Abstract Network data, represented by graph-based structures, are used in a variety of applications such as social networks and disease complication networks. A crucial task in many applications is graph comparison, with the goal of understanding the structural differences between pairs of graphs. However, traditional graph visualization techniques, node-link diagrams, and adjacency matrices are not intrinsically designed for comparison tasks. In this paper, we present TrammelGraph, a novel visual graph abstraction technique for graph comparison. TrammelGraph uses graph embedding and node alignment methods to create a map-based representation that eliminates visual clutter and thus facilities graph comparison. The design results in a planar graph with a regularly-spaced, crossing-free layout that helps users identify high-level topological information for graph comparison tasks. To evaluate the effectiveness of TrammelGraph, we conducted a controlled user study with 20 participants that compares TrammelGraph with node-link diagrams and adjacency matrices on a variety of common graph comparison tasks. We also conducted an expert interview with a physician using the MIMIC dataset. Both the quantitative and qualitative results from the study and interview highlighted the key strengths of TrammelGraph as a tool for visual graph comparison. Graphic abstract

中文翻译：

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TrammelGraph：用于比较的可视化图形抽象

摘要 由基于图的结构表示的网络数据被用于各种应用，例如社交网络和疾病并发症网络。许多应用程序中的一项关键任务是图比较，目的是了解图对之间的结构差异。然而，传统的图形可视化技术、节点链接图和邻接矩阵本质上并不是为比较任务而设计的。在本文中，我们介绍了 TrammelGraph，这是一种用于图比较的新型视觉图抽象技术。TrammelGraph 使用图嵌入和节点对齐方法来创建基于地图的表示，从而消除视觉混乱，从而实现图比较。该设计导致平面图具有规则间隔，无交叉布局，可帮助用户识别图形比较任务的高级拓扑信息。为了评估 TrammelGraph 的有效性，我们对 20 名参与者进行了一项受控用户研究，该研究将 TrammelGraph 与节点链接图和邻接矩阵在各种常见图形比较任务上进行了比较。我们还使用 MIMIC 数据集对医生进行了专家访谈。研究和访谈的定量和定性结果都突出了 TrammelGraph 作为可视化图形比较工具的主要优势。图形摘要 我们还使用 MIMIC 数据集对医生进行了专家访谈。研究和采访的定量和定性结果都突出了 TrammelGraph 作为可视化图形比较工具的主要优势。图形摘要 我们还使用 MIMIC 数据集对医生进行了专家访谈。研究和采访的定量和定性结果都突出了 TrammelGraph 作为可视化图形比较工具的主要优势。图形摘要