Tag Archives: research data management

Open Data – moving science forward or a waste of money & time?

November 27, 2015UncategorizedBlog posts, CERN, compliance, data, funders, Medical Research Council, open data, policy, publishing, research, research data management, reward, social mediaOffice of Scholarly Communication

On the 4 November the Research Data Facility at Cambridge University invited some inspirational leaders in the area of research data management and asked them to address the question: “is open data moving science forward or a waste of money & time?”. Below are Dr Marta Teperek’s impressions from the event.

Great discussion

Want to initiate a thought-provoking discussion on a controversial subject? The recipe is simple: invite inspirational leaders, bright people with curious minds and have an excellent chair. The outcome is guaranteed.

We asked some truly inspirational leaders in data management and sharing to come to Cambridge to talk to the community about the pros and cons of data sharing. We were honoured to have with us:

Rafael Carazo-Salas, Group Leader, Department of Genetics, University of Cambridge
@RafaCarazoSalas
Sarah Jones, Senior Institutional Support Officer from the Digital Curation Centre; @sjDCC
Frances Rawle, Head of Corporate Governance and Policy, Medical Research Council; @The_MRC
Tim Smith, Group Leader, Collaboration and Information Services, CERN/Zenodo; @TimSmithCH
Peter Murray-Rust, Molecular Informatics, Dept. of Chemistry, University of Cambridge, ContentMine; @petermurrayrust

The discussion was chaired by Dr Danny Kingsley, the Head of Scholarly Communication at the University of Cambridge (@dannykay68).

What is the definition of Open Data?

The discussion started off with a request for a definition of what “open” meant. Both Peter and Sarah explained that ‘open’ in science was not simply a piece of paper saying ‘this is open’. Peter said that ‘open’ meant free to use, free to re-use, and free to re-distribute without permission. Open data needs to be usable, it needs to be described, and to be interpretable. Finally, if data is not discoverable, it is of no use to anyone. Sarah added that sharing is about making data useful. Making it useful also involves the use of open formats, and implies describing the data. Context is necessary for the data to be of any value to others.

What are the benefits of Open Data?

Next came a quick question from Danny: “What are the benefits of Open Data”? followed by an immediate riposte from Rafael: “What aren’t the benefits of Open Data?”. Rafael explained that open data led to transparency in research, re-usability of data, benchmarking, integration, new discoveries and, most importantly, sharing data kept it alive. If data was not shared and instead simply kept on the computer’s hard drive, no one would remember it months after the initial publication. Sharing is the only way in which data can be used, cited, and built upon years after the publication. Frances added that research data originating from publicly funded research was funded by tax payers. Therefore, the value of research data should be maximised. Data sharing is important for research integrity and reproducibility and for ensuring better quality of science. Sarah said that the biggest benefit of sharing data was the wealth of re-uses of research data, which often could not be imagined at the time of creation.

Finally, Tim concluded that sharing of research is what made the wheels of science turn. He inspired further discussions by strong statements: “Sharing is not an if, it is a must – science is about sharing, science is about collectively coming to truths that you can then build on. If you don’t share enough information so that people can validate and build up on your findings, then it basically isn’t science – it’s just beliefs and opinions.”

Tim also stressed that if open science became institutionalised, and mandated through policies and rules, it would take a very long time before individual researchers would fully embrace it and start sharing their research as the default position.

I personally strongly agree with Tim’s statement. Mandating sharing without providing the support for it will lead to a perception that sharing is yet another administrative burden, and researchers will adopt the ‘minimal compliance’ approach towards sharing. We often observe this attitude amongst EPSRC-funded researchers (EPSRC is one of the UK funders with the strictest policy for sharing of research data). Instead, institutions should provide infrastructure, services, support and encouragement for sharing.

Big data

Data sharing is not without problems. One of the biggest issues nowadays it the problem of sharing of big data. Rafael stressed that with big data, it was extremely expensive not only to share, but even to store the data long-term. He stated that the biggest bottleneck in progress was to bridge the gap between the capacity to generate the data, and the capacity to make it useful. Tim admitted that sharing of big data was indeed difficult at the moment, but that the need would certainly drive innovation. He recalled that in the past people did not think that one day it would be possible just to stream videos instead of buying DVDs. Nowadays technologies exist which allow millions of people to watch the webcast of a live match at the same time – the need developed the tools. More and more people are looking at new ways of chunking and parallelisation of data downloads. Additionally, there is a change in the way in which the analysis is done – more and more of it is done remotely on central servers, and this eliminates the technical barriers of access to data.

