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Figurative frames: A critical vocabulary for images in information visualization
Information Visualization ( IF 1.8 ) Pub Date : 2017-08-29 , DOI: 10.1177/1473871617724212
Lydia Byrne 1 , Daniel Angus 2 , Janet Wiles 1
Affiliation  

Critical analyses provide information visualization practitioners with insight into the range and suitability of different techniques for visualization. Theory provides the necessary models and vocabulary to deconstruct, explain and classify visualizations, allowing the analysis and comparison of alternate designs, and evaluation of their success. While the critical vocabulary for information visualization in general is well developed, the same cannot be said for ‘hybrid’ information visualizations which combine abstract representation of data with figurative elements such as illustrations. Figurative elements are widely used in information visualization in practice and are increasingly recognized as beneficial for memorability. However, the information encoded by a figurative image and how that information contributes to the overall content of the visualization lacks robust definition within visualization theory. To support critical analysis of hybrid visualization, we provide a model of the information content of a figurative image, which we call the figurative frame model. We use the model to classify hybrid visualizations along two dimensions: information density in the images (defined as the number of features and preserved measurements) and integration of figurative and abstract forms of representation. The new vocabulary for analysing hybrid visualizations reveals how the figurative images expand the expressiveness of information visualization by integrating descriptive and abstract information and allows the formulation of new measures of visualization quality which can be applied to hybrid visualizations.

中文翻译:

形象框架:信息可视化中图像的关键词汇

批判性分析使信息可视化从业者深入了解不同可视化技术的范围和适用性。理论提供了必要的模型和词汇来解构、解释和分类可视化,允许对替代设计进行分析和比较,并评估它们的成功。虽然信息可视化的关键词汇总体上已经得到了很好的发展,但对于将数据的抽象表示与插图等图形元素相结合的“混合”信息可视化来说,情况并非如此。图形元素在实践中广泛用于信息可视化,并且越来越被认为有利于记忆。然而,由具象图像编码的信息以及该信息如何对可视化的整体内容做出贡献,在可视化理论中缺乏可靠的定义。为了支持混合可视化的批判性分析,我们提供了一个形象化图像的信息内容模型,我们称之为形象化框架模型。我们使用该模型沿两个维度对混合可视化进行分类:图像中的信息密度(定义为特征数量和保留的测量值)以及图形和抽象表示形式的集成。
更新日期:2017-08-29
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