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Data Visualization: What is Data Visualization?

Tools, tips, and resources on creating visual representations of data, including infographics, charts and graphs, and more.

What is Data Visualization?

Data visualization refers to communicating relevant information visually, through the use of tools such as infographics, maps, charts, graphics and interactive data displays. Dense information and complex data can be made understandable and relevant through this form of visual communication. With the help of software and good design principles, complex and repetitive statistical data can be rendered into visual schemas that readers can better understand at a glance.

Three Perspectives on Data Visualization

Providing context and presenting data in a visually appealing way that can be easily understood by readers is paramount, whether you’re teaching in a classroom setting, presenting research materials or persuading business clients.

Imagine if you wanted to find out what types of alcohol British Columbians consumed the most in 2012.

Would you prefer the information in a spreadsheet? Or would you prefer this in a graph?

 

Keep in mind that the spreadsheet itself is also a form of visualization - just not a very interesting one to look at. Numbers on a spreadsheet don’t often mean much at a glance, while the graph format makes the information more memorable, providing a sense of scale and putting the sales of these different beverages in perspective.

David McCandless, a guru in the field of data visualization, said in an infographic that the best visualization combines:

  • Information (data)
  • A story (concept)
  • A goal (the purpose)
  • Visual elements (metaphors)

The right combination of these elements will allow you to deliver knowledge in a way that is informative, relevant, and most of all, interesting.

Visualization can give birth to new points of view by making data analysis accessible for both scholars and novices. Hans Rosling, in his TED talk Let My Dataset Change Your Mindset, dispels many of the misconceptions surrounding long-life expectancies in the Western world and short-life expectancies in developing world. Rosling achieves this by turning summary statistics into interactive graphics, allowing viewers to better track global socio-economic development.

Data Visualization and Florence Nightingale


"Diagram of the Causes of Mortality in the Army in the East" by Florence Nightingale is in the public domain

Way before data visualization became trendy, Florence Nightingale used a polar area graph to fight for reform in the British Army hospital administration.

Her iconic Diagram of the Causes of Mortality in the Army in the East was designed, in her words, “to affect thro’ the Eyes that we fail to convey to the public through their word-proof ears."

While serving in the Crimean War, Nightingale witnessed soldiers living in unsanitary, inhumane conditions, and dying because of the military hospital’s inability to coordinate the delivery of essential items, such as food and clothing. She also observed that the hospitals did not have a systematic and uniform way of recording important information, including the soldiers’ health and mortality.

In Notes on matters of the efficiency, health and the hospital administration of the British Army, Nightingale used data she collected to reveal the British hospital administration’s incompetence. Her graph shows that the majority of the soldiers did not die from war wounds (shown in red), but diseases like cholera, dysentery and scurvy (shown in blue), all of which could have been prevented in a sanitary environment (31). The black areas shown below indicate death from other causes.

To read more about Florence Nightingale and her contribution to statistics and data visualization, see M. Eileen Magnello's article, Victorian statistical graphics and the iconography of Florence Nightingale's polar area graph.

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