10 Recommendations on Research Data Management: What's next?
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The document outlines ten recommendations for libraries to enhance their research data management (RDM) capabilities, emphasizing the need for practical information and specific skill sets. The workshop features speakers from various esteemed institutions sharing insights into collaboration, policies, and workforce development for RDM support. Key areas of focus include building advisory services, addressing skill gaps, and providing resources and case studies for effective implementation.
10 Recommendations on Research Data Management: What's next?
- 1. Ten Recommendations on Research Data Management - What's Next? Scientific Information Infrastructures (SII) Working Group Munich, LIBER Conference, 2013, June 26 Rob Grim Chair of the SII Working Group Head of Research Support/Research Data Specialist Library & IT Services e-mail: rob.grim@uvt.nl
- 2. Aim of this workshop: Inform & Engage Brief introduction to the SII working group Working plan & working group members Starting point: 10 recommendations for libraries to get started with Research Data Management (RDM) How to proceed with these recommendations? Introduce our speakers
- 3. Mr Wolfram Horstmann, Bodleian Library Oxford, UK Ms Jūratė Kuprienė, Vilnius University Library, Lithuania Ms Natalia Grygierczyk, Radboud Universiteit Nijmegen, The Netherlands Mr Ayhan Kaygusuz, Istanbul Sehir University, Turkey Mr Esa-Pekka Keskitalo, National Library of Finland, Finland Ms Annikki Roos, Viikki Campus Library, Helsinki, Finland Mr Frank Scholze, Karlsruhe Institute of Technology, Germany Mr Paolo Budroni, Library of the University of Vienna, Austria Mr Rob Grim, (Chair)Tilburg University, The Netherlands Mr Jeroen Rombouts, 3TU.Datacentrum, The Netherlands Ms Birte Christensen-Dalsgaard, (Co-Chair) The Royal Library, Denmark Ms Birgit Schmidt, Göttingen State and University Library, Germany SII working group members:
- 4. How to proceed with the 10 recommendations? 3 activity areas: Gather and present practical information on RDM support. Articulate - from a technical perspective -, the role of the libraries, taking into account strategic, operational and technical issues. Identify and describe the skills sets and profiles relevant to RDM support in academic libraries. 3 speakers: Jeroen Rombouts (3TU.Datacentrum): Collaboration and services Wolfram Horstmann (Oxford University): Policies and infrastructure Rob Grim (Tilburg University): Skilling the workforce
- 5. Re-Skilling the workforce Is it necessary? Libraries see RDM services as a priority, with a particular emphasis on advisory, policy support and training services (Pinfield & Cox, 2013) Little effort is put into developing skill sets relevant to support e- Science: curation, automated capture and tool development (Hey, 2009.) In some of the libraries, some of the staff, have some of the relevant skills… Questions for the audience: Do you have people working on RDM support? Are these people coming from a library or computer science / IT background?
- 6. Re-Skilling the Workforce: What to expect from us? Information on how to do it... Resources: Harvard: Data Scientist Training for Librarians Course. Other: DCC, Data Intelligence four Librarians,etc. Case studies on RDM support and share lessons learned: Oxford, Tilburg University, 3TU, Göttingen, Bielefeld Guidance on hard and soft skills (and how to make use of them) Data scientists or data librarians? Guidance on data management plans and institutional RDM policy plans Formal education and profiles of data professionals: academic curriculum, LIS schools, job descriptions relevant to LiBER community.
- 7. Discussion Engage with the LIBER community …
Editor's Notes
- #2: 3. General notes In the discussions held with the working group members also the following more generic issues came up. Does the skills gap within research libraries require a - Subject specific or a more generic approach? - An institutional or more substantial collaborative reaction at national or international level? - A library centric approach? If the answer to this question is yes: why? And what is specific to a library centric approach?
- #3: Aim of the workshop 1. Aim of the working group In this workshop our focus is on how to proceed with the recommendations that were released earlier. We grouped the 10 recommendations and divided them into three strands of activity. We agreed to: 1 Carry out desk research, and gather practical information for Research Data Management support. 2 Identify and describe skills sets and professional profiles to support RDM in RL. 3 Articulate the role of the library from a technical perspective, taking into account strategic operational and technical issues. Notes: - 1. Carry out desk research and gather practical information for Research Data Management (RDM) support. This work should incorporate data management plans, a FAQ for RDM support in libraries, and additional practical recommendations for offering RDM support i.e. virtual consultation hours for RDM available to consortia members, etc. 2. To articulate the skill sets and professional profiles which are necessary in academic/research libraries to curate, preserve and archive research data. This work should build on existing literature and resources and focus specifically on the library workforce. The work should/might cover the skills of the next generation of the library workforce and the re-skilling of the current staff. The work should take into account that library staff serves different academic disciplines as well as the cultural heritage sector and museums. 3. Explore the role of libraries from a technical viewpoint in infrastructure development and its role as a service provider for research data. The work needs to address: - The issues which are relevant at the institutional level, e.g. the institutional repository level. - The ‘interoperability’ of the digital library within a networked environment. How does the library interoperate with data centers, data archives, data repositories and other actors in providing information and data services which are relevant to end-users? - Metadata management at the level Of the infrastructure i.e. through registries, metadata hubs, metadata harvesting and access management. Of individual datasets and dataset collections. RDM vs. information management. Other challenges… 2. Specific to skill sets In addition working group members agreed to articulate each recommendation with one or more statements and to identify best practices. Statements provided by working group members for the recommendations that address the skills gap - Should this position be linked to a specific field or can it be generic ? - Various online trainings are available for reuse in institutional trainings (MANTRA, Data Intelligence 4 Librarians, etc.). - Integration into curricula of library schools, build up groups of practitioners (national, international). - Need for MSc level data-professionals. - Prepare a statement for the research institutions explaining the importance of data librarian posts for RDM. - Prepare guidelines for librarians. Make a list of documents prepared by the institutions dealing with RDM.