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Rachel Bruce UK research and data management where are we now

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Rachel Bruce UK research and data management where are we now

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Rachel Bruce UK research and data management where are we now

  1. 1. The UK and Research Data Management: where are we? Rachel Bruce, Jisc
  2. 2. Research Data Directions for Universities 2 Structure • Give some context to the meeting & an overview mainly focused on universities • Policy drivers & context • Elements of the infrastructure (people, policy and services ) • Findings on the progress of universities • Gaps • Some emerging solutions
  3. 3. Research Data Directions for Universities 3 Policy & definitions “Research data is defined as recorded factual material commonly retained by and accepted in the scientific community as necessary to validate research findings; although the majority of such data is created in digital format, all research data is included irrespective of the format in which it is created.” (Epsrc) “Research data’ refers to information, in particular facts or numbers, collected to be examined and considered as a basis for reasoning, discussion or calculation….examples of data include statistics, results of experiments, measurements, observations resulting from fieldwork, survey results, interview recordings and images. The focus is on research data that is available in digital form.” (H2020)
  4. 4. Research Data Directions for Universities 4 RCUK Common Principles on Data Policy » Public good: Publicly funded research data are produced in the public interest should be made openly available with as few restrictions as possible » Planning for preservation: Institutional and project specific data management policies and plans needed to ensure valued data remains usable » Discovery: Metadata should be available and discoverable; Published results should indicate how to access supporting data » Confidentiality: Research organisation policies and practices to ensure legal, ethical and commercial constraints assessed; research process should not be damaged by inappropriate release » First use: Provision for a period of exclusive use, to enable research teams to publish results » Recognition: Data users should acknowledge data sources and terms & conditions of access » Public funding: Use of public funds for RDM infrastructure is appropriate and must be efficient and cost‐effective http://www.rcuk.ac.uk/research/datapolicy/
  5. 5. Research Data Directions for Universities 5 HEFCE: • Where an HEI can demonstrate that it has taken steps towards enabling OA for outputs beyond just articles and conference proceedings, credit will be given in the research environment component of post 2014 REF. H2020: • Develop a Data Management Plan • Deposit in a research data repository • Make it possible for third parties to access, mine, exploit, reproduce and disseminate data; free of charge for any user • Provide information on the tools and instruments needed to validate the results
  6. 6. Research Data Directions for Universities 6 Science as an Open Enterprise Report, 2012 The Royal Society, UK » “The conduct and communication of science needs to adapt to this new era of information technology” » “As a first step towards this intelligent openness, data that underpin a journal article should be made concurrently available in an accessible database. We are now on the brink of an achievable aim: for all science literature to be online, for all of the data to be online and for the two to be interoperable.” http://royalsociety.org/policy/projects/science‐public‐enterprise/report/
  7. 7. Research Data Directions for Universities 7 Science as an Open Enterprise Report Six key challenges » A shift away from a research culture where data is viewed as a private preserve » Expanding the criteria used to evaluate research to give credit for useful data communication and novel ways of collaborating » The development of common standards for communicating data » Mandating intelligent openness for data relevant to published scientific papers » Strengthening the cohort of data scientists needed to manage and support the use of digital data (which will also be crucial to the success of private sector data analysis and the government’s Open Data strategy) » The development and use of new software tools to automate and simplify the creation and exploitation of datasets
  8. 8. Research Data Directions for Universities 8 UK Open Research Data Forum: Research Data Concordat See the draft …
  9. 9. Research Data Directions for Universities 9 Roadmap Business Plan and Data Management Planning Sustainability Selection and RDM Policy and Deposit Tools Retention Advocacy, Guidance, Training and Support Research Data Registry Research Data Management Support Service Data Repositories/Catalo gues Managing Active Data
  10. 10. Research Data Directions for Universities 10 Russell Group (39) Others 10%+ (35) Others (13) From 61 institutions
  11. 11. Research Data Directions for Universities 11 Most advanced areas % indicating piloting or live 0 20 40 60 80
  12. 12. Research Data Directions for Universities 12 % indicating piloting or live 32 34 36 38 40 42 Managing implementation as a whole Data cataloguing & publishing Access & storage systems
  13. 13. Research Data Directions for Universities 13 Least progress % indicating piloting or live 18 20 22 24 26 Governance of data access & reuse Digital preservation & continuity planning Business planning & sustainability
  14. 14. Research Data Directions for Universities 14 Expected timeline for enabling long‐term access to research data 9 18 3 44 38 40 31 38 43 14 14 8 Others Others 10%+ Russell Group Currently provide Within the next 12 months After 12 months
  15. 15. Research Data Directions for Universities 15 Barriers to progress Low priority for researchers Availability of funding Lack of appropriate staff resources and infrastructure 64 71 59 % citing
  16. 16. Do you intend to archive your data with a data centre or repository? Reasons why not: • It is not something I had ever considered ‐ 42% • It is not something my funder requires ‐ 35% • There isn't a suitable data centre for my discipline – 18% University of York, Jen Mitcham
  17. 17. Research Data Directions for Universities 17 Gaps & need for external support Advocacy to senior management Clarify costs from grants Defining what research data the HEI should retain & for what period Support metadata creation for discovery Tools & infrastructures for data management or preservation Developing data catalogues & registers
  18. 18. Research Data Directions for Universities 18 Gaps – sharing “ lack of recognition that a national rather than an institutional approach would save everyone time and resource” Collective work with software user groups, common metadata, interoperability, storage. Shared storage Shared training Dialogue on incentivising researchers Develop data scientist role between library and researchers Share practice, exchange events
  19. 19. Research Data Directions for Universities 19 Research at Risk – some of the gaps (there were others identified!) • Storage. • Metadata. • Preservation. • Defining compliance.
  20. 20. R@R: Support take up of citation DMP OnLine R@R: DMP registry R@R: busines s case & costs 20 Standards; policies; coordination & cooperation. EASY ACCESS Data identifiers Access & security Researcher/ organisational identifiers Funders policies Advice & guidance/good practice Deposit protocols R@R:UK Research Data Discovery (metadata) R@R: metrics & usage data service Cardio planning tool R@R: RD Experiments & prototypes Digital Curation UKDS /Institutional repositories R@R: shared Preservation Repositories (metadata) Centre Open Training Materials in Jorum Shared data centre Jisc Research Data Infrastructure R@R: comprehensive tool-kit; case studies Sherpa Juliet Funder policies R@R: Journal Policy registry R@R: EPSRC support R@R: RD Experiments & Prototypes, & BRISSkit Research Data Directions for Universities
  21. 21. So…. Research Data Directions for Universities 21 • If we’re driven solely by compliance will we miss some other important issues ? • This is new & challenging – there aren’t answers yet to everything • Lots of ideas and effort – can we be more efficient and effective? • Prioritise? Quick wins ? • What might we want to influence – policy? standards? who & how? • Build on what we have (there is good progress in the UK)
  22. 22. Research Data Directions for Universities 22 Final thought – DataPool, Southampton University “…it is clear that the issues surrounding research data management are becoming more complex rather than less. We now understand much more about the range of data to be managed, its size and sophistication and the expectations of researchers to manage workflows and share data. We also know that at institutional level the requirements of government and funders are placing potentially significant financial costs on institutions which they are finding challenging to discharge in the present financial climate.”
  23. 23. Research Data Directions for Universities 23 Thank you! Contact: r.bruce@jisc.ac.uk Twitter: rachelbruce Acknowledgements: Angus Whyte of DCC who undertook the survey, and cogdog flickr cc‐by‐sa for the images, notes from John Milner on storage.

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