The State of the Art in Visualizing Dynamic Graphs - STAR State of The Art Report

Oct 26, 2026

Dynamic graph visualization addresses how to present evolving relationships between entities in diagrams that remain readable, scalable, and effective. This survey consolidates a growing body of approaches, deriving a hierarchical taxonomy through systematic categorization and tagging of publications. It distinguishes dynamic representations by time: animated diagrams versus timeline-based static charts. Evaluations of animation emphasize dynamic stability and mental-map preservation, while other work compares animated diagrams with timeline approaches. The report concludes by outlining future research challenges.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages21

Reading Time53 min

AccessFree to download

Abstract

Categories and Subject Descriptors

1. Introduction

Dynamic Graph Visualization Survey Overview

Taxonomy Construction and Classifications

Evaluations and Applications

Eurographics Conference on Visualization (EuroVis) (2014) STAR – State of TheArt Report R. Borgo, R. Maciejewski, and I. Viola (Editors) The State ofthe Art in Visualizing Dynamic Graphs Fabian Beck1 , Michael Burch 1 , Stephan Diehl2 , and Daniel Weiskopf1 1VISUS, University of Stuttgart, Germany 2University of Trier, Germany | Dynamic Graph Visualization Techniques | | | | | | | | | | | hybrid | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | |
animation | | | | | timeline | | | | | | | | | | | | | + node-link | | | | + | | | | | | | | | | | | hybrid | matrix | | | |
?
online |
offline |
transition |
compound |
other | juxtaposed | superimposed | integrated | | intra-cell | layered | | hybrid: combinations of direct subcategories exist \# published techniques 1-10 11-20 > 20 Figure 1: Illustrated hierarchical taxonomy of dynamic graph visualization techniques; the number of published techniques per taxonomic category is encoded in the brightness of the background (for details see Table 4). Abstract Dynamic graph visualization focuses on the challenge of representing the evolution of relationships between en tities in readable, scalable, and effective diagrams. This work surveys the growing number of approaches in this discipline. We derive a hierarchical taxonomy of techniques by systematically categorizing and tagging publica tions. While static graph visualizations are often divided into node-link and matrix representations, we identify the representation of time as the major distinguishing feature for dynamic graph visualizations: either graphs are represented as animated diagrams or as static charts based on a timeline. Evaluations of animated approaches focus on dynamic stability for preserving the viewer's mental map or, in general, compare animated diagrams to timeline-based ones. Finally, we identify and discuss challenges for future research. Categories and Subject Descriptors (according to ACM CCS): H.5.2 [Information Interfaces and Presentation]: User Interfaces—Graphical user interfaces (GUI) 1. Introduction The world is constantly evolving, there is nothing static or stable in it. But sometimes we pretend there is—just for simpliﬁcation. In particular when analyzing data, this constraint is often applied: either we choose a single point in time or we aggregate longer spans of time. And indeed, the simpliﬁcation is very helpful as it reduces the amount of data, makes computations faster, and simpliﬁes reasoning as well as communication. However, this approach has its clear limitations: we learn nothing about the dynamics. As a consequence, we neither understand how and why certain stages are reached nor can foresee future changes. 􀀍c The Eurographics Association 2014 . Many aspects of the analog and digital world can be considered as objects being related to each other, for instance, people forming a social network, proteins interacting with each other, or components of a software system communicating through calls. We usually model relational data as graphs and a very active research community has formed around visualizing these structures: many visualization techniques have been introduced [vLKS􀀃 11], criteria for readable graph visualization have been studied [BRSG07] . And in fact, in most cases, the above simpliﬁcation has been applied, visualizing static graphs only. However, over the years, researchers started to question this constraint and be- F. Beck, M. Burch, S. Diehl & D. Weiskopf / The State of theArt in Visualizing Dynamic Graphs Figure 2: Yearly number of publications on dynamic graph visualization according to our literature database; light gray bars indicate the total number of publications, colored bars distinguish the publications by type. gan thinking about the visualization of dynamic graphs—relations between objects that change over time, as it is nat

FAQs

What distinguishes dynamic graph visualizations in this survey?

Time representation is the main distinguishing feature: dynamic graphs are shown either as animated diagrams or as static charts based on a timeline.

How are evaluations of animated dynamic graph approaches typically assessed?

They often focus on dynamic stability, especially preserving the viewer’s mental map, and they may compare animated diagrams to timeline-based alternatives.

What does the paper contribute overall?

It provides a state-of-the-art survey, including a hierarchical taxonomy derived from systematic literature categorization, and it discusses evaluation results and future challenges.

Oct 26, 2026

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