4.1 Visualization matters  (Page 2/4)

The human visual system: the user is key.

Will Schroeder et al. in The Visualisation Toolkit (Schroder et al. 1998) stated “informally visualisation is the transformation of data or information into pictures. Visualisation engages the primal human sensory apparatus, vision, as well as the processing power of the human mind. The result is a simple and effective medium for communicati ng complex and/or voluminous information.” Based upon using the massive amount of brain power within the human visual system that constitutes about 1/3 of the total brain size, visualizations have been shown to be one of the best and sometimes the only way of conveying a huge amount of data in a short period of time. One of the key reasons for visualization as a specific field to study was the rapid increase in quantity of data being produced by simulations on supercomputers of physical, natural and theoretical problems. This has been termed as the data-deluge problem and frequently has been so large that graphical representations offer the only viable way to assimilate the data.

The simulation models themselves have also been increasing in complexity, involving large numbers of independent and dependent variables whose relationships need to be understood. For example, in climate modelling, we may wish to explore how temperatures, water vapour content, pressure, wind directions and velocities vary within a 3D region, over time and all at once. The process of visualization is therefore concerned with ways to represent the data as well as defining tools for interactively exploring the multidimensional and multi-variant models. One of the early active research areas was to find ways to link this visualization process with interactive control of the simulations themselves, opening up completely new possibilities for interactive exploration and understanding of complex phenomena. Over the years a number of visualization systems have emerged, which provide a framework for this kind of model exploration.

Visualization tools: evaluating a graph

Plenty of literature and course notes are now available but as a simple example, a few rules are presented next on how to create an effective graph. A graph should present a reasonable amount of data, say something about the behaviour of that data and it should avoid giving a false impression of the data. In other words, the graph must communicate something. Tukey (1977) pp 128,157 said “ t here cannot be too much emphasis on our need to see behaviour. Graphs force us to note the unexpected; nothing could be more important” .

Excel and MATLAB are two of the most popular visualization tools currently used, even though users may not consider them as such. They produce numerous 2D and 3D graphs of different sizes and dimensions but the visualization choices are rarely thought about. Figure 2 shows two views using MATLAB of a simple formulae (y = (x-1) ^-2 + 3(x-2) ^-2 ). Both show the same numerical sampled data but the second, by cropping the y-axis to a limited range [0:50], could be said to present a large amount of extra information highlighting an important area. This process has been termed focus and context zoom interaction.