GAN'SDA Wrap: Geographic And Network Structured Data on surfaces that Wrap around

TL;DR

This study evaluates interactive spherical map projections and compares spherical, toroidal, and standard network layouts, demonstrating that interactive projections improve spatial estimation accuracy and that spherical and toroidal layouts enhance network understanding.

Contribution

It introduces a comprehensive evaluation of interactive spherical map projections and compares spherical, toroidal, and standard network layouts for visualization tasks.

Findings

Interactive projections improve area, direction, and distance estimation.

Spherical and toroidal layouts outperform standard layouts in network cluster tasks.

Participants showed higher accuracy with spherical and toroidal layouts.

Abstract

There are many methods for projecting spherical maps onto the plane. Interactive versions of these projections allow the user to centre the region of interest. However, the effects of such interaction have not previously been evaluated. In a study with 120 participants we find interaction provides significantly more accurate area, direction and distance estimation in such projections. The surface of 3D sphere and torus topologies provides a continuous surface for uninterrupted network layout. But how best to project spherical network layouts to 2D screens has not been studied, nor have such spherical network projections been compared to torus projections. Using the most successful interactive sphere projections from our first study, we compare spherical, standard and toroidal layouts of networks for cluster and path following tasks with 96 participants, finding benefits for both spherical and toroidal layouts over standard network layouts in terms of accuracy for cluster understanding tasks.