Parallel bargrams for consumer-based information exploration and choice

In this paper we introduce multidimensional visualization and interaction techniques that are an extension to related work in parallel histograms and dynamic querying. Bargrams are, in effect, histograms whose bars have been tipped over and lined up end-to-end. We discuss affordances of parallel bargrams in the context of systems that support consumer-based information exploration and choice based on the attributes of the items in the choice set. Our tool called EZChooser has enabled a number of prototypes in such domains as Internet shopping, investment decisions, college choice, and so on, and a limited version has been deployed for car shopping. Evaluations of the techniques include an experiment indicating that trained users prefer EZChooser over static tables for choice tasks among sets of 50 items with 7-9 attributes.