ABSTRACT
Domain-modeling techniques form the last class of visualization techniques. This chapter presents a number of different modeling techniques: cutting, selection, constructing grids from scattered points, and grid-processing techniques. Cutting methods are domain-modeling techniques that map the data from a given source domain to a target subdomain. The chapter provides some of the most widely used variants of the cutting operation: extracting a brick, slicing, cutting with an implicit function, and generalized cutting. Extracting a brick, also called bricking or extracting a volume of interest, is a cutting operation that produces a target dataset with the same dimensionality as the source dataset. In contrast to cutting, which projects the values of a source dataset to a target domain, selection methods extract the data from a source dataset based on data properties. Since selection generally yields an arbitrary subset of points and cells from the input dataset, its output is an unstructured grid.
