Discuss, Debate, Disseminate – PhD and Early Career Researcher data management workshop, University of Exeter, 22 June 2012

Jill and Hannah of the Open Exeter project have not been holding back with their user requirements research – not content with attracting hundreds of responses to their survey of Exeter postgraduates, they’re also augmenting this with their own research as well as running events like Friday’s, in an admirably thorough approach to gathering information on what postgraduate students and early career researchers at their institution need, how they work and where the gaps are in the current infrastructure provision.

Twenty enthusiastic participants turned up on 22 June, happily from across the sciences and humanities, and contributed with gusto to group discussion, intensive one-to-one conversations and a panel session.  The project has recruited six PhD students – Stuart from Engineering; Philip from Law; Ruth from Film Studies; Lee from Sport Sciences and Duncan from Archaeology, plus one more currently studying abroad – to help bridge the gap between project staff and their PhD peers.  These six are working intensively with the project team to sort out common PhD-level data management issues and activities in the context of their own work, which allows them to not only improve their own practice but also to share their experiences and tips with other PhD students and ECRs in their own disciplines at Exeter.  (You can see more about this at http://blogs.exeter.ac.uk/openexeterrdm/)

One of the most interesting aspects of working on this programme, for me, is understanding the nuts and bolts of research data management in a specific disciplinary context, in a particular institution.  In other words, the same context in which each researcher is working.  Although funders are increasingly calling the shots with requirements and expectations for research data management, the individual researcher still has to find a way to put these requirements into practice with the infrastructure they have to hand.  That means it’s all very well for the EPSRC or AHRC or whoever to require you to do something, and you may even understand why and want to do it, but who do you ask in IT to help?  Why isn’t it OK to just put data on Dropbox?  What to do with data after you finish your PhD or project?  And what is metadata anyway?

Despite the generally-held view by researchers that their RDM requirements are unique to their discipline, these questions – and other like them – are actually fairly consistent across institutions when researchers are sharing concerns in an open and relaxed environment.  And this was one of the achievements of today’s event: by keeping things friendly, low-key and informal, the team got some very useful information about what PhDs and ECRs are currently doing with RDM, the challenges they’re encountering and what Exeter needs to provide to support well-planned and sustainable RDM.

Some additional detail from the event:

–       Jill offered a working definition of ‘data’ for the purposes of the workshop: “What we mean by data is all inclusive.  It could be code, recordings, images, artworks, artefacts, notebooks – whatever you feel is information that has gone into the creation of your research outputs.”  This definitely seemed to aid discussion and meant we didn’t spend time in semantic debate about the nature of the term.

–       Types of data used by participants:
o       Paper, i.e. printouts of experiment
o       Word documents
o       Excel spreadsheets
o       Interview transcripts
o       Audio files (recordings of interviews)
o       Mapping data
o       PDFs
o       Raw data in CSV form
o       Post-processed data in text files
o       Graphs
o       Tables for literature review
o       Search data for systematic review
o       Interviews and surveys: audio files, word transcripts
o       Photographs
o       Photocopies of documents from the archives
o       NVivo files
o       STATA files

–       Common RDM challenges included: the best way to back-up, use of central university storage, number of passwords, complexity of working online (which can make free cloud services more attractive), lack of support with queries or uncertainty about who to contact; selection and disposal, uncertainty over who owns the data.

–       Sources of help identified during the event: subject librarians, departmental IT officers, and during the life of the project, Open Exeter staff, existing online resources such as guides from the Digital Curation Centre (http://www.dcc.ac.uk) and the Incremental project (http://www.gla.ac.uk/datamanagement and http://www.lib.cam.ac.uk/preservation/incremental/).

Digital curation tools: what works for you?

I’m undertaking a piece of work with Monica Duke and Magdalena Getler of the DCC, and we need your help!  We’re looking at which DCC-developed digital curation tools are used by the MRD02 projects.  This is a happy case of our interests overlapping in a Venn diagram-type way: I’m interested in which digital curation tools, DCC or not, are used (or considered but rejected) by the projects.  Monica and Magda are interested in the use of DCC tools by the MRD02 projects as well as by other people.

