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

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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

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Lessons learned from Jisc Research Data Champions

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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?

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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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Engaging Researchers with Good Data Management: Perspectives from Engaged Individuals

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We need to recognise good practice, engage researchers early in their career with research data management and use peers to talk to those who are not ‘onboard’. These were the messages five attendees at the Engaging Researchers in Good Data Management conference held on the 15th of November.

The Data Champions and Research Support Ambassadors programmes are designed to increase confidence in providing support to researchers in issues around data management and all of scholarly communications respectively. Thanks to the generous support of the Arcadia Foundation, five places were made available to attend this event. In this blog post the three Data Champions and two Research Support Ambassadors who were awarded the places give us the low-down on what they got out of the conference and how they might put what they heard into practise.

Recordings of the talks from the event can be found on the Cambridge University Library YouTube channel.

Financial recognition is the key

Dr Laurent Gatto, Senior Research Associate, Department of Biochemistry, University of Cambridge and Data Champion

As a researcher who cherishes good and reproducible data analysis, I naturally view good data management as essential. I have been involved in research data management activities for a long time, acting as a local data champion and participating in open research and open data events. I was interested in participating in this conference because it gathered data champions, stewards and alike from various British and European institutions (Cambridge, Lancaster, Delft), and I was curious to see what approaches were implemented and issues were addressed across institutions. Another aspect of data championship/stewardship I am interested in is the recognition these efforts offer (this post touches on this a bit).

Focusing on the presentations from Lancaster, Cambridge and Delft, it is clear that direct engagement from active researchers is essential to promote healthy data management. There needs to be an enthusiastic researcher, or somebody that has some experience in research, to engage with the research community about open data, reproducibility, transparency, security; a blunt top-down approach lead to limited engagement. This is also important due to the plurality of what researchers across disciplines consider to be data. An informal setting, ideally driven by researchers and, or in collaboration with librarians, focusing on conversations, use-cases, interviews, … (I am just quoting some successful activities cited during the conference) have been the most successful, and have sometime also lead to new collaborations.

Despite the apparent relative success of these various data championing efforts and the support that the data champions get from their local libraries, these activities remain voluntary and come with little academic reward. Being a data champion is certainly an enriching activity for young researchers that value data, but is comes with relatively little credit and without any reward or recognition, suggesting that there is probably room for a professional approach to data stewardship.

With this in mind, I was very interested to hear the approach that is currently in place at TU Delft, where data stewards hold a joint position at the Centre for Research Data and at their respective faculty. This defines research data stewardship as an established and official activity, allows the stewards to pursue a research activity, and, explicitly, links research data to research and researchers.

I am wondering if this would be implemented more broadly to provide financial recognition to data stewards/champions, offer incentives (in particular for early-career researchers) to approach research data management professionally and seriously, make data management a more explicit activity that is part of research itself, and move towards a professionalisation of data management posts.

Inspiration and ideas

Angela Talbot, Research Governance Officer, MRC Biostatistics Unit and Data Champion

Tasked with improving and updating best practice in the MRC Biostatistics Unit, I went along to this workshop not really knowing what to expect but hopeful and eager to learn.

Good data management can meet with resistance as while it’s viewed as an altruistic and noble thing to do many researchers worry that to make their research open and reproducible opens them to criticism and the theft of ideas and future plans. What I wanted to know are ways to overcome this.

And boy did this workshop live up to my expectations! From the insightful opening comments to the though provoking closing remarks I was hooked. All of the audience were engaged in a common purpose, to share their successes and strategies for overcoming the barriers that ensure this becomes best practice.

Three successful schemes were talked through: the data conversations in Lancaster, the Data Champion scheme at the University of Cambridge and the data stewards in TU Delft. All of these successful schemes had one thing in common: they all combine a cross department/ faculty approach with local expertise.

Further excellent examples were provided by the lightning talks and for me, it was certainly helpful to hear of successes in engaging researchers on a departmental level.

The highlight for me were the focus groups – I was involved in Laurent Gatto’s group discussing how to encourage more good data management by highlighting what was in to for researchers who participate but I really wish I could have been in them all as the feedback indicated they had given useful insights and tips.

