Information visualization and Internet collaboration are key techniques for working in an information-rich world. Visualization systems apply humans' impressive visual processing capabilities to make sense of abstract data. Internet applications let people around the globe work together, enter and leave collaborations on their own schedules, even multitask between several projects in different windows. Collaborative Internet visualization applications put these together and enable multiple analysts to collaborate remotely. However, this flexibility and the lack of real-world awareness cues make it difficult for users to keep track of what they and other users are doing and have done during each collaboration session. This thesis describes our application of session history and multi-user awareness tools to reduce the cognitive load of collaborative visual data exploration. We introduce a history model, a history management framework, and a history-based recommender system for collaborative visual data exploration systems. The history model and framework support synchronous collaborations of multiple collaborative individuals or groups. They capture and store group collaborative visualization sessions and history metadata including user annotations in a history database. The history management framework also includes a number of features and tools for users to enhance and interact with the history data: annotating, querying, visualizing and analyzing, replaying, editing and making use of collaborative exploration sessions. The exploration recommender system generates exploration recommendations for users based on their own or their group's previous exploration sessions and profiles. The history management framework and the exploration recommender system have been realized in two example applications. The first is a prototype web-based collaborative visualization system used to test new kinds of collaboration features. Selected features are incorporated into a collaborative visualization project named WEAVE, a project funded by the Open Indicators Consortium for the web-based visualization and analysis of a variety of measures and indicators useful for urban planning.

We describe interactions between kinetic (moving) and static information displays. We have implemented "moxel" kinetic displays in a classic discovery platform with many standard information visualization and analytic tools, and experimented with interactions between them. Moxels, which generalize pixels, are an advanced, moving, form of iconographic display of the kind first developed in static form by Pickett and White (1966). As with the static graphic icons of those early displays, moxels provide a way of mapping together in one image multiple data variables, but with potentially more potency with in-place motion. We show examples of how the two kinds of displays have been integrated, and discuss issues with the integration of dynamic and static visualizations in a single environment. We discuss several interaction paradigms between them including linked brushing, multiple selections, and operations on selected regions.