One of my favorite data visualizations of all time is John Snow’s “Ghost Map” that helped identify the cause of the 1854 London cholera epidemic.
I am currently reading Steven Johnson’s exciting book on this tragic chapter in London’s history. The book is titled The Ghost Map: The Story of London’s Most Terrifying Epidemic – and How it Changed Science, Cities and the Modern World. I am planning on talking about Mr. Johnson’s book and the events it discusses in next month’s DataViz History blog.
As a preview of this upcoming blog (and an interesting treat), I thought I would share some paper sculpture art from Matthew Picton. Below is a photo of Mr. Picton’s art titled “Ghost Map” The 1854 London Cholera epidemic 2011.
Notice that it is a 3D version of John Snow’s famous map made out of paper. In the detail view below, note that he shows the deaths at each building with red dots and the location of the water pumps with blue dots.
Mr. Picton studied Politics and History at the London School of Economics. He has been a professional artist since 1998 and has exhibited widely on the West and East coast of the United States and participated in numerous art fairs. He has exhibited internationally in the UK and Germany His work has been reviewed in many publications including Art Forum, Art News, Art Ltd, Art Week, The Los Angeles Times, The San Francisco chronicle, The Washington Post, The Independent (UK) and the Atlantic Cities amongst others, His work is included in the collections of The De Young Museum, San Francisco, The Herbert Museum of Art, Coventry UK, The Fidelity Bank collection, London UK.
If you come across current art that depicts historical data visualizations, please send it my way and I will blog about it (and of course, credit you as the sender).
I actually remember seeing this when I was a little boy.
Michael Bentine explains why it would be madness for Britain to join the Common Market, while all hell breaks loose behind him thanks to a bit of Biographic genius. Keen-eyed Bob Godfrey connoisseurs may recognise the cutout figures and vehicles from the ‘chase’ section of 1959’s ‘The Do It Yourself Cartoon Kit’, which was of course narrated by Bentine.
The funnest 2 minutes you will spend today.
Charles Apple is a freelance visual journalist and instructor. A longtime news artist and designer, he is the former graphics director of the Virginian-Pilot and the Des Moines Register. He is currently en route (I am following his trip on Twitter @charlesapple) to his new job as the editor and designer of the Orange County Register‘s daily Focus page.
Here is one Charles posted back on February 7th. [SOURCE]
This interesting graphic from the Winnipeg Sun showing results of an informal poll of readers was making the rounds last night.
I’m not quite sure how something like that would make it past a copy editor. Sigh…
So I go from talking about Florence Nightingale and her achievements yesterday to poop today. *Sigh*
Not every infographic needs to be two feet tall with dozens of icons, charts and graphs. Sometimes an infographic can get its message across with a single image. Infographics like this one which feature some interesting facts about poop and its image of a multi-color poop. I’m hoping that is not real poop. I’m hoping that is play-doh poop. In any case, it is a visual that catches you quickly and the color coding disarms the potential vulgarity or distaste that poop’s more natural coloring might cause. [SOURCE]
I have reviewed some really poopy infographics, but I have to say this is the poopiest of them all. Let’s get to know our poop.
For the record, your average poop contains:
- 1% protein
- 4% salts
- 75% water
- 8% indigestible fibers
- 8% dead bacteria (eww!)
- 4% fats
I love the history of data visualization. From Minard to Snow, I love to read the historical stories about the various graphs and maps that played a significant part in World history. Each month, I will have a special column titled “DataViz History” where I will showcase one of these visualizations. This month I am highlighted Florence Nightingale’s Diagram of the Causes of Mortality.
While Florence Nightingale is most well-known as the founder of modern nursing and worldwide healthcare reform, she was also a passionate statistician and a pioneer in statistical graphics. [SOURCE]
Florence Nightingale was born on May 12, 1820, to a wealthy, upper-class British family. Her parents provided her with a well-rounded education that included mathematics, in which she excelled. As a young adult, she rejected the expected role of a woman of her status and entered nursing in 1844 despite the opposition of her family.
