SPP 1335:  Scalable Visual Analytics: Interactive Visual Analysis Systems of Complex Information Spaces

• Subject Area: Computer Science, Systems and Electrical Engineering
• Term: from 2008 to 2018
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 43045503

Data sets with rapidly growing complexity and dynamics are generated in research and development as well as in numerous application areas. A central challenge is to detect the important information and to communicate it to humans in an appropriate way. Interactive visual data analysis techniques extend the perceptual and cognitive abilities of humans with automatic data analysis techniques. Only by a combination of data analysis and visualisation techniques, an effective access to otherwise unmanageably complex data sets is possible. Visual analysis techniques make the unexpected more easily discoverable and help to gain new insights. The primary goal in the field of visual analytics is to represent real or abstract data graphically in a way that structural connections, relevant characteristics and other interesting properties of the data can be easily detected.
Focus of the Priority Programme is research covering the theoretical foundations of new visual analytics algorithms, the development and practical implementation of scalable visual analytics techniques, as well as their integration and evaluation. A central challenge is scalability, which relates not only to the size of the data set but also to important properties of the data such as dimensionality, production rate, homogeneity, actuality, precision and completeness. In addition, the visual analytics techniques themselves should be scalable, which means that they should be interactive and convey the quality and relevance of the data.
The scalability of visual analytics methods can only be achieved by a close cooperation between scientists from different areas of computer science. Participants in the Priority Programme come from the research areas visualisation, data analysis and data base technology, as well as human computer interaction, but also include other areas, which contribute to visual analytics, such as statistical analysis, geographical data analysis and cognitive science. Most of the projects combine at least two different research areas. The goal is to develop new techniques, which are successfully used in a concrete application and show significant improvements over existing approaches.

• DFG Programme: Priority Programmes
• International Connection: USA

Projects

• Developing new visual analysis methods to be integrated into simulation processes, focusing on the exploration of cell biological systems in space and time (Applicant Schumann, Heidrun )
• Koordinationsprojekt (Applicant Keim, Daniel )
• Scalable Visual Analysis of Patent and Scientific Document Collections (Applicant Ertl, Thomas )
• Scalable Visual Analytics of Video Data (Applicants Heidemann, Gunther ;  Weiskopf, Daniel )
• The project develops new techniques for the interactive navigtion, visualization, and analysis of heterogeneous biological networks (Applicants Kaufmann, Ph.D., Michael ;  Kohlbacher, Oliver ;  Lenhof, Hans-Peter )
• Topology-based Visual Analysis of Information Spaces (Applicant Scheuermann, Gerik )
• Towards semantically steered navigation in shape spaces exemplified by rodent skull morphology in correlation to external attributes (Applicants Klein, Reinhard ;  Schunke, Anja )
• Umfassende visuelle Informationssuche in multidimensionalen Datensätzen (Applicants Magnor, Marcus ;  Theisel, Holger )
• Variational Methods for Model-based Interacitve Analysis of Flows (Applicants Cremers, Daniel ;  Rumpf, Martin )
• Visual analysis of movement and event data in spatiotemporal context (Applicants Keim, Daniel ;  Wrobel, Stefan )
• Visual Analytics for Large and heterogeneous Life Science data with emphasis on expression data (Applicants Nieselt, Kay Katja ;  Scheuermann, Gerik )
• Visual Analytics Methods for Modeling in Medical Imaging (Applicant Landesberger von Antburg, Tatiana )
• Visual Analytics methods to steer the subspace clustering process (Applicants Deussen, Oliver ;  Seidl, Thomas )
• Visual feature space analysis (Applicant Schreck, Tobias )
• Visual Interactive Exploration of Geo-Located Infrastructure and Facilities in Urban Areas (Applicant Boll, Susanne )
• Visualization of and interaction with complex graphs on large-scale and high-resolution displays: models, metaphors, and interaction paradigms (Applicant Liggesmeyer, Peter )
• Visually guided exploration of point cloud data in Euclidean space (Applicant Giesen, Joachim )
• Visuelle Analyse in der Epidemiologie (Applicants Preim, Bernhard ;  Tönnies, Klaus-Dietz ;  Völzke, Henry )
• Zoomable Cell (Applicants Gumhold, Stefan ;  Schroeder, Michael )

• Spokesperson: Professor Dr. Daniel Keim