Tag Archives: open data

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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Championing RDM training

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During International Data Week 2016, the Office of Scholarly Communication is celebrating with a series of blog posts about data. The first post was a summary of an event we held in July. This post looks at the challenges associated with financially supporting RDM training.

The problem

There is a desperate need for training in research data management. Our significant engagement with researchers at the University of Cambridge over the past 18 months has indicated to us that research data cannot be effectively shared if it has not been properly managed during the research lifecycle. Researchers cannot be expected to share their data at the end of their research project if they are unable to locate their data, if the data is not correctly labelled or if it lacks metadata to make the data re-usable. We have stated that on several occasions, including our response to the draft UK Concordat on Open Research Data which was released in its final form on the 28th July this year.

To test whether our beliefs were in-line with researchers’ needs, last year we conducted a short survey on research data management needs among our academic community. Of those responding, 94% of researchers indicated that it would be ‘useful’ or ‘very useful’ to have workshops on research data management (see our earlier blog post for the full discussion of the survey results). In response to this we developed a 1.5 hour introductory workshop to research data management and started delivering this to researchers in Cambridge in July 2015.

Train early, train often

Our workshops have evolved substantially since the initial sessions, through responses to the feedback we collect. The workshops are now considerably improved, not only more interactive, but also have been extended to 2.5 hours to allow time to provide more practical examples of good data management.

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The feedback from our workshops was overwhelmingly positive. As a result, many departments identified research data management skills as core competencies needed by every PhD student and asked us to deliver our workshops as part of their compulsory training for PhD students. This is fantastic news for both our team and the awareness of RDM at Cambridge, and we have therefore accepted all these individual requests.

But sometimes you can be a little too successful. We recently received another request from the Graduate School of Life Sciences to make our workshop compulsory for all their PhD students. While this is great news, there are 400 new PhD students every year at the Graduate School of Life Sciences. The maximum capacity at our workshop is 20 attendees, which means we would need to deliver 20 workshops throughout the year to cover this cohort. And when we consider the Graduate School of Life Sciences is one of five schools accepting PhD students in Cambridge, we need to look at how we would respond if other schools approached us with similar requests.

Another issue is that while our improved workshop on research data management covered the basic research data management needs, researchers have told us they need more in-depth discipline-specific training. We recognise this, and do try to provide training that is directed at the audience – a challenge when we need to serve all researchers across the University – from arts and humanities through social and life sciences, to medical research and particle physics (and many, many other disciplines).

So we have identified a broad need for RDM training, a specific need for training for PhD students as they begin their research, as well as discipline-specific support for all researchers. But there are only two staff members in the Research Data Team who can deliver RDM training, and delivering training is only one of many tasks which we need to undertake for the Research Data Facility to function. We simply do not have the capacity to meet this obvious need. After discussion we have agreed to deliver four workshops out of the requested 20 for the Graduate School of Life Sciences and to reconsider the situation in the summer break next year.

The plan – Data Champions

We have begun to think both about how we can meet RDM training needs given current staff capacity and how we can link the experts in different aspects of data management that we know exist around the University of Cambridge. There is already an active OpenCon Cambridge group which promotes the benefits of Open Access, Open Data and Open Education; but we wanted to focus on all aspects of RDM.

We have started to develop the idea of having Data Champions in each department, institute or college who can act as the local experts as well as delivering some discipline-specific training to their community. This has the advantage of increasing the number of trainers across the University, making the workshops tailored to the relevant audience, and building a community of experts.

The University of Cambridge is not alone in facing this problem and the several other universities are pursing, or already have, Data Champions in some form. The idea was recently discussed on both Jisc RDM mailing lists and at the Research Data Network meeting which was held at Corpus Christi College, Cambridge last week. At this meeting several different models were proposed, including a national network of champions who could advocate within disciplines at a senior level.

Whilst a national network of champions would be great in the long term we still have an immediate problem within the University of Cambridge and so we have launched a Call for Data Champions to help us raise awareness and increase the amount of training available. The call is open until 17th October and we would welcome any research or support staff or research student with an interest in RDM. There will be support available in learning how to deliver RDM training, a template workshop provided, the opportunity to influence the future of RDM services and a website built to showcase our Data Champions.

We hope to bring all the Data Champions together towards the end of the Michaelmas term so they can start delivering workshops in 2017. We hope to foster a community of experts who can share their knowledge with each other and the Research Data Team so we are in a better position to support our researchers.

The future

The community of Data Champions we hope to bring together at Cambridge will begin to ameliorate some of the problems we are facing with regards to RDM training. However, we will still struggle with staff capacity and at some point researchers will need to be appropriately rewarded for sharing data and supporting others to do the same, a theme of our recent Open Research discussion event.

