Toward a Multi-Analyst, Collaborative Framework for Visual Analytics

Toward a Multi-Analyst, Collaborative Framework for Visual Analytics
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迈向可视化分析的多分析师协作框架

DOI:
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发表时间:
2006
期刊:
2006 IEEE Symposium On Visual Analytics Science And Technology
影响因子:
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通讯作者:
A. Kaufman
A. Kaufman
中科院分区:
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文献类型:
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作者:
S. Brennan;K. Mueller;G. Zelinsky;I. Ramakrishnan;D. Warren;A. Kaufman

文献摘要

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我们描述了一个用于显示复杂、多维数据的框架,旨在促进多个分析师之间的探索、分析和协作。该框架旨在通过更轻松地共享表征、从一种观点转换为另一种观点、解释论点、在基本假设发生变化时更新结论以及证明或解释决策或行动来支持人类协作。多维可视化技术与交互式、上下文相关且可调的图形一起使用。使用基于注释逻辑的知识表示方案灵活地生成视觉表示;这不仅可以跟踪和融合不同的观点,还可以将它们拆开。融合表示支持多维元显示的创建以及从一个观点到另一个观点的转换或映射。与此同时,分析师还需要能够解开彼此复杂的推理链,特别是当他们得出不同的结论时,并在基本假设或证据被证明是错误的时候确定其影响(如果有的话)。该框架使我们能够支持各种场景,并系统地生成和测试关于不同类型的视觉表示对分布式分析师团队的交互式协作的影响的实验假设
We describe a framework for the display of complex, multidimensional data, designed to facilitate exploration, analysis, and collaboration among multiple analysts. This framework aims to support human collaboration by making it easier to share representations, to translate from one point of view to another, to explain arguments, to update conclusions when underlying assumptions change, and to justify or account for decisions or actions. Multidimensional visualization techniques are used with interactive, context-sensitive, and tunable graphs. Visual representations are flexibly generated using a knowledge representation scheme based on annotated logic; this enables not only tracking and fusing different viewpoints, but also unpacking them. Fusing representations supports the creation of multidimensional meta-displays as well as the translation or mapping from one point of view to another. At the same time, analysts also need to be able to unpack one another's complex chains of reasoning, especially if they have reached different conclusions, and to determine the implications, if any, when underlying assumptions or evidence turn out to be false. The framework enables us to support a variety of scenarios as well as to systematically generate and test experimental hypotheses about the impact of different kinds of visual representations upon interactive collaboration by teams of distributed analysts