RSVP for VPSA : A Meta Design Study on Rapid Suggestive Visualization Prototyping for Visual Parameter Space Analysis

Manfred Klaffenboeck, Michael Gleicher, Johannes Sorger, Michael Wimmer, Torsten Möller
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Abstract

Visual Parameter Space Analysis (VPSA) enables domain scientists to explore input-output relationships of computational models. Existing VPSA applications often feature multi-view visualizations designed by visualization experts for a specific scenario, making it hard for domain scientists to adapt them to their problems without professional help. We present RSVP, the Rapid Suggestive Visualization Prototyping system encoding VPSA knowledge to enable domain scientists to prototype custom visualization dashboards tailored to their specific needs. The system implements a task-oriented, multi-view visualization recommendation strategy over a visualization design space optimized for VPSA to guide users in meeting their analytical demands. We derived the VPSA knowledge implemented in the system by conducting an extensive meta design study over the body of work on VPSA. We show how this process can be used to perform a data and task abstraction, extract a common visualization design space, and derive a task-oriented VisRec strategy. User studies indicate that the system is user-friendly and can uncover novel insights.
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VPSA : 用于可视参数空间分析的快速建议性可视化原型的元设计研究 RSVP
可视化参数空间分析(VPSA)使领域科学家能够探索计算模型的输入输出关系。现有的 VPSA 应用程序通常采用可视化专家针对特定场景设计的多视图可视化,这使得领域科学家很难在没有专业帮助的情况下根据自己的问题进行调整。我们介绍的 RSVP 是快速建议可视化原型系统,它编码了 VPSA 知识,使领域科学家能够根据自己的具体需求定制可视化仪表板原型。该系统在为VPSA优化的可视化设计空间上实施了面向任务的多视图可视化推荐策略,以指导用户满足其分析需求。我们通过对有关 VPSA 的大量工作进行广泛的元设计研究,得出了系统中实施的 VPSA 知识。我们展示了如何利用这一过程进行数据和任务抽象、提取通用的可视化设计空间并推导出面向任务的 VisRec 策略。用户研究表明,该系统对用户友好,并能发现新的见解。
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