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Cambridge Data Champions – reflections on an expanding community and strategies for 2019

The Cambridge Data Champions (DCs) advocate good Research Data Management (RDM) and Open Data practices to researchers locally in their departments, within Cambridge University in general, and sometimes further afield. They network with one another, exchange good methods of RDM, share ideas and, as a collective, reflect on current issues surrounding RDM, Open Data and researcher engagement, where a major shared goal is to establish best practices when it comes to research data. By attending bi-monthly forums facilitated by the Research Data Team, the DCs convene as a community, hear speakers presenting on relevant topics, and engage in workshops that will help them in their ‘championing’ activities. Following up from our latest blog which summarised how a workshop led to the creation of cartoon postcards as a new tool to add to the DCs’ resource kit for RDM advocacy, we are now reflecting on initiatives that sprung from workshops during the past year and are considering the challenges and opportunities that this programme brings as it approaches the end of its third year. 

Growing 

The programme started in Autumn 2016, comprising researchers who volunteered to become local community experts and advocate on research data management and sharing. Our first call welcomed 43 DCs (September 2016), our second call 20 DCs (March 2018) and the third call 40 DCs (January 2019). For simplicity, this year we also added to our statistics the “affiliate” DCs, who are colleagues who contribute to the DC community in other ways (as interested members of Cambridge’s RDM Project Group) and not necessarily through channelling their RDM efforts for the benefit of a specific department.

We are now a community comprised of 87 active DCs. 

Graph showing number of Data Champions (current and alumni) per year between 2016 and 2019.
Total number of Data Champions who joined in each year (orange column indicates Champions who are still active; blue column indicates Champions who are now alumni).

Communities within a community 

Over the last year we caught ourselves using words such as the ‘old DCs’ and the ‘new DCs’ and what we really meant was ‘established DCs’ and ‘new DCs’, with the latter group being those joining the programme each year. In September we celebrate the programme’s third birthday and it is reasonable to expect that there will be more experienced DCs who have already built their networks and have, more or less, a stable offering of RDM support and an enhanced understanding of the needs of their department. On the other hand, there are those who are being welcomed into the group who seek, to differing degrees, initial support from both the RDM team and their fellow colleagues in order to become successful DCs. It is easy to imagine that different layers are being developed with different needs, both in terms of support and engagement.  

Through various activities and feedback from DCs, we now have a good quantity of raw data to analyse their needs for being, as we called it, ‘a good Data Champion’. We have brainstormed ideas which we are putting into action to respond to the challenges of an ever-growing Data Champions group. 

Planning  

DC Welcome Pack 

Word cloud image of "welcome" in different languages  - front page of the Data Champion Welcome pack.

Every year we circulate the Data Champions Welcome Pack to coincide with the inductions we organise to welcome new DCs into the group. This year we included in the pack what it is expected from a DC when s/he joins the programme so that expectations are clearly communicated from the beginning and are the same for everybody. 

Document describing what Data Champions are expected to do as part of the Programme.
Page from the Cambridge Data Champions Welcome Pack

Bi-monthly forums 

Lightning talks have been introduced as a standard item in each forum. These have provided DCs with the opportunity to discuss aspects of RDM they are working on (e.g. new tools and techniques), or to feed back to the group on DC activities undertaken in their departments and data-related events they have attended so that the whole group can benefit. Importantly, the lightning talks have been used by DCs to problem solve, where the collective knowledge and experience of DCs attending a forum has been harnessed to address particular challenges faced by individual DCs. This is where the community aspect of the programme truly shines. 

It is always a priority for us to invite speakers to forums who are external to the programme, reflecting the needs of both the new and established DCs. For example, Hannah Clements from Cambridge University’s Researcher Development Programme (RDP) spoke to the DCs at the January forum about mentoring, providing guidance on how support can be best delivered within the DC community. In the May forum, we had talks and discussions from a panel of experts working on different aspects of data archiving. The panellists came from across the University bringing a diversity of experience, grounded in clinical governance, computing, and more traditional archiving. These examples are just a couple of the themes that we have covered so far in the forums, which have been derived predominantly from information provided by (and the needs of) the DCs themselves. Additional topics that we plan to cover in future forums include issues surrounding reproducibility, IP and commercialisation, publishing and the impact of research data.  

