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Engaging Researchers with Data Management

Connie Clare
Maria Cruz
Elli Papadopoulou
et al.

Case studies

3. Engagement through Training

Connie Clare, Annemarie Hildegard Eckes-Shephard, Yan Wang, Alicia Hofelich Mohr, Jenny McBurney et Helene N. Andreassen

Texte intégral

1Direct training requires substantial time and effort, but is one of the most effective ways to make people aware of the importance of Research Data Management (RDM) best practices. The following case studies are each aimed to engage researchers with research data through different training methods:

  • Bring Your Own Data (B.Y.O.D.) workshop at the University of Cambridge;

  • Methods Class Outreach at the University of Minnesota;

  • PhD course at UiT The Arctic University of Norway;

  • Open courses at UiT The Arctic University of Norway.

These cases were initiated either by individuals or a small group of RDM support staff, illustrating the potential for a few people to make a difference. The size of the relevant institutions ranges from small to large, showing how such approaches can be implemented across a diverse range of institutional settings.

Where There’s a Will, There’s a Way

2Don’t worry if you’re short of resources: our contributors had the same concerns. These activities don’t cost much in terms of training materials and infrastructure, and you can select the most suitable training approaches according to the number of staff at your disposal. If you already have an RDM team in place, you can gain inspiration from UiT in Norway and focus on organising a course tailored to a particular target group. If you have concerns about the capacity of your team, you might find the cases from Cambridge and Minnesota particularly appealing. We hope that you will be inspired by these stories and that you can find suitable training methods for your own institution.

3.1. Bring Your Own Data (B.Y.O.D.) Workshop at the University of Cambridge

A University of Cambridge Data Champion shows how one volunteer can engage with peers and provide valuable support through leading an interactive workshop on RDM best practices.

Table 3.1,

CC BY 4.0.

3Note that the figures above are for the Department of Geography, University of Cambridge, and not for the University of Cambridge overall.

4Scientific papers tend to be written and presented with clarity and structure, but most would agree that clarity and structure are not always features of the underlying raw data. Although most researchers embark on their academic journey with the intention of adhering to good data management practices, as soon as they are faced with balancing data management against the other pressing demands of a deadline-driven research schedule, it drops in priority. It rarely takes long before finding and organising files becomes a dreaded digital chore.

A Helping Hand

5University of Cambridge Data Champion, Annemarie Hildegard Eckes-Shephard, is currently undertaking a PhD in Biogeography. Her doctoral research focuses on developing a mechanistic growth model to determine how trees respond to climate change, and this research experience — together with her previous role as a crop database curator — has made Annemarie familiar with large datasets and well-equipped with tips and tricks to help others.

6Annemarie understands the many challenges of managing research data and identifies time as a major constraint: ‘Researchers are often too busy to allocate time for organising their digital files, yet if they could only prioritise this task, it promises to save time and frustration in the long-term.’ Annemarie highlights other barriers to proper data management as ‘a general lack of motivation to structure data or insufficient training on the topic’: researchers simply don’t know how or where to start organising their data.

A ‘B.Y.O.D.’ Invitation

7As an empathetic PhD student, Annemarie wanted to share her knowledge about best practice with her colleagues within the Department of Geography. She therefore started ‘Bring Your Own Data’ (B.Y.O.D.), a project part-funded by Jisc,1 which brought researchers together for monthly workshops on how to organise their data to improve the quality of their research. Each two-hour workshop began with a short introductory talk delivered by Annemarie to teach important aspects of data management, including:

  • file-naming conventions;

  • writing ‘README’ files (messages to future self);

  • structuring files and folders;

  • using a data audit framework2 to help researchers think about their data management.

As the name implies, B.Y.O.D. encouraged participants to bring their own laptops and start organising their data in an interactive and inclusive environment. Annemarie hoped that working in a group would facilitate collaboration and networking whilst inspiring individuals to work towards open science using good data management practices. She also believed that ‘making an official event in their calendar and therefore setting time aside would help researchers overcome the perception of not having enough time for data management.’

