management Training.
The document focuses on responding to the skills needed by PhD students and early career researchers regarding research data and software management. While the focus is on TU Delft, we recognise the need to work with others to make this fully successful (for example, 4TU.ResearchData membership of the Carpentries)
1. Where possible, data and software management training should be built upon the existing generic and faculty-specific courses
2. But new courses are also necessary to deal with the fast changing demand in research data
3. Building and delivering such training must be a collaborative effort between faculties (researchers and support staff), the library, graduate school and other university services. Engaging with organisations outwith TU Delft will also be vital to make training resources sustainable.
4. In order to successfully implement this vision, researchers should receive the proper incentives to take part and contribute to the training.
5. The library and graduate schools should continuously engage in consultation processes with PhD students and researchers (including PhD supervisors), and used the feedback to iteratively improve and update the content
6. All material produced for the courses described in this vision will be published and made available under a Creative Commons – Attribution License (CC-BY 4.0)
7. All newly developed courses will be accompanied by clear learning objectives, a lesson plan and a description of the methods selected for the training
In the diagram, each separate rectangle is a course that TU Delft wishes to create or is already teaching.
The courses on the lower rungs are more generic and run on a regular basis, with TU Delft library playing a leading role
The courses higher up are more specific. Here the library coordinates but the input comes from researchers with specific interest in the topic.
The Carpentries are a key part of this. Their model for building and sustaining course lessons is ideal to develop training lessons that are flexible, scalable and long-lasting.
Presentation given by Alastair Dunning as part of OECD Global Science Forum: Digital Skills for Data Intensive Science Workshop, Cologne, 28th October 2019.
MOOC tutors. From left to right: Sarah Jones, Rene van Horik, Alexandra Delipalta, S. Venkat, Ellen Verbakel.
In the second week of the Delivering Research Data Management Services we focused on “Finding the gap” in your RDM Services. One way to find the gap is by using the RISE tool. This tool can be used to define how mature the institution is on topics like research data policy and strategy, digital preservation, training, and active data management.
We asked the learners about their experiences and they found it useful reflecting on this:
“That was a good exercise, naming strengths and challenges. I am always very aware of the challenges, but it is good to reflect a moment on the strengths and realize that we have done some good work already.”
Many learners identified areas in which their organisations were not doing everything well. Some had a lack of money, people, resources or interest from researchers. Several learners also realised that services are in place in their institutions but very diffuse and spread across multiple units.
Learners liked the gap analysis exercise and the SPARC online tool https://sparceurope.org/evaluate-your-rdm-offering. You can see an example output from this above. In the online forum learners shared results which showed a great difference in strengths and weaknesses across organisations. Naturally, some organisations didn’t want to share the outcomes because the information can be very confidential. We encouraged them to speak with others in the organization to evaluate the assessment.
Many learners realised that they didn’t know about all the services already in place in their institution. Their first steps will be to make an inventory of what is available and see how they can align these with their own activities. Collaborating with colleagues to coordinate provision is key.
After finding the gap and having evaluated their efforts so far, the learners started week 3, focusing on how to set up services and good starting points.
Our MOOC runs until 14th October and will run again later in the year or early 2020. Find out more at https://www.futurelearn.com/courses/delivering-research-data-management-services
Image: MOOC tutors. From left to right: Sarah Jones, Rene van Horik, Alexandra Delipalta, S. Venkat, Ellen Verbakel.
Just over a week in and we all continue to be overwhelmed by responses to our new MOOC* on Delivering Research Data Management Services. We have over 1400 learners from 116 countries and they have been very active in the discussion forum. Literally hundreds of comments and questions – and such insightful responses to the material.
Ellen and Sarah moderated the first week of the MOOC and have been inspired to do more online teaching as a result. This week you have Rene, Sarah and Ellen answering your questions. In the first week we learnt about the basics of RDM services, the data lifecycle and making the case for support. Participants watched various videos and read case studies, then reflected on the priorities at their own institution. Forum comments show that participants found the inputs from people we interviewed useful:
‘I agree with Gavin that ‘well managed data leads to higher quality research’.
‘I liked the summary by Tanita Casci (Head of Research Policy at the University of Glasgow) of what good research is like: “Good research is research that is well-planned, well-executed, well-documented, and widely shared.’
Data Management Planning and data stewardship were key discussion points. Many funders and organisations worldwide are encouraging DMPs but there are concerns about ensuring requirements are realistic and support researchers’ practices. The data stewardship approach at Delft also raised a lot of discussion. People appreciated their emphasis on open science and found the model a great way to bridge between the various services available in the institutions, as well as between data services and research communities.
The discussion on the stakeholders provided us with lots of insights from the institutions you all work in. The overall conclusion was that there is often a lack of engagement from senior management. Many people wanted to raise awareness, especially amongst researchers. Services could also be unconnected across the institution so support staff wanted to join up provision to offer a coordinated set of RDM services.
We have a few learners from a research background too. Our course is aimed specifically at those delivering RDM services. Some lessons will be transferable to other contexts, but those wanting to learn how to manage and share data should check out parallel courses such as those noted below:
Our MOOC runs until 14th October and will run again later in the year or early 2020. Find out more at: https://www.futurelearn.com/courses/delivering-research-data-management-services
* A MOOC is a Massive Open Online Course. Our MOOC is available on the FutureLearn platform and is free to all.
This blog post is also posted here.