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Introduction to panel presentations from Universities of Edinburgh, Southampton, Yale, Cornell at IPRES 2015 conference, Chapel Hill, North Carolina, 3 Nov 2015
This presentation was provided by Sandi Caldrone of Purdue during the NISO Virtual Conference held on Feb 15, 2017, entitled Institutional Repositories: Ensuring Yours is Populated, Useful and Thriving.
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A 30 minute seminar presented at the National Bioscience Database Center, part of the Japanese Science and Technology Agency, based in Tokyo, Japan. This presentation covers the FAIR Principles, the aims, methodology and use of FAIRsharing, related projects such as Bioschemas, and international initiatives such as ELIXIR and EOSC.
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RDAP 16 Lightning: An Open Science Framework for Solving Institutional Challe...ASIS&T
Research Data Access and Preservation Summit, 2016
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Presenter:
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This presentation was provided by Scott Warren and Anne Rauh of Syracuse University during the NISO virtual conference, Research Information Systems: The Connections Enabling Collaboration, held on August 16, 2017.
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amplification of information services (e.g. data curation, institutional repositories, scholarly publishing).
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Video of Talk--Vimeo: https://vimeo.com/149713097
Video of Talk--YouTube: https://www.youtube.com/watch?v=L0G9JsPMEXY
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“Where do we start?”: opportunities for libraries to support research data management
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,…)
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
19. 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
22. Thank you!
Any questions?
Find out more at www.libereurope.eu and
www.recodeproject.eu
Coming soon…FOSTER project to ‘train the trainer’
Editor's Notes
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.