Visual to Parametric Interaction (V2PI).

Visual to Parametric Interaction (V2PI).
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DOI:
10.1371/journal.pone.0050474
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发表时间:
2013
期刊:
影响因子:
3.7
通讯作者:
North C
North C
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Leman SC;House L;Maiti D;Endert A;North C

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典型的数据可视化是由线性管道产生的,线性管道首先使用模型或算法来描述数据以降维并总结结构,最后以降维形式显示数据。当用户有机会观察、消化和内化所显示的任何信息时,可以在管道的末端进行意义生成。然而,当模型或算法约束(例如,参数规范)与数据中的信息相矛盾时,一些可视化会掩盖有意义的数据结构。然而,由于管道的线性,用户没有自然的手段来调整显示器。在本文中,我们提出了一个创建动态数据显示的框架,该框架依赖于机械数据摘要和专家判断。关键是我们开发了一种新的人-数据交互的理论和方法,我们称之为“从视觉到参数交互”(V2PI)。使用V2PI,管道变得双向,因为用户嵌入到管道中;用户从可视化中学习,可视化根据专家的判断进行调整。我们通过两个示例演示了V2PI和双向管道的实用程序。
Typical data visualizations result from linear pipelines that start by characterizing data using a model or algorithm to reduce the dimension and summarize structure, and end by displaying the data in a reduced dimensional form. Sensemaking may take place at the end of the pipeline when users have an opportunity to observe, digest, and internalize any information displayed. However, some visualizations mask meaningful data structures when model or algorithm constraints (e.g., parameter specifications) contradict information in the data. Yet, due to the linearity of the pipeline, users do not have a natural means to adjust the displays. In this paper, we present a framework for creating dynamic data displays that rely on both mechanistic data summaries and expert judgement. The key is that we develop both the theory and methods of a new human-data interaction to which we refer as “ Visual to Parametric Interaction” (V2PI). With V2PI, the pipeline becomes bi-directional in that users are embedded in the pipeline; users learn from visualizations and the visualizations adjust to expert judgement. We demonstrate the utility of V2PI and a bi-directional pipeline with two examples.
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