Introduction to the topics of this module

Visualization, meant as the “The display of data with the aim of maximizing comprehension rather than photographic realism. [1] , has had a great expansion over the last years thanks to the availability of more and more powerful computers at low cost. The discipline of Information Visualization (IV) (Spence, 2001; Card et al., 1999) was originated in late ’80 with the intent to explore the use of computers to generate interactive, visual representation to explain and understand specific features of data. The basic principle of IV is to present data in a visual form and use human perceptual abilities for their interpretation.

As in many other fields, several people have tried to give a rigorous, scientific definition of the discipline of IV. The definition that received most consensus from the community of the researchers seems to be the one given by Card et al. in their “bible” of IV: the readings (Card et al., 1999). According to them, IV is: “The use of computer-supported, interactive, visual representations of abstract data to amplify cognition ”. By this definition, four terms are the key to understand this domain: visual representation , interaction , abstract data and cognitive amplification . We will try to analyze each of them with the purpose of clearly describe the field and their applications.

Visual representations


Some graphical representations of data.

There are several situations in the real world where we try to understand some phenomena, data, and events using graphics. Some aspects, such as when people need to find a route in a city, the stock market trends during a certain period, the weather forecast, may be understood better using graphics rather than text. Graphical representation of data, compared to the textual or tabular (in case of numbers) one, takes advantage of the human visual perception which is very powerful as they instantly convey large amounts of information to our mind, and allow us to recognize essential features and to make important inferential processes. This is possible thanks to the fact that there's a series of identification and recognition operations that our brain performs in an "automatic" way without the need to focus our attention or even be conscious of them. Perceptual tasks that can be performed in a very short time lapse (typically between 200 and 250 milliseconds or less) are called pre-attentive , since they occur without the intervention of consciousness (Ware, 1999).

Computers may facilitate the visualization process with some visualization tools. This is especially true in the latest years with the use of more and more powerful computers at low cost. However, the above definition is independent from computers: although computers can facilitate visualization, it still remains an activity that happens in the mind.


Recently there has been great progress in high-performance, affordable computer graphics. Common personal computer has reached a graphic power that only 10 years ago was possible only with very expensive graphic workstations specifically built for the graphic process. At the same time, there has been a rapid expansion in information that people have to process for their daily activities. This need lead scientists to explore new ways to represent huge amount of data with computers, taking advantage of the possibility of users to interact with the algorithms that create the graphical representation. Interactivity takes advantage of people’s ability to also identify interesting facts when the visual display changes, and allows them to manipulate the visualization or the underlying data to explore such changes.

Abstract data

IV definitions introduce the term “abstract data”, for which some clarification is needed. The data itself can have a wide variety of forms, but we can distinguish between data that have a physical correspondence and is closely related to mathematical structures and models (e.g. the airflow around the wing of an airplane, or the density of the Ozone layer surrounding earth), and data that is more abstract in nature (e.g. the stock market fluctuations, or the effects of temperature on the Napoleon’s army movements in the Russian campaign). The former is known as Scientific Visualization , and the latter as Information Visualization . (Spence, 2001; Uther, 2001; Hermann et al., 2000). Scientific Visualization was developed in response to the needs of scientists and engineers to view experimental or phenomenal data in graphical formats (examples are given in Figure 1 ), while IV is dealing with unstructured data sets as a distinct flavor (Hermann et al., 2000).


The Ozone hole representation occurred in 22 September, 2004.

Cognitive amplification

Graphics aid thinking and reasoning in several ways. Graphics use the visual representations that help to amplify cognition. They convey information to our minds that allows us to search for patterns, recognize relationship between data and perform some inferences more easily.

[1] A Dictionary of Computing. Oxford University Press, 2004. Oxford Reference
Online, Oxford University Press.

Last modified: Friday, 2 February 2007, 3:01 PM