Invited paper for EU-funded RECODE Project workshop in Riga, Latvia on 1 July, 2014. http://recodeproject.eu/events/recode-workshops/

1. Engaging researchers in
RDM & Open Data at
Edinburgh University
Robin Rice
EDINA and Data Library
Information Services
University of Edinburgh
#RECODE, Riga, Latvia: 1st July, 2014

2. Overview
• UoE RDM Policy regarding open data
• Data lifecycle & our RDM Programme
• Data Library – supporting re-use of data
• Edinburgh DataShare – institutional data repository
• MANTRA – online course about RDM
• Benchmark: DCC 2014 UK survey results - RDM
services in place
• Challenges in RDM support & open data advocacy
• Benchmark: DCC 2014 UK survey results – Obstacles
in supporting RDM

3. UoE RDM Policy &
Open Access to Data
“The University will provide
mechanisms and services
for storage, backup,
registration, deposit and
retention of research data
assets in support of current
and future access, during
and after completion of
research projects.”
“Any data which is retained
elsewhere, for example in
an international data
service or domain repository
should be registered with
the University.”
• “Research data of future
historical interest, and all
research data that
represent records of the
University, including data
that substantiate
research findings, will be
offered and assessed for
deposit and retention in
an appropriate national
or international data
service or domain
repository, or a University
repository.”

4. ‘A’ Data Lifecycle
Image by Anthony Beitz, Monash University Re-used with permission.
CollaborateConceive Design Experiment Publish ExposeAnalyseDesign
Data
Management
Planning
Expose
National Repository or
Institutional Repository or
Electronic Journal or
Community Portal
Research Data Management
Platform
CollaborateExperiment PublishAnalyse

5. UoEResearch Data Management
Roadmap (2012-2014)
Note: A 2007 Research Computing Survey at UoE showed
access to backup and storage was the most pressing need
amongst researchers across disciplines.

7. UoE Data Library Service
• finding…
• accessing …
• using …
• teaching …
• managing
ChartsBin and mkandlez on flickr

8. Data Library experience:
engaging researchers
• Supporting secondary
analysis – users’
headaches and barriers
• Data increasingly easier
to obtain and to analyse;
hence RDM
• Data/statistical literacy
capacity building
• More high level
requirements (eg
visualisation, integration)‘Data Nerd’ by R Rice

9. DataShare – open data
repository

10. DataShare experience:
engaging researchers
• Woo early adopters;
gather good reputation
• Focus on benefits
• Keep developing it to
meet more user
needs/expectations
• Save the time of
depositors BUT
• Keep the end-user in
mind (QA)
• Set policies to avoid
‘mission creep’
RETAIN AS IS, by R Rice

11. From Stuart Lewis, 2013:
http://datablog.is.ed.ac.uk/2013/12/06/
the-four-quadrants-of-research-data-curation-systems/
DataShare & related
UoE RDM services

13. MANTRA experience:
engaging researchers
• Bringing MANTRA into
classroom setting
• Disciplinary-specific vs
generic RDM training
• Open vs closed:
(Inter)national reach vs
institutional reach
• Self-assessment vs for-
credit course
• Librarians like it (even)
more

14. Benchmark: DCC 2014 UK
survey - RDM services in place
n=87 respondents at 61 institutions incl. 24 Russell Group.
Angus Whyte, DCC, http://www.dcc.ac.uk/blog/rdm-
strategy-action-glass-half-full

15. Challenges in RDM
support & advocacy
• Reaching critical mass of students and academics
at point of need (timing, priorities, scheduling)
• ‘Turnaround time’ in writing data management
plans
• Identifying ‘RDM’ requests at helpdesk; proper
routing to expert support
• Costing intensive data services & in-depth support
in grants
• Getting balance right for private and open data
o Incentivising sharing
• Working ‘upstream’ in research process is hard

16. DCC 2014 UK survey results
Obstacles to RDM provision (Table 8) % (n=87)
Lack of appropriate staff resources and infrastructure 71%
Availability of funding 64%
Low priority for researchers 56%
Lack of relevant accepted standards 38%
Lack of knowledge of appropriate solutions 36%
Lack of appropriate skills and expertise to implement solutions 34%
Low priority for management 23%
“Pre‐release Briefing 1” [email], 23 April 2014. Angus Whyte, Diana Sisu, DCC.

17. Thanks to RECODE
• Email: R.Rice@ed.ac.uk
• RDM Website: www.ed.ac.uk/is/data-management
• Data Library: www.ed.ac.uk/is/data-library
• Blog: http://datablog.is.ed.ac.uk
• DCC 2014 UK Survey Results:
http://www.dcc.ac.uk/blog/rdm-2014-survey