Users, analysts and decision makers from science, industry, administration and the public are increasingly confronted with enormous amounts of data, which possess a very heterogeneous character both in terms of their content and their origin. On the one hand, satellites and measuring stations, e. g., provide high-dimensional data for Earth observation while smartphone users on the other hand can capture data of different types and varying quality. What content and structures are hidden in these data and how can they effectively be extracted and analyzed? How can the data help us to gain new insights into the world and derive reasonable decisions from it? The research field ‘Visual Analytics’ addresses these and other questions and tries to answer them in an iterative process that combines visual and automated analysis methods.
Our research group is engaged with researching and developing novel visual methods for the analysis of big data that place the human and his cognitive abilities at the center of the analytics process. To this end we use data mining techniques to process huge streams of data and to discover unexpected relationships and content therein. The results are then visualized in a user-oriented way such that the analyst is able to identify complex correlations, statistical uncertainties as well as peculiarities in the data. This requires intuitive interaction techniques between man and machine, which we examine and evaluate not only for classic input and output media but also for innovative devices such as large display walls, head-mounted displays or multi-touch tables. In order to enable a high degree of interactivity in the respective applications, efficient software architectures and rendering methods have to be created that should take advantage of the characteristics, i.a., of distributed systems, high-performance computing clusters, databases and graphics cards, respectively.
With our project partners from Max Planck Institute for Biogeochemistry in Jena, the Friedrich Schiller University in Jena and the Bauhaus University Weimar, we are initially working on cross-scale analysis methods and interactive visualizations for earth system analysis.