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Title: Visualizing Demographic Evolution using Geographically Inconsistent Census Data

Citation Type: Working Paper

Publication Year: 2018

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Abstract: Selection: All regions with high education level in 2010 Maj. white pop. Maj. black pop. High level of ed. Details Identified clusters IQR Figure 1: Higher increase in the education level (purple cluster) in Chicago between 1970 and 2010. While the whole city follows this trend, the change was far more pronounced in these regions. The relevant clusters defined by Black (green) and White (orange) majority of population are also visible. 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.

Url: http://sociology.utoronto.ca/wp-content/uploads/2018/04/Working-Paper-2018-03.pdf

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Authors: Dias, Fabio; Silver, Daniel

Series Title: UT Sociology Working Paper

Publication Number: 2018-03

Institution: University of Toronto

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Data Collections: IPUMS NHGIS

Topics: Methodology and Data Collection

Countries: Canada