Fig. 3.1 The ‘Bring Your Own Data’ workshop is underway at the University of Cambridge.

© Annemarie Eckes-Shephard, CC BY 4.0.

Feedback for Future Learning

8Participants were asked to complete a short survey before and after each workshop to provide information about their aims and objectives for the session and how they were planning to achieve them, and to provide feedback with suggestions for how future workshops could be improved.

9While B.Y.O.D. was well-received by all the participants, Annemarie admits that over time it became difficult to encourage people to attend the event, and that more support would have been required to publicise future workshops. Perhaps the use of promotional materials (for example, posters and flyers) would have increased visibility to a wider audience. Nevertheless, B.Y.O.D. is a shining example of how an individual effort can generate a demonstrable impact and drive cultural change within a research community.

3.2. Introducing Data Management into Existing Courses at the University of Minnesota

To provide more discipline-relevant support, the University of Minnesota RDM team contacts staff who are teaching graduate research methods, and works with them to embed suitable RDM training in their courses.

Table 3.2,

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From Grassroots to Widespread Influence

10Back in 2015, two recent PhD graduates working at the University of Minnesota (UMN) contacted every instructor of graduate research methods in social science, and proposed integrating disciplinary Research Data Management (RDM) education into their courses. It was a bold proposal, but since then this disciplinary RDM training has grown from its small-scale, grassroots beginnings, becoming integrated into 60 courses across 7 colleges.

11Alicia Hofelich Mohr, one of these two PhD graduates, is currently a library collaborator at the College of Liberal Arts. These collaborators are disciplinary experts based at their domain-specific college, and their job is to work closely with the RDM colleagues from the library to jointly provide general and domain-specific research support, including training, to all faculty members.

12The University of Minnesota has a strong culture of good RDM. This is partly thanks to its early adoption of RDM support; since 2010, the RDM team has grown from around 10 staff members to more than 25, and includes librarians and collaborators from different colleges.

13Being embedded in regular research methods courses, the RDM training usually lasts between 60 to 90 minutes with a class size of five to 20 students. All courses start with the same basic RDM principles: file-naming and file organisation; data sharing; archiving; and security issues. Additional subjects are introduced depending on the discipline.

A Lightweight Approach Makes for an Excellent Return on Investment

14If you want to introduce elements of RDM training to existing courses within your institution, Alicia suggests you can ‘find a few motivated people and that is really all you need to start. When you are a small team, you can do things quickly’. Their lightweight approach does not cost much but makes an excellent return on investment, and the disciplinary elements of the training clearly demonstrate the relevance of RDM to the attendees.

15The training received good anecdotal feedback, and was a welcome addition to courses. Many people are now aware of RDM in general, and interest in data management has grown. The RDM training providers no longer need to approach course instructors: instead the course instructors (re) invite them, and many instructors have even found it useful to use RDM practice in their own work. The RDM training is also starting to attract the interest of researchers and principal investigators who hear about it from their students. ‘Sometimes principal investigators learn about RDM through word-of-mouth, and then ask for help from us so they can incorporate the things we talk about in class into their own projects, ’ says Jenny McBurney, a research services librarian at the UMN Libraries.

Fig. 3.2 RDM training in one of the research methods classes at the University of Minnesota.

© Kate Peterson / UMN Libraries, CC BY 4.0.

Create a Community to Make It Sustainable

16‘One challenge we are still facing is how to talk about RDM in disciplines where RDM is not a “thing” yet, ’ says Alicia. This is where you need the disciplinary collaborators: they can find the place to introduce RDM topics that resonate well with the researchers. This ensures the training delivers not just appropriate knowledge about RDM, but also engages the interest of the researchers with data management skills and provides examples of how to turn their knowledge into practice.

