Exploropleth: exploratory analysis of data binning methods in choropleth maps

TL;DR

The paper tackles the challenge of bin selection in choropleth maps by introducing Exploropleth, an open-source web-based tool that enables side-by-side exploration of sixteen binning methods, on-the-fly reclassification, and export of maps and artifacts. It provides a multi-view interface (Browse, Compare, Combine, Create) and supports data import, manual adjustments, and Resiliency-based analyses, evaluated through expert interviews with sixteen GIS practitioners. Findings indicate the tool facilitates education, enhances exploratory analysis, and has potential to integrate into existing workflows, while also highlighting risks of misuse and the need for open standards and extensibility. The work contributes a practical, extensible platform that can improve mapmaker decision-making and foster better understanding of how binning choices shape spatial patterns and reader takeaways.

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 a new, 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. We interviewed 16 cartographers and geographic information systems (GIS) experts from 13 government organizations, non-government organizations (NGOs), and federal agencies who identified opportunities to integrate Exploropleth into their existing mapmaking workflow, and found that the tool has potential to educate students as well as mapmakers with varying levels of experience. Exploropleth is open-source and publicly available at https://exploropleth.github.io.

Figures (6)

• Figure 1: Browse View showing a catalog of the same dataset and attribute across different data binning strategies. Users can a) configure the dataset, b) select binning methods and categories to explore, c) chose a color scheme, d) visualize the resulting binning outputs, and e) inspect details by interacting with a specific output.
• Figure 2: Detail View showing a choropleth with descriptions of the binning method used and resultant bin breaks and sizes.
• Figure 3: Export View offers affordances to help users export the map in vector as well as raster formats, copy the resultant bin breaks, bin sizes, corresponding source code and the visualization specification.
• Figure 4: Compare View shows the underlying data distribution (as a dot plot) and small multiples of established and custom binning method outputs (as bar charts), the latter facilitating a visual comparison based on the resultant bin counts (black ticks), intervals (bar length), number of items in each bin (bar height).
• Figure 5: Combine View lets users analyze a) a combination of one or more binning methods by visualizing b) the Most Consistent Bin, c) the Frequency of the Most Consistent Bin, and d) both together for each U.S. county in separate choropleths. The new, Resiliency binning method then utilizes this information to g) determine "resilient" bins (counts, intervals) that are also visualized in a choropleth. Hovering any county on the map shows a tooltip with relevant information about the county, as shown in e) and f).