SPP 1335: Scalable Visual Analytics: Interaktive visuelle Analysesysteme für komplexe Informationswelten
Zusammenfassung der Projektergebnisse
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. Interactive visual data analysis techniques combine 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 unmanageable complex data sets becomes possible. Visual analysis techniques make the unexpected more easily discoverable and help to gain new cognitions and insights. The primary goal of the SPP 1335: Scalable Visual Analytics is to represent abstract data graphically in such a way that structural connections and relevant characteristics become visible. New visual analysis techniques were developed, which fulfill present and future requirements. The techniques enable scalable visual analysis systems, which connect automatic data analysis methods with interactive visualization techniques and can be integrated smoothly into custom-designed data exploration processes for the analysis of complex information spaces. In the SPP 1335 researchers from 17 German universities and institutes worked together with foreign researchers in highly interdisciplinary research projects over the last six years. The participants contributed expertise in the fields of information visualization, data analysis, and human-computer interaction, but also incorporated other areas of research such as statistical analysis, geo-spatial data analysis, and perceptual psychology. The close collaboration resulted in remarkable results that were achieved within the SPP 1335. Analysis methods, visualizations, and concepts were developed and combined to create scalable visual analytics systems that enable the exploration and analysis of complex information spaces. Thanks to successes in text analysis, movement and event analysis, life science and medicine and more generally in the field of exploration and analysis of complex and high-dimensional data, a number of real-world application problems could be tackled. These successes gave impulses for further research activities, one prominent example being the SFB-TRR 161. In addition to the scientific achievements, substantial funding-policy goals were achieved. One highlight being the reoccurring workshops promoting women in science at major visualization and visual analytics conferences.
