Research & Projects
In data science, research and innovation in visual analytics and information visualization are crucial as the human analyst is indispensable for the analytical process and the final decision making. In this context, the iVis group mainly focuses on the explorative analysis and visualization of typically large information spaces, for example, in environmental research, transportation systems, social sciences, or artificial intelligence.
Information Visualization (InfoVis) is a research field that focuses on the use of visualization techniques to help people understand and analyze data. While related fields such as Scientific Visualization involve the presentation of data that has some physical or geometric correspondence, Information Visualization centers on abstract information without such correspondences. Examples of such abstract data are symbolic, tabular, networked, hierarchical, or textual information sources. Information Visualization also combines aspects of related fields, such as Scientific Visualization, Human-Computer Interaction, Data Mining, Information Design, Cognitive Psychology, Visual Perception, Cartography, Graph Drawing, Sonification, and Computer Graphics.
The research field of visual analytics (VA) investigates ways to better comprehend big and complex data by human- and machine-centered analyses that provide means for understanding system properties and characteristics from the existing data sets. At large, visual analytics combines the strengths of human and computational data processing, and it is formally defined as “the science of analytical reasoning facilitated by interactive visual interfaces”.