When the database grows larger and larger, the user no longer knows what is in the database. Nor does the user know clearly what should be retrieved. How to get at the data becomes a central problem for very large databases. This research addresses this problem through data visualization and visual reasoning. The main idea is to transform the data objects and present sample data in a visual space. The user can then incrementally formulate the information retrieval request in the visual space. By combining data visualization, visual query, visual examples, and visual cues, this research will yield better ways of formulating and modifying users' queries. A prototype system has been developed to serve as an experimental testbed. This research will develop a framework for testing new methodologies for visual reasoning as applied to information retrieval in very large databases. It will also lead to more powerful iconic user interfaces, and combine previous research results in spatial reasoning, example-based programming, and approximate retrieval from databases.
