Selection: 524,288 ways to say "this is interesting"

G. Wills
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引用次数: 109

Abstract

Visualization is a critical technology for understanding complex, data-rich systems. Effective visualizations make important features of the data immediately recognizable and enable the user to discover interesting and useful results by highlighting patterns. A key element of such systems is the ability to interact with displays of data by selecting a subset for further investigation. This operation is needed for use in linked-views systems and in drill-down analysis. It is a common manipulation in many other systems. It is as ubiquitous as selecting icons in a desktop GUI. It is therefore surprising to note that little research has been done on how selection can be implemented. This paper addresses this omission, presenting a taxonomy for selection mechanisms and discussing the interactions between branches of the taxonomy. Our suggestion of 524,288 possible systems [2/sup 16/ operation systems/spl times/2 (memory/memoryless)/spl times/2 (data-dependent/independent)/spl times/2 (brush/lasso)] is more in fun than serious, as within the taxonomy there are many different choices that can be made. This framework is the result of considering both the current state of the art and historical antecedents.
选择:524,288种表达“这很有趣”的方式
可视化是理解复杂的、数据丰富的系统的关键技术。有效的可视化可以立即识别数据的重要特征,并使用户能够通过突出显示模式来发现有趣和有用的结果。这种系统的一个关键要素是通过选择一个子集进行进一步研究来与数据显示进行交互的能力。在链接视图系统和向下钻取分析中需要使用此操作。这是许多其他系统中常见的操作。它就像在桌面GUI中选择图标一样无处不在。因此,令人惊讶的是,很少有人研究选择是如何实现的。本文解决了这一遗漏,提出了一种选择机制的分类法,并讨论了分类法分支之间的相互作用。我们建议的524,288种可能的系统[2/sup 16/操作系统/spl times/2(内存/无内存)/spl times/2(数据依赖/独立)/spl times/2(刷/套索)]与其说是严肃的,倒不如说是有趣的,因为在分类法中可以做出许多不同的选择。这个框架是考虑到当前的艺术状态和历史先例的结果。
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