Tag Archives: research data management

Beyond compliance – dialogue on barriers to data sharing

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Welcome to International Data Week. The Office of Scholarly Communication is celebrating with a series of blog posts about data, starting with a summary of an event we held in July.

JME_0629.jpgOn 29 July 2016 the Cambridge Research Data Team joined forces with the Science and Engineering South Consortium to organise a one day conference at the Murray Edwards College to gather researchers and practitioners for a discussion about the existing barriers to data sharing. The whole aim of the event was to move beyond compliance with funders’ policies. We hoped that the community was ready to change the focus of data sharing discussions from whether it is worth sharing or not towards more mature discussions about the benefits and limitations of data sharing.

What are the barriers?

So what are the barriers to effective sharing of research data? There were three main barriers identified, all somewhat related to each other: poorly described data, insufficient data discoverability and difficulties with sharing personal/sensitive data. All of these problems arise from the fact that research data does not always shared in accordance to FAIR principles: that data is Findable, Accessible, Interoperable and Re-usable.

Poorly described data

The event started with an inspiring keynote talk from Dr Nicole Janz from the Department of Sociology at the University of Cambridge: “Transparency in Social Science Research & Teaching”. Nicole regularly runs replication workshops at Cambridge, where students select published research papers and they work hard for several weeks to reproduce the published findings. The purpose of these workshop is to allow students to learn by experience on what is important in making their own work transparent and reproducible to others.

Very often students fail to reproduce the results. Frequently, the reasons for failures are insufficient methodology available, or simply the fact that key datasets were not made available. Students learn that in order to make research reproducible, one not only needs to make the raw data files available, but that the data needs to be shared with the source code used to transform it and with written down methodology of the process, ideally in a README file. While doing replication studies, students also learn about the five selfish benefits of good data management and sharing: data disasters are avoided, it is easier to write up papers from well-managed data, transparent approach to sharing makes the work more convincing to reviewers, the continuity of research is possible and researchers can build their reputation for being transparent. As a tip for researchers, Nicole suggested always asking a colleague to try to reproduce the findings before submitting a paper for peer-review.

The problem of insufficient data description/availability was also discussed during the first case study talk by Dr Kai Ruggeri from the Department of Psychology, University of Cambridge. Kai reflected on his work on the assessment of happiness and wellbeing across many European countries, which was part of the ESRC Secondary Data Analysis Initiative. Kai re-iterated that missing data make the analysis complicated and sometimes prevent one from being able to make effective policy recommendations. Kai also stressed that frequently the choice of baseline for data analysis can affect the final results. Therefore, proper description of methodology and approaches taken is key for making research reproducible.

Insufficient data discoverability

JME_0665We also heard several speakers describing problems with data discoverability. Fiona Nielsen founded Repositive – a platform for finding human genomic data. Fiona founded the platform out of frustration that genomic data was so difficult to find and access. Proliferation of data repositories made it very hard for researchers to actually find what they need.

IMG_SearchingForData_20160911Fiona started with doing a quick poll among the audience: how do researchers look for data? It turned out that most researchers find data by doing a literature research or by googling for it. This is not surprising – there is no search engine enabling looking for information simultaneously across the multiple repositories where the data is available. To make it even more complicated, Fiona reported that in 2015 80PB of human genomic data was generated. Unfortunately, only 0.5PB of human genomic data was made available in a data repository.

So how can researchers find the other datasets, which are not made available in public repositories? Repositive is a platform harvesting metadata from several repositories hosting human genomic data and providing a search engine allowing researchers to simultaneously look for datasets shared in all of them. Additionally, researchers who cannot share their research data via a public repository (for example, due to lack of participants’ consent for sharing), can at least create a metadata record about the data – to let others know that the data exist and to provide them with information on data access procedure.

The problem of data discoverability is however not only related to people’s awareness that datasets exists. Sometimes, especially in the case of complex biological data with a vast amount of variables, it can be difficult to find the right information inside the dataset. In an excellent lightening talk, Jullie Sullivan from the University of Cambridge described InterMine –platform to make biological data easily searchable (‘mineable’). Anyone can simply upload their data onto the platform to make it searchable and discoverable. One example of the platform’s use is FlyMine – database where researchers looking for results of experiments conducted on fruit fly can easily find and share information.

Difficulties with sharing personal/sensitive data

The last barrier to sharing that we discussed was related to sharing personal/sensitive research data. This barrier is perhaps the most difficult one to overcome, but here again the conference participants came up with some excellent solutions. First one came from the keynote speech by Louise Corti – with a talk with a very uplifting title: “Personal not painful: Practical and Motivating Experiences in Data Sharing”.

