The Garden of Forking Paths in Visualization: A Design Space for Reliable Exploratory Visual Analytics : Position Paper
The Garden of Forking Paths in Visualization: A Design Space for Reliable Exploratory Visual Analytics : Position Paper
复制标题
可视化分叉路径花园：可靠的探索性视觉分析的设计空间：立场文件
DOI：
10.1109/beliv.2018.8634103
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Matthew Kay
中科院分区：
文献类型：
--
作者：
Xiaoying Pu;Matthew Kay
图基几十年前就强调，将探索性发现作为证实是“极其愚蠢的”。我们根据格尔曼和洛肯的分叉路径花园重新构建了最近关于探索性视觉分析结果可靠性的讨论（例如多重比较问题），为解决视觉分析中的分叉路径问题奠定了设计空间。该设计空间包含解决分叉路径问题的现有方法（多重比较校正）以及尚未应用于探索性视觉分析（正则化）的解决方案。我们还讨论了如何使用感知偏差校正技术来纠正由于分叉路径问题而导致分析师对其数据的理解产生的偏差，并概述了如何将这个问题视为对 Munzner 可视化设计嵌套模型有效性的威胁。最后，我们建议论文评审指南，以鼓励审稿人在评估可视化分析工具的未来设计时考虑分叉路径问题。
Tukey emphasized decades ago that taking exploratory findings as confirmatory is “destructively foolish”. We reframe recent conversations about the reliability of results from exploratory visual analytics—such as the multiple comparisons problem—in terms of Gelman and Loken’s garden of forking paths to lay out a design space for addressing the forking paths problem in visual analytics. This design space encompasses existing approaches to address the forking paths problem (multiple comparison correction) as well as solutions that have not been applied to exploratory visual analytics (regularization). We also discuss how perceptual bias correction techniques may be used to correct biases induced in analysts’ understanding of their data due to the forking paths problem, and outline how this problem can be cast as a threat to validity within Munzner’s Nested Model of visualization design. Finally, we suggest paper review guidelines to encourage reviewers to consider the forking paths problem when evaluating future designs of visual analytics tools.
影响因子：
4.4
作者：
Yao, Yuling;Vehtari, Aki;Tonellato, Stefano
通讯作者：
Tonellato, Stefano
警告，可能会出现偏差：一种检测交互式视觉分析中认知偏差的提议方法
DOI：
10.1109/vast.2017.8585669
发表时间：
2017
期刊：
IEEE Visual Analytic Science and Technology (VAST
影响因子：
--
作者：
Wall, Emily;Blaha, Leslie M.;Franklin, Lyndsey;Endert, Alex
通讯作者：
Endert, Alex