“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.