Visual analytics of large dynamic digraphs
Visual analytics of large dynamic digraphs
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DOI：
10.1177/1473871616661194
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发表时间：
2017-07
影响因子：
2.3
通讯作者：
Michael Burch
中科院分区：
文献类型：
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作者：
Michael Burch
在本文中，我们研究了可视化表示和分析由许多顶点、边和时间步组成的大型动态有向图的问题。通过这项工作，我们不主要集中在图的细节，但更多的是实现一个概述长图序列的主要重点是可扩展的顶点，边缘和时间维度。为了达到这个目标，我们首先将每个图映射到一个二分布局，每个图的顶点顺序相同，支持保存观众的心理地图。一系列图形按从左到右的阅读方向放置。为了进一步减少链接交叉，我们绘制部分链接与用户可定义的长度，并最终应用边缘飞溅作为一个概念，强调图形结构的颜色编码生成的密度场。时变视觉图案可以通过检查显示器中某些区域中的颜色编码的变化来识别。我们在两个案例研究中说明了该方法的有用性，这些案例研究调查了21个版本的软件开发期间调用图的变化，这是一个相当短的图序列，但包含数千个顶点和边。在时间维度的视觉可扩展性显示了1000多个图形，从一个动态的社交网络数据集，包括面对面的接触，在超文本2009年会议期间获得的无线电频率识别徽章记录。
In this article, we investigate the problem of visually representing and analyzing large dynamic directed graphs that consist of many vertices, edges, and time steps. With this work we do not primarily focus on graph details but more on achieving an overview about long graph sequences with the major focus to be scalable in vertex, edge, and time dimensions. To reach this goal, we first map each graph to a bipartite layout with vertices in the same order for each graph supporting a preservation of the viewer’s mental map. A sequence of graphs is placed in a left-to-right reading direction. To further reduce link crossings, we draw partial links with user-definable lengths and finally apply edge splatting as a concept to emphasize graph structures by color coding the generated density fields. Time-varying visual patterns can be recognized by inspecting the changes in the color coding in certain regions in the display. We illustrate the usefulness of the approach in two case studies investigating call graphs changing during software development with 21 releases which is a rather short graph sequence but contains several thousand vertices and edges. Visual scalability in the time dimension is shown with more than 1000 graphs from a dynamic social network dataset consisting of face-to-face contacts acquired during the Hypertext 2009 conference recorded by radio-frequency identification badges.