‘A visualisation is a graphical representation of evidence, a tool for analysis, communication and understanding.’ Alberto Cairo
There is much debate around the roles of data visualisation and the forms that it takes. There are those who make art from data and others who use data to tell stories. There are visualisations that guide users through data and those that create open-ended representations for users to explore and draw their own conclusions.
So how do you judge a data visualisation? Alberto Cairo, a key practitioner in the field, has listed four criteria for good visualisations. He says that a good visualisation is:
- Functional: The visualisation should be informative, enabling the viewer to answer questions raised by the data. It should be ‘readable’ and accurate, referencing its sources.
- Beautiful: An attractive visualisation encourages viewers to interact with it.
- Insightful: The visualisation should generate insights previously unnoticed.
- Enlightening: The overall effect of the visualisation should be to transform the way the viewer thinks about the topic.
The process of making data visualisations is both an art and a science. Here a few examples of data visualisations to explore:
One of the most classic, noteworthy data visualisations was made by the engineer Charles Minard in 1869. He created a graphic to visualise Napoleon’s Russian campaign of 1812. The light brown line represents the number of troops as they march towards Russia; the line gets thinner as the army is weakened. The thinning black line represents the defeated troops on their journey back to France. The bottom section of the map plots the harsh temperatures experienced by the troops as they retreated. The overall effect of the graphic is the story of an ill-fated military campaign represented in a single frame.
This is a dense visualisation designed by Accurat, a Milan-based design studio. It measures the age, sex, education and origin of Nobel Laureate winners from 1901-2012, across the categories of Chemistry, Economic Sciences, Physics, Literature, Physiology/Medicine and Peace.
Each laureate is represented by a dot on a timeline. The x-axis indicates when the prize was won and the y-axis the age of the winner. Different dots are used to indicate men and women. The graphic gives insight into the average age of winners in each field, what academic level the winner was at the time of the award and which university they belonged to. The graphic points out some interesting facts around the oldest and youngest awarded, siblings who won and a self-taught physics laureate. Interestingly most Literature laureates hold no degrees and New York is home to the greatest number of laureates.
This interactive visualisation by the Guardian contrasts the differing positions of American states on gay rights. Seven different rights issues are explained and mapped out, including marriage, hospital visitation, adoption, employment, housing, protection from hate-crimes and rights to schooling.
The story uses a wheel divided into states. Rights are colour-coded – the more liberal the brighter, grey stripes indicate bans and plain grey indicates where the law is unclear. Each state is highlighted and explained as the user scrolls over it, and each of the seven rights is further explained below. Facebook integration allows people to see how the laws affect their friends, this is a powerful addition to the visualization and personalises the experience.
There is a good description of the process behind developing this infographic here.
Bloomberg Billionaires offers a playful, yet informative tool to rank, plot, map and filter the world’s richest people by age, industry, country of origin, sex and source of wealth. Each individual’s net worth calculation is updated daily. Instead of pointing out insights this visualisation presents itself as a tool for finding interesting correlations and stories about the wealthiest people on the planet.
This article explains how Bloomberg crunch their numbers for this visualisation.
If you are interested to see and learn more about data visualisation, here are a few links to get you started:
Opinion makers & resources
Alberto Cairo: thefunctionalart.com
Data Stories: A monthly podcast on all topics related to dataviz
Andy Kirk: visualisingdata.com
Stephen Few: perceptualedge.com
Doing Journalism with Data: Canvas Network
Malofiej: Infographics Awards
There is so much to learn and share about this field.
Feel free to add your resources or opinions below.
Cairo, Alberto (2014). Doing Journalism with Data: First Steps, Skills and Tools. What visualization is: myths and misconceptions.
Choosing the Best Graphic Forms. https://www.canvas.net/courses/doing-journalism-with-data