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Case Studies of Visualization in the Social Sciences:
An Introduction

David Unwin & Peter Fisher

Departments of Geography

Birkbeck College
7-15 Gresse St
University of Leciester
University Road

1. Background

In the last few years Scientific Visualisation (ViSc) (as defined in the landmark report to the US National Science Foundation; McCormick et al., 1987) has become one of the standard investigative tools of all the physical and natural sciences (Hall, 1994). Visualisation in the sense used here is not a set of techniques to communicate the known as is done with traditional graphics and maps, but a means, a mechanism, for exploring data sets and structures, to generate ideas and explore alternatives. This has been defined as 'exploring data and information graphically, as a means of gaining understanding and insight into the data' (Earnshaw and Wiseman, 1992: Brodlie et al., 1993), and is often referred to as visual data analysis.
Many factors, both practical and theoretical, have driven this change from traditional static displays or presentations to visualization:

  • Developments in sensor technology and automated data capture have provided data at rates faster than can be easily converted into knowledge. These streams, or firehoses, of data are being added to the warehouses full of old data (McCormick et al., 1987). Such developments are appropriate to much social science data at, for example, the Essex Data Archive such as the Census and Opinion Polls.
  • Some of the most exciting discoveries in science have been associated with non-linear dynamics where apparently simple equations like the finite difference form of the logistic Xt+1 = aXt ( 1 - Xt ) conceal enormously complex, but real-world like behaviour that can only be appreciated when displayed graphically (Lorenz, 1993).
  • As science has progressed to produce ever more complex simulation models, so it has become necessary to use visualisation as the only practicable way to assimilate all the model outputs.
  • Improvements in computing mean that we now have networks of very fast workstation computers available whose primary output is to high resolution, colour screens. In looking at these effects of technology it is easy to lose sight of what is fast becoming commonplace. An obvious example is resolution and colour. In 1980 the Census Research Unit at Durham University published an Atlas of the 1971 UK Census of Population (Census Research Unit, 1980) which used the then new laser technology to produce, at great difficulty and expense, maps with individual colour symbolism for each and every kilometre grid square over Britain. At the time, these were the most detailed population maps at this scale and resolution ever produced, but using modern hardware similar displays are relatively easy to create at even higher spatial resolution using a full gamut of colours (Martin and Bracken, 1991).

This newer technology means that we can create entirely new forms of display which extend the number of available graphic variables beyond Bertin's original seven (plan, size, shape, value, orientation, hue, texture). These new visual variables include projection (Dorling, 1992, 1994), animation (Tobler, 1970; Moellering, H., 1976) and sound (Fisher, 1994). A major problem confronting the use of these new graphic variables is that, unlike conventional maps we know almost nothing about good design using them (Monmonier, 1991; Krygier, 1996). This leads to a potential for contrasting styles of use (Table 1).

Table 1
Comparison of Traditional and Computer Displays



Use symbolism

Often aim for realism (VR)

Are selective

Try to use as much data as possible

Are end products

Are aids to understanding

Demonstrate the known

Detect the unknown

Intended for many viewers

Used by one person



Used many times

Used once

Restricted dimensions (x,y)


ViSc is clearly in the tradition of exploratory data analysis in statistics (Tukey, 1977) in as much as it emphasises the use of graphics in the development of ideas, not, as in traditional graphics, in their presentation. Indeed, ViSc often turns the traditional process on its head by developing ideas graphically and then presenting them using non-graphic means.
McCormick et al. (1987) talk about visualisation as a method of analysis which 'transforms the symbolic into the geometric, enabling researchers to observe their simulations and computations' (p3) and 'a tool for both interpreting image data fed into a computer, and for generating images for complex multidimensional data sets'.

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