Abstract
Information visualization is the study of interactive visual representations of abstract data to reinforce human cognition. Most existing visualization techniques are not suited to explore and understand datasets from heterogeneous and complex sources. Assuming that agent-based models properly represent the complexity of a real system, we propose to use an approach based on the definition of an agent-based model to facilitate visual representation of simulation outputs and complex data. These concepts have been implemented in the GAMA modeling and simulation platform, in which we developed a 3D immersive environment offering the user different points of view and ways to interact. We implemented models chosen for their properties to support a linear progression in terms of complexity to test their flexibility, modularity, and adaptability. Finally, we demonstrate through the particular case of data visualization, how our approach allows us, in real time, to represent, clarify, or even discover dynamics and how that progress in terms of visualization can contribute, in turn, to improve the modeling of complex systems.