Treebar Maps: Schematic Representation of Networks at Scale

TL;DR

This paper introduces treebar maps, a novel visualization method for large-scale networks that provides clear, schematic two-dimensional representations capturing key structural features efficiently.

Contribution

The paper presents a new algorithmic framework and visual metaphor, enabling quick and comprehensible schematic visualization of massive networks at scale.

Findings

Visualizations created in a few hundred seconds

Effective at capturing network structure

Instantaneous comprehension of diverse graph structures

Abstract

Many data sets, crucial for today's applications, consist essentially of enormous networks, containing millions or even billions of elements. Having the possibility of visualizing such networks is of paramount importance. We propose an algorithmic framework and a visual metaphor, dubbed treebar map, to provide schematic representations of huge networks. Our goal is to convey the main features of the network's inner structure in a straightforward, two-dimensional, one-page drawing. This drawing effectively captures the essential quantitative information about the network's main components. Our experiments show that we are able to create such representations in a few hundreds of seconds. We demonstrate the metaphor's efficacy through visual examination of extensive graphs, highlighting how their diverse structures are instantly comprehensible via their representations.