Tag Archives: EPSRC

Software Licensing and Open Access

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As part of the Office of Scholarly Communication Open Access Week celebrations, we are uploading a blog a day written by members of the team. Wednesday is a piece by Dr Marta Teperek reporting on the Software Licensing Workshop held on 14 September 2015 at Cambridge.

Uncertainties about sharing and licensing of software

If the questions that the Research Data Service Team have been asked during data sharing information sessions with over 1000 researchers at the University of Cambridge are any indicator, then there is a great deal of confusion about sharing source code.

There have been a wide range of questions during the discussions in these sessions, and the Research Data Service Team has recorded these. We are systematically ensuring that the information we are providing to our research community is valid and accurate. To address the questions about source code we decided to call in expert help. Shoaib Sufi and Neil Chue Hong* from the Software Sustainability Institute agreed to lead a workshop on Software Licensing in September, at the Computer Lab in Cambridge. Shoaib’s slides are here, and Neil’s slides on Open Access policies and software sharing are here.

Malcolm Grimshaw and Chris Arnot from Cambridge Enterprise also came to the workshop to answer questions about Cambridge-specific guidance on software commercialisation.

We had over 50 researchers and several research data managers from other UK universities attending the Software Licensing workshop. The main questions we were trying to resolve was: Are researchers expected to share source code they used in their projects? And if so, under what conditions?

Is software considered as ‘research data’ and does it need to be shared?

The starting question in the discussion was whether software needed to be shared. Most public funders now require that research data underpinning publications is made available. What is the definition of research data? According to the EPSRC research data “is defined as recorded factual material commonly retained by and accepted in the scientific community as necessary to validate research findings”. Therefore, if software is needed to validate findings described in a publication, researchers are expected to make it available as widely as possible. There are some exceptions to this rule. For example, if there is an intention to commercialise the software there might not be a need to share it, but the default assumption is that the software should be shared.

The importance of putting a licence on software

It is important that before any software is shared, the creator considers what they would like others to be able to do with it. The way to indicate the intended reuse of the software is to place a licence on it. This governs the permission being granted to others with regards to source code by the copyright holder(s). A licence determines whether the person who wants to get hold of software is allowed to use, copy, resell, change, or distribute it. Additionally, a licence should also determine who is liable if something goes wrong with the software.

Therefore, a licence not only protects the intellectual property, but also helps others to use the software effectively. If people who are potentially interested in a given piece of software do not know what they are allowed to do with it, it is possible they will search for alternative solutions. As a consequence, researchers could lose important collaborators, buyers, or simply decrease the citation rate that could have been gained from people using and citing software in their publications.

Who owns the copyright?

The most difficult question when it comes to software licensing is determining who owns the copyright – who is allowed to license the software used in research? If this is software created by a particular researcher then it is likely that s/he will be the copyright owner. At the University of Cambridge researchers are the primary owners of intellectual property. This is however a very generous right – typically employers do not allow their employees to retain copyright ownership. Therefore, the issue of copyright ownership might get very complicated for researchers involved in multi-institutional collaborations. Additionally, sometimes funders of research will retain copyright ownership of research outputs.

Consequences of licensing

An additional complication with licensing software is that most licences cannot be revoked. Once something has been licensed to someone under a certain licence, it is not possible to take it back and change the licence. Moreover, if there is one licence for a set of software, it might not be possible to license a patch to the software under a different licence. The issue of licence compatibility sparked a lot of questions during the workshop, with no easy answers available. The overall conclusion was that whenever possible, mixing of licences should be avoided. If use of various licences is necessary, researchers are recommended to get advice from the Legal Services Office.

Good practice for software management

So what are the key recommendations for good practice for software management? Before the start of a research project, researchers should think about who the collaborators and funders are, and what the employer’s expectations are with regards to intellectual property. This will help to determine who will own the copyright over the software. Funders’ and institutional policies for research data sharing should be consulted for expectations about software sharing With this information it is possible to prepare a data management plan for the grant application.

