Visual Analytics: Combining Automated Discovery with Interactive Visualizations

Daniel A. Keim, Florian Mansmann, Daniela Oelke, Hartmut Ziegler

Abstract: In 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. Approaches, which work either on a purely analytical or on a purely visual level, do not sufficiently help due to the dynamics and complexity of the underlying processes or due to a situation with intelligent opponents. Only a combination of data analysis and visualization techniques make an effective access to the otherwise unmanageably complex data sets possible.