One of the most important data visualizations in history and possibly the best statistical graphic ever drawn was Charles Minarda��s 1861 map of Napoleona��s invasion of Russia. This data visualization captures four different changing variables in a single two-dimensional image. Beginning at the Polish-Russian border, the thick band shows the size of the army at each position. The path of Napoleon’s retreat from Moscow in the bitterly cold winter is depicted by the dark lower band, which is tied to temperature and time scales.

The 1900s saw fewer developments in the field of data visualization; instead it was a time of popularization. Data visualization began to be used in textbooks, and graphical methods were soon used in science curriculums, particularly physics and biology. In 1962, John Tukey wrote a manifesto calling for the recognition of data analysis as a separate branch of statistics. And in 1967, Jacques Bertin, a French cartographer, published the Semiologie Graphique, considered the theoretical foundation of data visualization.

Throughout history, there have been many influential visualizations, but perhaps the biggest changes came with the development of computers. Not only could computers help with the processing of huge amounts of data, but software was being developed that would allow people to construct graphic forms as well as construct new ones. From Bell Laboratories to pen plotters, from the mouse to tablets, technology made data visualization easier than ever.

And then, of course, came the Web, and with it, new visual ways to display data. Around 2002 or so, tag clouds began to show up on blogs and websites. Also known as word clouds, these data visualizations visually display the frequency of the most commonly used words or the most common web referrals.

In 2004, Edward Tufte created the sparkline: a small, word-sized graphic that can be embedded into sentences, tables, headlines, spreadsheets or graphics. Sparklines present trends and variations associated with a measurement like average temperature or stock market activity in a simple and condensed way. These data visualizations are meant to be succinct, memorable and located right where they are discussed, rather than off in a chart away from the flow of text.

Therea��s no way of knowing how the history of data visualization will change in the future, but an important step is free web-based data visualization tools — making it easier than ever to create data visualizations.

Need help understanding the history of data visualization and how that could help you achieve your goals? Contact us for some enlightenment.

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