There is a list of the DCC tools developed to date at http://www.dcc.ac.uk/resources/tools-and-applications, and there is a freshly-revised catalogue of digital curation tools developed by people other than the DCC at http://www.dcc.ac.uk/resources/external/tools-services (although please note this latter link is currently still in development – it should be finalised by the week commencing 30 April 2012).

We plan to look at the project plans, blogs and so on to see where digital curation tools are mentioned.  After this initial perusal, the plan is currently for DCC to send out a brief survey to projects where we don’t already have a full picture from their blogging (and this may also be a way of helping to get the new RDMTrain02 projects involved), asking for information on their use of DCC tools.

If you’re on one of the projects and keen to contribute, it would be immensely helpful to me if you could let me know which tools for digital curation (DCC-developed or not) you have considered using.  If you’re going ahead with use of them, please let me know what you think of them, and if you’ve decided against use of a particular tool, please let me know why.  I welcome this feedback by email to laura.molloy AT glasgow.ac.uk, or in the comments below.  Thanks!

The future of the past: closing workshop for the Data Management Planning projects

It always provokes mixed feelings to attend a closing event marking the end of a project or raft of projects.  On the one hand, it’s melancholy to say goodbye to people, or to know that there will be no more interesting outputs coming from a particular project.  On the other, there is (hopefully) the sense of achievement that comes with having finished a piece of work.  Having something finished, ready to show, then getting ready for the next activity, preparing for the future.  It was useful and thought-provoking to see the findings and outputs of the ‘strand B’ or data management planning projects of the MRD02 programme at the Meeting Challenges in Research Data Planning workshop in London on 23 March.  This event marked the closing of these projects, and gave them an opportunity to share what they’d been doing.  Data management planning by definition is about considering the future, and there was a sense of energy and enthusiasm from the projects on the day which suggested we could easily have met for longer and talked more.  And yet, some elements of the discussion made me think about the past.

Back in MRD01 (2009-11), there were a few projects such as Oxford’s Sudamih and Glasgow-Cambridge’s Incremental project which performed institution-specific scoping work about what researchers need to improve both their understanding and practice of RDM.  As one of the Incremental team, I felt at the time that, to be honest, a lot of it seemed to be stating the blooming obvious, but we recognised the value of gathering original data on these issues in order (1) to check that our suspicions were correct; and (2) to wave in front of those making decisions about whether and how to fund RDM infrastructure.

You can read the full report of Sudamih here and Incremental here, but the main ideas we found evidence for were things like: researchers are almost always more interested in doing their research than spending time on data management, so engagement relies on guidance being short and situated in one obvious, easy-to-navigate place; there are lots of guidance resources at institutions already but they’re scattered and not well advertised; lots of researchers in the arts and humanities don’t consider their material as ‘data’ and so the terminology of RDM doesn’t engage them or may actively alienate them; researchers may be party to multiple data expectations from their institution and / or their funder, but a lot of them are not aware of that fact, never mind what these are and where to find them in writing.  Also, different disciplines have different data sharing conventions and protocols, which affect researcher behaviour; some researchers can be quite willing to practice good data management, but they need to know who to call or email about it at their own place; guidance written by digital curation specialists is great and fine, but often needs translating into non-specialist language, and there are lots of researchers who are just not going to engage with a policy document.  All that kind of thing.  Readers of this blog will possibly be amazed that such fundamental ideas are not more widely understood out there in the wider research community, but that in itself probably just confirms the knowledge gap between RDM people and the general researcher population.

So back at the event on 23 March, we heard from, amongst others, Richard Plant of the DMSPpsych project explaining the importance of local guidance for the institution’s researchers, and Norman Gray of MaRDI-Gross explaining the influence of the data sharing culture in big science on its researchers (although I never did get around to asking him if the project did indeed reach ‘the broad sunlit uplands of magnificently-managed big-science data’, as promised in the project blog).

History DMP from Hull charmed with an appearance by one of their tame researchers, who came along to give a brief account of his experience with the project.  He was happy not being familar with RDM terminology or principles or, as he put it,

‘This process has been very straightforward for me.  I don’t understand the technical elements but I don’t need to.’

The benefits of easier remote access to and confidence in the security of his data storage were the pay-off for him, and left everyone feeling optimistic.

