课题基金 / 基金详情

Collaborative Research: Learning to Use Essential Tools and Resources for Data Science with a Cloud-Based Virtual Environment

Collaborative Research: Learning to Use Essential Tools and Resources for Data Science with a Cloud-Based Virtual Environment
协作研究:学习在基于云的虚拟环境中使用数据科学的基本工具和资源
批准号:
1726816
负责人:
Weijia Xu
金额:
$36.26万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-01 至 2021-08-31

项目摘要

项目成果

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中文摘要
翻译
企业、政府和科学研究人员正在产生大量复杂的数据。这些庞大的数据集的可获得性推动了对数据驱动型分析和21世纪能够使用数据分析来回答问题和解决问题的劳动力的需求。这个合作项目将开发一个基于云的虚拟平台,培训本科生如何使用数据科学必不可少的软件工具。该平台将使学生和教职员工更容易获得最先进的计算资源,包括强大的数据分析工具和并行硬件系统,即使他们所在的机构没有本地可用的高功率计算系统。该项目旨在帮助学生培养数据科学方面的关键劳动力技能。该项目还将提供专业发展机会,帮助教师在课程和研究中使用数据分析工具。该项目的目标是以虚拟科学平台的形式开发一个基于云的基础设施,并提供相关的培训模块。首先,它将利用现有的构建网络应用程序的框架,提供对合作大学的开源、高性能计算资源的广泛访问,并通过NSF极端科学和工程发现环境。这个基于云的平台将支持学生的培训和学生之间的协作。其次,该项目将制作面向本科生的数据科学课程。该课程还将适合研究生、博士后研究人员和对数据科学感兴趣的信息技术专业人员。该项目将提供一整套关于使用和配置该平台的互动文档和视频教程。教育活动将使用图形化、交互式、基于模拟和体验式学习组件,通过基于云的平台访问,教授数据科学概念和计算技能。通过该平台,学生将有机会学习如何使用强大的数据科学资源,使他们能够将数据丰富的计算机科学和工程问题转化为实际解决方案。第三,该项目将为多个机构的教师提供专业发展,帮助他们学习如何在课堂和自己的研究中使用数据科学。该项目致力于解决国家利益,使最先进的计算资源更容易为学生所用,支持他们发展关键的劳动力技能。
英文摘要
Business, government, and science researchers are producing massive amounts of complex data. The availability of these huge datasets fuels a need for both data-driven analytics and a 21st-century workforce that can use data analytics to answer questions and solve problems. This collaborative project will develop a cloud-based virtual platform to train undergraduate students how to use software tools essential to data science. The platform will make state-of-the-art computing resources, including both powerful data analysis tools and parallel hardware systems, more accessible to students and faculty, even if they are at institutions without locally available high-power computing systems. The project aims to help students develop critical workforce skills in data science. The project will also provide professional development opportunities to help faculty use data-analysis tools in their courses and research.The goal of this project is to develop a cloud-based infrastructure in the form of a virtual science platform with related training modules. First, it will leverage an existing framework for building web applications to provide broad access to open source, high performance computing resources at the collaborating universities and through the NSF Extreme Science and Engineering Discovery Environment. The cloud-based platform will support both training of students and collaboration among students. Second, the project will produce a data science curriculum targeted to undergraduate students. The curriculum will also be suitable for graduate students, post-doctoral researchers, and information technology professionals interested in data science. The project will deliver a full set of interactive documents and video tutorials on using and configuring the platform. The educational activities will use graphical, interactive, simulation-based, and experiential learning components to teach data science concepts and computing skills, accessed through the cloud-based platform. Through the platform, students will have the opportunity to learn how to use powerful data science resources, enabling their potential to transform data-rich computer science and engineering problems into practical solutions. Third, the project will deliver professional development for faculty at multiple institutions, to help them learn how to use data science in their classrooms and their own research. This project addresses national interests by making state-of-the-art computing resources more accessible to students, supporting their development of critical workforce skills.
期刊论文(6)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1109/bigdata50022.2020.9378438
发表时间: 2020-12
期刊: 2020 IEEE International Conference on Big Data (Big Data)
影响因子: --
作者: [Weijia Xu;M. Esteva;Peter Cui;E. Castillo;Kewen Wang;H. R. Hopkins;Tanya E. Clement;Aaron Choate;Ruizhu Huang]
通讯作者: Weijia Xu;M. Esteva;Peter Cui;E. Castillo;Kewen Wang;H. R. Hopkins;Tanya E. Clement;Aaron Choate;Ruizhu Huang
DOI: 10.1145/3219104.3229290
发表时间: 2018-07
期刊: Proceedings of the Practice and Experience on Advanced Research Computing
影响因子: --
作者: [Yige Wang;Ruizhu Huang;Weijia Xu]
通讯作者: Yige Wang;Ruizhu Huang;Weijia Xu
DOI: --
发表时间: 2021
期刊: EduHPC-21: Workshop on Education for High Performance Computing
影响因子: --
作者: [Xu, Weijia, Zhang, Hui]
通讯作者: Zhang, Hui
Enabling User Driven Web Applications on Remote Computing Resource
在远程计算资源上启用用户驱动的 Web 应用程序
DOI: --
发表时间: 2018
期刊: 2018 IEEE World Congress on Services
影响因子: --
作者: [Xu, Weijia, Huang, Ruizhu, Wang, Yige]
通讯作者: Wang, Yige
6
    国内基金
    海外基金
    Research on Quantum Field Theory without a Lagrangian Description
    • 批准号:
      24ZR1403900
    • 项目类别:
      省市级项目
    • 资助金额:
      --
    • 批准年份:
      2024
    • 负责人:
      SATOSHI NAWATA
    • 依托单位:
    Cell Research
    Cell Research
    Cell Research (细胞研究)