Data vis (short for data visualization) is viewed by many disciplines as a modern equivalent of visual communication.
One of the best definitions for this field has been provided by Andy Kirk, author of Data Visualization, who defines data vis as the “representation and presentation of data to facilitate understanding”.
Why is this definition important? Because it breaks down the statement into 4 distinct categories: Representation, Presentation, Data, and Understanding. These are the four pillars of good data visualization.
Representations of data are individual displays of information. From a simple text statement to a slope chart, any grain of data can be represented one way or another. The most widely used categories are pie charts, bar charts, intermediate bar charts, line charts, waffle charts and finally, scatter plots.
When you are starting to tell a story, combining the different representations into one cohesive experience, you now have a Presentation of data.
Data can be almost anything. You can collect it from the open web, you can create your own, or acquire it by paying a data provider. The one thing to remember is that knowing your data (and what is represents) is the most important thing and at the same time, it’s the single most effective way to accurately represent it.
Finally, to facilitate Understanding is to ask yourself what is the message you want the user to take away from the presentation of data, why should they care and is the data important, or relevant? Can the user understand the data without prior knowledge of the subject?
Making an impact and giving a voice even to people who are more introverted than others, so that they can tell compelling stories, makes data vis one of the most effective ways of visual communication.