During the project researchers need to ensure that their software is hosted in an appropriate code repository – for example, GitHub or Bitbucket. It is important to create (and keep updating!) metadata describing any generated data and software.

Finally, when writing a paper, researchers need to deposit all releases of data/software relevant to the publication in a suitable repository. It is best to choose a repository which provides persistent links e.g. Zenodo (which has a GitHub integration), or the University of Cambridge data repository (Apollo). It is important to ensure that software is licensed under an appropriate licence – in line with what others should be allowed to do with the software, and in agreement with any obligations there might be with any other third parties (for example, funders of the research). If there is a need to restrict the access to the software, metadata description should give reasons for this restriction and conditions that need to be met for the access to be granted.

Valuable resources to help make right decisions

Both Neil and Shoaib agreed that proper management and licensing of software might be sometimes complicated. Therefore, they recommended various resources and tools to provide guidance for researchers:

The workshop was organised in collaboration with Stephen Eglen from the Department of Applied Mathematics and Theoretical Physics (University of Cambridge) who chaired the meeting, and with Andrea Kells from the Computer Lab (University of Cambridge) who hosted the workshop.

The Research Data Service is also providing various other opportunities for our research community to pose questions directly of the funding bodies. We invited Ben Ryan from the EPSRC to come to speak to a group of researchers in May and the resulting validated FAQs are now published on our research data management website. Similarly, researchers met with Michael Ball from the BBSRC in August.

These opportunities are being embraced by our research community.

*About the speakers

Shoaib Sufi – Community Lead at the Software Sustainability Institute

Shoaib leads the Institute’s community engagement activities and strategies. Graduating in Computer Science from the University of Manchester in 1997, he has worked in the commercial sector as a systems programmer and then as software developer, metadata architect and eventually a project manager at the Science and Facilities Technologies Council (STFC).

Neil Chue Hong – Director at the Software Sustainability Institute

Neil is the founding Director of the Software Sustainability Institute. Graduating with an MPhys in Computational Physics from the University of Edinburgh, he began his career at EPCC, becoming Project Manager there in 2003. During this time he led the Data Access and Integration projects (OGSA-DAI and DAIT), and collaborated in many e-Science projects, including the EU FP6 NextGRID project.

Published 21 October 2015
Written by Dr Marta Teperek
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The purpose, practicalities, pitfalls and policies of managing and sharing data in the UK

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As part of the Office of Scholarly Communication Open Access Week celebrations, we are uploading a blog a day written by members of the team. Tuesday is a piece by Dr Danny Kingsley reflecting the talk she gave this morning to  the Royal Society of Chemistry, Chemical Information and Computer Applications Group conference – Measurement, Information and Innovation: Digital Disruption in the Chemical Sciences.

The data policy landscape

The policy position on data management in the UK is driven on many levels. Many institutions now have policies – an example is the Cambridge University Research Data Management Policy Framework. Increasingly publishers such as PLOS are requiring that research published in their journals is accompanied by the data underpinning the research. Some journals, such as Nature’s Scientific Data are specifically data-only journals

There has been a country-wide movement towards opening up data. Consultation on the Draft Concordat on Open Research Data released by the RCUK ended on 28 September. Cambridge coordinated a joint response to the Concordat with several other universities.

However the real driver for action this year has been funder policies – specifically, the Engineering and Physical Sciences Research Council (EPSRC) which announced it was going to (and has begun) checking compliance as of 1 May 2015.

The devil is in the detail

While the Research Councils UK have RCUK Common Principles on Data Policy stating “Publicly funded research data are a public good (…), which should be made openly available with as few restrictions as possible”, these common principles are idiosyncratic when looked at from the individual council perspective, as the graphic on the second page of this document demonstrates.

There are variations on whether a data management plan is required, where the data should be stored, the level of support offered and even whether this can be funded through the grant (in most cases it can, but not all).

Places to share data

Open (cross-disciplinary) repositories

These include commercial options such as figshare which is owned by Digital Science who also produce Symplectic Elements research management systems and are is an offshoot company to Macmillian/Springer.