During the Crimean War, she was recruited by the Secretary of War, Sidney Herbert, to assemble a team of nurses to serve at the British hospital in the Crimea at Scutari. When she arrived at the hospital, she found it to have horrid conditions with poor hygiene, overworked staff, and a lack of food and supplies. She immediately set to work improving the conditions of the hospital with hard work and compassion. In addition to the horrid hospital conditions, she also found the medical records to be disorganized, deficient and inconsistent between hospitals. She then began systematizing the medical record keeping and collecting data for analysis. By the time Florence left the Crimea in 1856, the conditions of the hospitals in Crimea improved drastically, with death rates dropping from 42% to 2%.
After returning to Britain, Nightingale remained greatly disturbed by the many needless deaths caused by disease in the military hospitals in the Crimea. As a result, she asked Queen Victoria to appoint a Royal Commission on the Health of the Army so that the data she had collected in the Crimea, as well as other army medical data, could be analyzed for medical reform. She turned to William Farr, a leading British statistician and a founder of medical statistics, to help her analyze the data.
The statistical analysis of the data from the Crimea showed that the unsanitary living conditions led to the diseases that caused the high mortality rates, not lack of food and supplies as she had originally believed. They also discovered that the problems in the military hospitals were not limited to wartime. In peacetime, soldiers died at twice the rate as civilians aged 25 to 35.
The statistical analysis results showed a strong need for reform, but Nightingale feared that Queen Victoria and the members of Parliament who could enact reform would not be likely to read or understand her statistical reports. Thus, she created a clever graphical presentation of the statistical results called a polar area diagram, which has also been referred to as a “coxcomb.” The figure below shows the polar area diagrams, “Diagram of the causes of mortality in the army in the East,” that Nightingale used to persuade Queen Victoria of the need for reform by improving the sanitary conditions of military hospitals.
In these polar area diagrams, the circles are divided into 12 wedges, representing months of the year. The area of each wedge is proportional to the number of deaths for that month. The blue part of the wedges represents death due to disease, the red part of the wedges represents death due to wounds, and the black part of the wedges represents death due to other causes. The polar area diagram on the right shows the months from April 1854 to March 1855, and the polar area diagram on the left shows the months from April 1855 to March 1856. The deaths caused by disease generally increased from April 1855 to March 1856. However, when a sanitary commission arrived from Britain in March 1855 to improve the sanitation of the hospitals, the deaths due to disease dropped dramatically. Nightingale’s use of graphical presentation of statistics, her report and the commission were powerful tools that persuaded the government to reform sanitation methods in both military and civilian hospitals.
Nightingale continued to use statistics to reform medical record-keeping in Britain and to reform sanitary living conditions in rural India. In 1858, Nightingale became the first woman elected as a Fellow of the Royal Statistical Society for her work on army and hospital statistics and sanitation reform. She was also elected as an honorary member of the American Statistical Association in 1874. Nightingale died on Aug. 13, 1910, at the age of 90. She left a legacy of many saved lives and medical reform that was fueled by the use of statistical graphics as a powerful tool of persuasion.
How you are unlikely to die
ON FEBRUARY 15th DA14, an asteroid 45 metres across, sailed past the Earth at 7.8km a second (4.9 miles a second). At just 27,700km away, it is well within the range of communication satellites. It was the closest encounter on record with an asteroid this big. In 1908 an asteroid estimated to be around 100 metres in diameter destroyed 2,000 km² of forest in Siberia. Thankfully, such events are rare. NASA has identified 9,600 “near-Earth objects” since 1995, but just 861 with a diameter of 1km or more. The greatest threat to Earth currently is the 130-metre wide 2009 FD; but it has just a 1-in-526 chance of hitting the planet, and not until March 29th 2185. More prosaic things are far more dangerous. According to data from America’s National Safety Council, 27 people died in 2008 in America from contact with dogs (a one in 11m chance of death). The chart below compares the odds of dying in any given year from choking, cycling, being struck by lightning or stung by a bee. [SOURCE]
I have always liked New Orleans. I don’t think there is any city like it anywhere else in the World. It hums and sings all night and day. The food is great and the people are a unique brand all their own.
