The Needs of Stakeholders in the RDM Process - the role of LEARN

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: [email protected]


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


Content


LERU Roadmap

LEARN


Exemplar issues


Agencies


LEARN Toolkit

Conclusions

3




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)


• 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

5 http://en.wikipedia.org/wiki/File:DNA_orbit_animated.gif

http://en.wikipedia.org/wiki/File:DNA_orbit_animated.gif

http://en.wikipedia.org/wiki/File:DNA_orbit_animated.gif


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)


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/

http://www.lanecrothers.net/politicalprof/the-policy-cycle-and-our-frozen-politics/















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




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

http://www.uzh.ch/research/LERU_Roadmap_for_Research_data.pdf

http://www.uzh.ch/research/LERU_Roadmap_for_Research_data.pdf


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


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


Content


LERU Roadmap

LEARN


Exemplar issues


Agencies


LEARN Toolkit

Conclusions

12




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

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


% 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


Content


LERU Roadmap

LEARN


Exemplar issues


Agencies


LEARN Toolkit

Conclusions

16




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


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


What does LEARN have to deliver?

Awareness of

RDM issues

19




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


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

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

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)


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


Content


LERU Roadmap

LEARN


Exemplar issues


Agencies


LEARN Toolkit

Conclusions

25




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

Education

The Needs of Stakeholders in the RDM Process - the role of LEARN