17To keep the RDM training growing, you also need a good team. Despite the low overall cost, some time and effort are required to choose an appropriate target course, and to prepare and coordinate the delivery of topics relevant to that particular discipline. ‘After a while you receive recurring course invitations; meanwhile you want to reach out to new courses — it takes dedicated people, ’ explains Jenny. Sufficient availability of trainers, both librarians and disciplinary collaborators, is needed to ensure coverage of courses across multiple disciplines throughout the academic year.

3.3. Engaging with RDM through a PhD Course on Academic Integrity and Open Science at UiT The Arctic University of Norway

UiT The Arctic University of Norway engages with PhD students by embedding modular RDM training in its academic skills course, and ensuring close alignment with its other transferable skills training.

Table 3.3, CC BY 4.0.

Why PhDs?

18‘PhDs are in most cases very positive about new developments and we should motivate them to do what is expected or required, ’ explains Helene N. Andreassen, the Head of Library Teaching and Learning Support at UiT The Arctic University of Norway. One of the courses Helene and her team provide is a bi-annual multidisciplinary seminar series3 with a focus on academic integrity and open science, available to all PhD students at the institution. Since it began in 2015, participants have come from a rich variety of disciplines, and since 2019 the seminar series has been made obligatory for law students. What’s more, an increasing number of participants choose Research Data Management (RDM) topics for their final essay, which is required to complete the course.

What Works? Good Content and a Thoughtful Course Layout

19In order to prepare the content of the course, the team works closely with other groups at the university, such as the research administration and the IT department. While the overall approach and the reading list are multidisciplinary, the course design still takes disciplinary differences into account by including activities that allow reflection on similarities and differences across disciplines and methodological approaches. In the RDM session participants can choose between different modules based on the type of data they deal with in their research.

20After a general introduction, the course is split into groups focusing separately on data with sensitive information and data with non-sensitive information. There might not always be a perfect format that suits everyone given the heterogeneous nature of research and the increasing number of interdisciplinary studies. Nevertheless, Helene and her team continuously work on improving the content and how they deliver the course.

Fig. 3.3 A moment during the PhD course.

© Erik Lieungh/UiT The Arctic University of Norway, CC BY-ND.

Course Preparation is an Educational Process Itself

21Ten people teach and develop the content of the whole course, with three dedicated to the RDM modules. These teachers coordinate with staff responsible for PhD programs at the faculties that give credits to students, as well as the High North Academy,4 a special unit that coordinates all doctoral courses on transferable skills at UiT. Teachers also devote time to promoting the course through formal and informal information channels, and evaluating the exam essays.

22The course preparation is, in itself, a team-building and professional development activity. The teaching group meets every month to read relevant papers and reflect upon how to support PhDs. Development of the reading list for the course is a joint task.

23Contributing to the development and execution of the course is a lot of work and requires people’s time and commitment. ‘It is all voluntary, but very good for the team spirit, and I think we will continue doing it, ’ says Helene.

RDM Training as an Institutional Effort

24RDM is an emerging subject requiring joint efforts across the university to help develop and promote it. In addition to working on their own course, the team is also in close contact with leaders of related courses, to share materials and ensure consistency of message across the curriculum. For instance, supervisors attending a course on supervising PhD students are now encouraged to send their students to complete the RDM training. The team also talks about RDM training to the university’s vice-chancellor of research, whose support contributes in raising awareness across the various departments of the institution.

3.4. Open Courses at UiT The Arctic University of Norway

Lessons learned while engaging researchers through a series of open, online RDM training courses at UiT The Arctic University of Norway.

Table 3.4,

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Opening the Door to RDM Training

25In 2016, the library of UiT The Arctic University of Norway launched a brand new archive for open research data: UiT Open Research Data. To train researchers and graduate students how to use it, the library developed introductory courses, with time for questions and discussions. After one semester, they realised that they also needed to include more narrowly defined courses in the programme, and this opened the door to introducing various Research Data Management (RDM) topics. ‘If you open one door, there will be people knocking on other doors too. For instance, when we talk about open data, there is always someone in the audience wanting to talk about sensitive data, ’ reflects Helene N. Andreassen, Head of Library Teaching and Learning Support.

