This presentation by Rob Grim was given at the Scholarly Communication and Research Infrastructures Steering Committee Workshop. The workshop title was Libraries and Research Data Management – What Works?

1. Libraries and Research Data Management
– What Works?
Summary of a pre-survey
Steering Committee Scholarly Communication and Research Infrastructures
LIBER Annual Conference, Riga, 2 July 2014
Rob Grim, Tilburg University, Co-Chair SII

2. Pre-survey: Liber14 RDM Workshop
We would like to learn more about how the library engages in research data management at
your institution
•Starting point: 10 RDM recommendations for libraries
•Target group: workshop participants and authors of case studies (N=21)
In the questions below, please specify your institution's level of
engagement:
0 - No activity
1 - Some awareness
2 - Information gathering, explorative
3 - Specification and development
4 - Testing as a service, partly sustained
5 - Established service, mostly or fully sustained
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3. 10 Recommendations for libraries to get started with
research data management
Regrouping the recommendations – Areas of engagement
Support services
#1 Offer research data management support, including data management plans for grant applications,
intellectual property rights advice and information materials. Assist faculty with data management plans and the
integration of data management into the curriculum.
#6 Support the lifecycle for research data by providing services for storage, discovery and permanent access.
#9 Get involved in subject specific data management practices
Infrastructure & standards
#2 Engage in the development of metadata and data standards and provide metadata services for research
data.
#5 Liaise and partner with researchers, research groups, data archives and data centers to foster an
interoperable infrastructure for data access, discovery and data sharing.
#7 Promote research data citation by applying persistent identifiers to research data.
#8 Provide an institutional Data Catalogue or Data Repository, depending on available infrastructure.
#10 Offer or mediate secure storage for dynamic and static research data in co-operation with institutional IT
units and/or seek exploitation of appropriate cloud services.
Policy & disciplinary practices
#4 Actively participate in institutional research data policy development, including resource plans. Encourage
and adopt open data policies where appropriate in the research data life cycle.
#7 ... (with some disciplinary views on data citation)
Skills & staffing
#3 Create Data Librarian posts and develop professional staff skills for data librarianship.
#1 … and the integration of data management into the curriculum.
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4. 4

5. Engagement of libraries: overview
5
N Mean Std. Deviation
#4 Actively participate in institutional research data policy development,
including resource plans. Encourage and adopt open data policies where
appropriate in the research data life cycle.
21 2.714 1.4541
#10 Offer or mediate secure storage for dynamic and static research data in co-
operation with institutional IT units and/or seek exploitation of appropriate cloud
services.
21 2.667 1.1972
#6 Support the lifecycle for research data by providing services for storage,
discovery and permanent access.
21 2.667 1.3904
#2 Engage in the development of metadata and data standards and provide
metadata services for research data.
21 2.524 1.5040
#8 Provide an institutional Data Catalogue or Data Repository, depending on
available infrastructure.
21 2.381 1.5322
#5 Liaise and partner with researchers, research groups, data archives and
data centers to foster an interoperable infrastructure for data access, discovery
and data sharing.
21 2.381 1.5645
#1 Offer research data management support, including data management
plans for grant applications, intellectual property rights advice and information
materials. Assist faculty with data management plans and the integration of
data management into the curriculum.
21 2.333 1.1106
#3 Create Data Librarian posts and develop professional staff skills for data
librarianship.
21 2.143 1.4928
#9 Get involved in subject specific data management practice. 21 1.952 1.2836
#7 Promote research data citation by applying persistent identifiers to research
data.
21 1.905 1.2611
Valid N (listwise) 21
Descriptive Statistics
Recommendations sorted by engagement level

