Abstract

The Covid-19 pandemic disrupted the world as businesses and schools shifted to work-from-home (WFH), and comprehensive maps have helped visualize how those policies changed over time and in different places. We recently developed algorithms that infer the onset of WFH based on changes in observed Internet usage. Measurements of WFH are important to evaluate how effectively policies are implemented and followed, or to confirm policies in countries with less transparent journalism. This paper describes a web-based visualization system for measurements of Covid-19-induced WFH. We build on a web-based world map, showing a geographic grid of observations about WFH. We extend typical map interaction (zoom and pan, plus animation over time) with two new forms of pop-up information that allow users to drill-down to investigate our underlying data. We use sparklines to show changes over the …

Date

2021

Authors

Erica Stutz, Yuri Pradkin, Xiao Song, John Heidemann

Conference

2021 IEEE International Conference on Big Data (Big Data)

Pages

5633-5638

Publisher

IEEE