[Paper Review] Evaluating Cartogram Effectiveness

Sabrina Nusrat, Md. Jawaherul Alam+1 more|arXiv (Cornell University)|Apr 9, 2015

Data Visualization and Analytics41 references6 citations

TL;DR

This paper evaluates four major cartogram types—contiguous, non-contiguous, rectangular, and Dorling—through quantitative task performance (time and error), qualitative attitude and preference studies, and metrics-based evaluation. Results show that non-contiguous cartograms perform best overall, especially for area comparison and data accuracy, while Dorling and rectangular cartograms excel in schematic clarity, and contiguous cartograms are best for preserving adjacency relationships.

ABSTRACT

Cartograms are maps in which areas of geographic regions (countries, states) appear in proportion to some variable of interest (population, income). Cartograms are popular visualizations for geo-referenced data that have been used for over a century and that make it possible to gain insight into patterns and trends in the world around us. Despite the popularity of cartograms and the large number of cartogram types, there are few studies evaluating the effectiveness of cartograms in conveying information. Based on a recent task taxonomy for cartograms, we evaluate four major different types of cartograms: contiguous, non-contiguous, rectangular, and Dorling cartograms. Specifically, we evaluate the effectiveness of these cartograms by quantitative performance analysis, as well as by subjective preferences. We analyze the results of our study in the context of some prevailing assumptions in the literature of cartography and cognitive science. Finally, we make recommendations for the use of different types of cartograms for different tasks and settings.

Motivation & Objective

• To systematically evaluate the effectiveness of four major cartogram types—contiguous, non-contiguous, rectangular, and Dorling—in conveying geo-referenced data.
• To identify which cartogram type performs best across a range of geospatial tasks, such as area comparison, adjacency detection, and region identification.
• To integrate quantitative performance metrics with qualitative user preferences and metrics-based evaluations to provide a holistic assessment of cartogram usability.
• To inform design guidelines for cartograms by analyzing perceptual, cartographic, and demographic factors influencing user interpretation.
• To explore the role of interaction techniques (e.g., tooltips, highlighting) in mitigating cartogram limitations and improving task accuracy.

Proposed method

• Conducted a controlled experiment with seven standardized tasks from a recently developed cartogram task taxonomy.
• Measured quantitative performance using time to complete tasks and error rates in identifying geographic regions and comparing areas.
• Collected qualitative data through attitude surveys and subjective preference analysis to assess user perceptions and aesthetic judgments.
• Compared results from task performance and subjective evaluation with metrics-based cartogram evaluation (e.g., cartographic error, shape preservation).
• Used statistical analysis to validate performance differences across cartogram types and identify significant trends.
• Proposed a flowchart-based decision guide for selecting cartogram types based on task requirements and data characteristics.

Experimental results

Research questions

• RQ1 Which cartogram type yields the fastest and most accurate responses in area comparison tasks?
• RQ2 How do user preferences and perceived usability vary across different cartogram types?
• RQ3 To what extent do metrics-based evaluations (e.g., cartographic error) align with user performance and subjective ratings?
• RQ4 How do interaction techniques such as mouse-over labels and neighbor highlighting affect task accuracy, especially for difficult cartogram types?
• RQ5 In what scenarios is preserving adjacency or geographic shape more critical, and which cartogram type best supports these needs?

Key findings

• Non-contiguous cartograms achieved the highest overall performance, with the lowest error rates and fastest response times across most tasks, particularly in area comparison and data accuracy.
• Dorling cartograms were preferred for schematic clarity and ease of shape recognition, though they performed poorly on adjacency detection tasks.
• Contiguous cartograms were most effective for tasks requiring knowledge of regional adjacencies, as they preserved topological relationships better than other types.
• Rectangular cartograms showed strong performance in region comparison tasks and were favored for their simplicity and clean layout, especially in maps with few regions.
• Interaction techniques such as mouse-over tooltips and neighbor highlighting significantly reduced errors in adjacency and identification tasks, particularly for Dorling and rectangular cartograms.
• Subjective preferences largely aligned with quantitative performance, though some aesthetic preferences (e.g., for Dorling cartograms) did not match their task accuracy, indicating a trade-off between visual appeal and functional effectiveness.