I was sadden when Katrina almost wiped out the city. I have been rooting for its full recovery and for people to return to it. I love the HBO show Treme and how it depicts life right after Katrina.
I am currently in Alberto Cairo’s MOOC class, Introduction to Infographics and Data Visualization. Each week, Dr. Cairo recommends sites we should go to to see great data visualizations and infographics. This week, I went out the The New York Times Infographics site (Small labs, Inc.). I found this infographics about the population decline in New Orleans.
The overall population of New Orleans has decreased by 29 percent since a decade ago, according to data released by the Census Bureau on Thursday, January 31, 2013. The Lower Ninth Ward, the poorest neighborhood in the city and the one hardest hit by the storm, had the largest population decrease. Pockets of New Orleans East, a low-lying section of the city that was also devastated by the storm, also had large drops. The few areas with an increase in population tended to be along the Mississippi River, a higher-elevation section of the city that was not significantly flooded after the storm. [Source]
This is very sad news to hear. I hope through people visiting for Marti Gras, sports events, and other occasions will find it the right place for them to be and help bring the city back to a full recovery.
It’s no great revelation that a lot of exotic scenes in Hollywood movies aren’t actually shot on location, but this fascinating map, produced by Paramount Studios in 1927 to reassure film financiers that they were capable of doing things on the cheap, shows just how California-centric the film industry can be. They even shot New England scenes in NorCal!
It’d be interesting to see just how much things have changed in an era of cheap commercial air travel for the masses, but given the convenience factor of being near one’s studio and its resources, I suspect the answer is ‘not as much as you’d think. [SOURCE]
Here is an image of the original map and the cover of the book, Hollywood Utopia, by Justine Brown (2002) that talks about the map.
Every evening, I search the Web to try and find you interesting data visualizations and infographics to discuss. I often find myself thankful in my daily work life that I don’t have to deal with topics related to politics, tragedy, and other less pleasant topics. This infographic I am going to discuss today unfortunately deals with the worst of the worst, but I feel it is an important one for us to discuss as we venture out to create infographics for our intended audience. [SOURCE]
In reviewing the infographic below, we first need to ask what is the message the author was trying to convey?
This infographic shows on January 15, 2013, 919 people have been killed by firearms since the Sandy Hook Massacre that occurred on December 14, 2013 in Newtown, Connecticut (31 days earlier). Children ages 0 – 13 are shown as various forms of red figures; teens and adults ages 14+ are shown as various forms of dark figures. Fast fact notes relating to some of the deaths are shown interspersed chronologically between the days. I find that the fast facts are what pulls you into the story the infographic is trying to tell.
From a data visualization perspective, I like the infographic and the way it visually portrays the data. I can think of instances at Apollo Group where we talk about student enrollment, retention, and other data pertinent to our business where an infographic like this would work well. However, the question again is what is the author trying to convey? If the point is that 919 deaths in 31 days is a lot, then the point is well made. However, if the point is “well, we only had 919 deaths out of 300 million people in 31 days, so there is no issue here,” then we need to be concerned. Are all gun-related deaths equal? The infographic states that 60% of gun-related deaths are suicides and often go unreported. Why does the author point this out?
Both sides of the gun control debate have strong, passionate feelings on this issue. Saving hundreds of lives a month is a worthwhile goal in absolute and relative terms (we will discuss absolute versus relative data in a future topic). This infographic is one that could be used by both sides for a national debate.
So, is an infographic like this helpful to the national discussion or is it deceptive in its simplicity? I leave that to you to decide.
BTW, if you have found an interesting data visualization or Infographic you would like to share, please send it to me along with your thoughts on it. I would be happy to blog about what you find interesting in the world of data visualization.