So we have a temporary solution, and one which we hope will significantly improve the RDM training available at Cambridge, but the issue will not be solved until the underlying incentives for sharing data, publications and all the other research outputs have been addressed.

Published 14 September 2016
Written by Rosie Higman and Dr Marta Teperek
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In conversation with Wellcome Trust and CRUK

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On Friday 22 January Cambridge University invited our two main charity funders to discuss their views on data management and sharing with Cambridge researchers. David Carr from the Wellcome Trust and Jamie Enoch from Cancer Research UK came to the University to talk to our researchers.

The related blog ‘Charities’ perspective on research data management and sharing‘ summarises the presentations Jamie and David gave. After this event, a group of researchers from the School of Biological Sciences and from the School of Clinical Medicine at the University of Cambridge were invited to ask questions about the Wellcome Trust data management and sharing policy and CRUK data sharing and preservation policy directly of David and Jamie.

This blog is a summary of the discussion, with questions thematically grouped. These questions will be added to the list of Frequently Asked Questions on the University’s Research Data Management Website.

In summary:

  • It is not recommended that researchers simply share a link and release the data when requested. Research data should be available, accessible and discoverable.
  • The first responsibility is to protect the study participants. The funders provide guidance documents on sharing of patient data. Ethics committees also provide advice and guidance on what data can be shared. In principle, patient data should be safeguarded, but this should not preclude sharing. There are models for managed access to data that allow personal/sensitive data to be shared for legitimate purposes in a safe and secure manner.
  • The funders do not want to prevent new collaborations. When sharing data they recommend data generators provide a statement in the description of the data that they are willing to collaborate
  • It is recognised that it is often appropriate for researchers to have a defined period of exclusive access to the data they generate, but this should be determined by disciplinary norms. Any exemptions or delays have to be justified on a case by case basis, ideally at the outset of the project.
  • The funders expect research data that supports publications to be made accessible and publications should have a clear statement explaining how to access the underlying research data.
  • However researchers need to decide what is useful to be shared considering the effort of preparing the data for deposit and of sharing the data. If nobody is going to use the data, sharing is not a good use of researcher’s time.
  • Discipline-specific data repositories, where these exist, are recommended preferentially over general purpose or institutional repositories
  • Biosharing is an excellent resource with references to discipline-specific metadata schemas.
  • Staff members whose role is to manage data is an eligible cost on a grant
  • There are no funds for sharing data from old projects, although there are exceptions on a case by case basis
  • The funders are considering monitoring data management plans but their current primary goal is to encourage people to think about data management and sharing from the very start of the project

Access to research data

Q: Are funders benefiting from the expertise of organisations such as UK Data Service when providing advice on data access? UK Data Service has been managing controlled access to research data for a long time and it would be advantageous to benefit from their expertise.

A: Yes, we are in discussion with the UK Data Service. We are also working with the UK Data Service to consider whether it might be appropriate for hosting data from other disciplines beyond social science. We also believe there is significant scope to share lessons and best practices for data sharing between the social and biomedical sciences.

Q: Could we just share research data only when asked for it?

A: This is not a recommended solution: research data should be available, accessible and discoverable. Data access controls and criteria for what needs to happen for the access to be granted have to be made clear in metadata description.

Q: I have patient data which has to be stored in a secure space. I always say in my data management plan that I cannot share my data. I would like to get ethical guidance which will explain to me how to share these data. It is very easy to say that data cannot be shared. I would like to share my data, but I would like to do it properly. With patient data it is extremely difficult, especially with genomics data, where there is a risk that patients can be identified.

A: Sharing of clinical data is not easy. Both Wellcome Trust and Cancer Research UK are helping to drive a great deal of work which is considering access and governance models through which sensitive patient data can be made available for research in a safe, secure and trusted manner. They provide guidance documents on sharing of patient data. Safety of patients and patients’ data is important. Ethics committees also provide advice and guidance on what data can be shared.

Q: What about sharing of physical materials? I have received a request to share a culture derived from a patient material, but the Ethics Committee did not approve sharing of this material. What shall I do?

A (Peter Hedges, Head of Research Office): If your ethical approval says that you cannot share that material, you cannot share it. Your first responsibility is to protect your study participants.

Q: If I share my data via a repository and people can simply download my data, I can no longer collaborate with them to work on the data and I have lost the possibility of getting credit for my data.

A: Nobody wants to prevent new collaborations from happening. A solution might be to add a statement that you are willing to collaborate in the description of your data. Your data requestor might be interested in collaborating, simply because you know your data the best. Funders also expect that the data re-used by others is appropriately acknowledged/cited, and they want to ensure that due credit results from the secondary use of data.

Quality control of research data

Q: If researchers start sharing unpublished research data via data repositories there is a risk that these data will not be of good quality as they will not be peer-reviewed.

