Nathan Yau’s “Data Points” follows in the great tradition of Edward Tufte (“The Visual Display of Quantitative Information”). It is a timely book given the increasing need to present ever bigger mounds of “Big Data” in ways that reveals patterns and enables insight. It is a very good book and one worth reading if you are interested in how to use visuals to make data and its analysis more effective (and beautiful). As a combination of art and science, right brain and left brain, the book speaks to the philosophical leanings of this author. Mr. Yau has another book in this vein, “Visualize This: The Flowing Data Guide to Design, Visualization, and Statistics.”
A beautiful example of what data visualization can do is the work of Fernanda Viégas and Martin Wattenberg, co-directors of Google’s “Big Picture” visualisation research group. In their animated online infographic, “Wind Map” (pictured), which was created in 2012, they took hourly data from the National Digital Forecast Database to show windflows across America. The intensity of the white lines represents the gusts’ force. The result is a unique way to show near real-time data in a way that is both informative and elegant.
You play this visualization in real-time at: http://hint.fm/wind/
For that is what data-visualisations are: a blend of the aesthetic and informational. Having one without the other means producing something that is less useful and enjoyable than it might be, argues Nathan Yau, a statistician who runs a blog called FlowingData.com. Visualisation is a whole new medium, he writes in his new book, “Data Points”. It is a “continuous spectrum that stretches from statistical graphics to data art”.
Translating data into images allows people to spot patterns, anomalies, proportions and relationships. When done well, it lets the eye create the narrative; people teach themselves, rather than being told. Neurologically, humans use a different part of the brain when information is presented visually rather than through numbers. The right hemisphere handles imagery; the left is more analytical. Seeing data pictorially makes good use of both sides of the brain and lets one grasp meaning more quickly.
Mr Yau’s book does an excellent job of explaining what makes a good data illustration. In the past, this would have been the sort of stuff that might appeal to graphic designers. But today every professional interacts with data and charts, be it by poring over a spreadsheet, watching a PowerPoint presentation or reading a newspaper.
The book walks the reader through myriad examples—world airline routes, road deaths across America, even the distance to the nearest McDonald’s outlet—to explain what works and why. In one section, for instance, a dull table of American educational statistics is visualised in 20 different ways across 12 pages to unleash vibrant insights that had been trapped within the rows and columns. (Who knew that Washington, DC, saw the biggest improvement in high-school graduation rates between 2000 and 2009, while Texas fell to the bottom of the ranking?) (The Economist)