Libraries and Research Data Management – What Works?

Summary of a pre-surveySteering Committee Scholarly Communication and Research Infrastructures

LIBER Annual Conference, Riga, 2 July 2014

Rob Grim, Tilburg University, Co-Chair SII

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 activity1 - Some awareness2 - Information gathering, explorative3 - Specification and development4 - Testing as a service, partly sustained5 - Established service, mostly or fully sustained

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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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Engagement of libraries: overview

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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

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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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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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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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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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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Training

Have you participated in research data management trainings over the last two years?

YES: 40%

Copyright, standards, Open Access policiesData management basicsDigital Curation, RDM in arts & humanities, various workshops and conferencesOpenAIRE workshopsRDM for librariansSupporting researchers to write a data management plan and store research data

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Training

What is missing? More advanced training would be usefulPreservation, the role of effective embedded librariansThe 'hands on' data experience and data science skillsHow 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 nowVery practical approach to specific issues as 'how to...'

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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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