“The greatest value of a picture is when it forces us to notice what we never expected to see.” – John Tukey, American Mathematician
You may have heard the terms information design or infographics, but both share the common ground of using a picture, or visual, to display information.
Information visualization (also referred to as data visualization) is not new. Michael Friendly delivers a brief history in his book Handbook of Data Visualization, offering a chart which depicts “the frequency of events considered milestones” with milestones defined as significant visual depictions created during each time period as shown in the reproduction of his chart below (Friendly, 2008).
Time, or each “epoch” is measured on the horizontal axis while density (an estimation based on the visual milestones chosen) is measured on the vertical axis.
“Density estimation is estimating the probability density function of the population from the sample” (An Overview of Density Estimation, n.d.).
As you can see there is a slow rise from the 1500s to the early 1700s, transitioning to a much faster increase in the use of visuals as we moved closer to the 20th century, considered the Golden Age by Friendly.
Enhancing visual form
To heighten my understanding of what caused this rise to occur I added icons representing the types of visuals popular during each time period.
Taking it one step further I chose to move the timeline to the top of the diagram. I also moved the descriptions of the popular visuals closer to each icon and used color to indicate the change in centuries.
Although these additions are helpful they do not tell the entire story, nor do they intend to. It is, however, a reminder of what makes a good visualization. Additional elements are needed to provide full disclosure. The trick is to do it without overwhelming the viewer.
Data-journalist and information designer David McCandless proposes four elements necessary to deliver a good visualization:
- information (the data itself)
- visual form (its appearance)
- goal (its function)
- story (the concept behind the visual)
If you overlay these elements onto Friendly’s graph, the evolution becomes more evident. At the base of the visual below you will see that information is always the foundation. As you move along the timeline note the layering of form, goal, and story as data visuals move toward the 21st century.
Case in point: Florence Nightingale’s Diagram of the Causes of Mortality, delivered in 1801, stands out as an example of a worthy goal — to convince the British government to expend public funds to improve city sanitation and help control epidemic disease.
WHAT DO YOU SEE?
As designers we bear an intellectual burden.
“Intellect is a term used in studies of the human mind, and refers to the ability of the mind to come to correct conclusions about what is true or false, and about how to solve problems” (Intellect, 2020).
Do you use the elements of data and form responsibly to achieve an honest goal? Are you treating the viewer with the respect they deserve by allowing them to come to an objective conclusion given the visual’s compressed format? Is the format clear and understandable?
“… visualizing information … is a form of knowledge compression. It’s a way of squeezing an enormous amount of information and understanding into a small space.” (McCandless, 2010).
Good information visualization takes time and you must consider the following questions:
- What data should I use?
- Is there data that can be safely left out?
- How much information is too much?
- Is it possible to stay neutral and reach the widest audience yet still be effective?
SIMPLE AND EFFECTIVE
In short, what makes a good visual? Consider this visualization of the Coronavirus Riskiest Activities by David McCandless — it is the best example I have seen during these stressful pandemic times. It does not lean left or right, it uses size and color appropriately, and allows the viewer to determine their course of action based on information from over five hundred epidemiologists and health professionals.
These are the facts; you get to decide. Definitely milestone quality in my opinion.
“As visual communicators, we must carefully consider the content of a message, the efficiency of how we deliver that message, technology used for its implementation, and the ultimate impact that it has” (Marchese, n.d.).
What do you think?
until nxt time …
An Overview of Density Estimation. (n.d.). KDnuggets. Retrieved July 12, 2020, from https://www.kdnuggets.com/an-overview-of-density-estimation.html/
Cartogram Maps: Data Visualization with Exaggeration. (2016, September 18). GIS Geography. https://gisgeography.com/cartogram-maps/
Dykes, B. (n.d.). 31 Essential Quotes On Analytics And Data | Web Analytics Action Hero. Analytics Hero. http://www.analyticshero.com/2012/10/25/31-essential-quotes-on-analytics-and-data/
Foster, H. (2020). Visual Milestones.
Friendly, M. (2008). A Brief History of Data Visualization. In C. Chen, W. Härdle, & A. Unwin, Handbook of Data Visualization (pp. 15–56). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-33037-0_2
Information is Beautiful (2020). COVID-19 #CoronaVirus Infographic Datapack. Information Is Beautiful. https://informationisbeautiful.net/visualizations/covid-19-coronavirus-infographic-datapack/
Intellect. (2020). In Wikipedia. https://en.wikipedia.org/w/index.php?title=Intellect&oldid=965398954 Page Version ID: 965398954
Marchese, C. (n.d.). History of Data Visualization. https://quinnipiac.blackboard.com/bbcswebdav/pid-3358426-dt-content-rid-44373043_1/xid-44373043_1
McCandless, D. (2010). The beauty of data visualization. https://www.ted.com/talks/david_mccandless_the_beauty_of_data_visualization
Small, H. (2010, October 7). Did Nightingale’s ‘Rose Diagram’ save millions of lives? Retrieved from: http://www.florence-nightingale-avenging-angel.co.uk/?p=462