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Increasing the readability of graph drawings with centrality-based scaling

机译:通过基于中心度的缩放比例来提高图形的可读性

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摘要

A common problem in visualising some networks is the presence of localised high density areas in an otherwise sparse graph. Applying common graph drawing algorithms on such networks can result in drawings that are not highly readable in the dense areas. Additionally, networks whose layouts are defined geographically often have dense areas that are located within small geographical regions relative to the size of the entire network. In cases where relationships within these dense areas are of interest, it is desirable to be able to distort the graph layout such that the denser areas are enlarged from their original sizes.

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In this paper, we propose a technique for enlarging dense areas of a given graph layout, and shrinking sparse areas. This technique is applied to geographical layouts of railway networks and force-directed layouts of non-geographical networks. The results show an increase in readability of dense parts of the networks. In addition, they provide improved starting layouts for schematisation methods which may be used to further increase readability.

机译:在可视化某些网络时,常见的问题是在稀疏图中存在局部高密度区域。在此类网络上应用通用图形绘图算法可能会导致在密集区域中无法高度可读的绘图。另外,其布局在地理上定义的网络通常具有相对于整个网络的大小位于较小地理区域内的密集区域。在需要关注这些密集区域内的关系的情况下,希望能够使图形布局变形,以使较密集区域从其原始大小开始扩大。 rn

在本文中,我们提出了一种扩大给定图形布局的密集区域并缩小稀疏区域的技术。此技术适用于铁路网络的地理布局和非地理网络的力导向布局。结果表明,网络密集部分的可读性有所提高。此外,它们为方案化方法提供了改进的起始布局,可用于进一步提高可读性。

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