Toward a Multi-Analyst, Collaborative Framework for Visual Analytics
Toward a Multi-Analyst, Collaborative Framework for Visual Analytics
复制标题
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:
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通讯作者:
A. Kaufman
中科院分区:
文献类型:
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作者:
S. Brennan;K. Mueller;G. Zelinsky;I. Ramakrishnan;D. Warren;A. Kaufman
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