Louise based her talk on the long experience of the UK Data Service with providing managed access to data containing some forms of confidential/restricted information. Apart from being able to host datasets which can be made openly available, the UKDS can also provide two other types of access: safeguarded access, where data requestors need to register before downloading the data, and controlled data, where requests for data are considered on a case by case basis.

At the outset of the research project, researchers discuss their research proposals with the UKDS, including any potential limitations to data sharing. It is at this stage – at the outset of the research project, that the decision is made on the type of access that will be required for the data to be successfully shared. All processes of project management and data handling, such as data anonymisation and collection of informed consent forms from study participants, are then carried in adherence to that decision. The UKDS also offers protocols clarifying what is going to happen with research data once they are deposited with the repository. The use of standard licences for sharing make the governance of data access much more transparent and easy to understand, both from the perspective of data depositors and data re-users.

Louise stressed that transparency and willingness to discuss problems is key for mutual respect and understanding between data producers, data re-users and data curators. Sometimes unnecessary misunderstandings make data sharing difficult, when it does not need to be. Louise mentioned that researchers often confuse ‘sensitive topic’ with ‘sensitive data’ and referred to a success case study where, by working directly with researchers, UKDS managed to share a dataset about sedation at the end of life. The subject of study was sensitive, but because the data was collected and managed with the view of sharing at the end of the project, the dataset itself was not sensitive and was suitable for sharing.

As Louise said “data sharing relies on trust that data curators will treat it ethically and with respect” and open communication is key to build and maintain this trust.

So did it work?

JME_0698The purpose of this event was to engage the community in discussions about the existing limitation to data sharing. Did we succeed? Did we manage to engage the community? Judging by the fact that we have received twenty high quality abstract applications from researchers across various disciplines for only five available case study speaking slots (it was so difficult to shortlist the top five ones!) and also because the venue was full – with around eighty attendees from Cambridge and other institutions, I think that the objective was pretty well met.

Additionally, the panel discussion was led by researchers and involved fifty eight active users on the Sli.do platform for questions to panellists. There were also questions asked outside of Sli.do platform. So overall I feel that the event was a great success and it was truly fantastic to be part of it and to see the degree of participant involvement in data sharing.

Another observation is also the great progress of the research community in Cambridge in the area of sharing: we have successfully moved away from discussions whether research data is worth sharing to how to make data sharing more FAIR.

It seems that our intense advocacy, and the effort of speaking with over 1,800 academics from across the campus since January 2015 paid off and we have indeed managed to build an engaged research data management community.

Read (and see!) more:

Published 12 September 2016
Written by Dr Marta Teperek
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Could Open Research benefit Cambridge University researchers?

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This blog is part of the recent series about Open Research and reports on a discussion with Cambridge researchers  held on 8 June 2016 in the Department of Engineering. Extended notes from the meeting and slides are available at the Cambridge University Research Repository. This report is written by  Lauren Cadwallader, Joanna Jasiewicz and Marta Teperek (listed alphabetically by surname).

At the Office of Scholarly Communication we have been thinking for a while about Open Research ideas and about moving beyond mere compliance with funders’ policies on Open Access and research data sharing. We thought that the time has come to ask our researchers what they thought about opening up the research process and sharing more: not only publications and research data, but also protocols, methods, source code, theses and all the other elements of research. Would they consider this beneficial?

Working together with researchers – democratic approach to problem-solving

To get an initial idea of the expectations of the research community in Cambridge, we organised an open discussion hosted at the Department of Engineering. Anyone registering was asked three questions:

  • What frustrates you about the research process as it is?
  • Could you propose a solution that could solve that problem?
  • Would you be willing to speak about your ideas publicly?

20160608_163000Interestingly, around fifty people registered to take part in the discussion and almost all of them contributed very thought-provoking problems and appealing solutions. To our surprise, half of the people expressed their will to speak publicly about their ideas. This shaped our discussion on the day.

So what do researchers think about Open Research? Not surprisingly, we started from an animated discussion about unfair reward systems in academia.

Flawed metrics

A well-worn complaint: the only thing that counts in academia is publication in a high impact journal. As a result, early career researchers have no motivation to share their data and to publish their work in open access journals, which can sometimes have lower impact factors. Additionally, metrics based on the whole journal do not reflect the importance of the research described: what is needed is article-level impact measurements. But it is difficult to solve this systemic problem because any new journal which wishes to introduce a new metrics system has no journal-level impact factor to start with, and therefore researchers do not want to publish in it.

