A Framework for Knowledge-Based, Interactive Data Exploration

Abstract

In this paper we propose a framework that combines the functionality of data exploration and automatic presentation systems to create a knowledge-based interactive data exploration system. The purpose of a data exploration system is to enable users to uncover and extract relationships hidden in large data sets. The purpose of an automatic presentation system is to reduce the need for users to have graphic design expertise and for them to spend a lot of time interacting with graphics packages to view their data. Previous work on data exploration was limited to query mechanisms that were often complex to learn and difficult to use, data manipulation mechanisms that did not provide complete coverage of the operations needed by users (especially the ability to form ad hoc groupings of data), and graphics that were restricted to a small set of predefined visualizations. Automatic presentation research, although addressing these issues, has been limited to the display of small data sets. Furthermore, this research has not supported interactive, user-directed processes of design and data manipulation in automatic presentation systems. We propose a framework that overcomes these limitations of current data exploration systems and integrates new interactive capabilities with automatic presentation components. This approach to supporting data exploration integrates recent work on SageTools, an environment for interactive and automatic presentation design, with a prototypical interactive data manipulation system called IDES. In this paper we present our work on the IDES data manipulation capabilities and discuss requirements for coordinating them with automatic presentation of large data sets.