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 leading to better decision-making. In this context, the to-be-adopted temporal resolution is crucial in constructing and analyzing the layout visually. The choice of a resolution is critical, e.g., 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, choosing a suitable temporal resolution is not trivial. In this paper, we propose TDANetVis, 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. To achieve this goal, TDANetVis leverages zigzag persistent homology, a well-established technique from Topological Data Analysis (TDA). To enhance visual graph analysis, TDANetVis also incorporates the colored barcode, a novel timeline-based visualization built on the persistence barcodes commonly used in TDA. We demonstrate the usefulness and effectiveness of TDANetVis through a usage scenario and a user study involving 27 participants.

翻译：时序图常用于表示复杂系统并追踪其组成要素随时间演变的过程。对这些图的可视化至关重要，因为它能快速识别异常、趋势、模式及其他属性，从而优化决策。在此背景下，所采用的时间分辨率对于构建和视觉分析布局至关重要。当处理时间稀疏图时，分辨率的选择尤为关键。此时，通过将连续时间戳的事件（即边）进行分组（即时间切片技术）来改变时间分辨率，可辅助分析并揭示原本难以察觉的模式。然而，选择合适的时间分辨率并非易事。本文提出TDANetVis方法，该方法能建议可能适用于分析给定图的潜在时间分辨率——即那些能导致图结构发生显著拓扑变化的分辨率。为实现此目标，TDANetVis利用拓扑数据分析（TDA）领域成熟技术——之字形持续同调。为增强可视化图形分析，TDANetVis还引入彩色条形码，这是一种基于TDA中常用持续条形码的新型时间线可视化形式。我们通过应用场景及包含27名参与者的用户研究，验证了TDANetVis的有效性与实用性。