A successful visual database system must provide facilities to manage both image data and the products extracted from them. The extracted items usually consist of textual and numeric data from which multiple visualizations can be created. Such visualizations are difficult to automate because they are domain-specific and often require data from multiple sources. In the Database Environment for Vision Research (DEVR) we address these issues. DEVR is an entity- oriented, scientific, visual database system. In DEVR, entities are stored in hierarchical, relational data structures. The schema for each entity contains a name, a set of properties, a set of parts, a set of attributed relations among the parts and a set of graphic definitions which describe how to build instance-specific visualizations. Graphic definitions are composed of one or more graphical primitives. For each primitive, the user identifies required data sources by graphically selecting various properties or parts within the schema hierarchy. As instances are created, the graphic definitions are used to automatically generate visualizations, which can later be viewed via a graphical browser. In this paper, we describe the visualization subsystem of the DEVR system, including schema construction, graphical definition, and instance browsing.