A presentation given by Paul Ayris at the 5th LEARN workshop in Barcelona (26 Jan 2017). www.learn-rdm.eu

1. UCL LIBRARY SERVICES
The Needs of stakeholders in
the RDM process – the role of
LEARN
Dr Paul Ayris
Pro-Vice-Provost (UCL Library Services)
Director of UCL Library Services
Co-Chair of the LERU community of Chief Information Officers
Adviser to the LIBER Board on Horizon 2020 and EU issues
e-mail: p.ayris@ucl.ac.uk

2. UCL LIBRARY SERVICES
Content
 Research Data Management
 LERU Roadmap
 LEARN
 Open Science (Science 2.0)
 Exemplar issues
 Role for Research Funding
Agencies
 Issues Addressed in the
LEARN Toolkit
 Conclusions
2
Plaster Relief by John Flaxman,
Flaxman Gallery, UCL

3. UCL LIBRARY SERVICES
Content
 Research Data Management
 LERU Roadmap
 LEARN
 Open Science (Science 2.0)
 Exemplar issues
 Role for Research Funding
Agencies
 Issues Addressed in the
LEARN Toolkit
 Conclusions
3
Plaster Relief by John Flaxman,
Flaxman Gallery, UCL

4. UCL LIBRARY SERVICES
LERU Roadmap for Research Data
 Overseen by Research Data
Working Group
Pablo Achard (University of Geneva)
Paul Ayris (UCL, University College London)
Serge Fdida (UPMC, Paris)
Stefan Gradmann (University of Leuven)
Wolfram Horstmann (University of Oxford)
Ignasi Labastida (University of Barcelona)
Liz Lyon (University of Bath)
Katrien Maes (LERU)
Susan Reilly (LIBER)
Anja Smit (University of Utrecht)

5. UCL LIBRARY SERVICES
• Identifies how policy development and leadership are undertaken
Policy and Leadership
• Who undertakes advocacy and what is the message?
Advocacy
• Technical Issues around collection and curation
Selection, Collection, Curation, Description, Citation, Legal Issues
• Where is it stored and by whom?
Research Data Infrastructure
• How much does it cost?
Costs
• What skills are required by which communities?
Roles, Responsibilities, Skills
• Who does what?
Recommendations to different stakeholder groups
5http://en.wikipedia.org/wiki/File:DNA_orbit_animated.gif

6. UCL LIBRARY SERVICES
Key Messages
 Each LERU university
needs a Research Data
Management Strategy
 Researchers should have
Research Data
Management Plans
 LERU universities need to
bring stakeholders together
 Benefits of ‘open data’ for
sharing and re-use should
be advocated and explored
A Box of Useful Knowledge
(Brougham Papers, UCL Library Services)

7. UCL LIBRARY SERVICES
Policy Development
 Case Study on Policy
development from UCL
 Drivers
 External funders
 Need to inform researchers
 Raise awareness of issues
facing UCL researchers
 Identifies roles and
responsibilities
 Data to be made open in
the most open manner
appropriate
 Researchers should have
Data Management Plans
 LERU slams lack of data
policies – Research Europe
See www.lanecrothers.net/politicalprof/the-policy-
cycle-and-our-frozen-politics/

8. UCL LIBRARY SERVICES
Open Data
 Open Data allows research data to be shared and re-used
 Avoids costly duplication of research activity
 Provides greater transparency in research activity
 Potential to speed discovery of solutions to societal Grand
Challenges, such as health care & environmental science
 Can all research data be open?
 Certain categories probably cannot
 National security
 Data protection
 Commercial Funder requirements
http://en.wikipedia.org/wiki/File:Open_Data_stickers.jpg

9. UCL LIBRARY SERVICES
LEARN – LEaders Activating Research
Networks
 Purpose is to develop the
LERU Roadmap for
Research Data to build a
global co-ordinated global
e-infrastructure
 Outputs
 Model Research Data
Management policy
 Toolkit to support
implementation
 Executive Briefing in five
core languages so as to
ensure wide outreach 9

10. UCL LIBRARY SERVICES
LEARN
 5 partners
 UCL (University College
London) – lead partner
 University of Barcelona
 University of Vienna
 LIBER
 ECLAC – UN Commission
for Latin America and the
Caribbean
 Started in June 2015; runs
for 24 months
 €497,000 budget
 100% funded
10
Wilkins Building, UCL, 1826

11. UCL LIBRARY SERVICES
LEARN Deliverables
 Model Research Data
Management Policy
 Fed by a study of RDM
policies and input from
Workshop attenders
 Toolkit to support
implementation
 Issues identified in
Workshops and in
literature
 Surveys and self
assessment tools
 Executive Briefing (in
several languages) 11
Wilkins Building, UCL, 1826

12. UCL LIBRARY SERVICES
Content
 Research Data Management
 LERU Roadmap
 LEARN
 Open Science (Science 2.0)
 Exemplar issues
 Role for Research Funding
Agencies
 Issues Addressed in the
LEARN Toolkit
 Conclusions
12
Plaster Relief by John Flaxman,
Flaxman Gallery, UCL

13. UCL LIBRARY SERVICES
13
Data Gathering
Analysis
Publication
Review
Conceptualization
Citizen Science
Open code
Pre-print
Open Access
Alternative Reputation Systems
Collaborative Bibliographies
Science Blogs
Open Annotation
Open Data
Open Lab Books/Workflows
Data Intensive
Open Science
- a paradigm shift in the modus
operandi of research and science
impacting the entire scientific process
Research Cycle Characteristics

