Collaborative Research:HNDS-I:Data Resources and Analytic Tools to Understand Population Scale Human Mobility for Applications in Social, Behavioral, and Economic Sciences Research

合作研究：HNDS-I：了解人口规模人类流动性的数据资源和分析工具，用于社会、行为和经济科学研究的应用

• 批准号: 2024335
• 负责人: Michael Kane
• 金额: $ 37.92万
• 依托单位: Yale University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2024335&HistoricalAwards=false
• 关键词: Collaborative; Research; HNDS; Data; Resources

This project develops privacy-centric methods along with data and software resources for understanding population-scale human mobility and its relationship with social, behavioral, and economic (SBE) dynamics through the creation of a large-scale database and tools. Human mobility, which includes knowing where people are, have been, and go to, is an essential feature for understanding SBE issues emerging from transitions through physical space. By better understanding the movement behavior of people, researchers can explore important areas of inquiry including economic patterns, segregation, inter-group dynamics, as well as a range of other SBE areas of interest. The project provides new opportunities for advancing such research. It will also provide educational and research opportunities for graduate and undergraduate students. This project develops community-level mobility models based on the aggregate movement of groups of cell devices through cell tower coverage areas of a national network. The project creates a privacy-centric alternative to mapping human spatial mobility that does not rely on device-level geolocation data. Specifically, the project will provide (1) a data repository containing human mobility network captured over various temporal intervals; (2) open-source software tools and user-friendly web applications for retrieving, processing, visualizing, and preparing these data for analyses in standard software packages; (3) interactive tutorials and instructional materials suitable for self-guided learning to familiarize users with the use of provided data, tools, and software packages; and (4) case use examples and illustrative studies to further our understanding of the relationship between the social world and human movement. Using the tools this project provides, researchers from a wide range of disciplines can answer important questions broadly concerned with the projection of social reality onto dynamic physical space.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.

该项目通过创建大型数据库和工具来开发以隐私为中心的方法以及数据和软件资源，以了解人口规模的人类流动性及其与社会，行为和经济（SBE）动态的关系。人类流动性包括了解人们的去向，是去去的，是了解从过渡到物理空间出现的SBE问题的重要特征。通过更好地理解人们的运动行为，研究人员可以探索重要的探究领域，包括经济模式，种族隔离，小组间动态以及许多其他感兴趣领域。该项目为进行此类研究提供了新的机会。它还将为研究生和本科生提供教育和研究机会。该项目基于基于细胞设备组在国家网络的覆盖范围区域的总体运动开发社区级别的移动模型。该项目创建了以隐私为中心的替代品来映射人类空间移动性，该替代不依赖设备级的地理位置数据。具体而言，该项目将提供（1）包含各个时间间隔内捕获的人类移动网络的数据存储库； （2）开源软件工具和用户友好的Web应用程序，用于检索，处理，可视化和准备这些数据以在标准软件包中进行分析； （3）互动教程和教学材料，适合自助学习，以使用户使用提供的数据，工具和软件包； （4）案例使用例子和说明性研究，以进一步了解社会世界与人类运动之间的关系。使用该项目提供的工具，来自广泛学科的研究人员可以回答与社会现实在动态物理空间上的预测有关的重要问题。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智力优点和更广泛的影响来通过评估来支持的。