Reproducibility crisis: where quantity, not quality, matters

Researchers also complained that the volume of produced research is higher and higher in terms of quantity and science seems to have entered an ‘era of quantity’. They raised the concern that the quantity matters more than the quality of research. Only the fast and loud research gets rewarded (because it is published in high impact factor journals), and the slow and careful seems to be valued less. Additionally, researchers are under pressure to publish and they often report what they want to see, and not what the data really shows. This approach has led to the reproducibility crisis and lack of trust among researchers.

Funders should promote and reward reproducible research

The participants had some good ideas for how to solve these problems. One of the most compelling suggestions was that perhaps funding should go not only to novel research (as it seems to be at the moment), but also to people who want to reproduce existing research. Additionally, reproducible research itself should be rewarded. Funders could offer grant renewal schemes for researchers whose research is reproducible.

Institutions should hire academics committed to open research

Another suggestion was to incentivise reward systems other than journal impact factor metrics. Someone proposed that institutions should not only teach the next generation of researchers how to do reproducible research, but also embed reproducibility of research as an employment criteria. Commitment to Open Research could be an essential requirement in job description. Applicants could be asked at the recruitment stage how they achieve the goals of Open Research. LMU University in Munich had recently included such a statement in a job description for a professor of social psychology (see the original job description here and a commentary here).

Academia feeding money to exploitative publishers

Researchers were also frustrated by exploitative publishers. The big four publishers (Elsevier, Wiley, Springer and Informa) have a typical annual profit margin of 37%. Articles are donated to the publishers for free by the academics, and reviewed by other academics, also free of charge. Additionally, noted one of the participants, academics also act as journal editors, which they also do for free.

[*A comment about this statement was made on 15 August 2017 noting that some editors do get paid. While the participant’s comment stands as a record of what was said, we acknowledge that this is not an entirely accurate statement.]

In addition to this, publishers take away the copyright from the authors. As a possible solution to the latter, someone suggested that universities should adopt institutional licences on scholarly publishing (similar to the Harvard licence) which could protect the rights of their authors

Pre-print services – the future of publishing?

Could Open Research aid the publishing crisis? Novel and more open ways of publishing can certainly add value to the process. The researchers discussed the benefits of sharing pre-print papers on platforms like arXiv and bioRxiv. These services allow people to share manuscripts before publication (or acceptance by a journal). In physics, maths and computational sciences it is common to upload manuscripts even before submitting the manuscript to a journal in order to get feedback from the community and have the chance to improve the manuscript.

bioRxiv, the life sciences equivalent of arXiv, started relatively recently. One of our researchers mentioned that he was initially worried that uploading manuscripts into bioRxiv might jeopardise his career as a young researcher. However, he then saw a pre-print manuscript describing research similar to his published on bioRxiv. He was shocked when he saw how the community helped to change that manuscript and to improve it. He has since shared a lot of his manuscripts on bioRxiv and as his colleague pointed out, this has ‘never hurt him’. To the contrary, he suggested that using pre-print services promotes one’s research: it allows the author to get the work into the community very early and to get feedback. And peers will always value good quality research and the value and recognition among colleagues will come back to the author and pay back eventually.

Additionally, someone from the audience suggested that publishing work in pre-print services provides a time-stamp for researchers and helps to ensure that ideas will not be scooped by anyone – researchers are free to share their research whenever they wish and as fast they wish.

Publishers should invest money in improving science – wishful thinking?

It was also proposed that instead of exploiting academics, publishers could play an important role in improving the research process. One participant proposed a couple of simple mechanisms that could be implemented by publishers to improve the quality of research data shared:

  • Employment of in-house data experts: bioinfomaticians or data scientists, who could judge whether supporting data is of a good enough quality
  • Ensure that there is at least one bioinfomatician/data scientist on the reviewing panel for a paper
  • Ask for the data to be deposited in a public, discipline-specific repository, which would ensure quality control of the data and adherence to data standards.
  • Ask for the source code and detailed methods to be made available as well.

Quick win: minimum requirements for making shared data useful

A requirement that, as a minimum, three key elements should be made available with publications – the raw data, the source code and the methods – seems to be a quick win solution to make research data more re-usable. Raw data is necessary as it allows users to check if the data is of a good quality overall, while publishing code is important to re-run the analysis and methods need to be detailed enough to allow other researchers to understand all the processes involved in data processing. An excellent case study example comes from Daniel MacArthur who has described how to reproduce all the figures in his paper and has shared the supporting code as well.

