Aspects of Data in Visualization: Overview 

Characterization of data


[BRO92], [GAL94]

Overview of selected data characteristics

Nominal, ordinal, quantitative

Priorities of Visual Attribute for Various Data Types (Excerpt) [MAC86]

Quantitative Ordinal Nominal
Position Position Position
Length Density Hue
Angle Saturation Density
Slope Hue Saturation
Area Length Shape
Density Angle Length
Saturation Slope Angle
Hue Area Slope
Shape Shape Area

Point, Scalar, Vector

Syntactical categories, additionally characterized by dimensions

"Continuous" data

"Continuous" data can be represented by (samples of) function:

yi = fi (X), where X = (x1 , x2 , x3 , ..., xn ); i=[1,....,m]
x .... independent variables; e.g space, time, spectral ("dimensions")
y .... dependent variables ("parameters")
x, y large ... multidimensional, multiparameter, multivariate data

=> regular/irregular format

Expressive visualizations of functions: similar to scalar, quantitative, ordinal

Interpolation methods: must be meaningful in problem space

Computation time for visualization techniques faster on regular grids

Note: for valid data must avoid aliasing artifacts

Topology/structure of non-continuous data

Other data characteristics

Aspects of Data
HyperVis Table of Contents

Last modified on February 11, 1999, G. Scott Owen,