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Assessing the Landscape of Research Computing and Data Support: The 2020 RCD Capabilities Model Community Dataset

Published: 17 July 2021 Publication History

Abstract

We describe the first Research Computing and Data Capabilities Model Community Dataset, aggregating the assessments of 41 Higher Education Institutions. These assessments were completed using the 1.0 version of the Research Computing and Data Capabilities Model (RCD CM), over a period of several months in the Spring and Summer of 2020. The RCD CM allows organizations to self-evaluate across a range of RCD services and capabilities for supporting research, leveraging a shared vocabulary to describe RCD support. The Model supports a range of stakeholders and provides structured input to guide strategic planning and enable benchmarking relative to peer institutions. This Community Dataset provides insight into the current state of support for RCD across the community and in a number of key sub-communities. The dataset shows stark differences between Public and Private institutions, between institutions with a larger and smaller share of national funding, etc. In many cases, the patterns in the data confirm common perceptions about support across the community, but the dataset provides a quantitative baseline for understanding current RCD support, as well as granular insights to groups of institutions that are seeking to collaborate on shared solutions and strategies to advance RCD support. Over time, longitudinal data will provide additional insight into trends, and a means of evaluating the impact of programs designed to increase RCD support.

References

[1]
Campus Research Computing Consortium. [n.d.]. . http://carcc.org
[2]
EDUCAUSE. [n.d.]. . https://www.educause.edu/
[3]
Indiana University Center for Postsecondary Research. [n.d.]. The Carnegie Classification of Institutions of Higher Education, 2018 edition. https://carnegieclassifications.iu.edu/
[4]
CaRCC RCD Capabilities Model Working Group. 2020. Capabilities Model Introduction and Guide to Use. Retrieved May 24, 2021 from https://docs.google.com/document/d/15xiDXMta7AlEvE6IpW4mvadAiW2PPshmBi73AVHTm9g
[5]
Internet2. [n.d.]. . https://internet2.edu/community/research-engagement/
[6]
Patrick Schmitz. 2020. 2020 RCD CM Community Data report. https://doi.org/10.5281/zenodo.4344057
[7]
Patrick Schmitz, Claire Mizumoto, John Hicks, Dana Brunson, Gail Krovitz, James Bottum, Joel Cutcher-Gershenfeld, Karen Wetzel, and Thomas Cheatham. 2020. A Research Computing and Data Capabilities Model for Strategic Decision-Making. In Practice and Experience in Advanced Research Computing (Portland, OR, USA) (PEARC ’20). Association for Computing Machinery, New York, NY, USA, 77–84. https://doi.org/10.1145/3311790.3396643

Cited By

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  • (2024)Kickstarting Research Support at Under-Resourced Institutions: A Starter Guide to Advance Your Self-Assessment of Research Computing and Data CapabilitiesPractice and Experience in Advanced Research Computing 2024: Human Powered Computing10.1145/3626203.3670572(1-4)Online publication date: 17-Jul-2024
  • (2021)Advancing the Workforce That Supports Computationally and Data Intensive ResearchComputing in Science & Engineering10.1109/MCSE.2021.309842123:5(19-27)Online publication date: 1-Sep-2021

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Published In

cover image ACM Conferences
PEARC '21: Practice and Experience in Advanced Research Computing 2021: Evolution Across All Dimensions
July 2021
310 pages
ISBN:9781450382922
DOI:10.1145/3437359
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

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Publication History

Published: 17 July 2021

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Author Tags

  1. Assessment
  2. Capabilities Model
  3. Cyberinfrastructure
  4. Research Computing and Data
  5. Research IT
  6. Strategic Planning

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  • Research-article
  • Research
  • Refereed limited

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PEARC '21
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Overall Acceptance Rate 133 of 202 submissions, 66%

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Cited By

View all
  • (2024)Kickstarting Research Support at Under-Resourced Institutions: A Starter Guide to Advance Your Self-Assessment of Research Computing and Data CapabilitiesPractice and Experience in Advanced Research Computing 2024: Human Powered Computing10.1145/3626203.3670572(1-4)Online publication date: 17-Jul-2024
  • (2021)Advancing the Workforce That Supports Computationally and Data Intensive ResearchComputing in Science & Engineering10.1109/MCSE.2021.309842123:5(19-27)Online publication date: 1-Sep-2021

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