It was also suggested that the Office of Scholarly Communication could implement some simple quality control measures to ensure that research data supporting publications is shared. As a minimum the Office could check the following:

  • Is there a data statement in the publication?
  • If there is a statement – is there a link to the data?
  • Does the link work?

This is definitely a very useful suggestion from our research community and in fact we have already taken this feedback aboard and started checking for data citations in Cambridge publications.

Shortage of skills: effective data sharing is not easy

The discussion about the importance of data sharing led to reflections that effective data sharing is not always easy. A bioinformatician complained that datasets that she had tried to re-use did not satisfy the criteria of reproducibility, nor re-usability. Most of the time there was not enough metadata available to successfully use the data. There is some data shared, there is the publication, but the description is insufficient to understand the whole research process: the miracle, or the big discovery, happens somewhere in the middle.

Open Research in practice: training required

Attendees agreed that it requires effort and skills to make research open, re-usable and discoverable by others. More training is needed to ensure that researchers are equipped with skills to allow them to properly use the internet to disseminate their research, as well as with skills allowing them to effectively manage their research data. It is clear that discipline-specific training and guidance around how to manage research data effectively and how to practise open research is desired by Cambridge researchers.

Nudging researchers towards better data management practice

Many researchers have heard or experienced first-hand horror stories of having to follow up on somebody else’s project, where it was not possible to make any sense of the research data due to lack of documentation and processes. This leads to a lot of time wasted in every research group. Research data need to be properly documented and maintained to ensure research integrity and research continuity. One easy solution is to nudge researchers towards better research data management practice could be formalised data management requirements. Perhaps as a minimum, every researchers should have a lab book to document research procedures.

The time is now: stop hypocrisy

Finally, there was a suggestion that everyone should take the lead in encouraging Open Research. The simplest way to start is to stop being what has been described as ‘a hypocrite’ and submit articles to journals which are fully Open Access. This should be accompanied by making one’s reviews openly available whenever possible. All publications should be accompanied by supporting research data and researchers should ensure that they evaluate individual research papers and that their judgement is not biased by the impact factor of the journal.

Need for greater awareness and interest in publishing

One of the Open Access advocates present at the meeting stated that most researchers are completely unaware of who are the exploitative and ethical publishers and the differences between them. Researchers typically do not directly pay the exploitative publishers and are therefore not interested in looking at the bigger picture of sustainability of scholarly publishing. This is clearly an area when more training and advocacy can help and the Office of Scholarly Communication is actively involved in raising awareness in Open Access. However, while it is nice to preach in a room of converts, how do we get other researchers involved in Open Access? How should we reach out to those who can’t be bothered to come to a discussion like the one we had? This is the area where anyone who understands the benefits Open Access has a job to do.

Next steps

We are extremely grateful to everyone who came to the event and shared their frustrations and ideas on how to solve some problems. We noted all the ideas on post it notes – the number of notes at the end of the discussion was impressive, an indication of how creative the participants were in just 90 minutes. It was a very productive meeting and we wish to thank all the participants for their time and effort.

20160608_160721

We think that by acting collaboratively and supporting good ideas we can achieve a lot. As an inspiration, McGill University’s Montreal Neurological Institute and Hospital (the Neuro) in Canada have recently adopted a policy on Open Research: over the next five years all results, publications and data will be free to access by everyone.

Follow up

If you would like to host similar discussions directly in your departments/institutes, please get in touch with us at info@osc.cam.ac.uk – we would be delighted to come over and hear from researchers in your discipline.

In the meantime, if you have any additional ideas that you wish to contribute, please send them to us. Everyone who is interested in being informed about the progress here is encouraged to sign up for a mailing distribution list here.

Extended notes from the meeting and slides are available at the Cambridge University Research Repository. We are particularly grateful to Avazeh Ghanbarian, Corina Logan, Ralitsa Madsen, Jenny Molloy, Ross Mounce and Alasdair Russell (listed alphabetically by surname) for agreeing to publicly speak at the event.

Published 3 August 2016
Written by Lauren Cadwallader, Joanna Jasiewicz and Marta Teperek
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Show me the money – the path to a sustainable Research Data Facility

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Like many institutions in the UK, Cambridge University has responded to research funders’ requirements for data management and  sharing with a concerted effort to support our research community in good data management and sharing practice through our Research Data Facility. We have written a few times on this blog and presented to describe our services. This blog is a description of the process we have undertaken to support these services in the long term.

