Tag Archives: data champions

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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