空间回收冰柱图

H. V. D. Wetering, Nico Klaassen, Michael Burch
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引用次数: 11

摘要

本文以冰柱的视觉隐喻为基础,描述了空间回收冰柱图的分层可视化。作为一种新颖的方法,我们试图在所有层次中回收空白空间。这种回收可以提高层次结构元素的可见性,尤其是那些在更深层次中的元素。我们实现了一种能够产生更多空间回收冰柱图变体的算法。可以调整几个视觉参数来改变图形的视觉外观和可读性:其中包括空间回收参数、空白空间收缩参数和间隙大小。为了说明这种新型可视化技术的有用性,我们将其应用于一个包含超过30万个元素、最大深度为42的NCBI分类法数据集。此外,我们通过应用几个视觉参数值来探索参数和设计空间。我们还进行了一项有17名参与者的受控用户研究,并从112名参加可视化课程的学生那里获得了定性反馈。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Space-Reclaiming Icicle Plots
This paper describes the space-reclaiming icicle plots, hierarchy visualizations based on the visual metaphor of icicles. As a novelty, our approach tries to reclaim empty space in all hierarchy levels. This reclaiming results in an improved visibility of the hierarchy elements especially those in deeper levels. We implemented an algorithm that is capable of producing more space-reclaiming icicle plot variants. Several visual parameters can be tweaked to change the visual appearance and readability of the plots: among others, a space-reclaiming parameter, an empty space shrinking parameter, and a gap size. To illustrate the usefulness of the novel visualization technique we applied it, among others, to an NCBI taxonomy dataset consisting of more than 300,000 elements and with maximum depth 42. Moreover, we explore the parameter and design space by applying several values for the visual parameters. We also conducted a controlled user study with 17 participants and received qualitative feedback from 112 students from a visualization course.
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