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Based on the seminar that took place in Dagstuhl, Germany in June 2011, this contributed volume studies the four important topics within the scientific visualization field: uncertainty visualization, multifield visualization, biomedical visualization and scalable visualization.
• Uncertainty visualization deals with uncertain data from simulations or sampled data, uncertainty due to the mathematical processes operating on the data, and uncertainty in the visual representation,• Multifield visualization addresses the need to depict multiple data at individual locations and the combination of multiple datasets,• Biomedical is a vast field with select subtopics addressed from scanning methodologies to structural applications to biological applications,• Scalability in scientific visualization is critical as data grows and computational devices range from hand-held mobile devices to exascale computational platforms.
Scientific Visualization will be useful to practitioners of scientific visualization, students interested in both overview and advanced topics, and those interested in knowing more about the visualization process.
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Enabling insight into large and complex datasets is a prevalent theme in visualization research for which different approaches are pursued.
Topology-based methods are built on the idea of abstracting characteristic structures such as the topological skeleton from the data and to construct the visualizations accordingly. There are currently new demands for and renewed interest in topology-based visualization solutions. This book presents 13 peer-reviewed papers as written results from the 2005 workshop “Topology-Based Methods in Visualization” that was initiated to enable additional stimulation in this field. It contains a longer chapter dedicated to a survey of the state-of-the-art, as well as a great deal of original work by leading experts that has not been published before, spanning both theory and applications. It captures key concepts and novel ideas and serves as an overview of current trends in topology-based visualization research.
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