Assessing requirements for research data management support in academic libraries: introducing a new multi-faceted capability tool

Liz Lyon, Manjula Patel, Kenji Takeda


This paper introduces the practice of assessing requirements for research data management (RDM) support in academic libraries, building on concepts of maturity, capability and readiness. An overview of existing RDM assessment methodologies, tools and instruments is presented, with institutional exemplars from the UK and the US. Drawing on consultations with the eScience community, we describe the development of the Community Capability Model Framework (CCMF), the derived capability factors and the CCM Profile tool. Finally, a Case Study for Agronomy research data is presented, showing how the CCM Profile tool can be applied to disciplinary research, to provide summaries and visualisations of data-intensive capability, which may inform planning for RDM support services in academic libraries.


Keywords: Research data management services, Capability assessment models, Data-intensive science



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