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）的关键组成部分。该项目将有助于从计算机科学与工程（CSE）和地理部门创建未来的CI专业人员，他们可以使用，开发，部署和维护高级CI。 CSE学生在时空数据方面几乎没有经验，而地理学生接受了时空数据的培训，但不熟悉高级计算技术和数据分析技术。为了填补课程中的这些空白，该项目将开发一套培训材料，涵盖CI的数据采集，传输，合成，计算和可视化的完整工作流程，重点是处理大规模时空数据。为了涵盖CI的跨学科性质，该项目将通过具有互补专业知识的教职员工开发培训材料，针对本科生和研究生，博士后和研究人员，以及具有这些实质性利益的研究人员。培训材料将达到深度越来越高的三个级别。第一级是主要组件上的一组基本训练模块及其在CI系统中的相互作用。第二层是一组开放式课程项目，该项目使用CI来解决具有挑战性的研究问题，而第三级是一个基于竞争的强化研讨会，它将通过跨学科的协作为学生提供解决现实世界中问题的经验。培训材料的背景将在城市计算中，这是一个跨学科领域，在很大程度上依赖于时空数据并具有深远的社会影响。该项目将为学生提供对CI系统的改进，使用CI有助于新知识和发现，并扩展跨学科合作者的CI社区。培训材料可公开可用，并将通过各种外展计划大致传播。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响评估标准来评估的。

项目成果

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.

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

Land Use and Land Cover Mapping in the Era of Big Data

• DOI: 10.3390/land11101692
• 发表时间: 2022-10-01
• 期刊: LAND
• 影响因子: 3.9
• 作者: Zhang, Chuanrong;Li, Xinba
• 通讯作者: Li, Xinba