Visual Analysis of Heterogeneous Data
Gaining insights by exploring massive, complex data is the grand challenge of Visual Analytics - the science of analytical reasoning.
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Gaining insights by exploring massive, complex data is the grand challenge of Visual Analytics - the science of analytical reasoning. As heterogeneous data from different sources is being increasingly linked, it becomes difficult for users to understand how the data is connected, to identify what means are suitable to analyze a given data set, or to find out how to proceed for achieving a given analysis task. The analyst support a user needs is twofold: first, the analyst needs to be oriented within the information landscape - orientation support; and secondly, with orientation as a prerequisite, the user can be guided towards a specific analysis goal by following concrete recommended steps - guidance support. This talk will present work that illustrates how such a user support can be achieved on both of these levels. The presented visualization techniques are realized in the Caleydo visual analysis framework and demonstrated by means of real-world biomolecular data.
Marc Streit is assistant professor at the Institute of Computer Graphics at the Johannes Kepler University Linz, Austria. He received his master (2007) and PhD (2011) degree from the Graz University of Technology. In 2010 he was awarded with the Best Paper Award at the ACM Graphics Interface Conference and recently, in 2011, at the IEEE Conference on Information Visualization. His research focuses on the Caleydo project where he works on topics including information visualization, visual analytics and bioinformatics.
This lecture is organized by the Computer Graphics Group at the Institute of Computer Graphics and Algorithms. Supported by the Austrian Computer Society (OCG).
- Marc Streit, Institute of Computer Graphics, Johannes Kepler University Linz
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