Open source solutions such as Zenodo, an open dependable home for the long-tail of science, enabling researchers to share and preserve any research outputs in any size, any format and from any science, developed by CERN.

Disciplinary repositories

There are a significant number of disciplinary specific data repositories. In many ways these are the most natural place for data as disciplinary experts can curate the data. For example the Natural Environment Research Council (NERC) runs seven repositories.

The first repository ever created (in 1991) was arXiv, holding e-prints in Physics, Mathematics, Computer Science, Quantitative Biology, Quantitative Finance and Statistics. The public functional genomics data repository is Gene Expression Omnibus . Social science data can be deposited in the UK Data Service. The Oxford Text Archive holds literary and linguistic texts for higher education.

Institutional options

Cambridge University is using its DSpace repository Apollo to store and share data. To date the largest dataset we have received is 28 GB – huge datasets need to sit externally to this repository. Not all institutions provide a data repository service. There are significant overheads associated with this activity both for the technology and the people to upload and curate the data.

Journals

Journals are increasingly requiring researchers to publish (or at least provide links to) their supporting data alongside their research articles. PLOS brought in their data sharing policy in December 2013.

There is also a growing selection of data only journals on the market, for example Nature’s Scientific Data. Others include Journal of Open Archaeology Data, Open Health Data, Journal of Open Psychology Data, Gigascience, Bodiversity Data Journal and Earth System Science Data.

Aggregating services

The Australian National Data Service has built Research Data Australia (RDA) which collates and displays information about datasets held all over the country, both open and closed. As of the 20 October, the RDA contains 115,823 datasets, of which 23,322 are open.

There appears to be little appetite yet for this sort of service in the UK, or at least for providing funds to create one.

What are we actually trying to achieve ?

Cambridge University has taken a proactive approach to the RCUK data sharing policies by inviting funders to come and discuss issues with the research community. We have written up and published these discussions as an ‘In conversation with..’ series on our Unlocking Research blog.

In addition to clarification on some aspects of the policies, one of the questions we are trying to answer is what is the actual goal of these policies? Ben Ryan the Senior Manager, Research Outcomes of the EPSRC clarified that researchers needed to share:

  • the data that underpins publications
  • the data that validates research findings
  • the data that is worth keeping

To summarise the philosophical goals of the EPSRC policy:

  • The default position is ‘data should be open’
  • Published research findings should be testable
  • Maximise the impact of publicly funded research
  • Maintain public trust in science and research
  • They are trying to create a new research culture

Researcher responses

While these might seem like lofty and even admirable goals, it does not mean that the academic response to being informed of their grant requirement for sharing data have been met with welcoming arms. Far from it in some cases.

A small selection of the responses we have received in our meetings with over 1500 researchers this year at Cambridge include:

  • What’s the minimum we can get away with?
  • This is crap
  • ‘They’ are just doing this because ‘they’ can
  • But it will take a huge effort to get the data in a useable form
  • No-one will look at it
  • What a waste of time

This has prompted us to play a game we call ‘data excuse bingo’ at some of our Research Data Management Workshops – see slide 16.

We are trying to start at the end

The problem might be that everyone is fixated on sharing data at the end of the research process.  However this is one of the lesser data management activities if data management begins at the beginning.

The second of our “In conversation…” series was with Michael Ball the Strategy and Policy Manager at the Biotechnical and Biological Sciences Research Council (BBSRC). Amongst a long discussion about what exactly constitutes ‘data’ in the biological sciences, Michael emphasised that disciplines themselves must establish ways of dealing with data. This is the beginning of an ongoing process.

He noted that researchers need to consider how to deal with data from the beginning of a research project. Researchers can ask for money to manage data in the grant application (something which is currently quite rare).

The practice of sharing data requires the data to be: Accessible, Intelligible, Assessable and Reusable. So how do we achieve that?

