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.
Cited By
- Maack R, Scheuermann G, Hagen H, Peñaloza J and Gillmann C (2023). Uncertainty-aware visual analytics: scope, opportunities, and challenges, The Visual Computer: International Journal of Computer Graphics, 39:12, (6345-6366), Online publication date: 1-Dec-2023.
Saeed N, Nam H, Haq M and Muhammad Saqib D (2018). A Survey on Multidimensional Scaling, ACM Computing Surveys, 51:3, (1-25), Online publication date: 31-May-2019.- Jabbari A, Blanch R and Dupuy-Chessa S Beyond horizon graphs Proceedings of the 30th Conference on l'Interaction Homme-Machine, (73-82)
Index Terms
- Scientific Visualization: Uncertainty, Multifield, Biomedical, and Scalable Visualization
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Reviews
Soubhik Chakraborty
“One picture is worth a thousand words” goes the age-old saying. The term “scientific visualization” refers to the display of abstract data, obtained directly by observation or indirectly by simulation, through graphs and images. This carefully edited volume consists of papers contributed by the participants of a seminar held in Dagstuhl, Germany in 2011. In the editors' own words, “ Since vision dominates our sensory input, strong efforts have been made to bring the mathematical abstraction and modeling to our eyes through the mediation of computer graphics.” The four crucial areas within the domain of scientific visualization-uncertainty visualization, multi-field visualization, biomedical visualization, and scalable visualization-are covered in this volume. Part 1, on uncertainty visualization, opens up with an overview and a discussion on the state of the art of the topic, explaining the meaning of uncertainty and its mathematical modeling (this section includes probability theory). Other topics covered include color vision deficiency, analysis of uncertain scalar data with hixels, uncertainty in problem solving and in predictive models, uncertainty in decision making, and fuzzy fibers. Part 2, on multi-field visualization, first gives the definition of multi-field followed by its categorization, and discusses the fusion of visual channels, derived fields (pairwise distances and correlation measures, alignment and dependency measures, and so on), interactive visual exploration and analysis, feature analysis in multi-fields, and future challenges in this area. Part 3, on biomedical visualization, covers visualization in connectomics (for example, EEG, MEG, MRI, and fMRI; neural network modeling; and brain mapping); challenges in visualization in biology and medicine; and visualization associated with ultrasound and blood flow. Part 4, on scalable visualization, opens up by discussing vector field visualization; cross-scale, multi-scale, and multi-score data visualization; scalable devices; scalable representation; distributed post-processing; and rendering for large-scale scientific visualizations. The book will surely be well received by scientists, engineers, and medical practitioners. It is a must-have for a scientific library. Online Computing Reviews Service
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