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18 January 2010 Operator-centric design patterns for information visualization software
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Proceedings Volume 7530, Visualization and Data Analysis 2010; 75300J (2010)
Event: IS&T/SPIE Electronic Imaging, 2010, San Jose, California, United States
Design patterns have proven to be a useful means to make the process of designing, developing, and reusing software systems more efficient. In the area of information visualization, researchers have proposed design patterns for different functional components of the visualization pipeline. Since many visualization techniques need to display derived data as well as raw data, the data transformation stage is very important in the pipeline, yet existing design patterns are, in general, not sufficient to implement these data transformation techniques. In this paper, we propose two design patterns, operatorcentric transformation and data modifier, to facilitate the design of data transformations for information visualization systems. The key idea is to use operators to describe the data derivation and introduce data modifiers to represent the derived data. We also show that many interaction techniques can be regarded as operators as defined here, thus these two design patterns could support a wide range of visualization techniques. In addition, we describe a third design pattern, modifier-based visual mapping, that can generate visual abstraction via linking data modifiers to visual attributes. We also present a framework based on these three design patterns that supports coordinated multiple views. Several examples of multivariate visualizations are discussed to show that our design patterns and framework can improve the reusability and extensibility of information visualization systems. Finally, we explain how we have ported an existing visualization tool (XmdvTool) from its old data-centric structure to a new structure based on the above design patterns and framework.
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Zaixian Xie, Zhenyu Guo, Matthew O. Ward, and Elke A. Rundensteiner "Operator-centric design patterns for information visualization software", Proc. SPIE 7530, Visualization and Data Analysis 2010, 75300J (18 January 2010);

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