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Matrix visualizations are widely used to display large-scale network,tabular, set, or sequential data. They typically only encode a single value percell, e.g., through color. However, this can greatly limit the visualizations'utility when exploring multivariate data, where each cell represents a datapoint with multiple values (referred to as details). Three well-establishedinteraction approaches can be applicable in multivariate matrix visualizations(or MMV): focus+context, pan&zoom, and overview+detail. However, there islittle empirical knowledge of how these approaches compare in exploring MMV. Wereport on two studies comparing them for locating, searching, andcontextualizing details in MMV. We first compared four focus+context techniquesand found that the fisheye lens overall outperformed the others. We thencompared the fisheye lens, to pan&zoom and overview+detail. We found thatpan&zoom was faster in locating and searching details, and as good asoverview+detail in contextualizing details.

chi conference on human factors in computing systems

The Pattern is in the Details: An Evaluation of Interaction Techniques  for Locating, Searching, and Contextualizing Details in Multivariate Matrix  Visualizations