The State of the Art in Multilayer Network Visualization

TL;DR

This paper surveys the current state of multilayer network visualization, analyzing techniques, tools, and challenges across various domains to guide future research and development.

Contribution

It provides a comprehensive structured analysis of contemporary multilayer network visualization methods, tools, and challenges across multiple application domains.

Findings

Survey of visualization techniques for multilayer graphs

Identification of key challenges in multilayer network visualization

Suggestions for future research directions

Abstract

Modelling relationships between entities in real-world systems with a simple graph is a standard approach. However, reality is better embraced as several interdependent subsystems (or layers). Recently the concept of a multilayer network model has emerged from the field of complex systems. This model can be applied to a wide range of real-world datasets. Examples of multilayer networks can be found in the domains of life sciences, sociology, digital humanities and more. Within the domain of graph visualization there are many systems which visualize datasets having many characteristics of multilayer graphs. This report provides a state of the art and a structured analysis of contemporary multilayer network visualization, not only for researchers in visualization, but also for those who aim to visualize multilayer networks in the domain of complex systems, as well as those developing systems across application domains. We have explored the visualization literature to survey visualization techniques suitable for multilayer graph visualization, as well as tools, tasks, and analytic techniques from within application domains. This report also identifies the outstanding challenges for multilayer graph visualization and suggests future research directions for addressing them.