Building and Applying a Human Cognition Model for Visual Analytics
Building and Applying a Human Cognition Model for Visual Analytics
复制标题
构建和应用用于视觉分析的人类认知模型
DOI：
--
复制
发表时间：
2009
影响因子：
2.3
通讯作者：
Brian D. Fisher
中科院分区：
文献类型：
--
作者：
T. M. Green;W. Ribarsky;Brian D. Fisher
众所周知，可视化分析解决了评估和处理大量信息的困难。较少讨论的是为了实现这一目标而必须应用的日益复杂的分析和推理过程。可视化分析方法的成功将要求我们开发新的可视化模型，以预测计算过程如何促进人类洞察力并指导人类推理的流程。在本文中，我们试图通过提出一个框架，为人类的“更高的认知”，扩展更熟悉的感知模型，以推进可视化方法。基于这种方法，我们建议的视觉界面，更好地整合人类和计算机的互补能力的发展准则。虽然这些建议中有许多是新颖的，但有些可以在现有的可视化分析应用程序中找到。在后一种情况下，我们的贡献的大部分价值在于模型为这些原则提供了更深层次的理由。最后，我们通过几个可视化示例的评估来评估这些可视化分析指南。
It is well known that visual analytics addresses the difficulty of evaluating and processing large quantities of information. Less often discussed are the increasingly complex analytic and reasoning processes that must be applied in order to accomplish that goal. Success of the visual analytics approach will require us to develop new visualization models that predict how computational processes might facilitate human insight and guide the flow of human reasoning. In this paper, we seek to advance visualization methods by proposing a framework for human ‘higher cognition’ that extends more familiar perceptual models. Based on this approach, we suggest guidelines for the development of visual interfaces that better integrate complementary capabilities of humans and computers. Although many of these recommendations are novel, some can be found in existing visual analytics applications. In the latter case, much of the value of our contribution lies in the deeper rationale that the model provides for those principles. Lastly, we assess these visual analytics guidelines through the evaluation of several visualization examples.
思考太多：内省会降低偏好和决策的质量。
影响因子：
7.6
作者：
Wilson,TD;Schooler,JW
通讯作者：
Schooler,JW