Improving the fidelity of contextual data layouts using a Generalized Barycentric Coordinates framework

Shenghui Cheng, K. Mueller
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引用次数: 24

Abstract

Contextual layouts preserve the context of the data with the associated attributes (variables). However, their linear mapping causes errors in the layout - similar data points and variable nodes may not map to similar regions, and vice versa. In this paper, we first unify the various data layout schemes and choose the Generalized Bary-centric Coordinates (GBC) plot as the standard way to describe them. Second, we propose three algorithms - distance spaced lay-out, iterative error reduction, and force directed adjustment - to reduce the layout error of variables to variables, data to variables and data to data, respectively. We find that the combination of these three algorithms can yield large improvements in the layout error and so achieve a more comprehensive layout. Third, we describe an interface, the GBC Error Explorer, which allows users to explore the error using a variety of visualization schemes combined with some interactions.
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使用广义重心坐标框架提高上下文数据布局的保真度
上下文布局用相关的属性(变量)保存数据的上下文。然而,它们的线性映射会导致布局中的错误——相似的数据点和变量节点可能不会映射到相似的区域,反之亦然。在本文中,我们首先统一了各种数据布局方案,并选择广义巴里中心坐标(GBC)图作为描述它们的标准方式。其次,我们提出了距离间隔布局、迭代误差减少和力定向调整三种算法,分别减少变量对变量、数据对变量和数据对数据的布局误差。我们发现这三种算法的结合可以大大改善布局误差,从而实现更全面的布局。第三,我们描述了一个接口,GBC错误资源管理器,它允许用户使用各种可视化方案结合一些交互来探索错误。
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