Defining data visualization

It is important now to consider a definition of data visualization. To do this, we first need to consider the main agents involved in the exchange of information; namely, the messenger, the receiver, and the message. The relationship between these three is clearly very important, as this illustration explains:

On one side we have a messenger looking to impart results, analysis, and stories. This is the designer. On the other side, you have the receiver of the message. These are the readers or the users of your visualization. The message in the middle is the channel of communication. In our case this is the data visualization; a chart, an online interactive, a touch screen installation, or maybe an infographic in a newspaper. This is the form through which we communicate to the receiver.

The task for you as the designer is to put yourself in the shoes of the reader. Try to imagine, anticipate, and determine what they are going to be seeking from your message. What stories are they seeking? Is it just to learn something new or are they looking for persuasion, something with more emotional impact? This type of appreciation is what fundamentally shapes the best practices in visualization design: considering and respecting the needs of the reader.

The important point is this: to ensure that our message is conveyed in the most effective and efficient form, one that will serve the requirements of the receiver, we need to make sure we design (or "encode") our message in a way that actively exploits how the receiver will most effectively interpret (or "decode") the message through their visual perception capabilities.

From this illustration we can form the following definition to clarify, at this early stage, what we mean by data visualization:

The representation and presentation of data that exploits our visual perception abilities in order to amplify cognition.

Let's take a closer look at the key elements of this definition to clarify its meaning; these are as follows:

The definition that I've put forward here is not dissimilar to the many others articulated by authors, academics, and designers down the years. It is not intended to offer a paradigm shift in our understanding of what this is all about. Rather, it represents a personal perspective of the discipline influenced by many years of experience teaching, practicing, and constantly studying the subject.

The fact that data visualization is such a dynamic and evolving field, with this unique conjunction of art and science shaping its practice, means that a single, perfect, and universally-agreed definition is always going to be difficult to construct. However, this proposed definition should at least help you develop an appreciation of the boundaries of data visualization and recognize when something evolves into a different form of creative output.