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“Where do we start?”: opportunities for libraries to support research data management
“Where do we start?”: opportunities for libraries to support research data management
“Where do we start?”: opportunities for libraries to support research data management
“Where do we start?”: opportunities for libraries to support research data management
“Where do we start?”: opportunities for libraries to support research data management
“Where do we start?”: opportunities for libraries to support research data management
“Where do we start?”: opportunities for libraries to support research data management
“Where do we start?”: opportunities for libraries to support research data management
“Where do we start?”: opportunities for libraries to support research data management
“Where do we start?”: opportunities for libraries to support research data management
“Where do we start?”: opportunities for libraries to support research data management
“Where do we start?”: opportunities for libraries to support research data management
“Where do we start?”: opportunities for libraries to support research data management
“Where do we start?”: opportunities for libraries to support research data management
“Where do we start?”: opportunities for libraries to support research data management
“Where do we start?”: opportunities for libraries to support research data management
“Where do we start?”: opportunities for libraries to support research data management
“Where do we start?”: opportunities for libraries to support research data management
“Where do we start?”: opportunities for libraries to support research data management
“Where do we start?”: opportunities for libraries to support research data management
“Where do we start?”: opportunities for libraries to support research data management
“Where do we start?”: opportunities for libraries to support research data management
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“Where do we start?”: opportunities for libraries to support research data management

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Presentation on how libraries can support researcher's in making their data open. Presented in UCL on the 20th October 2013

Presentation on how libraries can support researcher's in making their data open. Presented in UCL on the 20th October 2013

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  • Libraries and data centres must support data publishing as a prerequisite for data availability, including persistent identification/citation of datasets, and solutions for data description and retrieval, which together facilitate findability. They must also ensure that data is properly documented as a condition for data interpretability and re-usability and prepare for long-term data archiving including data curation and preservation.
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    • 1. “Where do we start?”: opportunities for libraries to support research data management Susan Reilly Projects Manager LIBER: Ligue des Bibliothèques Européennes de Recherche UCL, 21 Oct 2013 susan.reilly@kb.nl @skreilly
    • 2. Contents  About LIBER  Opportunties for libraries: the researcher perspective  Opportunities for libraries: the policy perspective  Priorities?
    • 3. LIBER: reinventing the library of the future  Largest network of European reseach libraries: 450 in over 40 countries Mission: To provide an information infrastructure to enable research in LIBER institutions to be world class
    • 4. LIBER & EU Projects Reshaping The research library Advocacy Scholarly Communication & Research Infrastructure
    • 5. Looking at data sharing from the researcher‘s point of view “Without the infrastructure that helps scientists manage their data in a convenient and efficient way, no culture of data sharing will evolve.” Stefan Winkler-Nees (German Research Foundation, DFG)
    • 6. The Data Publication Pyramid (2) Further data explanations in any kind of supplementary files to articles (4) Data publications, describing available datasets (1) Data contained and explained within the article (3) Data referenced from the article and held in data centers and repositories (5) Data in drawers and on disks at the institute
    • 7. Library support for the researcher Libraries and data centres must support…  data as first class research object: publishing, persistent identification/citation of datasets Availability Findability  data description, metadata, standards documentation and retrieval  proper documentation of data Interpretability  long-term data archiving including data curation and preservation Re-usability
    • 8. Libraries’ Opportunities Data Issue: Libraries and data centres opportunities (Chapter 4): Availability   Lower barriers to researchers to make their data available. Integrate data sets into retrieval services. Findability    Support of persistent identifiers. Engage in developing common metadescription schemas and common citation practices. Promote use of common standards and tools among researchers Interpretability    Support crosslinks between publications and datasets. Provide and help researchers understand metadescriptions of datasets. Establish and maintain knowledge base about data and their context. Re-usability    Curate and preserve datasets. Archive software needed for re-analysis of data. Be transparent about conditions under which data sets can be re-used (expert knowledge needed, software needed). Citability   Engage in establishing uniform data citation standards. Support and promote persistent identifiers. Curation/Preservation     Transparency about curation of submitted data. Promote good data management practice. Collaborate with data creators Instruct researchers on discipline specific best practices in data creation (preservation formats, documentation of experiment,…)
    • 9. Demand for data management support
    • 10. Findability
    • 11. Citability
    • 12. Looking at it from the policy perspective…
    • 13. By Ken Lund (Flickr: Why, Arizona (2)) [CC-BY-SA-2.0 (http://creativecommons.org/licenses
    • 14. Barriers to success of open data policies Articulate values for disciplines that you Help to define work with but first work for different own Develop and embed on changing yourcommunities training culture! programmes  Cultural differences  Definition of research data  Lack of skills/education Develop and Engage in policy  Poorly defined roles and responsibilities connect development  Lack of infrastructure Altmetrics and citation  Lack of career incentives
    • 15. What should our priorities be? LIBER ten recommendations: http://www.libereurope.eu/news/ten-recommendations-for-libraries-to-get-started-with-researchdata-management
    • 16. Get started!
    • 17. Advocate “Many researchers do not appear to see the value and benefits of data citation. There is a gap, which could be filled by libraries, in advocacy for data sharing, the use of subject specific repositories, and best practice in data citation. These, if filled, would increase the number of researchers sharing and reusing data.” http://www.alliancepermanentaccess.org/wp-content/plugins/download-monitor/downlo
    • 18. 1. Identify & develop new skills
    • 19. What Skills ?
    • 20. Thank you!  Any questions?  Find out more at www.libereurope.eu and www.recodeproject.eu  Coming soon…FOSTER project to ‘train the trainer’

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