Cyberinfrastructure deployments on public research clouds enable accessible Environmental Data Science education

Cyberinfrastructure deployments on public research clouds enable accessible Environmental Data Science education
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公共研究云上的网络基础设施部署可实现环境数据科学教育

DOI:
10.1145/3569951.3597606
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发表时间:
2023
期刊:
ACM
影响因子:
--
通讯作者:
Swetnam, Tyson L
Swetnam, Tyson L
中科院分区:
--
文献类型:
--
作者:
McIntosh, Tyler L;Verleye, Erick;Balch, Jennifer K;Cattau, Megan E;Ilangakoon, Nayani T;Korinek, Nathan;Nagy, R. Chelsea;Sanovia, James;Skidmore, Edwin;Swetnam, Tyson L

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现代科学依赖于计算机,但并非所有科学家都能获得他们所需的计算规模。数字鸿沟将使用大型网络基础设施加速科学发展的科学家与那些没有使用大型网络基础设施或无法获得计算资源或学习机会以发展所需技能的科学家分开。数字鸿沟的排斥性质威胁着公平和创新的未来,因为它将人们排除在科学进程之外,同时过度放大了拥有资源的少数群体的声音。然而,也有潜在的解决方案:在开放科学革命期间开发的公共研究网络基础设施和资源的最新进展正在提供有助于弥合这一鸿沟的工具。这些工具可以使访问快速和强大的计算与适度的互联网连接和个人电脑。在这里,我们为缩小数字鸿沟贡献了另一种资源:在公共云基础设施上运行的可扩展虚拟机。我们描述了工具,基础设施和方法,这些工具,基础设施和方法使2023年2月的协作数据合成工作组成功部署了可复制和可扩展的网络基础设施架构。该平台使45名具有不同数据和计算技能的科学家能够在为期4天的研讨会上利用40,000小时的计算时间。我们的方法提供了一个开放的框架,可以复制任何数据和计算密集型学科的教育和协作数据合成经验。
Modern science depends on computers, but not all scientists have access to the scale of computation they need. A digital divide separates scientists who accelerate their science using large cyberinfrastructure from those who do not, or who do not have access to the compute resources or learning opportunities to develop the skills needed. The exclusionary nature of the digital divide threatens equity and the future of innovation by leaving people out of the scientific process while over-amplifying the voices of a small group who have resources. However, there are potential solutions: recent advancements in public research cyberinfrastructure and resources developed during the open science revolution are providing tools that can help bridge this divide. These tools can enable access to fast and powerful computation with modest internet connections and personal computers. Here we contribute another resource for narrowing the digital divide: scalable virtual machines running on public cloud infrastructure. We describe the tools, infrastructure, and methods that enabled successful deployment of a reproducible and scalable cyberinfrastructure architecture for a collaborative data synthesis working group in February 2023. This platform enabled  45 scientists with varying data and compute skills to leverage  40,000 hours of compute time over a 4-day workshop. Our approach provides an open framework that can be replicated for educational and collaborative data synthesis experiences in any data- and compute-intensive discipline.
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