Reward at UCL/Ubiquity Press did many interesting things whilst aiming to lower the barriers to good RDM and shared a deluge of findings echoing those of Incremental / Sudamih, including the value of drawing together institutional RDM-related resources to provide a single point of access; the effect of discipline-specific protocols on researcher behaviour (specifically data sharing); the value of clarifying benefits of good RDM to motivate researchers; the lack of current awareness about IPR, licensing and data protection; the reluctance to discard data; the need for training about RDM and particularly long term preservation of data; and many other points.

So what occured to me on 23 March was that it felt good to hear several of the MRD02 strand B projects reiterating our findings from their own experiences at their own institutions.  It reminded me of Heather Piwowar’s notion of ‘broad shoulders’.  It wasn’t that they were agreeing with us – I’m more than happy for my research to be challenged constructively.  It was that what we’d done in MRD01 seemed to be useful to some extent, allowing the MRD02 projects to extend and refine user requirements in RDM, and share what they found, which benefits us all.

Revisited: Meeting (Disciplinary) Challenges in Research Data Management Planning

The JISCMRD Workshop on ‘Meeting (Disciplinary) Challenges in Research Data Management Planning’ (March 23, 2012, London) saw the projects in this strand present their interim outputs; the development of DMPonline (now in v3.0), disciplinary templates and further institutional approaches rounded up the event.

The discussion circled around a number of issues and questions, some covered, some yet to be fully answered as Steve Hitchcock points out in his excellent blog piece (e.g. What is a DMPs scope, defined by whom? Where to best host a DMP? To what extent and how to (pre-)populate DMP records?).

Overall it is fair to say that a lot of good progress has been made on the DMP front – but challenges remain, especially as the implementation of funder requirements, data management policies and therefore DMPs has gained speed on institutional level:

  • For researchers/research groups “changing RDM culture is (going to be) hard work” as pointed out by Simon Dixon (SMDMRD project), representative of the overall discussion. Sticks AND carrots are needed (in a positive way: show benefits!).
  • Along with disciplinary working practices and cultures the requirements from DMPs in use are further evolving – not bound by project schedules and implementation time lines.
  • Furthermore, time is always a constraint for filling out DMPs, we have to try to mitigate the duplication of effort for data already stored electronically.
  • Good practice is not at all easy to implement and in connection to that training and documentation has to be a part of it all.
  • In the end, DMP tools not only need to mature in general, but the DMP as such has to be a dynamic thing (vs. a static snapshot only) in a running project before it will be put to rest in an archive at the end of the research lifecycle.

Meik Poschen  <meik.poschen@manchester.ac.uk>
Twitter:  @MeikPoschen

Chatham House at Weetwood Hall: emerging themes from the JISCMRD02 institutional RDM policy workshop

Earlier this week, I and my co-facilitator had four wide-ranging and thought-provoking discussions across two days with the JISCMRD02 projects who attended the programme workshop on institutional research data management policy development and implementation at Weetwood Hall in Leeds.  Conducted under the Chatham House rule, we hoped projects and interested Fellow Travellers would feel able to share their challenges, successes, questions and institutional quirks openly, and I’d like to thank the participants for their time and energy in doing so!

It has been indicated to me that some preliminary notes of themes arising from our discussion would be useful, in advance of more detailed reporting.  I’d like to share some of the main themes that emerged from our group, with the provisos that:

  • these only represent one of the several discussion groups – main themes from the others may vary (and you can read Bill Worthington’s useful account from another group here); and
  • these are presented here for interest and discussion – please don’t interpret any of them as the official position of or advice from the MRD02 programme, the DCC or JISC – they’re simply ideas that bubbled up from our group conversations and were contributed by twelve individuals representing ten very diverse institutions, as well as the thoughts of our facilitator.

That said, we hope the lessons they’ve learned from their work so far in RDM policy development will be useful to others travelling the same path.

Themes and observations:

– At this point (March 2012), institutions are still all at different stages with their research data management policies.  However, as far as  they’re funded by the major funding councils, research councils and associated bodies, institutions are all subject to a common set of requirements, mandates and expectations from those funders, in addition to UK and EU legislation. In other words, the responsibility to have these expectations and requirements clarified and complied with is already there. It’s now up to institutions to decide their approach to an appropriate and realistic response.

– The idea of having an institutional research data management policy in place at your institution can be reassuring.  However, having a policy in place without any real buy-in from staff can be more harmful over time – by breeding complacency – than having no policy yet in place. So it’s best to take a little longer and get it right than rush through a policy in which researchers, research support staff or senior management have no investment or of which they have little awareness.