Basics of Research Data Management

Good data management includes very basic practices such as:

  • Writing a research data management plan at the beginning of the research process – identifying all of these issues
  • Using a file naming protocol (including version control)
  • Backing up work in several places
  • Identifying any data that might be politically, personally or commercially sensitive
  • Determining who owns what data
  • Ensuring data that is being used for research across collaborations is shared in safe, secure and legal shared facilities, bearing in mind Export Control Legislation.
  • Having good metadata protocols
  • Using a reputable and reliable storage/sharing facility that offers persistent identifiers (DOIs)

Who owns the data?

This is an interesting question. EPSRC policies state that researchers should ensure that collaborators are aware of the sharing requirement before they embark on research. Then there are questions about who within the team might own the data – with again a suggestion to come to some sort of agreement before work starts.

Are all collaborators equal ‘owners’? Or does the Principal Investigator have a 50% stake, with the remaining split amongst the PhD students making up the remainder of the team? You might want to talk to your legal advisors and/or your research office about this issue.

There is also the related issue here of developing author-contribution transparency. Do you include author contribution statements in your articles?.

Staffing issues

If Michael Ball is correct and very few researchers are asking for funds associated with managing data, it is reasonable to assume that data is being managed in an ad hoc way – with reliance on the computer savvy postdoc the project hired …

Required skillsets for managing and curating data

There is a considerable range of skill sets associated with managing data, and these have been described by the Digital Curation Centre as data creator, data scientist, data librarian, data manager.

Alma Swan and Sheridan Brown’s 2008 report to Jisc on ‘The skills, role and career structure of data scientists and curators: an assessment of current practice and future needs’ described these as:

  • Data Creator: Researchers with domain expertise who produce data. These people may have a high level of expertise in handling, manipulating and using data
  • Data Scientist: People who work where the research is carried out – or, in the case of data centre personnel, in close collaboration with the creators of the data – and may be involved in creative enquiry and analysis, enabling others to work with digital data, and developments in data base technology
  • Data Manager: Computer scientists, information technologists or information scientists and who take responsibility for computing facilities, storage, continuing access and preservation of data
  • Data Librarian: People originating from the library community, trained and specialising in the curation, preservation and archiving of data

There is a simple graphic that clearly shows how these roles relate to one another.

Certainly an increasing number of data scientist jobs are being advertised. A search for ‘Data scientist’ + ‘London’ on the job site Indeed on 18 October produced 1,405 results. So where are all of these people coming from?

Training available

The Swan and Brown study in 2008 noted that ‘People in data science roles face a big, continuing challenge in remaining properly skilled up’ and this remain the situation today, although there are now many more opportunities for training – a few are listed here:

  • The Digital Curation Centre offers data management and curation education and training.
  • MANTRA is a free online course from the Data Library staff in Information Services, University of Edinburgh. It is designed for those who manage digital data as part of a research project. It was crafted for the use of post-graduate students, early career researchers, and also information professionals. It is freely available on the web for anyone to explore on their own.
  • Data Scientist training for Librarians is a collection of notes and discussions about data work done by librarians. They ran an experimental course in August to teach “the latest tools for extracting, wrangling, storing, analysing, and visualising data”.

In addition, the professionalisation of these skills is beginning. For example, Data Science London is a community of data scientists that meets regularly to discuss data science ideas, concepts, and tools, methods and technologies used by many startups to analyse large scale data (big data), extract predictive insight, and exploit business opportunities from data products. Their website offers a list of free data science courses.

Cambridge University is one of the five founding university partners of the about to be launched Alan Turing Institute, which is intended to be the UK’s national institute for data science. The Institute will be addressing some of the issues with the data management skill gap.

Issues with sharing data

For all of the ‘feel good’ ideals about sharing data, and the processes being put in place to support this, there are some serious issues raised by researchers about the requirement to share data.

To start, there is a very real concern that the UK will become unattractive for collaborations. Why would a commercial collaborator choose a UK partner when a partner from elsewhere is not under obligation to share their data?

There have been some discussions at information sessions about the possible need to change the type of research being done to reduce the amount of data being produced because of the cost of long term storage of this data.

Indeed, there is discussion in some circles about whether applying for EPSRC funding is worth the hassle. It is a fair bet that none of these were intended outcomes of the RCUK policies.

