Across science, engineering, social sciences, and the humanities, every university depends upon research computing and data (RCD) professionals and infrastructure. The rapid evolution and diversification of RCD infrastructure, services, and support poses significant challenges to academic institutions as they try to effectively assess and plan for the growing needs of researchers. Many institutions would also like to assess their capabilities in comparison to peers. The lack of a shared vocabulary to describe the various aspects of RCD support hinders coordinated efforts to advance support of and for researchers. These challenges are especially acute for smaller and emerging RCD support organizations, which often lack experience supporting RCD and have limited resources to develop an analysis framework for strategic planning. To address these gaps, a collaborative team developed a Research Computing and Data Capabilities Model that allows an organization to self-evaluate across a range of RCD services. The Model provides structured input to guide strategic planning, leveraging a defined and shared community vocabulary and enabling benchmarking relative to peer institutions. The 1.0 version became publicly available in January 2020, and has been downloaded by over 120 institutions of varying types and representing 44 states. Of these, 41 contributed assessments to the 2020 community data set, providing an initial baseline across the community, and many insights into the state of RCD support. We will describe the model, how it was developed, and what we are learning from the first annual community data set.
https://carcc.org/rcdcm/
