The widespread application and success of computational and data intensive research approaches in every discipline represented on our campuses has resulted in a rapid proliferation of organizations, technologies, and professions affiliated in different ways with the support and advancement of activities related to research computing and data (RCD). While most agree that this growth is helping to advance numerous disciplines, the proliferation of organizations seeking to support, promote, and advance RCD has led to some challenges. Specifically, a lack of understanding and consensus concerning which organizations should be considered a part of RCD support hampers our ability to encourage collaborations among its complementary constituents, leads to unneeded and redundant activities, and makes it difficult to identify strategic priorities and address gaps where specific needs are not being met to advance various disciplinary activities. In this paper we introduce the ecosystem metaphor to help characterize the rapidly changing relationships among the growing set of organizations that in some way support and enable activities related to RCD. The ecosystem concept lends itself well to describing the many entities related to RCD because it emphasizes the larger system over its individual component parts and highlights their interdependence, while explicitly expecting their change over time. Our work to characterize the current RCD ecosystem, while imperfect, will serve as a foundation and framework for the development of a more complete view of the ever-changing RCD ecosystem. A more complete view of the RCD ecosystem will in turn help to advance the broad goals of its members by helping to foster and accelerate new and meaningful collaborations among them.

Research Computing and Data is changing at an accelerating rate, while the range of fields and disciplines depending on the cyberinfrastructure is expanding and becoming increasingly diverse. This poses significant challenges to academic institutions as they try to effectively assess and plan for the necessary support infrastructure to keep pace with the needs of researchers. We present a Research Computing and Data Capabilities Model that identifies the range of relevant approaches to fully support and enable research computing and data on campuses. This model allows institutions to assess their current capabilities, and provides structured input into strategic decision making, using a shared community vocabulary. We describe the background of the Model, key concepts and features of the Model and an associated assessment tool, initial experience in the community and lessons learned, and a roadmap for further development.