A Bayesian Paradigma for Dynamic Graph LayoutUlrik

Dynamic graph layout refers to the layout of graphs that change over time. These changes are due to user interaction, algorithms, or other underlying processes determining the graph. Typically, users spend a noteworthy amount of time to get familiar with a layout, i.e. they build a mental map ELMS91]. To retain this map at least partially, consecutive layouts of similar graphs should not diier signiicantly. Still, each of these layouts should adhere to constraints and criteria that have been speciied to improve meaning and readability of a drawing. In BW97], we introduced random eld models for graph layout. As a major advantage of this formulation, many diierent layout models can be represented uniformly by a random variable. This uniformity enables us to now present a framework for dynamic layout of arbitrary random eld models. Our approach is based on Bayesian decision theory and formalizes common sense procedures. Example applications of our framework are dynamic versions of two well-known layout models: Eades' spring embedder Ead84], and Tamassia's bend-minimum orthogonal layout model for plane graphs Tam87].