Humans have a natural ability to correlate patterns from multiple sources to become aware of information. Most current human-computer interfaces however are limited to visual and more exactly text-based interaction. While it is true that current computer systems use a large number of symbolic elements and metaphors in the Graphical User Interface (like icons, windows, drag and drop, and so on), the primary mean of information exchange is still the written (or in the case of computers typed) word.

This approach (while having the advantage of simplicity) is very limiting from an information-bandwidth (the rate at which information can be exchanged between the user and the computer) point of view. Because typing / reading has an upper limit (although estimate vary from 40 to 250 words per minute for typing and between 250 and 700 words per minute for reading, it is clear that such limits do exists and that most people are not able to cross certain barriers, no matter the amount of training), it is logical to conclude that we must look to alternative ways to consume more information quicker. From a technical point of view the two methods which are the easiest to implement with current hardware are:

Both of these methods can easily be implemented with almost all consumer-grade computing equipment. The fact that both of these are “output” (from the computer point of view) methods can be justified that the rate at which outputs is produced (and needs to be consumed) is much larger than the rate of input we need to provide (two of the reasons being that a great deal of output is produced by automated systems and also because in todays interconnected world we consume the sum of many outputs). In the following pages I will focus on the first method and more specifically the way in which it applies to networking data.

Each part (after the introductory part about data visualization) will present one way to visualize data and discuss the applicability of the given method in the context of computer networking.

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