Consequences of not sharing data

However, this does need to be a balanced strategy. There is a considerable argument that openness is related to academic integrity as it allows work to be verified and validated.

Here are examples in three disciplines where sharing data had a dramatic effect:

  • Medicine – having the data publicly available in two trials of deworming pills demonstrated that a population wide deworming program did not improve school performance.
  • Economics – A study widely cited to justify budget cutting in the US had a mistake in the calculations which was only revealed when the Excel file was released
  • Physics – It took 12.5 years to withdraw Jan Hendrik Schon’s work on ‘organic semiconductors’ because the reviewers were unable to replicate the results without access to the original data or lab books.

Conclusion

Sharing data offers great challenges to the research community, not least because it is less than clear what ‘data’ means in different disciplines. It will take some time for the research community to change its philosophy and practice. But the positives outweigh the negatives and with hope we will look back at this time as a short transition period.

Note the slides from the talk are available in Slideshare.

Published 20 October 2015
Written by Dr Danny Kingsley
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In conversation with Ben Ryan from EPSRC

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Cambridge University hosted Ben Ryan and Amanda Chmura from the Engineering and Physical Sciences Research Council (EPSRC) on Friday 15 May for a discussion about how the University is meeting the EPSRC expectations for sharing research data.

We started the conversation with a demonstration of the services we offer our researchers including our Research Data Management website, and talked about the open data sessions and other training events we have been holding. So far we have managed to speak to 764 researchers about data sharing requirements (the numbers continue to grow).

Managing expectations

In 2011 EPSRC published nine key expectations on research data management. The expectations are directed principally at research organisations and highlight their role in supporting researchers to ensure research data is properly managed. EPSRC set a deadline, 1 May 2015, for research organisation compliance with their expectations.

One of the expectations is that data supporting publications arising from funded research is openly available – this reflects the Common Principles on Data Policy published by RCUK (2011) and in the Royal Society’s subsequent (2012) report ‘Science as a Public Enterprise’. To monitor compliance with this expectation EPSRC have said that this autumn they will conduct checks of papers published after 1 May 2015 to ensure these provide appropriate directions to the supporting data.

Ben clarified that the checks will help to determine the level of awareness of the policy and expectations. He noted that there is a balance in what the EPSRC is trying to do. They are trying to create a new research culture, and they are primarily focused on what the institution should be doing to support that.

According to the EPSRC policy, in situations where research arises from collaborations, or from work partially funded by commercial partners, any potential problems with research data sharing should be addressed before the start of the project, in a data management plan. We therefore asked Ben why the EPSRC – of all the RCUK funding bodies– don’t require researchers to create a data management plan. Ben indicated that the main value in data management planning is to the researcher and the research organisation – adding them to EPSRC’s funding submission process would simply add to the admin and peer review burden without it being clear how peer reviewers could properly judge them because they don’t know the infrastructure available where the research is being conducted.

The question arose of whether a single RCUK policy on research data might be possible. Ben noted that the different councils fund different types of work, which informs their individual policies, and explained that although a single policy might be achievable it would require every council to change their existing policy and would be very disruptive of current processes across the whole system. As such he felt it would need a ‘very strong steer externally’ to drive such a change.

However, the research councils recognise the need for more guidance and are about to publish cross-council guidelines presenting a collective position on what should be done with particular types of data.

Clarification

A question that often arises from researchers is ‘what data are we expected to keep and make available’? We were able to get confirmation that it is:

  • the data that underpins publications
  • the data that validates research findings
  • the data that is worth keeping

All questions should be answered by considering the principles behind the policy. The default position is data should be open – in a way that does not damage the research process. The important thing is that the validity of the published research findings is testable.

An example of the way this principle can be used is when considering another common question – what to do in the situation where several papers are expected to come out of the one set of data. Researchers are concerned that if they release the data on the first publication it jeopardises their subsequent publications as they may be scooped. Ben acknowledged this is a concern but asked is it reasonable to sit on data for, say, five years so that other people end up being funded to generate the same data again?

