A human-centered approach to movement data science

Keywords: human-centered data science, movement analysis, tracking data, mobility
Session Type: Virtual Paper Abstract
Day: Tuesday
Session Start / End Time: 3/1/2022 11:20 AM (Eastern Time (US & Canada)) - 3/1/2022 12:40 PM (Eastern Time (US & Canada))
Room: Virtual 21

Abstract

Movement patterns are the results of complex behaviors and processes which drive individuals’ activities in social and ecological systems. These patterns shape urban and natural ecosystem dynamics, structure human and wildlife social networks, and are instrumental to understanding human and wildlife’s behavioral responses to a changing environment. Ubiquitous tracking and the increasing access to movement data in both trajectory forms and aggregate indices have generated a tremendous interest in using data-driven approaches to model and understand behavioral responses to disruptive events such as the COVID-19 pandemic and to develop mitigation strategies. In this presentation, I argue for a human-centered approach to movement data science to analyze and map human responses to environmental disruptions.