Multivariate Interactive Web Map Design: Representing American Community Survey Uncertainty Data

Authors: Owen Mundy*, Davidson College, Seth E Spielman, University of Colorado, David Folch, Florida State University
Topics: Cartography, Population Geography, Urban and Regional Planning
Keywords: cartography, design, color, data, American Community Survey, census
Session Type: Paper
Day: 4/10/2018
Start / End Time: 10:00 AM / 11:40 AM
Room: Grand Ballroom A, Astor, 2nd Floor
Presentation File: No File Uploaded

Recognizing problems with hue- and value-based cartographic representations of multivariate census data in choropleth maps, this project aims to communicate reductions in the margin of error of survey data from the American Community Survey (ACS) through an interactive approach. The largest survey of US households and principal source for neighborhood scale information about the US population, the ACS is used to allocate billions in federal spending and is a critical input to social scientific research in the US. However, estimates from the ACS can be highly unreliable. Uncertainty of this magnitude complicates the use of social data in policy making, research, and governance. Our website presents the data from 388 metropolitan statistical areas, before and after a process called regionalization, in order to explain, demonstrate, and circulate the results and data. This presentation will discuss issues with blended color, and hue- and value-based distinctions in multivariate choropleth maps, particularly for color-blind audiences. We will share our methods, which include experimental interactive and time-based approaches, and the conclusion, which allows users to search, filter, and compare multivariate data on an open-source, web-based map using Leaflet and D3.

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