Key aims of these forums are to not only facilitate networking between DCs but to also act as an arena for the transfer of knowledge along the ‘researcher pipeline’, from forum to DCs and from DCs to researchers in their departments.   

DC specialisation group 

As a community, we need to be able to map expertise internally and understand the make-up of such an organic group at any given moment. This makes it is easier to support each other and create collaborations, but also improves how we promote the programme externally.

Table showing specialisation categories and sub-categories for Data Champions
Areas of expertise amongst our Data Champions

This led to the formation of the DC specialisation group, consisting of one of us and six of the DCs, which determined how to categorise expertise within the group. As a result, a spreadsheet was created where all DCs can chart their specialist areas and update or amend when necessary (and at least annually). We have top level categories for simple statistical analysis and second level categories that offer more specific details for the benefit of the DC community. 

The next stage is to include the wider research community and improve how various stakeholders can reach the appropriate Data Champions for initial advice and support in RDM issues. One way to do this is by presenting more coherent and consistent specialisations on the Data Champions’ website, using the categories which we have already created for internal use within the group. This stage is due to begin this month and we hope to report on our efforts next year.  

Branding group 

A growing community is inevitably going to bring to the forefront various identity discussions. With this in mind, we formed a branding group to examine if a DC logo should be created to enhance the Data Champions’ visibility and raise their profile amongst their peers when advocating for RDM. A logo has been created and is going through various stages of approval before it will be released later this year. 

Pilot programme – Mentoring  

In February 2019, we initiated a pilot mentoring project as part of the induction process for the new DCs. The mentors are established DCs who have volunteered to support those new DCs wishing to take part in this pilot exercise. This followed on from our January forum where the benefits of mentoring for both mentees and mentors were outlined by Hannah Clements of RDP. At this forum, which preceded the University-wide call for new DCs, we also held a workshop where DCs were divided into three groups and asked three questions: what do you wish you knew when you first became a DC that you know now; what could you offer as mentors to the new DCs; how do you think the mentor-mentee system could work? The responses from DCs in the three groups informed the implementation, structure and aims of the mentoring pilot.  

Our aim is to learn from this project in close consultation with both mentors and mentees. We want to see if this process helps new DCs to establish themselves within their departments/institutes. Will it be effective? The findings will inform our steps for the following year. Watch this space! 

Fostering clusters within departments 

We have excellent examples of departments that promote their DCs within their institutions. A good example is the Chemistry department, which has a cluster of five DCs who work together in their advocacy. During this year’s call for new DCs, and with help from the Department Librarian, we used a targeted approach at advertising the DC Programme within the Department of Engineering. This was highly successful, resulting in ten new Data Champions from Engineering from various roles and Academic Divisions. They represent a hub with the local knowledge, experience and skills to assess their department’s needs and explore best approaches to support good RDM practices and Open Research, ones that are tailored to the discipline.  

Alumni community 

Heading toward the programme’s third birthday means that we are growing bigger but also that we are developing an alumni community as well. This is a different kettle of fish but it is on our radar to investigate how we can foster this distinct group and build a network that is not only Cambridge based but has a more national and even international outlook.  

Funding  

Let’s not forget that the DC programme consists of volunteers. We are in the process of seeking more funds to support this ever increasing community, to run expanding bimonthly forums, and to be able to offer grants to assist DCs in their endeavours. As an example, we supported one of the DCs, James Savage, to bring the programme to the international stage in November at the SCIDataCon 2018 in Botswana. He talked about the programme as well as his experience of being a DC. This resulted in James writing a paper together with Lauren Cadwallader, to be published soon in Data Science Journal (the accepted manuscript and associated data available now in Apollo, the Cambridge University institutional repository). 

