CyberTraining: Pilot: Cyberinfrastructure Training in Computer Science and Geoscience

网络培训：试点：计算机科学和地球科学的网络基础设施培训

• 批准号: 2118102
• 负责人: Bing Wang
• 金额: $ 29.94万
• 依托单位: University of Connecticut
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2118102&HistoricalAwards=false
• 关键词: CyberTraining; Pilot; Cyberinfrastructure; Training; Computer

Computation, data, and workforce development are critical components of cyberinfrastructure (CI). This project will help create future CI professionals from the Computer Science and Engineering (CSE) and Geography Departments who can use, develop, deploy, and maintain advanced CI. CSE students have little experience with spatio-temporal data, while Geography students have training in spatio-temporal data but are unfamiliar with advanced computing techniques and data analytics techniques. To fill these gaps in curricula, this project will develop a set of training materials covering the full workflow of data acquisition, transfer, synthesis, computation, and visualization of CI, with a focus on handling large-scale spatio-temporal data. To encompass the interdisciplinary nature of CI, this project will develop training materials by faculty with complementary expertise in both CSE and Geography, targeting undergraduate and graduate students, postdocs and researchers with these substantive interests. The training materials will be at three levels that are in increasing depth. The first level is a set of basic training modules on the main components and their interactions in a CI system. The second level is a set of open-ended course projects that uses CI to solve challenging research problems, while the third level is an intensive competition-based workshop that will provide the students with the experience of solving real-world problems using CI through interdisciplinary collaboration. The context of the training materials will be in urban computing, an interdisciplinary field that relies heavily on spatio-temporal data and has profound societal impacts. This project will provide students with improved understanding of CI systems, contribute to new knowledge and discoveries using CI, and expand the CI community of interdisciplinary collaborators. Training materials be made publicly available and will be broadly disseminated through various outreach programs.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

计算、数据和劳动力发展是网络基础设施(CI)的关键组件。该项目将帮助培养来自计算机科学与工程(CSE)和地理系的未来CI专业人员，他们可以使用、开发、部署和维护先进的CI。CSE的学生几乎没有时空数据的经验，而地理专业的学生接受过时空数据的培训，但不熟悉先进的计算技术和数据分析技术。为了填补课程中的这些空白，该项目将编写一套培训材料，涵盖传播与信息的数据获取、传输、综合、计算和可视化的整个工作流程，重点是处理大规模时空数据。为了涵盖CI的跨学科性质，该项目将由在CSE和地理学方面具有互补专业知识的教师开发培训材料，目标是具有这些实质性兴趣的本科生和研究生、博士后和研究人员。培训材料将分为三个层次，内容越来越深入。第一级是关于CI系统中主要组件及其相互作用的一套基本培训模块。第二级是一套开放式课程项目，使用CI来解决具有挑战性的研究问题，而第三级是以竞赛为基础的密集研讨会，将为学生提供通过跨学科协作使用CI解决现实世界问题的经验。培训材料的背景将是城市计算，这是一个严重依赖时空数据并具有深远社会影响的跨学科领域。该项目将使学生更好地了解CI系统，利用CI促进新知识和新发现，并扩大CI跨学科合作者社区。培训材料将公开提供，并将通过各种外展计划广泛传播。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Urban Green Space Prioritization to Mitigate Air Pollution and the Urban Heat Island Effect in Kathmandu Metropolitan City, Nepal

尼泊尔加德满都市优先考虑城市绿地以减轻空气污染和城市热岛效应

• DOI: 10.3390/land11112074
• 发表时间: 2022
• 期刊: Land
• 影响因子: 3.9
• 作者: Bhandari, Sabina;Zhang, Chuanrong
• 通讯作者: Zhang, Chuanrong

Towards Dynamic Crowd Mobility Learning and Meta Model Updates for A Smart Connected Campus

实现智能互联校园的动态人群流动学习和元模型更新

• 发表时间: 2022
• 期刊: International Conference on Embedded Wireless Systems and Networks EWSN
• 作者: Yang, X.;He, S.;Tabatabaie, M.;Wang, B.
• 通讯作者: Wang, B.