Unit visualizations are a family of visualizations where every data item is represented by a unique visual mark\u2014a visual unit\u2014during visual encoding. For certain datasets and tasks, unit visualizations can provide more information, better match the user\u2019s\u00a0mental model, and enable novel interactions compared to traditional aggregated visualizations. Current visualization grammars cannot\u00a0fully describe the unit visualization family. In this paper, we characterize the design space of unit visualizations to derive a grammar that\u00a0can express them. The resulting grammar is called ATOM, and is based on passing data through a series of layout operations that divide\u00a0the output of previous operations recursively until the size and position of every data point can be determined. We evaluate the\u00a0expressive power of the grammar by both using it to describe existing unit visualizations, as well as to suggest new unit visualizations.<\/p>\n","protected":false},"excerpt":{"rendered":"
Unit visualizations are a family of visualizations where every data item is represented by a unique visual mark\u2014a visual unit\u2014during visual encoding. For certain datasets and tasks, unit visualizations can provide more information, better match the user\u2019s\u00a0mental model, and enable novel interactions compared to traditional aggregated visualizations. Current visualization grammars cannot\u00a0fully describe the unit visualization 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