(BQ) Part 1 book "Visualization analysis and design" has contents: Arrange spatial data, arrange networks and trees, map color and other channels, manipulate view, facet into multiple views, reduce items and attributes, analysis case studies,.and other contents. | Chapter 8 Arrange Spatial Data The Big Picture For datasets with spatial semantics, the usual choice for arrange is to use the given spatial information to guide the layout. In this case, the choices of express, separate, order, and align do not apply because the position channel is not available for directly encoding attributes. The two main spatial data types are geometry, where shape information is directly conveyed by spatial elements that do not necessarily have associated attributes, and spatial fields, where attributes are associated with each cell in the field. Figure summarizes the major approaches for arranging these two data types. In a visualization context, geometry data typically either is geographic or has explicitly been derived from some other data type due to a design choice. For scalar fields with one attribute at each field cell, the two main visual encoding idiom families are isocontours and direct volume rendering. For both vector and tensor fields, with multiple attributes at each cell, there are four families of encoding idioms: flow glyphs that show local information, geometric approaches that compute derived geometry from a sparse set of seed points, texture approaches that use a dense set of seeds, and feature approaches where data is derived with global computations using information from the entire spatial field. Why Use Given? The common case with spatial data is that the given spatial position is the attribute of primary importance because the central tasks revolve around understanding spatial relationships. In these cases, the right visual encoding choice is to use the provided spa- 179 180 The expressiveness principle is covered in Section . 8. Arrange Spatial Data tial position as the substrate for the visual layout, rather than to visually encode other attributes with marks using the spatial position channel. This choice may seem obvious from common sense alone. It also follows from the effectiveness .
