ABSTRACT
This chapter presents the various types of datasets commonly used in the visualization practice and detail their relative advantages, limitations, and constraints. It discusses several aspects related to efficiently implementing the dataset concept. The main goal of visualization is to produce pictures that enable end users get insight into data that describe various phenomena or processes, including both natural and human-controlled phenomena. The name reflects the fact that continuous data usually measure physical quantities that are studied by various scientific and engineering disciplines, such as physics, chemistry, mechanics, or engineering. The sampling and reconstruction mechanisms described so far can be applied to more data attributes than surface geometry alone. Some data visualization applications classify attribute data into node or vertex attributes and cell attributes. The suitability of one interpolation scheme versus the other one depends on the nature of the continuous data that the vector dataset samples.
