In this project we propose novel internal and visual representations of dynamic and evolving networks that are both more scalable and intuitive than traditional representations. These representations are tuned to reflect the reality that most networks are not static over either time or topology, but rather they are complex time-varying entities that morph significantly with time. Our visual representations provide an "out of the box" solution to the age old problems of clutter and overlap that have plagued traditional network visualization efforts, and we provide a smoother more continuous representation that maps naturally to the human perceptual system. The target domain for our application is in situation awareness in net-centric military applications. We will enable the user to have a better awareness of the information within, and context provided by, the rich network environment. A key feature of our technology is the ability to effectively portray uncertainties within this environment.
Keywords: NETWORK, VISUALIZATION, UNCERTAINTY, SITUATION AWARENESS, NETWORK VISUALIZATION