He pointed out that the RCUK Common Principles state that those who undertake Research Council funded work may be entitled to a limited period of privileged use of the data they have collected to enable them to publish the results of their research. However, the length of this period varies by research discipline.

There is also the consideration of the way another user can access the data and reproduce results. The question is – how far do we go to enable a user to reproduce the work? The minimum is that we should provide the information that someone would need to be able to validate published work – this is also critical to maximise the impact of publicly funded research and to maintain public trust in science and research.

The software situation

We had representatives from Cambridge Enterprise and from the School of Technology at the meeting who had specific questions about sharing software. While Ben indicated he might need to reflect on some of the questions, we did come to some clarification on others.

Although software is different from other forms of intellectual property the same basic question arises: “is the institution best served by making it freely available or by commercialising it?” Both approaches can lead to the creation of jobs and economic impact. EPSRC is clear that the choice of exploitation strategy rests with the research organisation.

The EPSRC does not have an expectation about the licence under which software should be released.

It was agreed that if there is material that is potentially commercial, then we should take the steps to make it available and commercialise the software. It was confirmed we are able to make software arising from a research project available free for non-commercial re-use by other researchers (within the academic community) while at the same time making it available to others under a commercial licence

One can argue that since the taxpayer funded the work in the first place the taxpayer should not have to pay for it again, but this position, taken to its natural conclusion, of course would mean that no commercialisation of funded research should ever occur.

There is also the situation where a researcher has put their ‘life and soul’ into generating outputs and naturally feels they have some ownership of the work. Ben agreed that many of these questions are ‘very challenging’, but noted that researchers seldom ‘own’ their outputs – under RCUK grant conditions the research organisation owns all the intellectual assets arising from the funded research and is responsible for seeing that they are used to the benefit of society and the economy. Some of these questions stem from a mindset that insufficiently recognises the importance of ensuring that the economy and society as a whole benefits from publicly funded research, and a culture change is needed in addition to new processes.

The EPSRC do wish to avoid people sitting on data indefinitely because they don’t want to release their software. Ben said that in principle it is permissible for people to make software available through GitHub, but he would need to investigate how sustainable it is and how it is governed before being able to say whether GitHub is a reasonable option in terms of meeting EPSRC expectations..

Addressing (some) concerns

Time prevented us covering all of the topics we wished to raise. Many Cambridge researchers have raised questions about sharing data from collaborations – with concern that non-UK partners who do not have a data sharing requirement may find the UK requirements onerous and that this could decrease the amount of international collaborations in which UK institutions are involved.

There was also no magic bullet for the challenge of paying the not insignificant cost of storing research data safely for 10 years+. The problem is that where researchers were unaware of this expectation at the time they applied for their grant there is no allowance for it in their budget. This will not be an issue in the future as current grants are approved, but we are in a transition period now as the research from existing grants is published and the supporting data is being made available and stored. When we discussed this, Ben explained that the EPSRC does not have any additional funds to support this transition period, and that the costs need to be found within existing resources.

There have been some challenges with communication of the EPSRC policy. Many researchers at the University of Cambridge have said they would have liked to be informed about it directly by EPSRC (as, for example, they would expect to have been by e.g. the Wellcome Trust). Ben explained that the approach had deliberately been to communicate the policy through research organisation senior managers (e.g. ProVCs Research), and that this was because the expectations are addressed principally to research institutions, which have primary responsibility for ensuring that researchers manage their data effectively and have access to appropriate facilities to do so. However, he acknowledged that EPSRC could have communicated more with researchers and undertook to explore how more information could be made available directly to researchers.

Therefore it was helpful to be able to express some of the concerns and fears amongst the research community. We have been collating the questions that people have asked during our sessions and will compile a FAQ from this that will appear on our Research Data Management website. Ben indicated that there might be a possibility of a selection of these FAQs also appearing on the RCUK website to help address the universal questions about sharing research data. This step would be welcomed by the University.

Published 21 May 2015
Written by Dr Danny Kingsley
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