– A useful approach may be to craft an aspirational, high-level document which outlines principles as opposed to specific attributions of responsible persons, workflows, budgets and so on.  This high-level statement is often more easily understood by senior management and so can be the most effective way to get the policy through university senior committees and into institutional regulations.  This high-level policy should then be accompanied by, and executed by way of, working documents which translate the principles into specific tasks allocated to specific roles.  It should be anticipated that the high-level policy will not need frequent changes; it should allow enough room for, for example, new funder requirements, whereas the working documents should be regularly updated and seen as much more volatile documents.  This is, however, only one type of approach to institutional RDM policy development.  See also the JISCMRD02 Open Exeter project’s blog on the value of aspirational policy here.

– Policy and infrastructure need to evolve in correlation.  Some policies have been well-written but have foundered at the point of senior approval because they have specified responsibilities and workflows which the institution didn’t yet have the infrastructure to deliver.  At the same time, a well-organised policy can help to make the case to senior management for the investment in the necessary infrastructure.  This is another argument in favour of the high-level principles-based approach to the main policy, which can then be used to justify moving towards a more detailed position over time, via the working documents, whilst avoiding the danger of being rejected because of the lack of infrastructure.  It’s also an argument in favour of carrying out some surveying of the current state of infrastructure at your institution – including the ‘soft’ infrastructure elements of training provision, current skills levels in relevant staff groups, staff awareness of the requirements under which they’re currently working, etc.

– Consider the other policies – both internal and external – with which your new research data management policy should work in concert.  It’s obviously better to identify and iron out any potential wrinkles between these before you start plugging the new policy to senior management.  Examples of internal documents may include institutional policies on digital preservation, IT equipment use, open data, response to Freedom of Information requests, data protection, research ethics, intellectual property and academic integrity.  External documents to consider may include the Data Protection Act, Freedom of Information legislation, INSPIRE regulations, environmental data legislation, expectations and requirements of your funding council, expectations and requirements of your research funders, the Research Integrity Office’s research code of conduct, the RCUK code of research practice and relevant legislation relating to use of government data, intellectual property and copyright.

– Retain awareness of the different roles and legislation for research data and administrative data.  Whilst anyone drafting a research data management policy would benefit from knowledge of how the institution handles administrative data, and there may be some crossover in relevant legislation (particularly UK and EU legislation for some aspects of both), it’s important to remember these two categories of data have different purposes, different stakeholders, and attract different expectations by funders, and so should be dealt with by discrete policies, clearly pitched to the relevant audience for each.

– Try to avoid taking the view that researchers will automatically resist implementation of a research data management policy.  Some may be suspicious of it, some will be enthusiastic – and the difference is often down to the approach used.  In institutions where the development and implementation of such a policy is presented as a way to help researchers (e.g. ‘We’ll look after it so you don’t have to’, promotion of the benefits to the researcher, etc.), as opposed to being a new rule or requirement imposed by the central administration, researchers have generally responded enthusiastically.

– Whilst recent research (e.g. the JISC/RIN/DCC DaMSSI project) found that researchers respond well to data management training when it is presented as just one of many aspects of excellence in research practice, there is a tension between embedding RDM training as just another part of routine business and highlighting it sufficiently to attract attendance at training and to ensure researchers pay attention to good RDM practice.  Motivation can be helped by underlining the benefits of good RDM practice to the researcher’s career and profile, their enhanced ability to find their own work in the future, increased impact and a more efficient way of working.

Do any of these points chime with your experience?  Or contradict it?  Let us know in the comments!

Synthesis of first JISCMRD programme benefits

Useful presentations summarising the benefits identified in the first JISCMRD programme 2009-11 from individual projects/institutes and as synthesised by Neil Beagrie on behalf of the programme can be accessed from the JISC national conference 2011 site.
There is also a more general online overview of the outputs of the first JISCMRD programme now available.

