Characterizing the US Research Computing and Data (RCD) Workforce

Characterizing the US Research Computing and Data (RCD) Workforce
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美国研究计算和数据 (RCD) 劳动力特征

DOI:
10.1145/3491418.3530289
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发表时间:
2022
期刊:
PEARC '22: Practice and Experience in Advanced Research Computing
影响因子:
--
通讯作者:
Reidy, Chris
Reidy, Chris
中科院分区:
--
文献类型:
--
作者:
Maimone, Christina;Yockel, Scott;Middelkoop, Timothy;Stauffer, Ashley;Reidy, Chris

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学术界内外越来越多的计算和数据密集型研究需要计算和数据专业人员的参与和支持。然而,人们对研究计算和数据(RCD)劳动力的组成知之甚少。本文介绍了一项调查的结果(N=563)的RCD专业人员的人口和教育背景,工作经验,目前的职位,工作职责,并在RCD领域工作的意见。我们估计刚果民盟劳动力的规模,并讨论如何在刚果民盟劳动力的人口多样性和背景的分布不匹配的较大的学术和技术劳动力。这些调查结果进一步支持了实地工作人员的见解,即需要征聘更多种类的专业人员进入刚果民盟职业,更好地界定职务说明和职业发展道路,并提高对刚果民盟工作价值的机构认可。
A growing share of computationally and data-intensive research, both inside and outside of academia, requires the involvement and support of computing and data professionals. Yet little is known about the composition of the research computing and data (RCD) workforce. This paper presents the results of a survey (N=563) of RCD professionals’ demographic and educational backgrounds, work experience, current positions, job responsibilities, and views of working in the RCD field. We estimate the size of the RCD workforce and discuss how the demographic diversity and distribution of backgrounds of those in the RCD workforce fail to match that of the larger academic and technical workforces. These survey results additionally support the insights of those working in the field concerning the need to recruit a wider variety of professionals into the RCD profession, better define job descriptions and career pathways, and improve institutional recognition for the value of RCD work.
促进研究计算和数据生态系统中组织之间的合作
DOI: 10.1145/3311790.3396645
发表时间: 2020
期刊: Practice and Experience in Advanced Research Computing
影响因子: --
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DOI: --
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期刊:
影响因子: --
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