All in all I came away from the day buzzing with ideas. I spent the next morning jotting down ideas of events and schemes that could work within my own unique department and eager to share what I had learnt. Who knows, maybe next time I’ll be up there sharing my successes!!

We need to speak to the non-converted

Dr Stephen Eglen, Reader in Computational Neuroscience, Department of Applied Mathematics & Theoretical Physics, University of Cambridge and Data Champion

The one-day meeting on Engaging Researchers in Good Data Management served as a good chance to remind all of us about the benefits, but also the responsibilities we have to manage, and share, data. On the positive side, I was impressed to see the diversity of approaches lead by groups around the UK and beyond. It is heartening to see many universities now with teams to help manage and share data.

However, and more critically, I am concerned that meetings like this tend to focus on showcasing good examples to an audience that is already mostly convinced of the benefits of sharing. Although it is important to build the community and make new contacts with like-minded souls, I think we need to spend as much time engaging with the wider academic community.   In particular, it is only when our efforts can be aligned with those of funding agencies and scholarly publishing that we can start to build a system that will give due credit to those who do a good job of managing, and then sharing, their data. I look forward to future meetings where we can have a broader engagement of data managers, researchers, funders and publishers.

I am grateful to the organisers to have given me the opportunity to speak about our code review pilot in Neuroscience. I particularly enjoyed the questions. Perhaps the most intriguing question to report came in the break when Dr Petra ten Hoopen asked me what happens if during code review a mistake is found that invalidates the findings in the paper? To which I answered (a) the code review is supposed to verify that the code can regenerate a particular finding; (b) that this is an interesting question and it would probably depend on the severity of the problem unearthed; (c) we will cross that bridge when we come to it. Dr ten Hoopen noted that this was similar to finding errors in data that were being published alongside papers. These are indeed difficult questions, but I hope in the relatively early days of data and code sharing, we err on the side of rewarding researchers who share.

Teach RDM early and often

Kirsten Elliott, Library Assistant, Sidney Sussex College, University of Cambridge and Research Support Ambassador

Prior to this conference, my experience with Research Data Management (RDM) was limited to some training through the Office of Scholarly Communication and Research Support Ambassadors programme. This however really sparked my interest and so I leapt at the opportunity to learn more about RDM by attending this event. Although at times I felt slightly out of my depth, it was fascinating to be surrounded by such experts on the topic.

The introductory remarks from Nicole Janz were a fascinating overview of the reproducibility crisis, and how this relates to RDM, including strategies for what could be done, for example setting reproducing studies as assignments when teaching statistics. This clarified for me the relationship between RDM and open data, and transparency in research.

There were many examples throughout the day of best practice in promoting good RDM, from the “Data Conversations” held at Lancaster University, international efforts from SPARC Europe and even some from Cambridge itself! Common ground across all of them included the necessity of utilising engaged researchers themselves to spread messages to other researchers, the importance of understanding discipline specific issues with data, and an expansive conception of what counts as “data”.

I am based in a college library and predominantly work supporting undergraduate students, particularly first years. In a way this makes it quite a challenge to present RDM practices as many of the issues are most obviously relevant to those undertaking research. However, I think there’s a strong argument for teaching about RDM from very early in the academic career to ingrain good habits, and I will be thinking about how to incorporate RDM into our information literacy training, and signposting students to existing RDM projects in Cambridge.

Use peers to spread the RDM message

Laura Jeffrey, Information Skills Librarian, Wolfson College, University of Cambridge and Research Support Ambassador

This inspirational conference was organised and presented by people who are passionate about communicating the value of open data and replicability in research processes. It was valuable to hear from a number of speakers (including Rosie Higman from the University of Manchester, Marta Busse-Wicher from the University of Cambridge and Marta Teperek from TU Delft) about the changing role of support staff, away from delivering training to one of coordination. Peers are seen to be far more effective in encouraging deeper engagement, communicating personal rather than prescriptive messages (evidenced by Data Conversations at Lancaster University). A member of the audience commented that where attendance is low for their courses, the institution creates video of researcher-led activities to be delivered at point of need.

