Common Ground: a policy framework for open access to research data

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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

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Common Ground: a policy framework for open access to research data

  1. 1. Common Ground A Policy Framework for Open Access to Research Data Susan Reilly, LIBER Projects Manager susan.reilly@kb.nl @skreilly
  2. 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. 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. 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. 5. By Ken Lund (Flickr: Why, Arizona (2)) [CC-BY-SA-2.0 ( http://creativecommons.org/licenses
  6. 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. 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. 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. 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. 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. 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. 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. 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. 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. 15. 5 case studies • Particle physics • Clinical science • Human physiology • Enviromental science • Archeology and related disciplines
  16. 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. 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. 18. Thank you from the ReCODE partners!

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