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.

Agency
National Science Foundation (NSF)
Institute
Division of Behavioral and Cognitive Sciences (BCS)
Type
Standard Grant (Standard)
Application #
2024233
Program Officer
Tyler Kendall
Project Start
Project End
Budget Start
2020-09-01
Budget End
2024-08-31
Support Year
Fiscal Year
2020
Total Cost
$269,143
Indirect Cost
Name
Bucknell University
Department
Type
DUNS #
City
Lewisburg
State
PA
Country
United States
Zip Code
17837