Rachel Bruce UK research and data management where are we now

1. The UK and Research Data
Management: where are we?
Rachel Bruce, Jisc

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. 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. 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. 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. 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. 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. Research Data Directions for Universities 8
UK Open Research Data Forum: Research Data
Concordat
See the draft …

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. Research Data Directions for Universities 10
Russell Group (39)
Others 10%+ (35)
Others (13)
From 61 institutions

11. Research Data Directions for Universities 11
Most advanced areas
% indicating piloting or live
0 20 40 60 80

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. 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. 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. 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. 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. 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. 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. Research Data Directions for Universities 19
Research at Risk – some of the gaps (there were
others identified!)
• Storage.
• Metadata.
• Preservation.
• Defining compliance.

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. 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. 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. 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.