用于指导多维可视化评估的任务分类

Eliane Regina de Almeida Valiati, M. Pimenta, C. Freitas
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引用次数: 87

摘要

多维可视化技术的设计基于这样一个假设,即大型数据集的图形化表示可以为用户提供更多的洞察力,为用户在利用数据的过程中提供更直观的支持。在开发可视化技术时,用户可能需要或想要对数据执行的分析和探索任务应该指导该技术实现的可视化和交互隐喻的选择。可视化技术的可用性测试还需要对用户的任务进行定义。在从数据的可视化表示中获取知识的过程中,对用户任务性质的识别和理解是信息可视化研究的一个新分支。一些作品提出了分类方法来组织可视化技术应该支持的任务。本文提出了一种可视化任务分类法,该分类法基于现有的分类法以及对用户在多维数据集中执行探索性任务的观察,使用两种不同的可视化技术,Parallel Coordinates和RadViz。对于一些高水平任务的完成,我们估计了涉及低水平任务的不同场景,并将它们与用户在实验中观察到的场景进行了比较。
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A taxonomy of tasks for guiding the evaluation of multidimensional visualizations
The design of multidimensional visualization techniques is based on the assumption that a graphical representation of a large dataset can give more insight to a user, by providing him/her a more intuitive support in the process of exploiting data. When developing a visualization technique, the analytic and exploratory tasks that a user might need or want to perform on the data should guide the choice of the visual and interaction metaphors implemented by the technique. Usability testing of visualization techniques also needs the definition of users' tasks. The identification and understanding of the nature of the users' tasks in the process of acquiring knowledge from visual representations of data is a recent branch in information visualization research. Some works have proposed taxonomies to organize tasks that a visualization technique should support. This paper proposes a taxonomy of visualization tasks, based on existing taxonomies as well as on the observation of users performing exploratory tasks in a multidimensional data set using two different visualization techniques, Parallel Coordinates and RadViz. Different scenarios involving low-level tasks were estimated for the completion of some high-level tasks, and they were compared to the scenarios observed during the users' experiments.
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