Presentation by Susan Reilly at RDA National event in Florence, Italy, November 2016

1. LIBER:
Collaborate to Share
RDA Florence, 14 November, 2016
Susan Reilly, Executive Director, LIBER

2. Overview
 Open data in the LIBER vision
 Benefits of open data
• FAIR data
• Supporting FAIR Data

3. LIBER is Europe’s largest
research library
network…

4. Mission
Enable world class research…
= Collaborative
– Growth in collaboration from 13% (2003)- 17% (2011)
= International
– 40% of French & German research outputs a result of international
collaboration
– Rate of citation grows as geographic extent of collaboration increases
=Interdisciplinary
– Foundation of frontiers research
=Data intensive
• supports interdisciplinary exploration
… and open

5. 2022
Libraries powering
sustainable knowledge
in the digital age…
Vision

6. Vision
• Open Access is the default
• Research data is FAIR
• Digital skills underpin open, transparent
research lifecycle
• Research infra is participatory and
tailored to different disciplines
• Cutural heritage build on today’s digital
info
2022

7. Knowledge as a Public Good
 Non rivalrous
-sharing it doesn’t deplete it as a resource
 Non excludable
-it’s impossible stop the supply of knowledge
 Copyright reconises this by only exerting
control over the “expression of an idea” not
the idea itself
 In the digital age data can be infinately
accessible

8. Benefits of Open Data
For society
Solves global challenges e.g. hunger, pollution
For researchers:
Data re-use, avoiding costly duplication
Data re-use,facilitate complex interdisciplinary enquiry
Validation of results – quality control
For policy:
Inform decision making
For industry:
In development of new products & services

9. Fake data!

10. Barriers
 Cultural differences
 Definition of research data
 Lack of skills/education
 Poorly defined roles and responsibilities
 Lack of infrastructure
 Lack of career incentives

11. European Member States
Commitment
 All member states to transition towards Open
Science (council conclusion May 2016)
 Open access the default by 2020
 Research data from publically funded projects
a public good
 Data management standard scientific practice
 DMPs obilgatory
 Follow FAIR principles

12. EU Horizon 2020 Mandates
 Open Access Mandatory (2015)
 Open Data Pilot (7 funding areas, 2015)
 Open Data pilot extended to all funding
areas from 2017

13. H2020 Open Data Pilot
 Opt out at any stage (1/3 opted out so far)
 All research data, including metadata, needed
to validate the results in a peer-reviewed
publication
 Other curated or raw data, and its associated
metadata, specified in the DMP even if it did
not result in a publication
 Documentation, software, hardware or tools
required to enable reuse of the data
 DMP obilgatory

14. http://knowledgebase.e-irg.eu/documents/243153/246094/E-infrastructures+-+making+Europe+the+best+place+for+research+and+innovation.pdf

15. The European Open Science Cloud
 A virtual environment to store and
process large volumes of information
http://libereurope.eu/blog/2015/11/04/an-open-and-community-driven-open-science-cloud

16. The Challenge
Research data are the evidence
that underpins the answer to the
research question, and can be
used to validate findings
regardless of its form…

17. Research Data is…
ODE data publication pyramid

18. Research Data is…
Findable
 Metadata
 Persistent identifiers
 Indexed in a searchable resource
Accessible (openly)
 Open and standardised communication protocols
Interoperable
 Shared language for knowledge representation
Reusable
 Clear provenance and licences
 Detailed provenance

20. Supporting
FAIR Data
• Active
– Offering and planning RDS service
– Consultative (Discussion e.g. metadata, policy,
training, outreach)
– 38% provide tech support
• On the horizon
– 42% plannig tech support
– 48% planning ID support
– 43% planning metadata services
– West and north more involved in discussions

21. Findable…
Data management planning support (46%)
Identifiers
Support for citation and finding datasets
Identification of datasets for repositories

22. Accessible…
Consulting on data standards and methods
Preparing datasets for deposit 25%
Web guides
Data storage 78%

23. Interoperable…
Consulting on data standards and methods
(44%)
Partnering with researchers (32%)
ID Datasets
Collaborating with disciplinary departments
Collaborting with other institutions and infra

24. Reusable…
Policy development and planning (66%)
Gudiance and training e.g. re copyright (54%)
Tools for data analysis (23%)

25. Regional differences in consultative RDS
availability

26. Regional differences in technical RDS
availability

27. Why collaborate?
• No one size fits all approach (work across
disciplines)
• Need to work across services (libraries, IT,
research)
• Need to work across infrastructures
• Potential for interdiciplinary research
• Shared responsibility!

28. Ways to collaborate
• Get involved in the RDA
– Libraries in RDM Interest Group
– Repositories Interest Group
– …start a group!
– Start a discussion

29. Roadmap RDM!Roadmap RDM!
 Policies
 Costs
 Infrastructure
 Skills
 Advocacy and engagement
Barcelona, 26 Jan 2017!
http://learn-rdm.eu/
Self assessment
Dialogue
RDM Templates

30. ARE YOU WITH US?
www.libereurope.eu
@skreilly
Thank
you!