Many real-world datasets are large, multivariate, and relational in nature and relevant associated decisions frequently require a simultaneous consideration of both attributes and connections. Existing visualization systems and approaches often make an explicit trade-off between either affording rich exploration of individual data units or exploration of the underlying network structure. We demonstrate through a system called Graphicle how network structure can be layered on top of unit visualization techniques to create new opportunities for visual exploration of large multivariate networks.
The Computational Enterprise Science Lab focuses on the design, analysis, and management of complex enterprise systems (e.g. organizations, supply chains, business ecosystems) using information visualization, modeling/simulation, and system science approaches.