Choriented Maps: Visualizing SDG Data on Mobile Devices

TL;DR

This paper introduces choriented maps and choriented mobile visualizations that combine colour and orientation to improve the clarity and effectiveness of geographic data visualization on mobile devices, especially with many classes.

Contribution

It proposes two novel map visualization types that enhance data differentiation and are optimized for mobile devices, supported by a perceptual study comparing them to traditional maps.

Findings

Choriented maps perform comparably or better than traditional maps in effectiveness.

Choriented mobile visualizations are effective for mobile geographic data exploration.

These visualizations improve symbol selectivity and user performance in some scenarios.

Abstract

Choropleth maps and graduated symbol maps are often used to visualize quantitative geographic data. However, as the number of classes grows, distinguishing between adjacent classes increasingly becomes challenging. To mitigate this issue, this work introduces two new visualization types: choriented maps (maps that use colour and orientation as variables to encode geographic information) and choriented mobile (an optimization of choriented maps for mobile devices). The maps were evaluated in a graphical perception study featuring the comparison of SDG (Sustainable Development Goal) data for several European countries. Choriented maps and choriented mobile visualizations resulted in comparable, sometimes better effectiveness and confidence scores than choropleth and graduated symbol maps. Choriented maps and choriented mobile visualizations also performed well regarding efficiency overall and performed worse only than graduated symbol maps. These results suggest that the use of colour and orientation as visual variables in combination can improve the selectivity of map symbols and user performance during the exploration of geographic data in some scenarios.