Personal/sensitive data

Frances mentioned that in the case of personal and sensitive data, sharing was not as simple as in basic sciences disciplines. Especially in medical research, it often required provision of controlled access to data. It was not only important who would get the data, but also what they would do with it. Frances agreed with Tim that perhaps what was needed is a paradigm shift – that questions should be sent to the data, and not the data sent to the questions.

Shades of grey: in-between “open” and “closed”

Both the audience and the panellists agreed that almost no data was completely “open” and almost no data was completely “shut”. Tim explained that anything that gets research data off the laptop to a shared environment, even if it was shared only with a certain group, was already a massive step forward. Tim said: “Open Data does not mean immediately open to the entire world – anything that makes it off from where it is now is an important step forward and people should not be discouraged from doing so, just because it does not tick all the other checkboxes.” And this is yet another point where I personally agreed with Tim that institutionalising data sharing and policing the process is not the way forward. To the contrary, researchers should be encouraged to make small steps at a time, with the hope that the collective move forward will help achieving a cultural change embraced by the community.

Open Data and the future of publishing

Another interesting topic of the discussion was the future of publishing. Rafael started explaining that the way traditional publishing works had to change, as data was not two-dimensional anymore and in the digital era it could no longer be shared on a piece of paper. Ideally, researchers should be allowed to continue re-analysing data underpinning figures in publications. Research data underpinning figures should be clickable, re-formattable and interoperable – alive.

Danny mentioned that the traditional way of rewarding researchers was based on publishing and on journal impact factors. She asked whether publishing data could help to start rewarding the process of generating data and making it available. Sarah suggested that rather than having the formal peer review of data, it would be better to have an evaluation structure based on the re-use of data – for example, valuing data which was downloadable, well-labelled, re-usable.

Incentives for sharing research data

The final discussion was around incentives for data sharing. Sarah was the first one to suggest that the most persuasive incentive for data sharing is seeing the data being re-used and getting credit for it. She also stated that there was also an important role for funders and institutions to incentivise data sharing. If funders/institutions wished to mandate sharing, they also needed to reward it. Funders could do so when assessing grant proposals; institutions could do it when looking at academic promotions.

Conclusions and outlooks on the future

This was an extremely thought-provoking and well-coordinated discussion. And maybe due to the fact that many of the questions asked remained unanswered, both the panellists and the attendees enjoyed a long networking session with wine and nibbles after the discussion.

From my personal perspective, as an ex-researcher in life sciences, the greatest benefit of open data is the potential to drive a cultural change in academia. The current academic career progression is almost solely based on the impact factor of publications. The ‘prestige’ of your publications determines whether you will get funding, whether you will get a position, whether you will be able to continue your career as a researcher. This, connected with a frequently broken peer-review process, leads to a lot of frustration among researchers. What if you are not from the world’s top university or from a famous research group? Will you be able to still publish your work in a high impact factor journal? What if somebody scooped you when you were about to publish results of your five years’ long study? Will you be able to find a new position? As Danny suggested during the discussion, if researchers start publishing their data in the ‘open”’ there is a chance that the whole process of doing valuable research, making it useful and available to others will be rewarded and recognised. This fits well with Sarah’s ideas about evaluation structure based on the re-use of research data. In fact, more and more researchers go to the ‘open’ and use blog posts and social media to talk about their research and to discuss the work of their peers. With the use of persistent links research data can be now easily cited, and impact can be built directly on data citation and re-use, but one could also imagine some sort of badges for sharing good research data, awarded directly by the users. Perhaps in 10 or 20 years’ time the whole evaluation process will be done online, directly by peers, and researchers will be valued for their true contributions to science.

And perhaps the most important message for me, this time as a person who supports research data management services at the University of Cambridge, is to help researchers to really embrace the open data agenda. At the moment, open data is too frequently perceived as a burden, which, as Tim suggested, is most likely due to imposed policies and institutionalisation of the agenda. Instead of a stick, which results in the minimal compliance attitude, researchers need to see the opportunities and benefits of open data to sign up for the agenda. Therefore, the Institution needs to provide support services to make data sharing easy, but it is the community itself that needs to drive the change to “open”. And the community needs to be willing and convinced to do so.

Further resources

Click here to see the full recording of the Open Data Panel Discussion.
And here you can find a storified version of the event prepared by Kennedy Ikpe from the Open Data Team.

Thank you

We also wanted to express a special ‘thank you’ note to Dan Crane from the Library at the Department of Engineering, who helped us with all the logistics for the event and who made it happen.

Published 27 November 2015
Written by Dr Marta Teperek

Data sharing – build it and they will come

August 24, 2015Uncategorizeddata, data management plan, funders, open data, repository, research data managementOffice of Scholarly Communication

If a tree falls in the forest and no one was there to hear it, did it happen? You could ask the same philosophical question of research – if no-one can see the research results, what was the point in the first place?