I was struck by two key areas of activity that I could act on with immediate effect:

Inclusivity – Beth Montagu Hellen (Bishop Grosseteste) highlighted the pressing need for open data to be made relevant to all disciplines. Cambridge promotes a deliberately broad definition of data for this reason. Yet more could be done to facilitate this; I’ll be following @OpenHumSocSci to monitor developments. We’re fortunate to have a Data Science Group at Wolfson promoting examples of best practice. However, I’m keen to meet with them to discuss how their activities and the language they use could be made more attractive to all disciplines.

Communication – Significant evidence was presented by Nicole Janz, Stephen Eglen and others, that persuading researchers of the benefits of open data leads to higher levels of engagement than compulsion on the grounds of funder requirements. This will have a direct impact on the tone and content of our support. A complimentary approach was proposed: targeted campaigns to coincide with international events in conjunction with frequent, small-scale messages. We’ll be tapping into Love Data Week in 2018 with more regular exposure in email communication and @WolfsonLibrary.

As result of attending this conference, I’ll be blogging about open data on the Wolfson Information Skills blog and providing pointers to resources on our college LibGuide. I’ll also be working closely with colleagues across the college to timetable face-to-face training sessions.

Published 15 December 2017
Written by Dr Laurent Gatto, Angela Talbot, Dr Stephen Eglen, Kirsten Elliott and Laura Jeffrey
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Researchers championing data – what works?

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Here we follow up on our earlier piece “Creating a research data community”, where Rosie Higman and Hardy Schwamm discussed innovative ways of researcher engagement with research data management.

This blog discusses the outcome from a dedicated Birds of a Feather session at the 9th Research Data Alliance Plenary meeting in Barcelona in April 2017. The session discussed three different programmes for engaging researchers with data management and sharing: University of Cambridge Data Champions programme, TU Delft’s Data Stewardship and SPARC Europe’s Open Data Champions. The purpose of this session was to exchange practice, discuss the difference between the programmes and talk about possible next steps. All presentations from the sessions are available.

Cambridge’s Data Champions

Cambridge’s Data Champions programme was started in Autumn 2016 and is a programme in which researchers volunteered to become a local community expert and advocate on research data management and sharing. The main expectation of those appointed as Data Champions was to run at least one workshop on a topic related to research data management for their research community and to act as the local expert connecting researchers and central data services. In return Champions were offered new networking opportunities, training in research data management and sharing and also a boost to their CVs. Detailed information about the expectations, benefits of becoming a Champion, as well as the support from central services are publicly available.

The Data Champions programme is coordinated during bi-monthly meetings during which Champions exchange practice, talk to each other about their interactions with other researchers and provide each other with advice on tackling some of the data-related challenges. Over time Champions formed a community of practice and the central Research Data Team started to act more as hands-off facilitators of these activities and discussions rather than prescribing Champions what to do and how to best engage with researchers locally. The rationale behind this was that Data Champions would know their own research communities best and would be best positioned to decide what types of training and engagement methods would work for them.

And in fact the Champions delivered quite unexpected and diverse range of outputs. The initial requirement was to deliver a training on research data management to their local communities. The Research Data Management workshop template was shared with the Champions and they were all trained about the content and the methods of the workshop delivery. However, Champions were given discretion on what training they provided and how they wish to deliver. And in fact they developed all sorts of materials and strategies for engaging their local communities: from highly successful regular research data ‘tips’ emails sent to everyone in a department, through data sharing FAQs for chemists and ORCiD drop-in sessions, to organising Electronic Lab Notebooks trials. While certainly interesting and valuable, this also raised a questions as to whether the messages about data management and sharing are still consistent and aligned with the central data services, and also if the high quality of training is maintained.