26The UiT Library has gradually developed a series of short open courses:5 currently it consists of one introductory course focusing on the ‘whys’ and ‘hows’ of RDM, and seven thematic courses focusing on topics such as how to write a Data Management Plan (DMP) and how to share research data. The courses are announced on the university web portal, and all researchers, students, and administrative staff at UiT can freely attend any of the courses. All courses are delivered both in classrooms and via Skype, with Norwegian and English as the languages of instruction.

Tips for Embedding Engagement in the Course Delivery

27Helene offers the following tips for embedding engagement tactics into the courses:

  1. Provide online video-conferencing to reach people remotely. This is especially helpful for multi-campus institutions. UiT has nine campuses across the northern part of Norway, and providing regular classroom training to all UiT staff is challenging. People find it convenient to follow the courses via video-conference (Skype, for example) and bringing together a group in this way helps to bridge the distances. However, to make the best use of video-conference technology as a teacher, it is important to practice how to deliver the course in this new way. In particular, you should become familiar with aspects such as sharing screens, using desktop applications, and being comfortable with talking to people who are only present via a camera.

  2. Keep the courses short and focused. All UiT open courses are limited to 45 minutes and focus on specific topics so as not to overload participants.

  3. Make the course interactive; using a variety of teaching materials helps. A selection of thematic RDM issues are currently being recorded as separate instruction videos that will be made available online. This will make it possible to adjust the balance of the course: by asking participants to watch selected videos before coming to the course, more time can be devoted to activities and discussions.

  4. Keep the content of the course up-to-date. The team pays attention to emerging subjects, such as the European General Data Protection Regulation (GDPR), or data processing agreements, and regularly incorporates new topics into the course. Helene explains: ‘We actively seek out the gaps in the course series, as it should eventually reflect the entire RDM life cycle.’

  5. Use all channels at your disposal to promote the course. The RDM training at UiT is presented in a central portal, containing all the necessary course information, calendar of dates, and much more. The team use social media channels, mailing lists, personal contacts at the faculties and, of course, rely on the message being spread by word of mouth. Key individuals such as subject librarians (specialised librarians in certain disciplines) are also encouraged to send information to their networks.

  6. Do not just think about engagement: start doing it. This is especially crucial for large institutions with multiple campuses. The UiT RDM team is based on only one campus, but regularly goes on ‘Open Science Tours’ to other campuses. The team uses these tours as an opportunity to talk to campus managers and local library staff, provide courses, and generally to make themselves visible to colleagues on different campuses.

Since the introduction of the open courses, there has been an increasing proportion of researchers among the attendees, relative to administrative staff. This could indicate a cultural change across the institution, and an increasing appreciation of RDM principles among researchers.

28Helene offers a final tip to those interested in implementing a similar initiative: ‘Don’t wait too long until you get going. You don’t need a full-scale plan, just start with what you have. We have learned a lot simply by meeting people.’


1 Jisc,

2 Data Audit Framework methodology, 26 May 2009,

3 Information about the bi-annual multidisciplinary seminar series is available at

4 High North Academy,

5 Open Courses at UiT Library,

Table des illustrations

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Légende Table 3.1,
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Légende Fig. 3.1 The ‘Bring Your Own Data’ workshop is underway at the University of Cambridge.
Crédits © Annemarie Eckes-Shephard, CC BY 4.0.
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Légende Table 3.2,
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Légende Fig. 3.2 RDM training in one of the research methods classes at the University of Minnesota.
Crédits © Kate Peterson / UMN Libraries, CC BY 4.0.
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Légende Table 3.3, CC BY 4.0.
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Légende Fig. 3.3 A moment during the PhD course.
Crédits © Erik Lieungh/UiT The Arctic University of Norway, CC BY-ND.
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Légende Table 3.4,
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