Moving science forward and increasing the knowledge of the world around implies exchange of findings. Society cannot benefit from research if there is no awareness of what has been done. Managing and sharing research data is a fundamentally important part of the research process. Yet researchers are often reluctant to share their data, and some are openly hostile to the idea.

This blog describes the research data services provided at Cambridge University which are attempting to encourage and assist researchers manage and share their data.

A tough start

The Data Management Facility project at Cambridge began operations in January 2015. At the time there was very little user support for data management in place. There was no advocacy, no training and no centralised tools to support researchers in research data management.

There had been a substantial body of work undertaken in 2010-2012 as part of the ‘Incremental’ project into research data management, but once the project money ended, the resources remained available but were not updated.

One of the initial challenges was an out of date institutional repository. Cambridge University was one of the original test-bed institutions for DSpace in 2005. While there had been considerable effort invested in the establishment of the repository, it had in recent years been somewhat neglected. The lack of both awareness of the repository and support for researchers was reflected in the numbers: during the first decade of the repository, only 72 datasets had been deposited.

In addition, the Engineering and Physical Sciences Research Council (EPSRC) had compliance expectations for funded research kicking in May 2015. This gave us five months to pull the Research Data Facility together. It was a tough start.

Understanding researchers’ needs

Tight deadlines often mean the temptation is to create short-term solutions. But we did not want to take this path. Solutions created without prior understanding of the need have no guarantee they will resolve the actual issues at hand.

So we started talking with researchers. We met and spoke with hundreds of researchers across all disciplines and fields of study – Principal Investigators, postdocs, students, and staff members. These were both group sessions and individual meetings. We told them about the importance of sharing research data, and in return we listened to what researchers told us about their worries and possible problems with data sharing.

To date, we have spoken with over 1000 researchers, and from each meeting we kept detailed notes of all the questions/comments received.

We have additionally conducted a questionnaire to better understand researchers’ needs for research data management support. Of the researchers surveyed, 83% indicated that it is ‘very useful’ for the University to provided both information about funders’ expectations for research data sharing and management, and support.

Solution 1 – Providing information

In March 2015 we launched the Research Data Management website which is a single location for solutions to all research data management needs. The website contains:

Key information about what researchers need to know about research data management
Summaries of and links to funder requirements for research data sharing
Information about making data available

and much more.

The key idea behind the website is to provide an easy to navigate place with all necessary information. The website is being constantly updated, and new information is regularly added in response to feedback received from researchers.

Concurrently we have been conducting tailored information sessions about funders’ requirements for sharing data and support available at the University of Cambridge. We run these sessions at multiple locations across the University, and to audiences of various types. The sessions ranged from open sessions in central locations to dedicated sessions hosted at individual departments, and speaking with individual research groups. Slides from information sessions are always made available for attendees to download.

Solution 2 – Assistance with data management plans and supporting data management

In the survey 82% of researchers said it would be very helpful if there were someone at the University available to help with data management plans. To address this, we have:

Added tailored information about data management plans to our information sessions.
Linked the DMPonline tool from our data website. This allows researchers to prepare funder specific data management plans
Organised data management plan clinic sessions (one to one appointments on demand)
Prepared guidelines on how to fill in a data management plan.

Additionally, 63% researchers indicated that it would be ‘very useful’, and further 31% indicated that it would be ‘useful’ to have workshops on research data management. We have therefore prepared a 1.5 hour interactive introductory workshop to research data management, which is now offered across various departments across the University. We are also developing the skill sets within the library staff across the institution to deliver research data management training to researchers from their field.

Solution 3 – Providing an institutional repository

Finally, 79% of researchers indicated that it would make data sharing easier if the University maintained its own, easy to use data repository. We therefore had to do something about our repository, which had not been updated for a long time. We have rolled-out series of updates to the repository, taking it to Version 4.3, which will allow minting DOIs to datasets.

Meantime we also had to think of a strategy to make data sharing as easy as possible. The existing processes for uploading research data to the repository were very complicated and discouraging to researchers. We did not have any web-mediated facility that would allow researchers to easily get their data to us. In fact, most of the time we asked researchers to bring their data to us on external hard drives. This was not an acceptable solution in the 21^st century!

Researchers like simple processes, Dropbox-like solutions, where one can easily drag and drop files. We have therefore created a simple webform, which asks researchers for the minimal necessary metadata information, and allows them to simply drag and drop their data files.

The outcomes

It turned in the end it was really worth the effort of understanding researchers’ needs before considering solutions. As of 24 August 2015, the Research Data Management website has been visited 10,992 times. Our training sessions on research data management and data planning have received extremely good feedback – 73% of respondents indicated that our workshops should be ‘essential’ to all PhD students.