An exciting year so far! 

During this third year of the DC programme the number of active DCs across the University of Cambridge has doubled. We can only anticipate it growing further each year, yet balanced by an expanding community of alumni DCs as, for example, DCs leave Cambridge. The DC community is inherently dynamic, as is the programme. Because of this, we always seek to respond and adapt to changing conditions in novel and beneficial ways while maintaining the programme’s core structure to provide strong foundations. This has been a period of reflection, organisation and anticipation, all required to drive the Data Champion programme forward and tackle current challenges effectively, as well as those that lie ahead – more on this to come soon!  

Written by Maria Angelaki and Dr Sacha Jones

Published 20 June 2019

License logo CCBY

Lessons learned from Jisc Research Data Champions

In 2017 four Cambridge researchers received grants from Jisc to develop and share their research data management practices. In this blog, the four awardees each highlight one aspect of their work as a Jisc Data Champion.

The project

All four Champions embarked on a range of activities throughout the year including creating local communities interested in RDM practices, delivering training, running surveys to understand their department better, creating ‘how-to’ guides for would-be RDM mentors and testing Samvera as part of RDSS. They were excited by the freedom that the grant gave them to try out whatever RDM related activities they wanted, which meant they could develop their skills and see ideas come to fruition and make them reusable for others. For example, Annemarie Eckes developed a questionnaire on RDM practices for PhD students and Sergio Martínez Cuesta has posted his training courses on GitHub.  

However, throughout the duration of the award they also found some aspects of championing good RDM disconcerting. Whilst some sessions proved popular, others had very low attendee figures, even when a previous iteration of the session was well attended. They all shared the sense of frustration often felt by central RDM services that it is getting people to initially engage and turn up to a session that is the hard part. However, when people did come they found the sessions very useful, particularly because the Champions were able to tailor it specifically to the audience and discipline and the similar background of all the attendees provided an extra opportunity for exchanging advice and ideas that were most relevant.

The Champions tried out many different things. The Jisc Research Data Champions were expected to document and publicise their research data management (RDM) experiences and practices and contribute to the Jisc Research Data Shared Service (RDSS) development. Here the Champions each highlight one thing they tried out, which we hope will help others with their RDM engagement.

BYOD (Bring your own data)

Champion: Annemarie Eckes, PhD student, Department of Geography

The “Bring your own data” workshop was intended for anyone who thought their project data needed sorting, they needed better documentation, or even they needed to find out who is in charge or the owner of certain data. I set it up to give attendees time and space to do any kind of data-management related tasks: clean up their data, tidy up their computer/ email inbox, etc. The workshop was, really, for everyone whether at the start of their project and at the planning stage or in the middle of a project and had neglected their data management to some extent.

For the workshop the participants needed a laptop or login for the local computers to access their data and a project to tidy up or prepare, that can be done within two hours. I provided examples of file naming conventions and folder structures as well as instructions on how to write good READMEs (messages to your future self) and a data audit framework to give participants some structure to their organisation. After a brief introductory presentation about the aims and the example materials I provided, people would spend the rest of the time tidying up their data or in discussions with the other participants.

While this was an opportunity for the participants to sit down and sort out their digital files, I also wanted participants to talk to each other about their data organisation issues and data exchange solutions. Once I got everyone talking, we soon discovered that we have similar issues and were able to exchange information on very specific solutions.

1-on-1 RDM Mentoring

Champion: Andrew Thwaites, postdoc, Department of Psychology

I decided to trial 1-on-1 RDM mentoring as a way to customise RDM support for individual researchers in my department. The aim was that by the end of the 1-on-1 session, the mentee should understand how to a) share their data appropriately at the end of their project, and b) improve on their day-to-day research data management practice.

