ZigzagNetVis: Suggesting temporal resolutions for graph visualization using zigzag persistence

Abstract

Temporal graphs are commonly used to represent complex systems and track the evolution of their constituents over time. Visualizing these graphs is crucial as it allows one to quickly identify anomalies, trends, patterns, and other properties that facilitate better decision-making. In this context, selecting an appropriate temporal resolution is essential for constructing and visually analyzing the layout. The choice of resolution is particularly important, especially when dealing with temporally sparse graphs. In such cases, changing the temporal resolution by grouping events (i.e., edges) from consecutive timestamps -- a technique known as timeslicing -- can aid in the analysis and reveal patterns that might not be discernible otherwise. However, selecting an appropriate temporal resolution is a challenging task. In this paper, we propose ZigzagNetVis, a methodology that suggests temporal resolutions potentially relevant for analyzing a given graph, i.e., resolutions that lead to substantial topological changes in the graph structure. ZigzagNetVis achieves this by leveraging zigzag persistent homology, a well-established technique from Topological Data Analysis (TDA). To improve visual graph analysis, ZigzagNetVis incorporates the colored barcode, a novel timeline-based visualization inspired by persistence barcodes commonly used in TDA. We also contribute with a web-based system prototype that implements suggestion methodology and visualization tools. Finally, we demonstrate the usefulness and effectiveness of ZigzagNetVis through a usage scenario, a user study with 27 participants, and a detailed quantitative evaluation.

This document contains the main article and supplementary material, similar to published version. For associated code and software, see https://github.com/raphaeltinarrage/ZigzagNetVis

References in corpus (18)

• Temporal Networks
• What's in a crowd? Analysis of face-to-face behavioral networks
• Contact patterns in a high school: a comparison between data collected using wearable sensors, contact diaries and friendship surveys
• Estimating Potential Infection Transmission Routes in Hospital Wards Using Wearable Proximity Sensors
• Mitigation of infectious disease at school: targeted class closure vs school closure
• Data on face-to-face contacts in an office building suggests a low-cost vaccination strategy based on community linkers
• Persistence and periodicity in a dynamic proximity network
• Effects of time window size and placement on the structure of aggregated networks
• Detection of timescales in evolving complex systems
• Sampling of Temporal Networks: Methods and Biases
• Persistent Homology Guided Force-Directed Graph Layouts
• Temporal Network Analysis Using Zigzag Persistence
• LargeNetVis: Visual Exploration of Large Temporal Networks Based on Community Taxonomies
• An Online and Nonuniform Timeslicing Method for Network Visualisation
• A supervised approach to time scale detection in dynamic networks
• Finding Proper Time Intervals for Dynamic Network Extraction
• Quantitative Evaluation of Snapshot Graphs for the Analysis of Temporal Networks
• Updating Barcodes and Representatives for Zigzag Persistence