Treemaps: Visualizing Hierarchical and Categorical Data
Johnson, Brian Scott
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Treemaps are a graphical method for the visualization of hierarchical and categorical data sets. Treemap presentations of data shift mental workload from the cognitive to the perceptual systems, taking advantage of the human visual processing system to increase the bandwidth of the human-computer interface. Efficient use of display space allows for the simultaneous presentation of thousands of data records, as well as facilitating the presentation of semantic information. Treemaps let users see the forest and the trees by providing local detail in the context of a global overview, providing a visually engaging environment in which to analyze, search, explore and manipulate large data sets. The treemap method of hierarchical visualization, at its core, is based on the property of containment. This property of containment is a fundamental idea which powerfully encapsulates many of our reasons for constructing information hierarchies. All members of the treemap family of algorithms partition multi-dimensional display spaces based on weighted hierarchical data sets. In addition to generating treemaps and standard traditional hierarchical diagrams, the treemap algorithms extend non-hierarchical techniques such as bar and pie charts into the domain of hierarchical presentation. Treemap algorithms can be used to generate bar charts, outlines, traditional 2-D node and link diagrams, pie charts, cone trees, cam trees, drum trees, etc. Generating existing diagrams via treemap transformations is an exercise meant to show the power, ease, and generality with which alternative presentations can be generated from the basic treemap algorithms. Two controlled experiments with novice treemap users and real data highlight the strengths of treemaps. The first experiment with 12 subjects compares the Macintosh TreeVizTM implementation of treemaps with the UNIX command line for questions dealing with a 530 node file hierarchy. Treemaps are shown to significantly reduce user performance times for global file comparison tasks. A second experiment with 40 subjects compares treemaps with dynamic outlines for questions dealing with the allocation funds in the 1992 US Budget (357 node budget hierarchy). Treemap users are 50% faster overall and as much as 8 times faster for specific questions.