RCD Nexus

Research Computing and Data (RCD) Capabilities Model

The Research Computing and Data (RCD) Capabilities Model allows institutions to assess their support for computationally- and data-intensive research, to identify potential areas for improvement, and to understand how the broader community views Research Computing and Data support. The Capabilities Model was developed by a diverse group of institutions with a range of support models, in a collaboration among Internet2, CaRCC, and EDUCAUSE with support from the National Science Foundation. This Assessment Tool is designed for use by a range of roles at each institution, from front-line support through campus leadership, and is intended to be inclusive across small and large, and public and private institutions.

Want a quick summary and intro for your team? See our 1-page overview.

New online Assessment Tool, Community Data Viewer, and Engagement Guide!

We are excited to announce that our new online Assessment Tool is now available, streamlining the submission process. This new web-based version of the assessment tool, offering a better user experience since November 2024.

In addition, a new Community Data Viewer has also been released allowing users to explore and visualize the community dataset of assessments submitted by other institutions who have used the Capabilities Model. Users can also benchmark their institutional capabilities coverage relative to the community of contributors.

And if you’re looking to understand how to begin discussing RCD Capabilities assessment at your institution, especially if you’re a smaller campus or just starting to work toward coordinated RCD capabilities, check out our Engagement Guide and Script.

We are no longer accepting submissions through the former process, and encourage you to use the new tool to submit your assessments. The new assessment tool will accept submissions any time of year, and as soon as your submission has been reviewed and accepted, you can create benchmarking visualizations using the new Data Viewer tools. 

Figure: Example bar graph showing Capabilities Coverage for the Strategy and Policy Facing, comparing R1, R2, and other academic institutions and with a benchmarking overlay.

How will my institution benefit?

The Capabilities Model can help you answer these questions: 

  • How well is my institution supporting computationally- and data-intensive research, and how can we get a comprehensive view of our support? 
  • What is my institution not thinking about or missing that the community has identified as significant? 
  • How can my institution (and my group) identify potential areas for improvement? 

Some common uses for the Capabilities Model include: 

  • To identify and understand areas of strength and weakness in an institution’s support to aid in strategic planning and prioritization.
  • To benchmark your institution’s support against peers – often when making an argument for increased funding to remain competitive on faculty recruitment and retention. (See the list of contributors).
  • To compare local institutional approaches to a common community model (i.e., a shared vocabulary), to facilitate communications and collaboration. 

Need help or have questions? 

Just getting started with research computing and data (RCD) and looking for a simpler approach? 

You’re not alone, and our Focused Tools effort is creating tools that are geared at smaller and emerging programs. The first product of that work is our Engagement Facilitation Guide for Smaller and Emerging RCD Programs. For more on the Focused Tools work, check out the committee page!

Want to get involved?

Join the working group and help shape the future enhancements of the tools, or contribute to the analysis of the community dataset! If you’re interested, write to us at: capsmodel-help@carcc.org or contact the chairs: Patrick Schmitz (Semper Cogito) and Dana Brunson (Internet2).

Supported by the National Science Foundation

This work has been supported in part by an RCN grant from the National Science Foundation (OAC-1620695, PI: Alex Feltus, “RCN: Advancing Research and Education through a national network of campus research computing infrastructures – The CaRC Consortium”), and by an NSF Cyberinfrastructure Centers of Excellence (CI CoE) pilot award (OAC-2100003, PI Dana Brunson, “Advancing Research Computing and Data: Strategic Tools, Practices, and Professional Development”).