Working Paper 2018-03

Visualizing demographic evolution using geographically inconsistent census data

Fabio Dias, University of Toronto

Daniel Silver, University of Toronto

UT Sociology Working Paper No. 2018-03

March 2018

Keywords: Human-centered computing; Visualization; Visualization application domains; Visual analytics; Mathematics of computing; Probability and statistics; Statistical paradigms; Exploratory data analysis

Full Article


Abstract

Census measurements provide reliable demographic data going back centuries. However, their analysis is often hampered by the lack of geographical consistency across time. We propose a visual analytics system that enables the exploration of geographically inconsistent data. Our method also includes incremental developments in the
representation, clustering, and visual exploration of census data, allowing an easier understanding of the demographic groups present in a city and their evolution over time. We present the feedback of experts in urban sciences and sociology, along with illustrative scenarios in the USA and Canada.

This research was supported by a University of Toronto Connaught Global Challenge grant and is part of the Urban Genome Project.