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.

In this paper we propose new visual interface technology to address multidimensional data exploration and browsing tasks. MultiNav, a prototype from GTE Laboratories, is based upon a multidimensional information model that affords new data exploration and semantically structured browsing interactions. The primary visual metaphor is based on sliding rods, each of which is associated with an information dimension from the underlying model. Users can interactively select value ranges along the rods in order to reveal hidden relationships as well as query and restrict the set through direct manipulation. A novel focus+context view is afforded in which detail about individual items is revealed within the context of the global multidimensional attribute space. We propose a novel interaction technique to change focus, which is based on dragging rods from side to side. We relate this work on multidimensional information visualization to other research in the area, including Parallel Coordinates, Dynamic Histograms, Dynamic Queries, and focus+context tables.*.