Multivariate relationship specification and visualization

In this dissertation, we present a novel method for multivariate visualization that focuses on multivariate relationshipswithin scientific datasets. Specifically, we explore the considerations of such a problem, i.e. we develop an appropriate visualization approach, provide a framework for the specification of multivariate relationships and analyze the space of such relationships for the purpose of guiding the user toward desired visualizations. The visualization approach is derived from a point classification algorithm that summarizes many variables of a dataset into a single image via the creation of attribute subspaces. Then, we extend the notion of attribute subspaces to encompass multivariate relationships. In addition, we provide an unconstrained framework for the user to define such relationships. Althoughwe intend this approach to be generally applicable, the specification of complicated relationships is a daunting task due to the increasing difficulty for a user to understand and apply these relationships. For this reason, we explore this relationship space with a common information visualization technique well suited for this purpose, parallel coordinates. In manipulating this space, a user is able to discover and select both complex and logically informative relationship specifications

Constant Density Displays Using Diversity Sampling

The Informedia Digital Video Library user interface summarizes query results with a collage of representative keyframes. We present a user study in which keyframe occlusion caused difficulties. To use the screen space most efficiently to display images, both occlusion and wasted whitespace should be minimized. Thus optimal choices will tend toward constant density displays. However, previous constant density algorithms are based on global density, which leads to occlusion and empty space if the density is not uniform. We introduce an algorithm that considers the layout of individual objects and avoids occlusion altogether. Efficiency concerns are important for dynamic summaries of the Informedia Digital Video Library, which has hundreds of thousands of shots. Posting multiple queries that take into account parameters of the visualization as well as the original query reduces the amount of work required. This greedy algorithm is then compared to an optimal one. The approach is also applicable to visualizations containing complex graphical objects other than images, such as text, icons, or trees