Abstract
Sensor Networks are quickly realizing a potential to support data sensing, gathering and processing applications. These applications all share the same characteristics about acquiring large amounts of data, in some cases, at high frequency rates or with multiple imagery streams. These data requirements are exacerbated for large and ultra-scale sensor networks. For many intended applications, the information gathered by sensor networks needs to be presented to humans so that understanding leading to decision making is facilitated. A new visualization approach aimed at exploiting the relationship between an underlying model and the acquired data is proposed. This approach is based on an orthogonal organized finite state machine representation and includes multiscale, 3D scene embedded and transdimensional visualizations. Examples are presented that high-light the approach.