Presentation of the ReCODE project at LIBER 2013 in Munich. Presents the argument for stakeholder engagement in the development of open access policies for research data

1. Common
Ground
A Policy
Framework for
Open Access to
Research Data
Susan Reilly, LIBER Projects Manager
susan.reilly@kb.nl
@skreilly

2. Overview
• Introduction: Policy RECommendations
for Open access to research Data in Europe
(RECODE)
• The open research data agenda
• Environment and stakeholders
• The way forward

3. Project ReCODE
The project will leverage existing
networks, communities and projects to
address challenges within the open
access and data dissemination and
preservation sector and produce policy
recommendations for open access to
research data based on existing good
practice.

4. Project ReCODE Objectives
• Reduce stakeholder fragmentation
• Identify stakeholder values and inter-
relationships
• Identify gaps, tensions and good practices
• Produce a set of guidelines for the sharing
of scientific data
• Engagement of stakeholders
• Use 5 cases from different disciplines

5. By Ken Lund (Flickr: Why, Arizona (2)) [CC-BY-SA-2.0 (
http://creativecommons.org/licenses

6. 1. How can we define research data and what should we make open?
2. When and how does openness need to be limited
3. How should the issue of data resuse be addressed
4. Where should research data be stored and made accessible?
5. How can we enhance data awarenesss and a culture of sharing?

7. Clear benefits of open data
http://fav.me/d1y5efr
• 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

8. But there are barriers too:
• Cultural differences
• Definition of research data
• Lack of skills/education
• Poorly defined roles and responsibilities
• Lack of infrastructure
• Lack of career incentives

9. How do we define open access to research data?
• We can define ‘open access’ (see Berlin
Declaration):
license to copy, use, distribute and display material subject to
proper attribution of authorship and appropriate standard format,
online repository, enable unrestricted distribution,interoperability,
and long-term archiving.
• But how do we define research data?
Data underlying publications, all experimental data?

10. The entire data lifecycle must be addressed
• Open access to data extends across the life
cycle of the production of knowledge, from
ethical concerns about data collection,
characteristics of data collection, data analysis,
data management, access to findings, and the
status of findings.
• Although some developments are shared across
research practices, these are adapted within
specific disciplines in the physical sciences,
social sciences and in the humanities.

11. Stakeholder fragmentation
• Universities, publishers, public and private
research organizations, software developers,
libraries, funding bodies and repositories within
national, world regions and global science eco-
systems
• High interdependency, but lack
of clarity around roles and
responsibilities
By Oneblackline (Own work) [GFDL (http://www.gnu.org/copyleft/fdl.html) or CC-BY-3.0 (http://creativecommons.org/licenses/by/3.0)], via Wikimedia Commons

12. Infrastructure & technologies
• Interoperability
• Scalability
• Data quality
• Automatically
executable policies
By Anonymous (Guillaume Blanchard, Juillet 2004, Fujifilm S6900.) [CC-BY-SA-2.5-2.0-1.0 (http://creativecommons.org/licenses/by-sa/2.5-2.0-1.0), GFDL
(http://www.gnu.org/copyleft/fdl.html), CC-BY-SA-3.0 (http://creativecommons.org/licenses/by-sa/3.0/) or FAL], via Wikimedia Commons

13. Legal and ethical issues
• Intellectual property
– the database directive, copyright agreements
with publishers, can we (libraries/repositories)
change the format of data?
• Data protection
– right to be forgotten

14. Scientific discipline a key differentiator
• Different cultures re sharing and
collaboration
• Types of data determine level of
availability
• Differences in availability of appropriate
infrastructure
• Data valued differently

15. 5 case studies
• Particle physics
• Clinical science
• Human physiology
• Enviromental science
• Archeology and related disciplines

16. It seems a lot to do…
• Global context: Research Data Alliance,
COAR, Open Knowledge Foundation
• European context: LERU, LIBER,
SPARCEurope, OpenAire, Knowledge
Exchange
…we’re just trying to bring it all together

17. So first things first…
• Define stakeholder values and ecosystem
– Workshop at University of Sheffield,
September 4th 2013.
susan.reilly@kb.nl
www.recodeproject.eu

18. Thank you from the ReCODE partners!