To really master the challenges of the information age, we have to combine different research disciplines in an effective way. Visual analytics has become the new term for a field that links information visualization, data mining, and cognitive science, among others, to facilitate analytical reasoning. While everyone agrees on the necessity of such interdisciplinarity in visual analytics, we have only just begun to build sustainable bridges between the respective research communities. The goal of VisMaster, a European coordination action, is to build a visual analytics community with strong ties between information visualization and four selected disciplines: cognitive science, data mining, data management, and geographic sciences. This talk presents notions about these ties, shows examples of increased integration, and looks ahead at the next steps in this direction.

In research and development as well as numerous application areas fast growing data sets develop with ever higher complexity and dynamics. A central challenge is to filter the substantial information and to communicate it to humans in an appropriate way. Visual analysis techniques extend the perceptual and cognitive abilities of humans with automatic data analysis techniques. Only by a combination of data analysis and visualization techniques an effective access to otherwise unmanageably complex data sets is possible. Visual analysis techniques help to gain insights and to optimize and steer complicated processes. Approaches, which work either on a purely analytical or on a purely visual level, do not help due to the dynamics and complexity of the underlying processes or due to a situation with intelligent opponents.

In the talk, I will introduce the basic idea of Visual Analytics, explain how automated analysis and visualization methods can be combined, discuss the main challenges of Visual Analytics, and show that the combined automatic and visual analysis is the only chance to capture the complex, changing characteristics of the data and to take suitable measures. To demonstrate the idea of Visual Analytics, examples from a number of application areas will be provided.