A: Authors of unpublished data can simply state in the data description that the item was not peer-reviewed. If applicable, funders also encourage reciprocal links between publications and supporting research data.

What data needs to be shared and when?

Q: If researchers start to share everything there will be a lot of useless data available in data repositories. How to prevent a flood of useless data on the internet?

A: We would like researchers to decide what data is useful to be shared. If nobody is likely to use the data, sharing is not a good use of researcher’s time. Repositories also need to make decisions over what is worth keeping over time.

Comment (Peter Hedges, Head of Research Office): The Research Council UK focuses on research data supporting publications and this is what we recommend to researchers: share research data which underpins publications.

Q: Are we expected to share large datasets resulting from bigger projects (databases, long-term datasets) or data supporting individual publications?

A: We expect research data that supports individual publications to be made available with a hyperlink to the data. We also want researchers to consider and plan more broadly how they can make data assets of value resulting from our funded research available to others in a timely and appropriate manner.

Q: What about images? Is it useful to share them? It involves a lot of time to organise images. Besides, a single confocal picture with multiple layers is 1GB. In theory it is possible to share all raw data and all raw images, but who would want to look at them? 10 figures of 10 images is already 100 GB of data. Where would I store all these images, who is going to use these data and how am I going to pay for this?

A: The effort of preparing the data for deposit and of sharing the data should be proportionate to the potential benefits of data sharing. Researchers need to decide what is useful to be shared, following disciplinary best practices and norms (recognising that disciplines are in very different places in terms of defining these).

Q: Is there a set amount of time for exclusive use of research data?

A: Researchers should adhere to disciplinary norms. For example, in genomics research data is frequently shared before publication (sometimes under a publication moratorium which protects the data generator’s right to first publication). Any exemptions or delays have to be justified on a case by case basis.

Comment (Peter Hedges, Head of Research Office): Research is competitive. Sometimes it might be useful for researchers to know who wants to get the access to data and what do they need them for.

Cost of data sharing

Q: Can I ask in my grant for a staff member to help me with data management?

A: Yes, this is an eligible cost on grant applications: you can request a salary to support a research data manager for your research project, as long as it is justified.

Q: According to CRUK policy, costs for data sharing can be budgeted in grant applications only from August 2015. What about research data from older projects, when these costs were not eligible in grant applications? Is there any transition fund available to pay for this?

A: Unfortunately, there are no additional funds to pay for these costs. Researchers who have older datasets that might be of significant value to the community should contact CRUK – all requests for support will be considered on a case by case basis.

Q: Wellcome Trust encourages data sharing and data re-use, but does not allow for costs of long-term data preservation to be budgeted in grant applications. This does not make sense to me.

A: We are still reviewing our policy on costs of data management and sharing and we might be revisiting this issue – however, it is problematic for us to consider estimated costs for preservation that extend before the life-time of the grant. Our understanding is that costs of long-term data preservation are often less significant than costs of initial data ingestion by the repository (and we will cover ingestion costs).

Q: Who is then going to pay for the long-term data storage?

A: Wellcome Trust funds some discipline-specific repositories, but this is done jointly with other funders. We support bigger undertakings and we are also working with partners to develop platforms for data sharing and discoverability in some priority areas (notably clinical trials). Cancer Research UK pays for some long-term storage options, if these are justified for particular needs of the project. These decisions are made on a case by case basis, depending on how the costs are justified and whether these are directly related to the scientific value of the project.

Metadata standards

Q: At the moment there are many general purpose and institutional repositories, which are not well structured. To support efficient re-use of data it is important to use structured data repositories and adhere to metadata standards. What are funders’ opinions about this?

A: Wherever possible, discipline-specific data repositories should be used preferentially over general purpose or institutional repositories. Adherence to discipline-specific metadata standards is also encouraged. It has to be acknowledged that development of well-structured data repositories is very resource-intensive and not all disciplines have good quality repositories to support them. For example, it took over 30 years to adapt unified metadata standards at Cambridge Crystallographic Data Centre. The time need to properly solve problems should never be underestimated.

Q: Are funders planning to provide researchers with a list of recommended schemas for metadata?

A: Biosharing is an excellent resource with references to discipline-specific metadata schemas. It is a useful suggestion to include a reference to Biosharing on our website.

Policy implementation

Q: Are you planning to monitor researchers’ adherence to data management plans? For example, the BBSRC does not have the manpower to check all data management plans manually, but they are planning to create a system to check if data has been uploaded automatically.

A: We are considering this. At the moment we require data management plans with the primary goal to encourage people to think about data management and sharing from the very start of the project.

Published 5 February 2016
Written by Dr Marta Teperek, verified by David Carr and Jamie Enoch
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