Professionalization in Cyberinfrastructure

Berente, Nicholas; Howison, James; Cutcher‐Gershenfeld, Joel; King, John Leslie; Barley, Stephen R.; Towns, John

doi:10.2139/ssrn.3138592

Cited by 6 publications

(3 citation statements)

References 3 publications

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“…A report from the NSF-sponsored Professionalization in Cyberinfrastructure workshop in 2017 [8] outlined two main issues concerning RCD personnel: RCD personnel are scarce, and cyberinfrastructure is different from traditional Information Technology (IT). The workshop highlighted the critical role that RCD professionals play in supporting next-generation scientific research.…”

Section: Related Workmentioning

confidence: 99%

Understanding Factors that Influence Research Computing and Data Careers

Chaudhry

Pazouki

Schmitz

et al. 2022

Practice and Experience in Advanced Research Computing

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Research Computing and Data (RCD) professionals play a crucial role in supporting and advancing research that involve data and/or computing, however, there is a critical shortage of RCD workforce, and organizations face challenges in recruiting and retaining RCD professional staff. It is not obvious to people outside of RCD how their skills and experience map to the RCD profession, and staff currently in RCD roles lack resources to create a professional development plan. To address these gaps, the CaRCC RCD Career Arcs working group has embarked upon an effort to gain a deeper understanding of the paths that RCD professionals follow across their careers. An important step in that effort is a recent survey the working group conducted of RCD professionals on key factors that influence decisions in the course of their careers. This survey gathered responses from over 200 respondents at institutions across the United States. This paper presents our initial findings and analyses of the data gathered. We describe how various genders, career stages, and types of RCD roles impact the ranking of these factors, and note that while there are differences across these groups, respondents were broadly consistent in their assessment of the importance of these factors. In some cases, the responses clearly distinguish RCD professionals from the broader workforce, and even other Information Technology professionals. CCS CONCEPTS• Social and professional topics → Computing occupations.

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Section: Related Workmentioning

confidence: 99%

Understanding Factors that Influence Research Computing and Data Careers

Chaudhry

Pazouki

Schmitz

et al. 2022

Practice and Experience in Advanced Research Computing

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“…Our AI Bootcamps for CI professionals have the overarching goal of increasing the confidence and effectiveness of their support of AI researchers. We leverage the CI professionalization efforts of the Campus Research Computing Consortium (CaRCC) to organize our training outcomes based on four career facings [6]: Strategy/Policy facing, Researcher facing, Software/Data facing, and Systems facing. We can identify learning outcomes for each CI facing and organize training tracks customized to specific roles.…”

Section: A Description Of Workmentioning

confidence: 99%

Lightning Talks of EduHPC 2022

Qasem

Anzt

Ayguadé

et al. 2022

2022 IEEE/ACM International Workshop on Education for High Performance Computing (EduHPC)

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The lightning talks at EduHPC provide an opportunity to share early results and insights on PDC education and training efforts. The four lightning talks at EduHPC 2022 cover a range of topics in broadening PDC education: (i) curriculum development efforts for the European Masters in HPC program, (ii) bootcamps for CI professionals who support the running of AI workloads on HPC systems, (iii) a GPU programming course following the Carpentries model and (iv) peer-review assignments to help students write efficient parallel algorithms.

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“…), with Joel Cutcher-Gershenfeld serving as facilitator. An effort was made to select people with experience across a range of roles and perspectives; we grouped these individuals using the concept of facings that emerged from a February 2017 "Professionalization in Cyberinfrastructure" workshop [1], and that was incorporated into further work by the CaRCC CI Professionalization working group [6]. In addition, the institutions represented included both large and small institutions, public and private universities, several EPSCoR states, historically black colleges and universities (HBCUs), and several organizations that provide infrastructure.…”

Section: History and Background Of The Modelmentioning

confidence: 99%

A Research Computing and Data Capabilities Model for Strategic Decision-Making

Schmitz

Mizumoto

Hicks

et al. 2020

Practice and Experience in Advanced Research Computing

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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.CCS Concepts: • General and reference → Computing standards, RFCs and guidelines; Evaluation; • Social and professional topics → System management.

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Professionalization in Cyberinfrastructure

Cited by 6 publications

References 3 publications

Understanding Factors that Influence Research Computing and Data Careers

Understanding Factors that Influence Research Computing and Data Careers

Lightning Talks of EduHPC 2022

A Research Computing and Data Capabilities Model for Strategic Decision-Making

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