Commonalities & Differences: Requirements & Disciplines

Within our remit to identify themes and trends in the JISMRD Programme and to enable collaboration and synergies between its projects, exploring commonalities and differences is a key area with a multitude of angles. Diverse endeavours, domains, institutions and scopes on the project side entail a number of approaches, methods, user communities, research practices & cultures, data life cycles, workflows and therefore actual needs, requirements, benefits, data infrastrutures and policies. Knowledge transfer in the programme is crucial to not to re-invent the wheel (at least not every time), learn from previous experiences, discuss emerging topics, collaborate and hence (mutually) benefit from all those differences and commonalities.

In the weeks and months to come I shall focus on commonalities and differences on this blog under different aspects, starting with the requirements and disciplinary angle (albeit I am aware that a lot of areas are overlapping: requirements gathering involves methods as well as research practice and perceived benefits, which again have an impact on costs, et cetera et cetera). The thought would be to ideally start a discourse, get feedback and input from projects and people, gather documentation and discussion topics, facilitate and provide support. A workshop at some later stage might be an activity spawning from that, if deemed useful.

My own project related hat is that of the user liaison & researcher, e.g. gathering requirements, including looking into research practice and benefits of diverse communitites at the University of Manchester previously in the MaDAM project (JISCMRD phase 1; see here for outputs) and now in MiSS (JISCMRD02; see resources section). Our requirements approach in both projects is user-driven, iterative and based on close collaboration between RDM specialists, users/researchers, other stakeholders (high-level buy-in is especially important) and the project team/developers. In MaDAM we were focussing on pilot users from the Biomedical domain – in MiSS the RDMI will have to cater for the whole of the University with the challenge of establishing a balance between a generic, easy-to-use eInfrastructure and providing a system open enough for discipline specific needs (plug-in points). We have user champions in each faculty: Life Sciences (Core Facilities and MIB – large and diverse data), Engineering and Physical Science (Henry Mosley Centre, Material Sciences & MIB – large data), Medical and Human Sciences (sensitive data!) and Humanities (CCSR, applied quantitative social research – data service and diversity) and will also open up a user committee to the wider University for input and feedback in a few weeks. We just have completed our baseline requirements phase, so please watch out on this channel for more details and the report!

But back to you, the JISCMRD projects’ fields of interests and needs:

How do you approach your requirements process?

What are particular challenges, e.g. in specific disciplines?

What are particularly enthralling lessons learned (already)?

How to achive benefits and synergies between projects?

What would be your ideas on how to facilitate (by us) any exchange on such issues, any ideas are welcome!

Meik Poschen  <meik.poschen@manchester.ac.uk>
Twitter:  @MeikPoschen

Developing Research Data Management Policy

This is Jonathan Tedds (@jtedds): Senior Research Liaison Manager for IT Services; researcher in astronomy and research data management at the University of Leicester. By way of a first blog post proper here in JISCMRD Towers I want to introduce the increasingly higher profile area of Research Data Management (RDM) policy and why it’s rapidly moving from desirable to essential.

Following the agreement by the RCUK umbrella body of research funders on common data principles for making research data reusable – data as a public good – and similar moves by larger charitable trusts such as Wellcome, funders have then batted the ball back to institutions and said deal with it! The EPSRC in particular requires that institutions in receipt of grant funding establish a clear roadmap to align their policies and processes with EPSRC’s expectations by 1st May 2012, and are fully compliant with these expectations by 1st May 2015 – yes, you did read that correctly, that’s a roadmap by this May! Sarah Jones of the Digital Curation Centre (DCC) has just blogged about this following a refreshed look at this area during the very well attended recent DCC Roadshow at Loughborough in February 2012.

Of course there are many other reasons why any institution that it is serious about research should be investing in the support of RDM and Angus Whyte and I recently co-authored a DCC Briefing on making the case for research data management which sets the national and international context as well as describing the experiences in the last 3 years at the University of Leicester. As a consequence institutions (and more specifically those held accountable for supporting researchers) are now realising, if they didn’t already, that they need to plan for research data management infrastructure on the ground across the entire research data lifecycle. Crucially they will also need high level policy at the institutional level to make this a reality. So how to go about it?

Well there are a few institutions that already have policies in place including Edinburgh, Oxford, Northampton and Hertfordshire. The DCC maintains a list of these with links to relevant institutional data policies. Of course this in itself is a grey area as your institution may well already have a code of practice which covers at least some of this ground. But does the policy (or the code!) always connect to the practice on the ground? Bill Worthington, who leads the Research Data Toolkit (Herts) JISCMRD project, has recently blogged on their work in this area.

