Exploropleth: A Tour through the Data Binning Zoo for Choropleth Maps
CRIDC · 2023
★ Best Poster Award (EVPR)
Abstract
When creating choropleth maps, mapmakers often bin (i.e., group, classify) quantitative data values into groups to help show that certain areas fall within a similar range of values. For instance, a mapmaker may divide counties into groups of high, middle, and low life expectancy (measured in years). It is well known that different binning methods (e.g., natural breaks, quantile) yield different groupings, meaning the same data can be presented differently depending on how it is divided into bins. To help guide a wide variety of users, we present an open source, web-based, geospatial visualization tool, Exploropleth, that lets users interact with a catalog of established data binning methods, and subsequently compare, customize, and export custom maps. This tool advances the state of the art by providing multiple binning methods in one view and supporting administrative unit reclassification on-the-fly.
Citation
@misc{narechania2023exploroplethcridc,
author = {Narechania, Arpit and Endert, Alex and Andris, Clio},
title = {{Exploropleth: A Tour through the Data Binning Zoo for Choropleth Maps}},
year = {2023},
month = feb,
howpublished = {Poster at the Career, Research, and Innovation Development Conference (CRIDC), Georgia Tech},
note = {Best Poster Award, Executive Vice President for Research}
}