As anyone currently on social media knows, the ALS Ice Bucket Challenge has turned into a fun and successful way to help fight Amyotrophic Lateral Sclerosis or ALS. From neighborhood driveways and city streets to Facebook, Twitter and Instagram, people everywhere can be seen dumping buckets of ice water on their heads to raise awareness and funds to fight ALS.
Children, adults and celebrities alike are joining the social media phenomenon to fight back against a disease that currently has no treatments or cures. “We have been moved beyond words by the power of one family’s ability to make such a meaningful difference in the fight against a disease that has taken too many lives,” said MDA President and CEO Steven M. Derks. “All of us at MDA are incredibly grateful to everyone who has taken the ALS Ice Bucket Challenge to raise awareness and donations for ALS. It will take all of us working together to find treatments and cures, and MDA will not rest until we end ALS.”
The viral ALS Ice Bucket Challenge started when 29-year-old Pete Frates, diagnosed with ALS in 2012, posted an ice bucket video on social media and challenged a few friends to follow his lead. The #ALSIceBucketChallenge has since become a social media sensation, sweeping the country with compassion and support. “Increased awareness about ALS is critical to help us learn more about the disease,” Derks said. “But what we need more than ever is action. Together, our collective actions can translate into significant progress against ALS. We hope everyone will join us to fight back by making a donation at mda.org and participating with us at a local MDA event in your community.”
Vikesh Khanna (photo, right), took a rather unique approach to the ALS Bucket Challenge using data visualization. Mr. Khanna, is a Computer Science Masters student at Stanford University. He was born and brought up in Haridwar, a small religious town in North India. He likes computer programming, reading, badminton, music and wine. If you’re looking for his official symbol, that’d be a crashing Zeppelin.
Vikesh came up with an idea of visualizing all of the people who have taken the ALS Ice Bucket Challenge, who called that person out to do so, and any photos or videos associated with it. Using his application, you can interactively select a person to see how they did the challenge, who they called out to do it, and even the associated video. Below is a screenshot of Vikesh’s data visualization.
So, to test Vikesh’s application, I decided to see what Facebook’s Chief Operating Officer, Sheryl Sandberg, did for her ALS Ice Bucket Challenge. So, using the search page of Vikesh’s application, I searched for “Sheryl Sandberg.” The following information appeared (see two screenshots below). You will see information like: who challenged her (Mark Zuckerberg), how long it has been since she was challenged (278.9 hours), has she completed the challenge (she hasn’t yet), and her popularity score (493.914825).
For you folks that want to try Vikesh’s application, I recommend you try it on an iPad using the Safari browser. I had problems with Internet Explorer, Google Chrome, and Mozilla Firefox.
Here is a link to his application.
I thought I would finish this blog post by provided you some more information about ALS. Even if you don’t want to have a cold bucket of ice water dumped on your head, please donate.
What is amyotrophic lateral sclerosis?
ALS is a disease of the parts of the nervous system that control voluntary muscle movement. In ALS, motor neurons (nerve cells that control muscle cells) are gradually lost. As these motor neurons are lost, the muscles they control become weak and then nonfunctional.
The word “amyotrophic” comes from Greek roots that mean “without nourishment to muscles” and refers to the loss of signals nerve cells normally send to muscle cells. “Lateral” means “to the side” and refers to the location of the damage in the spinal cord. “Sclerosis” means “hardened” and refers to the hardened nature of the spinal cord in advanced ALS.
In the United States, ALS also is called Lou Gehrig’s disease, named after the Yankees baseball player who died of it in 1941. In the United Kingdom and some other parts of the world, ALS is often called motor neurone diseasein reference to the cells that are lost in this disorder.
Who gets ALS?
ALS usually strikes in late middle age (the late 50s is average) or later, although it also occurs in young adults and even in children, as well as in very elderly people. Some forms of ALS have their onset in youth. Men are slightly more likely to develop ALS than are women. Studies suggest an overall ratio of about 1.2 men to every woman who develops the disorder.
What causes ALS?
Years ago, it was widely believed that there might be one cause to explain all cases of ALS. Today, doctors and scientists know that can’t be the case, and they’re working to identify the multiple causes of the disorder. One thing they do know is that ALS cannot be “caught,” or transmitted from one person to another.
The causes of the vast majority of ALS cases are still unknown. Investigators theorize that some individuals may be genetically predisposed to developing the disease, but only do so after coming in contact with an environmental trigger. The interaction of genetics and environment may hold clues as to why some individuals develop ALS.
Although the majority of ALS cases are sporadic, meaning there is no family history of the disease, about 5 to 10 percent of cases are familial, meaning the disease runs in the family. A common misconception is that only familial ALS is “genetic.” Actually, both familial and sporadic ALS can stem from genetic causes. And some people who have a diagnosis of sporadic ALS may carry ALS-causing genetic mutations that can be passed on to offspring. A genetic counselor can help people with ALS understand inheritance and any associated risks for family members.