At Leicester we have been building up to an institutional level policy to fit alongside an existing code of practice adopting a rather ground up approach; building on exemplars such as the JISCMRD Halogen interdisciplinary database hosting project and the current BRISSkit UMF project I lead for cross NHS-University biomedical research alongside high profile central investment in high performance computing (HPC). I facilitate a Research Computing Management Group across the University which takes a strategic view of these issues and will inform our own institutional level policy working party.

A recent email exchange on the JISCMRD mailing list showed a strong interest from the many new (and established) institutes involved in getting together to discuss a number of issues around developing and implementing RDM policies. Following an online poll it was decided to host a lunch-to-lunch meeting, supported by the Programme and assisted by the DCC, to takes this forward at the University of Leeds on March 12-13th 2012. Based on the poll we are expecting up to 50 participants. I’ll link to further details as they are finalised and made available. Themes raised to date include:

  • How are projects/institutions developing policies? Covering considerations of general principles, guidelines from funders and other bodies, specific considerations for the institution in question.
  • How are people getting approval for policies? A chance to share – e.g. off the record or by the Chatham House Rule – some of the challenges which may be faced.
  • How are people planning to support the implementation of the policies? How do projects/institutions intend to support transition from policy to practice?  Policy, infrastructure and guidance.  Interplay of top-down and bottom-up elements?  How to build mention and requirements of subject specific and/or institutional services into institutional policies.
  • How technical solutions affect policy decisions How much will policy be driven by what is technically available to an institution as a (suite of) data management solutions.
  • How are we going to assess and critique the success of RDM systems and policies

Finally, there are of course difficulties in all of this focus on the institutional level. As a researcher myself (astronomy) I argue that a researcher or research group is likely to have much more in common regarding their requirements to manage their data with a similar researcher or group in the same discipline but residing in any other institution (including international) compared to another researcher/group even in the same building. So we are asking a lot for institutions to meet this full range of requirements across all of their research areas. Researchers rather tend to look to their disciplinary learned societies or evaluation panels established by funders to provide coordinated responses. To be sure, the institutions have a strong role to play and shoulder a strong measure of responsibility but they are by no means the whole answer to the problem as I blogged in Research Fortnight (February 2011).

Embedding Benefits and Impact: Ideas from the History DMP Project

I would like to draw JISC Managing Research Data Programme projects’ attention to elements in the History DMP Project’s plan which, as well as being good models for these sections, I think will be of broader interest to projects seeking to embed their work.  The plan may be found at http://historydmp.wordpress.com/history-dmp-project-plan/

The sections in question are 1.5 Anticipated Impact and 3.5 Sustainability Plan, specifically the short discussion after the table.  Other projects may find these sections useful prompts for their own considerations of benefits and impacts which may be generated, and for how a project may plan to achieve sustained benefits/impact after its life.

In the table, the History DMP Project makes plans for sustaining specific project outputs, and then continues:

[P]lanning for the sustainability of the work carried out in the project, and the data management plan itself, will also be incorporated into departmental planning during the project’s lifetime. The University’s annual strategic planning round for 2012-13 will take place during the project period, and this offers an opportunity to formally adopt approaches for support of the data management plan for future research. Specific possibilities, which will be considered at departmental and University level, include:

  • Identifying specific data impact case studies for submission to REF2014
  • Adding data management to the research & training seminar series
  • Adding data management to the Staff Development Programme
  • Incorporating data management into postgraduate workshops
  • Inclusion in research strategies

Institutionally we shall be guided by the DISC UK DataShare Policy-making for Research Data in Repositories Guide in establishing the management of datasets within the repository as part of the long-term implementation of the data management plan and extension of the role of the repository for this purpose.

I think this list forms a useful prompt for actions which may be appropriate for other projects seeking to sustain, embed and enhance the impact of their work.

Oh, the humanities! A discussion about research data management for the Arts and Humanities disciplines

Here are some brief notes from the Arts and Humanities breakout group at the JISC MRD02 Launch Workshop earlier this month.

We began with brief introductions around the table.

