Juniper: A Tree+ Table Approach to Multivariate Graph Visualization.
Juniper: A Tree+ Table Approach to Multivariate Graph Visualization.
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DOI：
10.1109/tvcg.2018.2865149
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发表时间：
2018-09-03
影响因子：
5.2
通讯作者：
Lex A
中科院分区：
文献类型：
--
作者：
Nobre C;Streit M;Lex A
分析大型多变量图在许多领域都是一个重要的问题，然而这些图的可视化是具有挑战性的。在本文中，我们介绍了一种新颖的、可扩展的、树+表的多变量图可视化技术，该技术使与多变量图分析相关的许多任务更容易实现。我们遵循的核心原则是有选择地查询感兴趣的节点或子图，并将这些子图可视化为图的生成树。该树是线性布局的，这使我们能够将节点与表可视化并置，其中可以显示各种属性。我们还使用这个表作为邻接矩阵，因此得到的技术是一种混合的节点链接/邻接矩阵技术。我们在Juniper中实现了这个概念，并辅以一组交互技术，使分析人员能够动态地增长、重组和聚合树，以及改变布局或显示节点之间的路径。我们在不同多元网络的使用场景中展示了我们的工具的实用性：一个由学者、论文和引用指标组成的二部分网络，以及一个由故事人物、地点、书籍等组成的多类型网络。
Analyzing large, multivariate graphs is an important problem in many domains, yet such graphs are challenging to visualize. In this paper, we introduce a novel, scalable, tree+table multivariate graph visualization technique, which makes many tasks related to multivariate graph analysis easier to achieve. The core principle we follow is to selectively query for nodes or subgraphs of interest and visualize these subgraphs as a spanning tree of the graph. The tree is laid out linearly, which enables us to juxtapose the nodes with a table visualization where diverse attributes can be shown. We also use this table as an adjacency matrix, so that the resulting technique is a hybrid node-link/adjacency matrix technique. We implement this concept in Juniper and complement it with a set of interaction techniques that enable analysts to dynamically grow, restructure, and aggregate the tree, as well as change the layout or show paths between nodes. We demonstrate the utility of our tool in usage scenarios for different multivariate networks: a bipartite network of scholars, papers, and citation metrics and a multitype network of story characters, places, books, etc.