Collaborative Research: CyberTraining: Implementation: Small: Broadening Adoption of Cyberinfrastructure and Research Workforce Development for Disaster Management

协作研究：网络培训：实施：小型：扩大网络基础设施的采用和灾害管理研究队伍的发展

• 批准号: 2321070
• 负责人: Shaowen Wang
• 金额: $ 12万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2321070&HistoricalAwards=false
• 关键词: Collaborative; Research; CyberTraining; Implementation; Small

Disasters are prominent global issues which simultaneously pose threats to multiple countries or regions. Disaster management is gradually empowered by increasing geospatial big data awareness and growing computing capabilities to produce spatial vulnerability and situational understanding for supporting timely decisions. This project will establish an international CyberTraining for Disaster Management (CTDM) network in which disaster research communities can broaden their cyberinfrastructure (CI) and geospatial skills by participating in the proposed training activities. The project will establish a CI-enabled geospatial disaster science network among academic institutions, governmental agencies, hazards research centers, industry, and educational organizations to leverage the expertise of pertinent communities in developing training materials for preparing the next-generation workforce. A novel training curriculum is developed to consist of various training modalities such as summer schools, workshop sessions, and online webinars, which utilize CI and scalable geospatial analytics for effective disaster management practice. We aim to train over 2000 students, researchers, and educators through our diverse collaboration networks. The project will broaden access to CI for disaster research communities and help enhance workforce development among diverse disciplines such as disaster science, geosciences, transportation, engineering, social, behavioral, and economic sciences. A variety of disaster data, training materials, and CI resources will be provided to underrepresented communities through partnerships with Hispanic Serving Institutions (e.g., Texas A&M University) and Historically Black Colleges & Universities (e.g., Morgan State University). The project will help disaster research communities broaden their CI-enabled disaster management and computational skills, thus improving decision-making capabilities for enhancing community resilience. CTDM is designed to greatly improve the well-being of socially vulnerable communities significantly impacted by climate change and related disasters.The project will introduce advanced CI and geospatial analytics to disaster research communities by developing a CI-enabled disaster management curriculum. A key approach is to apply CI and geospatial analytics in disaster management by introducing four interconnected training modules from basic to advanced learning levels: CI-Enabled Computing Module, Disaster Data Module, Geospatial Analytics Module, and Disaster Problem-Solving Module. The Disaster Data Module provides best practices of the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles and cutting-edge geospatial data analysis and visualization techniques. The CI-Enabled Computing Module Introduces fundamental concepts and skills of CI and high-performance computing to lower the barriers to taking advantage of CI in disaster management research. Through the Geospatial Analytics Module, learners will be equipped with advanced geospatial data analysis and visualization techniques to better understand disaster patterns across various spatiotemporal scales. Finally, the Disaster Problem-Solving Module serves as an integration framework to ensure disaster management concepts and practices will be well connected with the other three modules for a holistic understanding of disaster management challenges addressed by advanced CI. This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Directorate for Social, Behavioral, and Economic Sciences.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.

灾害是一个突出的全球性问题，同时对多个国家或地区构成威胁。通过提高对地理空间大数据的认识和提高计算能力，逐步增强灾害管理的能力，以了解空间脆弱性和情况，支持及时决策。该项目将建立一个国际灾害管理网络培训（CTDM）网络，灾害研究界可以通过参加拟议的培训活动来扩大其网络基础设施和地理空间技能。该项目将在学术机构、政府机构、灾害研究中心、工业和教育组织之间建立一个基于CI的地理空间灾害科学网络，以利用相关社区的专业知识开发培训材料，为下一代劳动力做好准备。开发了一种新的培训课程，包括各种培训模式，如暑期学校，研讨会和在线网络研讨会，利用CI和可扩展的地理空间分析进行有效的灾害管理实践。我们的目标是通过我们多样化的合作网络培训2000多名学生，研究人员和教育工作者。该项目将扩大灾害研究社区对CI的访问，并帮助加强灾害科学，地球科学，交通，工程，社会，行为和经济科学等不同学科的劳动力发展。将通过与西班牙裔服务机构（例如，德克萨斯A M大学）和历史上的黑人学院大学（例如，摩根州立大学）。该项目将帮助灾害研究界扩大其CI支持的灾害管理和计算技能，从而提高决策能力，增强社区的复原力。CTDM旨在极大地改善受气候变化和相关灾害严重影响的社会弱势群体的福祉。该项目将通过开发基于CI的灾害管理课程，向灾害研究界介绍先进的CI和地理空间分析。一个关键的方法是将CI和地理空间分析应用于灾害管理，从基础到高级学习水平引入四个相互关联的培训模块：CI启用计算模块，灾害数据模块，地理空间分析模块和灾害问题解决模块。灾害数据模块提供FAIR（可查找性、可访问性、互操作性和可重用性）原则的最佳实践以及尖端的地理空间数据分析和可视化技术。CI使能计算模块介绍CI和高性能计算的基本概念和技能，以降低在灾害管理研究中利用CI的障碍。通过地理空间分析模块，学习者将配备先进的地理空间数据分析和可视化技术，以更好地了解各种时空尺度的灾害模式。最后，灾害问题解决模块作为一个集成框架，以确保灾害管理的概念和实践将很好地与其他三个模块的灾害管理挑战的全面理解解决了先进的CI。该奖项由高级网络基础设施办公室颁发，并得到社会、行为和经济科学理事会的共同支持。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。