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Multivariate Network Visualization

Dagstuhl Seminar # 13201, Dagstuhl Castle, Germany, May 12-17, 2013, Revised Discussions

Paperback Engels 2014 9783319067926
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This book is the outcome of the Dagstuhl Seminar 13201 on Information Visualization - Towards Multivariate Network Visualization, held in Dagstuhl Castle, Germany in May 2013. The goal of this Dagstuhl Seminar was to bring together theoreticians and practitioners from Information Visualization, HCI and Graph Drawing with a special focus on multivariate network visualization, i.e., on graphs where the nodes and/or edges have additional (multidimensional) attributes. The integration of multivariate data into complex networks and their visual analysis is one of the big challenges not only in visualization, but also in many application areas. Thus, in order to support discussions related to the visualization of real world data, also invited researchers from selected application areas, especially bioinformatics, social sciences and software engineering. The unique "Dagstuhl climate" ensured an open and undisturbed atmosphere to discuss the state-of-the-art, new directions and open challenges of multivariate network visualization.


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Over Matt Ward

MATT WARD is the research lead for Bernard Marr & Co. Matt has a background in investigative journalism and spent the last few years working closely with Bernard Marr on the latest technology topics. Matt is an expert and experienced writer in the field of business technology and artificial intelligence, where he has worked with companies such as IBM, Intel, Citibank and NASA.

Andere boeken door Matt Ward


Introduction to Multivariate Network Visualization.- Multivariate Networks in Software Engineering.- Multivariate Social Network Visual Analytics.- Multivariate Networks in the Life Sciences.- Tasks for Multivariate Network Analysis.- Interaction in the Visualization of Multivariate Networks.- Novel Visual Metaphors for Multivariate Networks.- Temporal Multivariate Networks.- Heterogeneous Networks on Multiple Levels.- Scalability Considerations for Multivariate Graph Visualization.

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