What are the symptoms of ALS?
ALS results in muscles that are weak and soft, or stiff, tight and spastic. Muscle twitches and cramps are common; they occur because degenerating axons (long fibers extending from nerve-cell bodies) become “irritable.” Symptoms may be limited to a single body region, or mild symptoms may affect more than one region. When ALS begins in the bulbar motor neurons, the muscles used for swallowing and speaking are affected first. Rarely, symptoms begin in the respiratory muscles.
As ALS progresses, symptoms become more widespread, and some muscles become paralyzed while others are weakened or unaffected. In late-stage ALS, most voluntary muscles are paralyzed.
The involuntary muscles, such as those that control the heartbeat, gastrointestinal tract and bowel, bladder and sexual functions are not directly affected in ALS. Sensations, such as vision, hearing and touch, are also unaffected.
About 50 percent of people with ALS develop some degree of cognitive (thinking) or behavioral abnormality. Usually, cognitive and behavioral symptoms in ALS range from mild (such that only close family members may notice a difference) to moderate.
What is the life expectancy in ALS?
Each person’s disease course is unique. There are a number of examples of people who are leading productive and active lives more than two decades after an ALS diagnosis.
Standard longevity statistics citing an average survival time of three to five years after diagnosis may be somewhat out of date because changes in supportive care and technology — especially for breathing and nutrition — may help prolong life.
What can be done about ALS?
Medical interventions and technology have vastly improved the quality of life for people with ALS, by assisting with breathing, nutrition, mobility and communication. Proper management of symptoms, and proactive use of medical interventions and equipment, can make a positive difference in day-to-day living, and potentially may lengthen survival. The FDA-approved drug riluzole (brand name Rilutek) has been shown to slightly increase longevity.
What is the status of ALS research?
A number of strategies and approaches are being tested around the world, both in the laboratory and in human clinical trials. MDA’s basic science program is constantly pursuing new avenues of research to understand the underlying causes of ALS, with a sharp focus on developing treatments.
As of 2012, intense research is being conducted on genetic factors in ALS, the role of the immune system in ALS, and the role of cells other than nerve cells in this disease. In addition, many medications and other treatments are being tested for potential benefits in ALS. For details about current ALS research, go to Research and Clinical Trials.
Today I am going to show you a fantastic choropleth map created by Matthew Bloch, Matthew Ericson and Tom Giratikanon from The New York Times. Their graph maps poverty in America.
Now, before we look at the map, let’s discuss what a choropleth map is.
A choropleth map (Greek χώρο– + πλήθ[ος]), (“area/region” + “multitude”) is a thematic map in which areas are shaded or patterned in proportion to the measurement of the statistical variable being displayed on the map, such as population density or per-capita income.
The choropleth map provides an easy way to visualize how a measurement varies across a geographic area or it shows the level of variability within a region.
A special type of choropleth map is a prism map, a three-dimensional map in which a given region’s height on the map is proportional to the statistical variable’s value for that region.
The earliest known choropleth map was created in 1826 by Baron Pierre Charles Dupin. The term “choroplethe map” was introduced 1938 by the geographer John Kirtland Wright in “Problems in Population Mapping”.
Choropleth maps are based on statistical data aggregated over previously defined regions (e.g., counties), in contrast to area-class and isarithmic maps, in which region boundaries are defined by data patterns. Thus, where defined regions are important to a discussion, as in an election map divided by electoral regions, choropleths are preferred.
Where real-world patterns may not conform to the regions discussed, issues such as the ecological fallacy and the modifiable areal unit problem (MAUP) can lead to major misinterpretations, and other techniques are preferable. Choropleth maps are frequently used in inappropriate applications due to the abundance of choropleth data and the ease of design using Geographic Information Systems.
Incorrect (population, left) and correct (population density, right) application of a choropleth to data for Boston, Massachusetts
The dasymetric technique can be thought of as a compromise approach in many situations. Broadly speaking choropleths represent two types of data: Spatially Extensive or Spatially Intensive.
- Spatially Extensive data are things like populations. The population of the UK might be 60 million, but it would not be accurate to arbitrarily cut the UK into two halves of equal area and say that the population of each half of the UK is 30 million.
- Spatially Intensive data are things like rates, densities and proportions, which can be thought of conceptually as field data that is averaged over an area. Though the UK’s 60 million inhabitants occupy an area of about 240,000 km2, and the population density is therefore about 250/km2, arbitrary halves of equal area would not also both have the same population density.
Another common error in choropleths is the use of raw data values to represent magnitude rather than normalized values to produce a map of densities. This is problematic because the eye naturally integrates over areas of the same color, giving undue prominence to larger polygons of moderate magnitude and minimizing the significance of smaller polygons with high magnitudes. Compare the circled features in the maps at right.