Definitions of ‘research data’:

Chris Awre from History DMP, Hull, kicked off the discussion by asking: in the arts and humanities, how do you define what research data is?  The term ‘data’ means different things and different activities in different departments.  Also, a lot of what could be called data is secondary rather than primary, i.e. a lot is not new facts, but gathered facts.  Should we attempt to set a definition?
Marie-Therese Gramstadt from the Kaptur project outlined how they are trying to find a way of talking about research data that doesn’t use that particular term.  Instead they talk about looking at the materialisation of research.  They come across lots of paper-based research – do we concentrate just on the digital?  Or do we include hard copy as well as digital data when we talk about managing research data?
Simon Price, data.bris project, reported that in the Bristol theatre collection, a lot of the collection is physical artefacts, including scans and photos and objects, and getting them into a citable or preservable form is a challenge.
Anastasia Sakellariadi, REWARD project, noted that first steps may include finding out from the institute what people use.  You could ascertain that, e.g. through a survey of researchers in your department, and scope that first, then use that definition.  This may be a more useful way to engage with researchers.
Brian Hole, also from REWARD, noted that the REF now specifically talks about data, so that term is being used more now.  In REF terms we’re being compared with STEM [science, technology, engineering and mathematics] subjects who in some cases have much longer-established practice in data management and sharing.

Motivations for effective research data management:

Brian remarked that if we want researchers to plan to publish the data at the end of a project, we need to talk about it at the start.  That makes researchers think about it from the beginning.  It’s good to provide an aspirational model.  Keep the researchers’ eyes on that goal from the beginning.
Anastasia added that if we are achieve this paradigm shift, we have to encourage people to do research for themselves but to also think, ‘I’m doing this work for this project but for other people too.’
Laura Molloy, University of Glasgow, noted that in the JISC MRD01 projects Incremental and DaMSSI, the team found repeated evidence that terminology in awareness-raising efforts, skills training, policy and guidance must be very carefully considered as the use of information management- or digital curation-specific language, or legal language, immediately presents a barrier to many researchers and diminishes their engagement with potentially useful material.  Also, most researchers have other issues as their priority so to get their cooperation and increase motivation, benefits of good research data management must be clear.

Subject-specific differences in re-use:

The group noted differences within arts and humanities across disciplines re. data re-use.  Archaeology is strong on data re-use.  The case for the continuation of the Archaeology Data Service was relatively easy to make because of the unrepeatable nature of some archaeology work.
If there is a strong tradition of re-use in a discipline, the case is easier to make for good research data management.  If the discipline does not currently widely re-use data, we need to find ways to make re-use more attractive.
Simon Price noted that there are often problems putting video content online that has been digitised at Bristol because they can’t track down the rights holders – this is a common barrier to re-use of this type of data.

Data centres and sources of advice:

The group noted the current lack of advice for research data management across the arts and humanities disciplines, particularly with the closure of the Arts and Humanities Data Service (AHDS).
Chris queried the value of depositing data in a discipline-specific data centre, and/or an IR.  Julian Richards of the ADS noted that the value added by deposit in a discipline-specific data centre includes visibility, data mining and aggregation of datasets amongst other advantages.
Simon Price noted that institutions don’t necessarily need to keep data on-site.  The key elements are a citable point and the metadata, and any data centre will do as long as it’s a trusted centre.
Julian added that we need to harmonise metadata to make sure that when a researcher deposits data, they only need to create the metadata once, and APIs are needed to see access stats as this encourages use of data centres.

There then followed a discussion of work on DOIs to distinguish parts of datasets as opposed to the entire dataset.

Brian commented that during his work on the LIFE project, they discovered that in digital preservation, data probably needs to be migrated far less often than the team originally thought.
There’s a lot of data that can be lost when migrating from one format to another.  Julian noted that this is one of the arguments for discipline-specific repositories.  Staff with discipline knowledge are going to be more likely to be aware of these risks, and how to check that significant characteristics, properties and metadata of the file haven’t been lost.

Training for researchers:

When considering training to help researchers address research data management issues, presenting such training in a ‘digital humanities’ environment runs the risk of ‘preaching to the converted’ – a digital preservation / research data management event will definitely do so.  The group concluded that perhaps training would be better delivered in a subject-specific environment (particularly one more specific than ‘arts and humanities’ as this is far too broad an area to be useful).

If you were present at the group, please supply corrections and additions to laura.molloy AT glasgow.ac.uk – thank you.  Otherwise, please enter comments below!