And most importantly, since we launched our easy-to-upload website form for research data, we have received 122 research data submissions – in four months we have received more than 1.5 times more research outputs than in ten years of our repository’s lifetime.

So our advice to anyone wishing to really support researchers is to truly listen to their needs, and address their problems. If you create useful services, there is no need to worry about the uptake.

data-plasma4 This infographic demonstrates how successful the Research Data Facility has been. Prepared by Laura Waldoch from the University Library, it is available for download.

To know more about our activities, follow us on Twitter.

Published 24 August 2015
Written by Dr Marta Teperek and Dr Danny Kingsley

Data management – one size does not fit all

May 14, 2015UncategorizedArkivum, DCC, digital curation, DSpace, EPSRC, figshare, open data, research data management, UK Data ServiceOffice of Scholarly Communication

As the Research Data Facilitator at the University of Cambridge, I am part of the team establishing a Research Data Management (RDM) Facility at the University. This blog is a note of my impressions from the Digital Curation Centre (DCC) meeting held in London on the 28^th April 2015: Preparing Data for Deposit.

As always, the DCC meeting was extremely useful for networking. I met with people at similar roles at other institutions. And again, the breakout sessions were invaluable – they allowed us to exchange precious experience, feedback gained and lessons learnt while developing RDM services.

What could have been done better though is more appreciation for differences between universities.

Unrealistic staffing

The talk from the keynote speaker, Louise Corti, the Associate Director at the UK Data Service, was very inspirational. I loved the uplifting expression that RDM supporters are like artists evangelising researchers. It was great to hear about RDM solutions available at the UK Data Service, and the professional approach to research data, with every aspect of data curation addressed by the excellent team of 70 dedicated people, with precise workflows for data processing.

However, how realistic it is for a university to develop similar solutions locally? Which University would be able to dedicate similar amount of resources for the development of an RDM facility?

At the University of Cambridge, I am the only full-time employee dedicated to work on establishment and provision of RDM services to our researchers. There is a team of people supporting the facility but these staff are shared with other projects. I would have very much appreciated what would be the scalable solution that the UK Data Service could recommend universities to develop, knowing that resources available are nowhere near what a 70 people team could offer.

Scalability

On the other hand, we had a presentation from the University of Loughborough. The University, represented by Gary Brewerton, teamed up with Figshare and Arkivum (Mark Hahnel and Matthew Addis, respectively). The three of them explained to us the infrastructure developed to support RDM management at the University of Loughborough. The University data repository, DSpace, has been equipped with archival storage provided by Arkivum, which guarantees 100% data integrity. Additionally, researchers at the University of Loughborough can benefit from the use of Figshare, which provides them with a user-friendly research data sharing platform.

These systems seemed to offer excellent solutions to researchers, but somehow I could not help having the impression of listening to sales pitches. Are there any disadvantages of these solutions? Are there any alternatives?

Figshare charges for the file transfer (downloading of openly accessible data is actually not free for institutions). How substantial would be these charges for bigger institutions, producing huge amounts of valuable research data, frequently sought after and downloaded by others? Would institutions be able to sustain the cost of data access to their most valuable research datasets?

Risk management

The Loughborough solutions do not appear to take into account risks associated with implementation of services from third party providers at bigger, research-intense universities. At the University of Cambridge we have almost 300 EPSRC-funded research grants. In April this year alone our data repository received 40GB of research data deposits coming from EPSRC-funded projects. Producing valuable research outputs is business-critical for universities.

What would be the costs associated with the data transfer of supposedly open-access datasets if these were available via Figshare? Is there any upper limit on possible transfer charges?

What is the long-term risk of handing over university’s research data holdings to a third party service provider? Note that some UK research funders expect data to be stored long-term, and in some cases in perpetuity (10 years from the last access). What will be the conditions for research data storage offered by these external providers in 10, 20, 30 years time? How will the cost change? Will it be easy/possible to transfer all research data somewhere else?

Figshare has recently entered into a legal partnership with Macmillan (you can read more about it in a blog post from Dr Peter Murray-Rust) – how will this partnership evolve in the future?

Suggestion

It would be extremely valuable if RDM solutions proposed at DCC meetings could be discussed taking into account the size of the institution, the amount of research conducted at the University, and the size of the RDM team locally available to work on the implementation of the solution.

One size does not and will not fit all, and a better recognition of differences between organisations would greatly help developing optimal solutions for each individual institution. Additionally, it seems to me of key importance to openly talk about drawbacks of each solution for universities to efficiently mitigate future risks.

Published 14 May 2015
Written by Dr Marta Teperek

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Open Research at Cambridge