Before the meeting, I encouraged the mentee to compile a list of funders, and their funder’s data sharing requirements. During the meeting, the mentee and I would make a list of the data in the mentees project that they are aiming to share, and then I would then help them to choose a repository (or multiple repositories) to share this data on, and I’d also assist in designing the supporting documentation to accompany it. During the sessions I also had conversations about about GDPR, anonymising data, internal documentation and day-to-day practices (file naming conventions, file backups etc.) with the mentee.

As far as possible, I provided non-prescriptive advice, with the aim being to help the mentee make an informed decision, rather than forcing them into doing what I thought was best.

Embedding RDM  

Champion: Sergio Martinez Cuesta, research associate, CRUK-CI and Department of Chemistry

I came to realise early in the Jisc project that stand-alone training sessions focused exclusively on RDM concepts were not successful as students and researchers found them too abstract, uninteresting or detached from their day-to-day research or learning activities. I think the aerial view of the concept of 1-on-1 mentoring and BYOD sessions is beautiful. However, in my opinion, both strategies may face challenges with necessary numbers of mentors/trainers increasing unsustainably as the amount of researchers needing assistance grows and the research background of the audience becomes more diverse.

To facilitate take-up, I tapped into the University’s lists of oversubscribed computational courses and found that many researchers and students already shared interests in learning programming languages, data analysis skills and visualisation in Python and R. I explored how best to modify some of the already-available courses with an aim of extending the offer after having added some RDM concepts to them. The new courses were prepared and delivered during 2017-2018. Some of the observations I made were:

  • Learning programming naturally begs for proper data management as research datasets and tables need to be constantly accessed and newly created. It was helpful to embed RDM concepts (e.g. appropriate file naming and directory structure) just before showing students how to open files within a programming language.
  • The training of version control using git required separate sessions. Here students and researchers also discover how to use GitHub, which later helps them to make their code and analyses more reproducible, create their own personal research websites …
  • Gaining confidence in programming, structuring data / directories and version control in general helps students to acknowledge that research is more robust when open and contrasted by other researchers. Learning how researchers can identify themselves in a connected world with initiatives such as ORCID was also useful.

Brown Bag Lunch Seminar Series: The Productive Researcher

Champion: Melissa Scarpate, postdoc, Faculty of Education

I created the Productive Researcher seminar series to provide data management and Open Access information and resources to researchers at the Faculty of Education (FoE). The aim of the brown bag lunch format was to create an informal session where questions, answers and time for discussion could be incorporated. I structured the seminars so they covered 1) a presentation and discussion of data management and storage; 2) a presentation about Open Access journals and writing publications; 3) a presentation on grant writing where Open Access was highlighted.

While the format of the series was designed to increase attendance, the average was four attendees per session. The majority of attendees were doctoral students and postdocs who had a keen interest in properly managing their data for their theses or projects. However, I suspect it may be the case that those attending already understood data management processes and resources.

In conclusion, I think that whilst the individuals that attended these seminars found the content helpful (per their feedback) the impact of the seminars was extremely limited. Therefore, my recommendation would be to have all doctoral students take a mandatory training class on data management and Open Access topics as part of their methodological training. Furthermore, I think it may be most helpful in reaching postdocs and more senior researchers to have a mandated data management meetings with a data manager to discuss their data management and Open Access plans prior to submitting any grant proposals. Due to new laws and policies on data (GDPR) this seems a necessary step to ensure compliance and excellence in research.

Published 2 October 2018
Compiled and edited by Dr Lauren Cadwallader from contributions by Annemarie Eckes, Dr Andrew Thwaites, Dr Sergio Martinez Cuesta, Dr Melissa Scarpate
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How do you know if you’re achieving cultural change?

On 15th November 2017, the University of Cambridge held its first research data management (RDM) conference, Engaging Researchers in Good Data Management. The Office of Scholarly Communication collaborated with SPARC Europe and Jisc, hosted the one-day event at St. Catherine’s College. In attendance were researchers, administrators, and librarians all sharing their experiences with promoting good RDM. Having a mixture of people from various disciplines and backgrounds allowed many different points of view on engaging researchers to be discussed. In the afternoon, the attendees split off into focus groups to concentrate on a number of nagging questions.