When mapping quantitative data, a specific color progression should be used to depict the data properly. There are several different types of color progressions used by cartographers. The following are described in detail in Robinson et al. (1995)
Single-hue progressions fade from a dark shade of the chosen color to a very light or white shade of relatively the same hue. This is a common method used to map magnitude. The darkest hue represents the greatest number in the data set and the lightest shade representing the least number.
Two variables may be shown through the use of two overprinted single color scales. The hues typically used are from red to white for the first data set and blue to white for the second, they are then overprinted to produce varying hues. These type of maps show the magnitude of the values in relation to each other.
Bi-polar progressions are normally used with two opposite hues to show a change in value from negative to positive or on either side of some either central tendency, such as the mean of the variable being mapped or other significant value like room temperature. For example a typical progression when mapping temperatures is from dark blue (for cold) to dark red (for hot) with white in the middle. When one extreme can be considered better than the other (as in this map of life expectancy) then it is common to denote the poor alternative with shades of red, and the good alternative with green.
Complementary hue progressions are a type of bi-polar progression. This can be done with any of the complementary colors and will fade from each of the darker end point hues into a gray shade representing the middle. An example would be using blue and yellow as the two end points.
Blended hue progressions use related hues to blend together the two end point hues. This type of color progression is typically used to show elevation changes. For example from yellow through orange to brown.
Partial spectral hue progressions are used to map mixtures of two distinct sets of data. This type of hue progression will blend two adjacent opponent hues and show the magnitude of the mixing data classes.
Full spectral progression contains hues from blue through red. This is common on relief maps and modern weather maps. This type of progression is not recommended under other circumstances because certain color connotations can confuse the map user.
Value progression maps are monochromatic. Although any color may be used, the archetype is from black to white with intervening shades of gray that represent magnitude. According to Robinson et al. (1995). this is the best way to portray a magnitude message to the map audience. It is clearly understood by the user and easy to produce in print.
When using any of these methods there are two important principles: first is that darker colors are perceived as being higher in magnitude and second is that while there are millions of color variations the human eye is limited to how many colors it can easily distinguish. Generally five to seven color categories is recommended. The map user should be able to easily identify the implied magnitude of the hue and match it with the legend.
Additional considerations include color blindness and various reproduction techniques. For example, the red–green bi-polar progression described in the section above is likely to cause problems for dichromats. A related issue is that color scales which rely primarily on hue with insufficient variation in saturation or intensity may be compromised if reproduced with a black and white device; if a map is legible in black and white, then a prospective user’s perception of color is irrelevant.
Color can greatly enhance the communication between the cartographer and their audience but poor color choice can result in a map that is neither effective nor appealing to the map user; sometimes simpler is better.
Mapping Poverty in America: A View of Philadelphia
Below is a screenshot of the choropleth map from The New York Times Web site. For my example, I focused on Philadelphia (no specific reason; just the one I happened to click on).
To view the actual interactive version of this map, just click on the image below.
 T. Slocum, R. McMaster, F. Kessler, H. Howard (2009). Thematic Cartography and Geovisualization, Third Edn, pages 85-86. Pearson Prentice Hall: Upper Saddle River, NJ.
 Mark Monmonier (1991). How to Lie with Maps. pp. 22-23. University of Chicago Press
 Robinson, A.H., Morrison, J.L., Muehrke, P.C., Kimmerling, A.J. & Guptill, S.C. (1995) Elements of Cartography. (6th Edition), New York: Wiley.
 Patricia Cohen (9 August 2011). “What Digital Maps Can Tell Us About the American Way”. New York Times.
 Light et al. (2004). “The End of the Rainbow? Color Schemes for Improved Data Graphics””. pp. 385. Eos,Vol. 85, No. 40, 5 October 2004.
In the December 28, 2013 digital edition of The Washington Post, Kennedy Elliott and Dan Balz published an interactive data visualization titled Party Control by State. The recent gridlock in Congress has been blamed on political polarity — increasingly antagonistic political ideologies among Democrats and Republicans, with neither party in full control. But states are circumventing this problem by aligning completely with one party: Today, three-quarters of the states are controlled by either Republicans or Democrats, more than at any time in recent memory.
Here is a screenshot of their data visualization. Click on this image to go to The Washington Post Web site and interact with it yourself.
Source: BETSY MASON, 11/20/2013, WIRED
There is a temptation with any kind of data that has a geographical aspect to display it on a map. While maps are by far the best way to convey many of these data, sometimes they are not. This is one of those times.
Even though data on migration between states would seem to cry out to be mapped, this circular visualization by independent data journalist Chris Walker (@cpwalker07) can convey a lot of information far more neatly than a map. Patterns leap out that might have been obscured on a single map, or required many maps to convey the same information (see images below).
