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Demystifying Visual Analytics

机译:揭开视觉分析的神秘面纱

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摘要

Christian Chabot addresses the common misperceptions and stereotypes about visual analytics as the practice begins moving into widespread use. People typically associate visual analytics with four principles, all of which are false: the practice requires massive data, it's used to understand only complex problems, it requires the invention of new visual paradigms, and it focuses on finding hidden insights. Chabot explains why these principles are incorrect and why the visual analytics community would help the world at large by espousing its virtues.
机译:随着实践开始广泛使用,Christian Chabot解决了有关视觉分析的常见误解和陈规定型观念。人们通常将视觉分析与四个原则相关联,而所有这些原则都是错误的:实践需要大量数据,仅用于理解复杂的问题,需要发明新的视觉范式,并且着重于发现隐藏的见解。 Chabot解释了这些原理为何不正确以及视觉分析社区为什么会通过拥护自己的优点来帮助整个世界。

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