Based on the seminar that took place in Dagstuhl, Germany in June 2011, this contributed monograph 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."

Min Chen, Arie E. Kaufman and Roni Yage/ Volume graphics is concerned with graphics scenes defined in volume data types, where a model is specified by a mass of points instead of a collection of surfaces. The underlying mathematical definition of such a model is a set of scalar fields, which define the geometrical and physical properties of every point in three dimensional space. As true 3D representations, volume data types possess more descriptive power than surface data types, and are morphologically closer to many high-level modelling schemes in traditional surface graphics such as parametric surfaces, implicit surfaces and volume sweeping. The past decade has witnessed significant advances in volume visualisation, driven mainly by applications such as medical imaging and scientific computation. The work in this field has produced a number of volume rendering methods that enable 3D information in a volumetric dataset to be selectively rendered into 2D images. With modern computer hardware, such a process can easily be performed on an ordinary workstation. More importantly, volume-based rendering offers a consistent solution to the primary deficiencies of the traditional surface-based rendering, which include its inability to encapsulate the internal description of a model, and the difficulties in rendering amorphous phenomena. The emergence of volume-based techniques has not only broadened the extent of graphics applications, but also brought computer graphics closer to other scientific and engineering disciplines, including image processing, computer vision, finite element analysis and rapid prototyping.