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Visual analytics (VA) systems have been widely used to facilitatedecision-making and analytical reasoning in various application domains. VAinvolves visual designs, interaction designs, and data mining, which is asystematic and complex paradigm. In this work, we focus on the design ofeffective visualizations for complex data and analytical tasks, which is acritical step in designing a VA system. This step is challenging because itrequires extensive knowledge about domain problems and visualization to designeffective encodings. Existing visualization designs published in top venues arevaluable resources to inspire designs for problems with similar data structuresand tasks. However, those designs are hard to understand, parse, and retrievedue to the lack of specifications. To address this problem, we build KB4VA, aknowledge base of visualization designs in VA systems with comprehensive labelsabout their analytical tasks and visual encodings. Our labeling scheme isinspired by a workshop study with 12 VA researchers to learn user requirementsin understanding and retrieving professional visualization designs in VAsystems. The theme extends Vega-Lite specifications for describing advanced andcomposited visualization designs in a declarative manner, thus facilitatinghuman understanding and automatic indexing. To demonstrate the usefulness ofour knowledge base, we present a user study about design inspirations for VAtasks. In summary, our work opens new perspectives for enhancing theaccessibility and reusability of professional visualization designs.

KB4VA: A Knowledge Base of Visualization Designs for Visual Analytics