Dynamic Visualization of Complex Systems
The interest in networks and complex systems visualization continues to grow, as new uses and tools emerge.
In this young field, however, there are many common problems and unsolved challenges, such as the fact that network visualizations tend to be good at displaying overall and abstract patterns, or helping identifying very local facts, but are poor building structured narratives. There exist two main visualization strategies: the global one, that often reproduces a shape known as hairball, in which relations are unreadable; and the local one, that gives rich information about specific relations yet loosing the context. Complex Systems are often interesting because of the relations and communication flows between global and the locality.
I propose a series of advanced interactive techniques that connect the local view and the global view, and that build narratives out of subsets of nodes: partial linearities out of the non-linearity. My techniques, based on graph theory, topology and geometrical algorithms, include the use of interactive back and forth transitions between local and global views, simulations and stimulations that help to understand the spread of influences and information in a system, and the use of the “reenactment mode” in which dynamical and temporal behaviors are reproduced in a way new stories are created. By using these techniques the interactor has a complete experience of exploration and obtains insight from local, global and intermediate scales.
In my presentation I'll be featuring several examples of interactive projects that visualize networks and complex systems such as genetic networks, conversations, books, system maps and even a television series.