Visual reasoning for information retrieval from very large databases

When the database grows larger and larger, the user no longer knows what is in the database and nor does the user know clearly what should be retrieved. How to get at the data becomes a central problem for very large databases. We suggest an approach based upon data visualization and visual reasoning. The idea is to transform the data objects and present sample data objects 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 clues, we hope to come up with better ways for formulating and modifying a user's query. A prototype system using the Visual Language Compiler and the VisualNet is then described.