Institute for Data Analysis and Visualization

For types of data visualization where the cost of producing images is high, and the relationship between the rendering parameters and the image produced is less than clear, a visual representation of the exploration process can make the process more efficient and effective. Image graphs represent not only the results but also the process of data visualization. Each node in an image graph consists of an image and the corresponding visualization parameters used to produce it. Each edge in a graph shows the change in rendering parameters between the two nodes it connects. Image graphs are not just static representations: users can interact with a graph to review a previous visualization session or to perform new rendering. Operations which cause changes in rendering parameters can propagate through the graph. The user can take advantage of the information in image graphs to understand how certain rendering parameter changes affect visualization results. Users can share the image graphs they create to streamline the process of collaborative visualization. We have implemented a volume visualization system using the image graph interface. While our examples in the paper come from this implementation, we also discuss the applicability of image graphs to other problem domains.