Visualizing Scalars

Abstract

The previous chapter introduces the notion of the different degrees of freedom provided by the attributes of abstract visualization objects, together with some rules of thumb that help distribute features in data onto these attributes. This chapter now looks at the use of each technique for scalar data in turn, gradually working down the rows of Table 5.2. The large-scale organisation of the chapter thus reflects the dimension of the data domain, i.e., the independent variable. Within this overall approach, techniques for nominal and aggregated data are described first, followed by those for ordinal data. Since ordinal data may be continuous across the domain it requires a framework over which we can interpolate, so triangulation of 2D and 3D data is described at the appropriate point in each section.