Funders expect  that researchers make the data underpinning their research available and provide a link to this data in the paper itself. The EPSRC started checking compliance with their data sharing requirement on 1 May 2015. When we first created the Research Data Facility we spoke to many researchers across the institution and two things became very clear. One was that there was considerable confusion about what actually counts as data, and the second was that sharing data on publication is not something that can be easily done as an afterthought if the data was not properly managed in the first place.

We have approached these issues separately. To try and determine what is actually required from funders beyond the written policies we have invited representatives from our funders to come to discussions and forums with our researchers to work out the details. So far we have hosted Ben Ryan from the EPSRC, Michael Ball from the BBSRC and most recently David Carr and Jamie Enoch from the Wellcome Trust and CRUK respectively.

Dealing with the need for awareness of research data management has been more complex. To raise awareness of good practice in data management and sharing we embarked on an intense advocacy programme and in the past 15 months have organised 71 information sessions about data sharing (speaking with over 1,700 researchers). But we also needed to ensure the research community was managing its data from the beginning of the research process. To assist this we have developed workshops on various aspects of data management (hosting 32 workshops in the past year), a comprehensive website, a service to support researchers with their development of their research data management plans and a data management consultancy service.

So far, so good. We have had a huge response to our work, and while we encourage researchers to use the data repository that best suits their material, we do offer our institutional repository Apollo as an option. We are as of today, hosting 499 datasets in the repository. The message is clearly getting through.

Sustainability

The word sustainability (particularly in the scholarly communication world) is code for ‘money’. And money has become quite a sticking point in the area of data management. The way Cambridge started the Research Data Facility was by employing a single person, Dr Marta Teperek for one year, supported by the remnants of the RCUK Transition Fund. It became quickly obvious that we needed more staff to manage the workload and now the Facility employs half an Events and Outreach Coordinator and half a Repository Manager plus a Research Data Adviser who looks after the bulk of the uploading of data sets into the repository.

Clearly there was a need to work out the longer term support for staffing the Facility – a service for which there are no signs of demand slowing. Early last year we started scouting around for options.  In April 2013 the RCUK released some guidance that said it was permissible to recover costs from grants through direct charges or overheads – but noted institutions could not charge twice. This guidance also mentioned that it was permissible for institutions to recover costs of RDM Facilities as other Small Research Facilities, “provided that such facilities are transparently charged to all projects that use them”.

Transparency

On the basis of that advice we established a Research Data Facility as a Small Research Facility according to the Transparent Approach to Costing (TRAC) methodology. Our proposal was that Facility’s costs will be recovered from grants as directly allocated costs. We chose this option rather than overheads because of the advantage of transparency to the funder of our activities. By charging grants this way it meant a bigger advocacy and education role for the Facility. But the advantage is that it would make researchers aware that they need to consider research data management seriously, that this involves both time and money, and that it is an integral part of a grant proposal.

Dr Danny Kingsley has argued before (for example in a paper ‘Paying for publication: issues and challenges for research support services‘) that by centralising payments for article processing charges, the researchers remain ignorant of the true economics of the open access system in the way that they are generally unaware of the amounts spent on subscriptions. If we charged the costs of the Facility into overheads, it becomes yet another hidden cost and another service that ‘magically’ happens behind the scenes from the researcher’s point of view.

In terms of the actual numbers, direct costs of the Research Data Facility included salaries for 3.2 FTEs (a Research Data Facility Manager, Research Data Adviser, 0.5 Outreach and Engagement Coordinator, 0.5 Repository Manager, 0.2 Senior Management time), hardware and hardware maintenance costs, software licences, costs of organising events as well as the costs of staff training and conference attendance. The total direct annual cost of our Facility was less than £200,000. These are the people cost of the Facility and are not to be confused with the repository costs (for which we do charge directly).

Determining how much to charge

Throughout this process we have explored many options for trying to assess a way of graduating the costing in relation to what support might be required. Ideally, we would want to ensure that the Facility costs can be accurately measured based on what the applicant indicated in their data management plan. However, not all funders require data management plans. Additionally, while data management plans provide some indication of the quantity of data (storage) to be generated, they do not allow a direct estimate of the amount of data management assistance required during the lifetime of the grant. Because we could not assess the level of support required for a particular research project from a data management plan, we looked at an alternative charging strategy.

