Jörn Kohlhammer

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1 Department of Computer and Information Science, University of Konstanz, 78457 Konstanz, Germany, keim@informatik.uni-konstanz.de 2 Fraunhofer Institute for Intelligent Analysis and Information Systems(IAIS), Schloss Birlinghoven 53754 Sankt Augustin, Germany, gennady.andrienko@iais.fraunhofer.de 3 Université Paris-Sud, INRIA, Bât 490, F-91405 Orsay Cedex,(More)
Data Nodes, Edges Display Interactive Display Visual Analogues VisualItems in ItemRegistry User Figure 6.3: The Information Visualisation Reference Model, adapted from Heer et al.[57] 6.2 State of the Art 93 a visual analytics issue that should be better tackled by all the visualisation communities. Blending different kinds of visualisations in the same(More)
The analysis of large graphs plays a prominent role in various fields of research and is relevant in many important application areas. Effective visual analysis of graphs requires appropriate visual presentations in combination with respective user interaction facilities and algorithmic graph analysis methods. How to design appropriate graph analysis(More)
We present MotionExplorer, an exploratory search and analysis system for sequences of human motion in large motion capture data collections. This special type of multivariate time series data is relevant in many research fields including medicine, sports and animation. Key tasks in working with motion data include analysis of motion states and transitions,(More)
Many companies have recognized the strategic importance of the knowledge hidden in their large databases and have built data warehouses. Typically, updates are collected and applied to the data warehouse periodically in a batch mode, e.g., over night. Then, all derived information such as index structures has to be updated as well. The standard approach of(More)
Solving Problems with Visual Analytics Jörn Kohlhammer a,∗, Daniel Keim b, Margit Pohl c, Giuseppe Santucci d, Gennady Andrienko e a Fraunhofer IGD, Fraunhoferstr. 5, 64283 Darmstadt, Germany b University of Konstanz, 78457 Konstanz, Germany c Vienna University of Technology, Favoritenstraße 9-11, A-1040 Wien, Austria d Sapienza Università di Roma, Via(More)
Visual-interactive cluster analysis provides valuable tools for effectively analyzing large and complex data sets. Due to desirable properties and an inherent predisposition for visualization, the Kohonen Feature Map (or Self-Organizing Map, or SOM) algorithm is among the most popular and widely used visual clustering techniques. However, the unsupervised(More)
The analysis of large graphs plays a prominent role in various fields of research and is relevant in many important application areas. Effective visual analysis of graphs requires appropriate visual presentations in combination with respective user interaction facilities and algorithmic graph analysis methods. How to design appropriate graph analysis(More)
Visual Analytics seeks to combine automatic data analysis with visualization and human-computer interaction facilities to solve analysis problems in applications characterized by occurrence of large amounts of complex data. The financial data analysis domain is a promising field for research and application of Visual Analytics technology, as it(More)