Collaborative Research: HNDS-I: Cyberinfrastructure for Human Dynamics and Resilience Research

灾难复原力研究关注的是了解人们如何准备和处理因洪水、火灾、流行病和其他事关生存的威胁等事件而对社区造成的破坏。风险、脆弱性和可持续性的概念非常重要，因为它们对个人的生活和福祉有影响。然而，推进以科学为基础的复原力研究是困难的，因为用于衡量灾难复原力的数据来自许多不同的来源，很难合并。即使对于可用的数据，也几乎没有可用的工具来分析它们，特别是对于没有接受过广泛的量化培训的研究人员。该项目克服了这些困难，开发了一个名为人类动力学和复原力基础设施的国家网络基础设施，其中包含支持和推进人类动力学和复原力研究的大规模数据和分析工具。通过使用基础设施可视化和分析数据所获得的知识可以更好地为提高社区复原力的政策提供依据。该项目实现了四个目标。首先，它开发了四个新的数据库，其中包含来自全国各地的综合数据，包括社交媒体和手机移动数据。其次，它构建了可视化和分析工具，如地图、统计和动态建模和模拟，以促进探索性和深入研究。第三，它实施了一个培训和反馈模块，帮助研究人员、从业者和公众探索和进行分析，从而更好地理解复原力。最后，它包括三个案例研究，展示了基础设施如何能够带来关于人类流动性和弹性之间关系的新知识。该项目是由来自路易斯安那州立大学、南佛罗里达大学、德克萨斯农工大学和圣路易斯大学等四所大学的多学科调查人员合作完成的。该项目由人文网络和数据科学-基础设施和既定的激励竞争研究计划(EPSCoR)共同资助。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。

Disaster resilience research is concerned with learning how people prepare for and deal with damage to their communities because of events such as floods, fires, pandemics, and other existential threats. The concepts of risk, vulnerability and sustainability are very important because of the impact they have on individuals’ lives and well-being. However, advancing science-based resilience research is hard because the data that are used to measure disaster resilience come from many different sources and are difficult to merge. Even for available data there are few tools available to analyze them, especially for researchers who do not have extensive quantitative training. This project overcomes these difficulties by developing a national cyberinfrastructure called the Human Dynamics and Resilience infrastructure that contains large-scale data and analytic tools to support and advance human dynamics and resilience research. Knowledge gained from visualizing and analyzing the data using the infrastructure can better inform policies to increase community resilience. The project accomplishes four objectives. First, it develops four new databases containing integrated data from around the nation, including social media and cell-phone mobility data. Second, it constructs visualization and analytical tools, such as maps, statistics, and dynamic modeling and simulations to facilitate both exploratory and in-depth research. Third, it implements a training and feedback module to help engage researchers, practitioners, and the public to explore and conduct analyses that should lead to a better understanding of resilience. Finally, it includes three case studies that demonstrate how the infrastructure can lead to new knowledge about the relationship between human mobility and resilience. The project is a collaboration of multidisciplinary investigators from four universities, including Louisiana State University, University of South Florida, Texas A&M University, and Saint Louis University. This project is jointly funded by the Human Networks and Data Science -- Infrastructure and the Established Program to Stimulate Competitive Research (EPSCoR) 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.