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CoMoVA - A comprehension measurement framework for visualization systems.

机译:CoMoVA-用于可视化系统的综合测量框架。

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摘要

Despite the burgeoning interest shown in visualizations by many disciplines, there yet remains the unresolved question concerning comprehension. Is the concept that is being communicated through the visual easily grasped and clearly interpreted? Visual comprehension is that characteristic of any visualization system, which deals with how efficiently and effectively users are able to grasp the underlying concepts through suitable interactions provided for exploring the visually represented information. Comprehension has been considered a very complex subject, which is intangible and subjective in nature. Assessment of comprehension can help to determine the true usefulness of visualization systems to the intended users. A principal contribution of this research is the formulation of an empirical evaluation framework for systematically assessing comprehension support provided by a visualization system to its intended users.;Given the vast variety of users and their visualization goals, it may be noted that it is difficult for one to decide on the effectiveness of different visualization tools/techniques in a context independent fashion. We therefore propose an innovative way of evaluating a visualization technique by encapsulating it in a visualization pattern where it is seen as a solution to the visualization problem in a specific context. These visualization patterns guide the tool users/evaluators to compare, understand and select appropriate visualization tools/techniques.;Lastly, we propose a novel framework named as CoMoVA (Comprehension Model for Visualization Assessment) that incorporates 'context of use', visualization patterns, visual design principles and important cognitive principles into a coherent whole that can be used to effectively tell us in a more quantifiable manner the benefits of visual representations and interactions provided by a system to the intended audience. Our approach of evaluation of visualization systems is similar to other questionnaire-based approaches such as SUMI (Software Usability Measurement Inventory), where all the questions deal with the measurement of a common trait. We apply this framework to two static software visualization tools in the software visualization domain to demonstrate the practical benefits of using such a framework.;To assess comprehension i.e. to measure this seemingly immeasurable factor of visualization systems, we propose a set of criteria based on a detailed analysis of information flow from the raw data to the cognition of information in human mind. Our comprehension criteria are adapted from the pioneering work of two eminent researchers - Donald A. Norman and Aaron Marcus, who have investigated the issues of human perception and cognition, and visual effectiveness respectively. The proposed criteria have been refined with the help of opinions from experts. To gauge and verify the efficacy of these criteria in a practical sense, they were then applied to a bioinformatics visualization study tool and an immersive art visualization environment.
机译:尽管许多学科对可视化表现出了极大的兴趣,但是关于理解的问题仍然悬而未决。通过视觉传达的概念是否易于掌握和清晰解释?视觉理解是任何可视化系统的特征,它处理用户如何通过提供适当的交互来探索可视化表示的信息来有效地,有效地掌握基本概念。理解被认为是一个非常复杂的主题,本质上是无形的和主观的。对理解的评估可以帮助确定可视化系统对目标用户的真正有用性。这项研究的主要贡献是制定了一个经验评估框架,用于系统地评估可视化系统为其预期用户提供的理解支持。鉴于大量的用户及其可视化目标,可能会发现很难一个以上下文无关的方式决定不同可视化工具/技术的有效性的方法。因此,我们提出了一种通过将可视化技术封装在可视化模式中来评估可视化技术的创新方式,在可视化模式中可视为解决特定环境下可视化问题的一种方法。这些可视化模式可指导工具用户/评估人员比较,理解和选择合适的可视化工具/技术。最后,我们提出了一个名为CoMoVA(可视化评估理解模型)的新颖框架,该框架结合了“使用上下文”,可视化模式,视觉设计原理和重要的认知原理成为一个连贯的整体,可用于以更可量化的方式有效地告诉我们系统向目标受众提供的视觉表示和交互的好处。我们对可视化系统的评估方法类似于其他基于问卷的方法,例如SUMI(软件可用性度量清单),其中所有问题都涉及对共同特征的度量。我们将此框架应用于软件可视化领域中的两个静态软件可视化工具,以演示使用该框架的实际好处。为了评估理解力,即衡量可视化系统的这一看似不可衡量的因素,我们提出了一套基于从原始数据到人脑中信息认知的信息流的详细分析。我们的理解标准是根据两位著名研究者Donald A. Norman和Aaron Marcus的开创性工作改编而成的,他们分别研究了人类的感知和认知以及视觉效果问题。建议的标准已在专家意见的帮助下进行了完善。为了从实际意义上衡量和验证这些标准的有效性,然后将它们应用于生物信息学可视化研究工具和沉浸式艺术可视化环境。

著录项

  • 作者

    Padda, Harkirat Kaur.;

  • 作者单位

    Concordia University (Canada).;

  • 授予单位 Concordia University (Canada).;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 326 p.
  • 总页数 326
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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