6. Areas of Engagement
Most involved:
•Institutional research data policy development, including resource plans. Encourage
and adopt open data policies where appropriate in the research data life cycle (#4 ).
•Offer or mediate secure storage for dynamic and static research data in co-operation
with institutional IT units and/or seek exploitation of appropriate cloud services (#10).
•Supporting the lifecycle for research data by providing services for storage, discovery
and permanent access (#6 ).
•Engage in the development of metadata and data standards and provide metadata
services for research data (#2).
Least involved:
•Get involved in subject specific data management practices (#9).
•Promote research data citation by applying persistent identifiers to research data (#7).
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7. Areas of Engagement
Some involvement
•Provide an institutional Data Catalogue or Data Repository, depending on available
infrastructure #8.
•Liaise and partner with researchers, research groups, data archives and data centers to
foster an interoperable infrastructure for data access, discovery and data sharing #5.
•Offer research data management support, including data management plans for grant
applications, intellectual property rights advice and information materials. Assist faculty
with data management plans and the integration of data management into the
curriculum #1.
•Create Data Librarian posts and develop professional staff skills for data librarianship #3.
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8. Comments to the level of engagement
Support services
#1 RDM support
•A dedicated website, providing background information on funders requirements, a DMP-template is
currently being prepared, further guidance & advance provided individually upon request. Advisor. Project
based "e-Infrastructures Austria".
•We will start offering advice and assist faculty. Today we answer questions when we get them.
Responsibility for supporting Research Data Management within the university is scattered.
•We support research groups with DMP development. We have information on IPR on our website. Assisting
with DMP development is not standard practice within the library. We are "learning by doing".
#6 Providing lifecycle support
•IT department and university library have been traditionally providing such services for information
resources for a long time. These services now have to be extended to specific research data needs.
•The maturity level depends on: the research group, the workflow and the 'data types' involved. For small and
long tail science research data we provide full lifecycle support.
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9. Comments to the level of engagement
Infrastructure & Standards
•This is an explicit aspect of the RDM-project at the Radboud University. This is not only the task
of the University Library, but it is addressed broader within the University.
•We have the skills to do this, though it is currently not a priority due to lack of time and the fact
that this is not an assignment the library has. We are working towards this, though, and are
engaged in discussions on a national level.
•We just adopt current international standards but do not develop anything ourselves
•Helsinki University Library's experts take part on developing metadata standards on national
level. On university level metadata services for research data concern mainly some projects and
basic research data training to researchers.
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10. Comments to the level of engagement
Skills & Staffing
•For the time being, most related work is carried out by the repository central technical office.
•Library staff skills training program already completed. There are no full time data librarians, but a group of
librarians who take part in research data support services.
•This is an explicit aspect of the RDM-project at the Radboud University. The University Library is appointed by
the Executive Board to develop data librarian services. This is done as a pilot project in 2014-2015, with the
aim to establish a structural service as soon as possible.
•Together with one of our subject librarians we recently have started working on a RDM training for
researchers as part of information literacy skills.
•We do this, but not apart from developing professional skills in general.
•We were the 1st university library in the Netherlands with a position for a Data Librarian. An additional
information collection specialist is now being reskilled to become a Data Librarian.
•We will probably do something like this in the coming years.
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11. Training
Have you participated in research data management
trainings over the last two years?
YES: 40%
 Copyright, standards, Open Access policies
Data management basics
Digital Curation, RDM in arts & humanities, various workshops and conferences
OpenAIRE workshops
RDM for librarians
Supporting researchers to write a data management plan and store research data
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12. Training
What is missing?
More advanced training would be useful
Preservation, the role of effective embedded librarians
The 'hands on' data experience and data science skills
How to support researchers while managing their data during their research; libraries
talk mostly about metadata, standards, awareness, storage and catalogues, but in my
opinion the key step in the process is missing out now
Very practical approach to specific issues as 'how to...'
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13. Conclusions
Support services
•Writing DMP’s. Learning by doing! How to put theory into practice.
•RDM support services are resource intensive (development & deployment phase)
Skills & staffing
•Current practice: Re-skilling of subject librarians
•Development of professional staff skills for data librarianship needed
Infrastructure & standards
•Liaise and partner with researchers, research groups, data archives and data
centers to foster an interoperable infrastructure for data access, discovery and data
sharing.
Policy & disciplinary practices
•Heterogeneous picture. Many differences across institutions
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