We investigated charging according to the number of people on a team, given that the training component of the Facility is measurable by attendees to workshops. However, after investigation we were unable to easily extract that type of information about grants and this also created a problem for charging for collaborative grants. We then looked at charging a small flat charge on every grant requiring the assistance of the Facility and at charging proportionally to the size (percentage of value) of the grant. Since we did not have any compelling evidence that bigger grants require more Facility assistance, we proposed a model of flat charging on all grants, which require Facility assistance. This model was also the most cost-effective from an administrative point of view.

As an indicator of the amount of work involved in the development of the Business Case, and the level of work and input that we have received relating to it, the document is now up to version 18 – each version representing a recalculation of the costings.

Collaborative process

A proposal such as we were suggesting – that we charge the costs of the Facility as a direct charge against grants – is reasonably radical. It was important that we ensure the charges would be seen as fair and reasonable by the research community and the funders. To that end we have spent the best part of a year in conversation with both communities.

Within the University we had useful feedback from the Open Access Project Board (OAPB) when we first discussed the option in July last year. We are also grateful to the members of our community who subsequently met with us in one on one meetings to discuss the merits of the Facility and the options for supporting it. At the November 2015 OAPB meeting, we presented a mature Business Case. We have also had to clear the Business Case through meetings of the Resource Management Committee (RMC).

Clearly we needed to ensure that our funders were prepared to support our proposal. Once we were in a position to share a Business Case with the funders we started a series of meetings and conversations with them.

The Wellcome Trust was immediate in its response – they would not allow direct charging to grants as they consider this to be an overhead cost, which they do not pay. We met with Cancer Research UK (CRUK) in January 2016 and there was a positive response about our transparent approach to costing and the comprehensiveness of services that the Facility provides to researchers at Cambridge. These issues are now being discussed with senior management at CRUK and discussions with CRUK are still ongoing at the time of writing this report (May 2016). [Update 24 May: CRUK agreed to consider research data management costs as direct costs on grant applications on a case by case basis, if justified appropriately in the context of the proposed research].

We encourage open dialogue with the RCUK funders about data management. In May 2015 we invited Ben Ryan to come to the University to talk about the EPSRC expectations on data management and how Cambridge meets these requirements. In August 2015 Michael Ball from the BBSRC came to talk to our community. We had an indication from the RCUK that our proposal was reasonable in principle. Once we were in a position to show our Business Case to the RCUK we invited Mark Thorley to discuss the issue and he has been in discussion with the individual councils for their input to give us a final answer.

Administrative issues

Timing in a decision like this is challenging because of the large number of systems within the institution that would be affected if a change were to occur. In anticipation of a positive response we started the process of ensuring our management and financial systems were prepared and able to manage the costing into grants – to ensure that if a green light were given we would be prepared.  To that end we have held many discussions with the Research Office on the practicalities of building the costing into our systems to make sure the charge is easy to add in our grant costing tool. We also had numerous discussions on how to embed these procedures in their workflows for validating whether the Facility services are needed and what to do if researchers forget to add them. The development has now been done.

A second consideration is the necessity to ensure all of the administrative staff involved in managing research grants (at Cambridge this is a  group of over 100 people) are aware of the change and how to manage both the change to the grant management system and also manage the questions from their research community. Simultaneously we were also involved in numerous discussions with our invaluable TRAC team at the Finance Division at the University who helped us validate all the Facility costs (to ensure that none of the costs are charged twice) and establishing costs centres and workflows for recovering money from grants.

Meanwhile we have had to keep our Facility staff on temporary contracts until we are in a position to advertise the roles. There is a huge opportunity cost in training people up in this area.

Conclusion

As it happened, the RCUK has come back to us to say that we can charge this cost to grants but as an overhead rather than direct cost. Having this decision means we can advertise the positions and secure our staffing situation. But we won’t be needing the administrative amendments to the system, nor the advocacy programme.

It has been a long process given we began preparing the Business Case in March 2015. The consultation throughout the University and the engagement of our community (both research and funder) has given us an opportunity to discuss the issues of research data management more widely. It is a shame – from our perspective – that we will not be able to be transparent about the costs of managing data effectively.

The funders and the University are all working towards a shared goal – we are wanting a culture change towards more open research, including the sharing of research data. To achieve this we need a more aware and engaged research community on these matters.  There is much advocacy to do.

Published 8 May 2016
Written by Dr Danny Kingsley and Dr Marta Teperek
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