“It’s useful to think beyond maps especially for cases where you want to show interconnectedness between regions, which is what I was trying to do,” Walker wrote in an email to WIRED.
[NOTE: The interactive map discussed below can be found on WIRED's site by clicking the link here. I should note that it worked best for me using Google Chrome]
When I first saw Walker’s migration circle (which he built using D3.js), it looked like a jumble that was impossible to untangle, but that’s before I realized it was interactive. If you haven’t already, mouse over the graphic to display information from single states to see where people from that state moved to last year, and where the people who moved into that state came from. More than 7 million Americans moved within the country, so if you’re looking for a time sink, you’ll find it in this circle.
“I think we can learn a lot from migration patterns,” Walker wrote in an email. “In a way, migration flows are one of the oldest forms of crowdsourcing. They tell you which geographies the crowd deems to be low-opportunity, and which the crowd deems to be high-opportunity.”
I live in California, so I started there. I love this state, and it seems to me people are moving here all the time. But it turns out, more people are leaving (73,345 more). As you can see in the snapshot to the right, Californians don’t usually stray too far though, tending to migrate to other western states. Or Texas. A likely explanation for the outflux is that you could buy a mansion in some parts of the country for the same amount as a 2 bed, 1 bath house in the Bay Area.
Despite the initial jumble, a couple of things jump out before you even begin interacting with the graphic. A lot of people are moving out of New York (135,793 net loss) and ending up all over the place, including the other side of the country. The same is true for the Midwest, with people mostly landing in the Southeast, Southwest and California. These trends are clearer when you look at individual states, but the broader trends would be easier to grasp if you could mouse over the region names to see where, say, everyone in the Northeast moved.
One thing to note as you look at what’s happening with New York, for example, is that only exchanges of at least 10,000 people are depicted. This, Walker says in his blog post, is to keep the graphic from becoming to messy. So, while many people are moving into New York, most of them aren’t shown because they are coming from many different places in smaller numbers.
Some of the other things Walker noticed include that fact that a lot of people are moving to Florida, many of them likely retirees. “Interestingly the state contributing the most migrants to Florida is neighboring Georgia,” Walker wrote in his blog. “Texas, New York and North Carolina are the next largest contributors.”
The second largest draw for migrants was Texas. “Over 500,000 people moved to Texas in 2012,” Walker wrote. “People tend to come from the Southeast, Southwest and the West, with the biggest contributor being California. 62,702 Californians packed up and moved to the Lone Star state in 2012.”
People who leave D.C. don’t really leave, generally moving next door to Virginia or Maryland. In contrast, people moving from Maine and Alaska are chasing the sun all the way to California and Florida. Check out his blog post for more insight.
In contrast to Walker’s circular visualization, old census atlases used maps to show the migration data. In August, we visited the Prelinger Library here in San Francisco and took a look at some of these atlases in their collection. In the images below, you can see how the data was displayed. On the right is a map showing where New York natives lived in 1890. New York has the most natives, unsurprisingly, and is the darkest. But the migration pattern is similar to 2012 with New Yorkers heading all over the place. These maps highlight some of the limitations of maps for displaying this kind of data.
Maps from the 1890 Census Atlas at the Prelinger Library in San Francisco. (Ariel Zambelich/WIRED)
I though this interactive infographic from The International Consortium of Investigative Journalists (ICIJ) was interesting in that it shows you visually how to “follow the money.”
The International Consortium of Investigative Journalists is an active global network of 160 reporters in more than 60 countries who collaborate on in-depth investigative stories.
Founded in 1997, ICIJ was launched as a project of the Center for Public Integrity to extend the Center’s style of watchdog journalism, focusing on issues that do not stop at national frontiers: cross-border crime, corruption, and the accountability of power. Backed by the Center and its computer-assisted reporting specialists, public records experts, fact-checkers and lawyers, ICIJ reporters and editors provide real-time resources and state-of-the-art tools and techniques to journalists around the world.
Why ICIJ exists
The need for such an organization has never been greater. Globalization and development have placed extraordinary pressures on human societies, posing unprecedented threats from polluting industries, transnational crime networks, rogue states, and the actions of powerful figures in business and government.
The news media, hobbled by short attention spans and lack of resources, are even less of a match for those who would harm the public interest. Broadcast networks and major newspapers have closed foreign bureaus, cut travel budgets, and disbanded investigative teams. We are losing our eyes and ears around the world precisely when we need them most.
Meanwhile, in many developing countries, investigative reporters are killed, threatened, or imprisoned with alarming regularity. Amazingly unbowed by these life-and-death realities, journalists are in dire need of help from colleagues abroad, many of whom do similar work and can offer support.
This infographics shows us the distribution of wealth in America, highlighting both the inequality and the difference between our perception of inequality and the actual numbers. The reality is often not what we think it is.
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.