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After employing position and colour we are left with control over the size, shape
and orientation of the objects that represent our cases or places. An almost infi-
nite number of subtle alterations could be made to these aspects of the visual
representation. It is not the number of variables that can be crammed into its
features, but the number of variables that can be visually appreciated and inter-
preted in each particular context (Box 8.1) that limits and forms our multivariate
visualization methods.
The visual objects of concern here are often referred to as glyphs, meaning
sculptured characters or symbols (a shortening of the word 'hieroglyphics' 2 ).
This chapter begins with the simplest of glyphs and moves through to some of
the more complex and a little harder to understand, although not necessarily less
successful, representations. The aim is to begin to learn what it is that makes
glyphs work as visual representations, and how, when and why they fail.
Box 8.1
Areal interpolation
Statistics have often had to be reallo-
cated among areal units in this topic.
Where the destination level was a
super-set of the source level, this was
a simple amalgamation. Where the
boundaries of the two did not coin-
cide, the problem was somewhat more
difficult.
The formulae used to estimate the
value of a statistic ( v) from one set of units ( i) to another ( j) relies upon there
being available a second variable ( p) known to be related to the prevalence
of the first variable. The value of the second variable must be known for
every areal unit created from the intersection of the two sets of boundaries
( p ij ) . The formula is then
n
p ij
p i v i
v j =
i =
1
2 Others claim as many as nine or more variables can be understood: 'Donna Cox created an
innovative technique that clearly displayed a record nine distinct variables simultaneously changing
in an animated videotape. To pack variables to such a density, Cox invented a unique 3-D wedge
shape, the glyph (from hieroglyphics, the Egyptian pictographs), to represent each computed portion
of the flowing plastic. The shape, color (the blue side of the spectrum for pressure and the red for
temperature), and orientation of the wedge indicate the state of the flowing material at particular
points. The finished videotape shows the plastic (in the form of an army of small wedges) marching
into the mould, swivelling, changing direction and color, and eventually settling and hardening in a
series of complex steps' (Anderson, 1989, p. 17).
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