Our group’s topic of discussion: How do we effectively measure cultural change in attitudes towards data management? Leading the discussion was Marta Teperek from Delft University of Technology. There was a mixture of around 30 librarians and researchers from all over the world discussing strategies for engaging with researchers.

How do we set about achieving ‘cultural change’?

Marta started the conversation off by asking what everyone present was already doing at their institutions to engage researchers. Many shared their experiences and some frustrations at pushing good data management habits. One person shared that at his university the initial push toward better data management was achieved by creating and delivering RDM workshops for PhDs and young researchers in the Digital Humanities. These students were already interested in digital preservation, so they were a keen audience. Targeting PhD students and early career researchers may be a more effective strategy because they could develop good data management habits early in their careers. The earlier the intervention, the easier it would (hopefully) be.

Overall, most agreed that directly speaking to researchers is more effective than having initiatives relayed from the top-down. Attendees perceived compliance as a driver rather than a useful stick to persuade researchers to take data management seriously. Even if only a few researchers turned up to data management events, it was still increasing exposure.

Some argued for a multi-prong strategy. Initiatives like the Data Stewards at Delft TU and the Data Champions at the University of Cambridge were perceived as good ways to reach out to researchers in their departments and provide more customized advice. At the same time, having expectations of good data management relayed from on high could help creating greater impetus.

What do we mean by ‘cultural change’?

Naturally, the conversation progressed to what the phrase ‘cultural change’ actually means. It was difficult to determine in 45 minutes what kind of ‘cultural change’ we wanted to see within our different institutions. We started by asking some questions. What were our goals? What would need to happen before we said yes, the culture is changing? Which really meant what do we measure to find evidence of cultural change? Is it better metadata, more awareness of copyright, researchers reaching out to us for help, or an increase in number of grants awarded that would signal an actual change? It would seem that there could be many definitions of ‘cultural change’, but the crucial takeaway is that it is essential to define what your parameters of cultural change will be in the planning stages of any RDM programme.

Where is the evidence?

The conversation progressed to how do we find and gather evidence. With all of the work being done by researchers, librarians, and administrators, how do we know what is actually effective? We cannot state that engaging with researchers (which can be time-consuming) is working without having actual evidence to confirm it. A number of different ideas were discussed, with the time when feedback was gathered being a particular point of variance.

Quantifiable information such as number of datasets deposited, number of datasets downloaded and re-used, and number of grants with a Data Management Plan could be collected. For example, the University of Illinois conducted a detailed analysis of 1,260 data management plans using a controlled vocabulary list and looked at possible correlations between solutions for data management listed in funded and unfunded proposals.

Another method of benchmarking included asking researchers to periodically complete short surveys on data management practice in order to measure any noticeable changes. In that way, an institution can assess whether their engagement strategies work and whether it achieves the desirable effects (improvement of data management practice). Delft, EPFL, Cambridge and Illinois collaborated on development of an agreed set of survey questions. Conducting this same survey across different institutions enables benchmarking and comparison of the different techniques and how effective they are in achieving cultural change in data management. In addition to this survey, the team also interviews some researchers in order to gather additional qualitative data and more detailed insights into data management practice. The hope is that carrying out these quantitative surveys and qualitative interviews periodically will correct for the potential problem of self-selecting participants.

In the future

Ultimately, it turned out that most of those attending the focus group discussion were already working actively to develop systems to measure impact and gather feedback. However, the possibility of carrying out long-term cross-institutional research that would allow comparisons between different data management programmes is very tantalising. The final takeaway from this focus group discussion was that the majority of those attending would be very keen to take part in such research, so watch this space!

Published 18 December 2017
Written by Katie Hughes and Lucy Welch
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