Conheça um pouco da história dos gráficos que você utiliza diariamente.
Data Visualization in Historical Context
People have been arranging data into tables (columns and rows) at least since the 2nd century C.E., but the idea of representing quantitative information graphically didn't arise until the 17th century. For this innovation we have the French philosopher and mathematician Rene Descartes to thank. He developed a two-dimensional coordinate system for displaying values, consisting of a horizontal axis for one variable and a vertical axis for another, primarily as a graphical means of performing mathematical operations. It wasn't until the late 18th century that we began to exploit the potential of graphics for the communication of quantitative data, for which we have the Scotsman William Playfair to thank. Playfair pioneered many of the graphs that are commonly used today. He was the first person to use a line moving up and down as it progressed from left to right to show how values changed through time, as in the example below. He also invented the bar graph, and on one of his off days he invented the pie chart, which we have since found relatively ineffective, because it encodes values as visual attributes (primarily the area of each slice as well as the angle that it forms in the center of the pie) that we cannot easily perceive and compare.
Playfair included this graph in his The Commercial and Political Atlas (1786) to argue against England's policy of financing colonial wars through national debt. The use of quantitative graphs gradually increased over the years, but their methods and effectiveness evolved little until the second half of the 20th century. Jacques Bertin laid the foundation for much of the progress that's been made during the last half a century with the publication in 1967 of the book Semiologie graphique (The Semiology of Graphics, Bertin 1967). His work was pivotal because he discovered that visual perception operated according to rules that could be followed to express information visually in ways that represented it intuitively, clearly, accurately, and efficiently.
The person who really introduced us to the power of data visualization as a means for exploring and making sense of quantitative data was the Princeton statistics professor John Tukey, who in 1977 gave form to a whole new statistical approach called exploratory data analysis.
In 1983, the person working in the field today whose name is recognized above all others, Edward Tufte, published his groundbreaking book The Visual Display of Quantitative Information. In it he pointed out that there were effective ways of displaying data visually and then there were the ways that most people were doing it, which didn't work very well. Also working to improve data visualization practices around this time was William Cleveland, who extended and refined data visualization techniques for statisticians.
Soon thereafter, a new research specialty emerged in the academic world, which was coined "information visualization." In their 1999 book Readings in Information Visualization: Using Vision to Think, Stuart Card, Jock Mackinlay, and Ben Shneiderman collected the best academic work that had been done by that time into a single volume and made its discoveries accessible beyond the walls of academia (Card et al 1999).
Since the turn of the 21st century, data visualization has been popularized, too often in tragically ineffective ways as it has reached the masses through commercial software products. Gratefully, amongst the bevy of products that promote data visualization in ways that feature superficially appealing aesthetics above useful and effective data exploration, sense-making, and communication, there are a few serious contenders for our attention who are helping us fulfill its potential in practical and powerful ways.
This display, consisting of multiple views of the same data set, was created using Tableau Software, one of the few software vendors that currently understand data visualization.
Among those who have contributed to our understanding of data visualization, Colin Ware has done the most to base its practice on an understanding of human perception. Ware's two excellent books - Information Visualization: Perception for Design (Ware, 2004) and Visual Thinking for Design (Ware 2008) - compile, organize, and explain what we have learned from several scientific disciplines about visual thinking and cognition and apply that knowledge to data visualization.
This is the power of data visualization.
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