The State of the Art in Multilayer Network Visualization
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 12 Feb 2019.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 1.
3 papers.
- 2021Visualizing Graph Neural Networks with CorGIE: Corresponding a Graph to Its Embeddingcited by 8
- 2023Visual Analytics of Multivariate Networks with Representation Learning and Composite Variable Constructioncited by 3
- 2024Prismatic: Interactive Multi-View Cluster Analysis of Concept Stockscited by 0
- 2024Prismatic: Interactive Multi-View Cluster Analysis of Concept Stocks14 Feb 2024
- 2023Visual Analytics of Multivariate Networks with Representation Learning and Composite Variable Construction16 Mar 2023
- 2021Visualizing Graph Neural Networks with CorGIE: Corresponding a Graph to Its Embedding24 Jun 2021