14. UCL LIBRARY SERVICES
14
Data Gathering
Analysis
Publication
Review
Conceptualization
Citizen Science
Open code
Pre-print
Open Access
Alternative Reputation Systems
Collaborative Bibliographies
Science Blogs
Open Annotation
Open Data
Open Lab Books/Workflows
Data Intensive
Open Science
- a paradigm shift in the modus
operandi of research and science
impacting the entire scientific process
Research Cycle Characteristics

15. UCL LIBRARY SERVICES
% Agreement for Policy actions (abbrev.)
15
Question/Issue Need to
Intervene
Y
Need to
Intervene
N
Req’d
Action
Y
Req’d
Action
N
EU
Action
Y
EU
Action
N
Foster Open
Science – raise
awareness
52% 4% 48% 4% 19% 4%
Traditional Metrics
do not capture Open
Science
22% 7% 22% 7% 4% 7%
Develop research
infrastructures
56% 4% 11% 4% 48% 4%
OA to publications
and data
63% 11% 33% 26% 26% 11%
 The most significant total
in the Validation exercise
 Not much interest in any
intervention

16. UCL LIBRARY SERVICES
Content
 Research Data Management
 LERU Roadmap
 LEARN
 Open Science (Science 2.0)
 Exemplar issues
 Role for Research Funding
Agencies
 Issues Addressed in the
LEARN Toolkit
 Conclusions
16
Plaster Relief by John Flaxman,
Flaxman Gallery, UCL

17. UCL LIBRARY SERVICES
Research Funder policies
 UCL has tracked 15
global funder
policies
 Research funders
can set direction for
Open Science
 Funders have led
movement towards
Open Access
 They should now do
the same for
research data
17

18. UCL LIBRARY SERVICES
What should research funders ask for?
 Require Research Data
Management Policies in
institutions
 Require Data
Management Plans from
individual researchers
 Require that the default
position for research
data is Open
 Fund infrastructure -
like the UK Data Archive
18

19. UCL LIBRARY SERVICES
What does LEARN have to deliver?
 Awareness of
RDM issues
19
Plaster Relief by John Flaxman,
Flaxman Gallery, UCL

20. UCL LIBRARY SERVICES
UCL survey by Research Data Advocacy
Officer
 130 research departments, institutes, centres and units
represented in survey
 Response rate – 306 completed surveys out of 619
 Respondents
 18% early career researchers
 39% experienced researchers
 30% research students
20

21. UCL LIBRARY SERVICES
 45% of respondents used a personal computer for storage
 Choices included Cloud services; others used paper...
 Central UCL facility used by only 5% 21
17
196
130 116
145
112
64 60
22
178
112
109 122 79
36
21 21
19
105
68
50
94
45
50
22 22
29
0
50
100
150
200
250
300
350
400
External hard
drive or USB
stick
Hard drive of
personal PC
or laptop
Cloud service
(e.g.
Dropbox,
Google Docs,
iCloud)
Shared drive /
UCL server
Hard drive of
UCL PC or
laptop
On paper, on
UCL
premises
On paper,
off-site
Hard drive of
instrument /
sensor
Institutional
repository
(e.g.
Research
Data Storage;
Discovery)
for long-term archiving
to back them up
while working on them
Qu.34 In your most recent project, where did you keep your data? (433 respondents; multiple choice)

22. UCL LIBRARY SERVICES
22
20
29
30
33
49
52
57
74
84
89
94
111
143
175
0 50 100 150 200
Other
Commercial questions related to your data
No help needed
Citing data
Ethical questions related to your data
Finding data and publications to re-use
Creating metadata
Legal questions related to your data
Sharing data
Open Access to your publications
Project budget and costing data management
Storage & preservation of data (MOSTLY personal
and sensitive)
Data Management Plans
Storage & preservation of data (NOT personal or
sensitive)
Qu.64 Would you be interested in some help with data management? Please tick up to FIVE
preferred elements from the list below. (308 respondents; multiple choice)

23. UCL LIBRARY SERVICES
23
Beginning of the
project ("very early on",
"straightaway", "pre-
protocol", "at the outset",
etc.)
51%
"Always" ("all the time",
"throughout")
16%
Project development
("proposal writing", "for
ethical review",
"planning", etc.)
14%
Before or after "data
collection"
("questionnaire design",
"fieldwork preparation",
etc.)
4%
During the project
("periodically", "halfway
through", "1st year of
PhD")
4%
"Never"
4%
"Late" / "too late"
2%
End of the project ("at
the end", "towards the
end")
1%
Project completion
("ready for publication",
"database completion")
1%
"Ad-hoc"
1%
When a problem
occurred
0,5%
"Not until I took this
survey"
0,5%
Qu.61 At what stage of the project did you think about data management? (217
respondents; free text)

24. UCL LIBRARY SERVICES
Training Early Career Researchers
24
 LERU (League of European
Research Universities) held
week-long Doctoral Summer
School in July 2016 on
research data
 UCL (University College
London) has begun a
Training Programme with the
Doctoral School

25. UCL LIBRARY SERVICES
Content
 Research Data Management
 LERU Roadmap
 LEARN
 Open Science (Science 2.0)
 Exemplar issues
 Role for Research Funding
Agencies
 Issues Addressed in the
LEARN Toolkit
 Conclusions
25
Plaster Relief by John Flaxman,
Flaxman Gallery, UCL

26. UCL LIBRARY SERVICES
Conclusions
 RDM has many
stakeholders
 Data-driven research
changing the way
research is undertaken
 LEARN will provide
 Model RDM policy
 Exemplar case studies
 Executive Briefings
 LEARN will help deliver
infrastructure for data-
driven Science
 Happy to hear questions