TU Delft’s Data Stewardship programme

Madeleine de Smaele from TU Delft spoke about their Data Stewardship programme. The goal of the programme is to create mature working practices and policies for research data management across each of the eight faculties at TU Delft, so that any project can make sure their data is managed well. The programme is part of the broader Open Science agenda at TU Delft, which aims to make research more accessible and more re-usable. In contrast to the hands-off and decentralised Data Champions programme at Cambridge, TU Delft’s Data Stewardship programme has a solid framework as its core: a team of eight Data Stewards (a dedicated Data Steward for each one of eight TU Delft’s faculties), led centrally by the Data Stewardship Coordinator.

Data Stewards are disciplinary experts, who are embedded within faculties, and are able to understand and address the specific data management needs of their research communities. However, thanks to working as a team, which is centrally coordinated, the work of Data Stewards is coherent and aligned. This is reflected for example in research data policy development. TU Delft will have a central policy framework for research data management; however, it is Data Stewards working with their faculties who will develop research data policies, tailored to specific needs of individual faculties.

SPARC Europe’s Open Data Champions

SPARC Europe’s Open Data Champions initiative took yet a different approach from Cambridge and TU Delft and it aims to help promote the use of ambassadors or champions in the scientific community to help unlock more scientific data. The focus of the Open Data Champions Initiative is to achieve cultural change needed to see more research data shared and re-used.

Similarly to their previous SPARC Europe’s Open Access Champions initiative, the rationale behind the Open Data Champions is that activists who stimulate cultural change need to be promoted and supported to effect greater, speedier, more motivated research-driven change to help make Open the default in Europe. SPARC Europe wants to identify Champions at different career levels (from PhD students to vice chancellors), from a range of disciplines and from a variety of European countries to inspire broad range of stakeholders.

Are the programmes really effective?

After short presentations about the three programmes, the attendees started discussing different aspects of all programmes: their different aims, audiences, reward systems and sustainability of these activities. Perhaps the most interesting discussion was around measuring the effectiveness of these initiatives. All three programmes aim to ultimately achieve cultural change towards better data management and greater openness. Are the programmes all equally effective at achieving cultural change? Or are perhaps different modes of engagement bringing different results? How to measure cultural change?

And, finally, what are the costs and benefits of each programme? TU Delft’s Data Stewardship programme, with discipline-specific Data Stewards, is more resource-intensive than Cambridge’s Data Champions relying on researchers volunteering their time; both programmes are however more costly than SPARC Europe’s Open Data Champions.

Need for international collaboration and practice exchange

Our discussions brought more questions than answers but we all agreed that the exchange of ideas and practice was productive and useful. Many attendees expressed their interest for starting dedicated researcher engagement programmes at their institutions. Therefore, one of the main conclusions of the session was that it would be valuable to create a forum where those running programmes for researcher engagement could regularly discuss their programmes, exchange ideas and problem-solve jointly. This is particularly important for difficult questions, which the community struggles to address, such as metrics for assessing cultural change in data management and sharing. Working collaboratively can prove incredibly efficient, which was recently demonstrated by a teamwork effort which led to the development of metrics for assessment of data management training programmes.

Next steps

As a next step to extend our conversations and start identifying solutions to common problems, the University of Cambridge, SPARC Europe and Jisc are co-organising a dedicated event “Engaging Researchers in Good Data Management” on 15 November 2017 in Cambridge, United Kingdom. The event intends to bring together those working to support and engage researchers with open research and Research Data Management (RDM), including librarians, scholarly communication specialists and researchers from both the sciences and humanities. So if you are reading this blog post and would like to be part of these discussions, do come and join!

Published 15 September 2017
Written by Dr Marta Teperek
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Creating a research data community

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Are research institutions engaging their researchers with Research Data Management (RDM)? And if so, how are they doing it? In this post, Rosie Higman (@RosieHLib), Research Data Advisor, University of Cambridge, and Hardy Schwamm (@hardyschwamm),  Research Data Manager, Lancaster University explore the work they are doing in their respective institutions.

Whilst funder policies were the initial catalyst for many RDM services at UK universities there are many reasons to engage with RDM, from increased impact to moving towards Open Research as the new normal. And a growing number of researchers are keen to get involved! These reasons also highlight the need for a democratic, researcher-led approach if the behavioural change necessary for RDM is to be achieved. Following initial discussions online and at the Research Data Network event in Cambridge on 6 September, we wanted to find out whether and how others are engaging researchers beyond iterating funder policies.

At both Cambridge and Lancaster we are starting initiatives focused on this, respectively Data Champions and Data Conversations. The Data Champions at Cambridge will act as local experts in RDM, advocating at a departmental level and helping the RDM team to communicate across a fragmented institution. We also hope they will form a community of practice, sharing their expertise in areas such as big data and software preservation. The Lancaster University Data Conversations will provide a forum to researchers from all disciplines to share their data experiences and knowledge. The first event will be on 30 January 2017.

RDMFBreakoutHaving presented our respective plans to the RDM Forum (RDMF16) in Edinburgh on 22nd November we ran breakout sessions where small groups discussed the approaches our and other universities were taking, the results summarised below highlighting different forms that engagement with researchers will take.

Targeting our training

RDM workshops seem to be the most common way research data teams are engaging with researchers, typically targeting postgraduate research students and postdoctoral researchers. A recurrent theme was the need to target workshops for specific disciplinary groups, including several workshops run jointly between institutions where this meant it was possible to get sufficient participants for smaller disciplines. Alongside targeting disciplines some have found inviting academics who have experience of sharing their data to speak at workshops greatly increases engagement.

As well as focusing workshops so they are directly applicable to particular disciplines, several institutions have had success in linking their workshop to a particular tangible output, recognising that researchers are busy and are not interested in a general introduction. Examples of this include workshops around Data Management Plans, and embedding RDM into teaching students how to use databases.

An issue many institutions are having is getting the timing right for their workshops: too early and research students won’t have any data to manage or even be thinking about it; too late and students may have got into bad data management habits. Finding the goldilocks time which is ‘just right’ can be tricky. Two solutions to this problem were proposed: having short online training available before a more in-depth training later on, and having a 1 hour session as part of an induction followed by a 2 hour session 9-18 months into the PhD.

Tailored support

Alongside workshops, the most popular way to get researchers interested in RDM was through individual appointments, so that the conversation can be tailored to their needs, although this obviously presents a problem of scalability when most institutions only have one individual staff member dedicated to RDM.

IMG_20161122_121401There are two solutions to this problem which were mentioned during the breakout session. Firstly, some people are using a ‘train the trainer’ approach to involve other research support staff who are based in departments and already have regular contact with researchers. These people can act as intermediaries and are likely to have a good awareness of the discipline-specific issues which the researchers they support will be interested in.

The other option discussed was holding drop-in sessions within departments, where researchers know the RDM team will be on a regular basis. These have had mixed success at many institutions but seem to work better when paired with a more established service such as the Open Access or Impact team.

What RDM services should we offer?

We started the discussion at the RDM Forum thinking about extending our services beyond sheer compliance in order to create an “RDM community” where data management is part of good research practice and contributes to the Open Research agenda. This is the thinking behind the new initiatives at Cambridge and Lancaster.

However, there were also some critical or sceptical voices at our RDMF16 discussions. How can we promote an RDM community when we struggle to persuade researchers being compliant with institutional and funder policies? All RDM support teams are small and have many other tasks aside from advocacy and training. Some expressed concern that they lack the skills to market our services beyond the traditional methods used by libraries. We need to address and consider these concerns about capacity and skill sets as we attempt to engage researchers beyond compliance.

Summary

It is clear from our discussions that there is a wide variety of RDM-related activities at UK universities which stretch beyond enforcing compliance, but engaging large numbers of researchers is an ongoing concern. We also realised that many RDM professionals are not very good at practising what we preach and sharing our materials, so it’s worth highlighting that training materials can be shared on the RDM training community on Zenodo as long as they have an open license.

Many thanks to the participants at our breakout session at the RDMForum 16, and Angus Whyte for taking notes which allowed us to write this piece. You can follow previous discussions on this topic on Gitter.

Published on 30 November
Written by Rosie Higman and Hardy Schwamm
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