Tag Archives: infographics

Infographic: “Is Your McMansion Killing You?”

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Put together a number of statistics about large American homes and an infographic can point the way towards death. These factors – everything from more TV watching, eating poorly, not getting much exercise, and paying more for space that isn’t necessarily needed – are not necessarily related to McMansions. You could do all of this and live in a more modest home or have a really large home that is more architecturally pleasing. For example, did growing up in a 1880s Victorian home or a 1950s ranch necessarily lead to better behavior or were these larger social issues? In this line of reasoning, McMansions may just be a symptom of larger issues such as increased consumerism and individualism.

All that said, I could imagine even more data that could be added to the infographic:

-How much extra infrastructure needs to be built to support suburban McMansions (as contrasted with denser apartment living in big cities)?

-What about the loss of aesthetic beauty in seeing or living in mass-produced, poorly designed McMansions? Can’t this decrease one’s enjoyment of life?

-What is the cost of all the driving often done to accommodate McMansions?

-How about the decrease in civic life encouraged by such large and well-furnished private spaces?

This infogrphic could keep going on and on and on…

Flawed pie chart with too many categories, unhelpful colors

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AllMusic had a recent poll asking readers about their favorite Beatles album. Interesting topic but the pie chart used to display the results didn’t work out so well:

 

http://infogr.am/beatles-poll-results?src=web

Two main complaints:

1. There are a lot of categories to represent here:14 different albums. While it is relatively easy to see some of the larger categories, it gets more difficult to judge the proportions of the smaller categories.

2. There are some categories clearly bigger than others but the color scene seems to have little to do with the actual album title. The palette runs from black to light gray but it does not appear to be in any order. For example, they might have used the same palette but light gray would have been Please Please Me while the darkest color could have been Past Masters. As it currently stands, the reader has to pick out the category and then try to figure out where it is in the key.

Given this comes from an app intended to help create infographics, this one isn’t so great as it suffers from two issues – lots of categories and a limited color design – that I often warn my statistics students about when using pie charts.

Looking at Black America as a separate country

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A long infographic looks at how a country solely comprised of Black Americans would compare to other nations. Here is a brief summary:

In the infographics below, two pictures emerge. The first is of a strong nation with considerable manpower and purchasing power. The second is of a troubled, fragile state suffering from socioeconomic disparities and structural subjugation in ways that degrade life, liberty, and the pursuit of happiness (on some measures, black America resembles countries like Brazil, China, and Russia—emerging powers that are struggling with stark economic inequality). Essentially, what we’re witnessing is a nation that is comparable in certain ways to a regional power existing in the state of Disparistan (or, perhaps, Despairistan). This is more than an inconvenient truth; it fundamentally undermines the United States’ greatest contribution to humanity: the American idea.

Intriguing thought experiment. It would then be interesting to do this for each major racial/ethnic group in the United States to see the clear differences.

“A Behind-the-Scenes Look at How Infographics Are Made”

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A new book examines how designers make infographics:

A new book from graphic guru and School of Visual Arts professor Steven Heller and designer Rick Landers looks at that the process of more than 200 designers, from first sketch to final product. The Infographic Designers Sketchbook is almost exactly what it sounds like. The 350-page tome is essentially a deep dive into the minds of data designers. Heller and Landers have chosen more than 50 designers and asked them to fork over their earliest sketches to give us insights into how they turn a complex set of data into coherent, visually stunning data visualizations. “You see a lot more unbridled, unfettered work when you’re looking at a sketchbook,” says Heller. “You might be looking at a lot of junk, but even that junk tells you something about the artist who is doing it.”

Heller says there are a few through-lines to all good infographics, the first being clarity. The purpose of a data visualization has always been to communicate complex information in a readily digestible way. “You can’t throw curves,” he says. “If you’re going to do something that is complex, like the breakdown of an atomic particle, for example, you have to make it clear.” Clarity is key even in seemingly simple infographics, like Caroline + Young’s Mem:o, an app that visualizes personal data for things like sleep and fitness. The data viz tool uses simple shapes to communicate the various sets of data. This is no coincidence says Heller, adding that our eyes tend to respond to simple geometric forms. “If you start using parallelograms or shapes like that, it may get a little difficult,” he says. “But circle squares and rectangles, those are all forms we adjust our eyes to very quickly.”…

It’s fascinating to go behind the scenes of a designer’s work process, in the way it’s fascinating to flip through another person’s journal or leaf through the papers on their desk. If nothing else, the book is a testament to the sketching process. It shows how designers, and even non-designers, can use a pen and paper to sort through some hairy, complex ideas.

The post has some interesting examples you can look at. This hints at the larger process of interpreting data. If someone just handed you a spreadsheet of data or a few tables with data, it is not an automatic process between that and coming up with the “right” interpretation, whether that be in a written or graphical format. It takes time and skill to present the data in an engaging and informative way.

Summarizing a year of your life in an infographic report

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One designer has put together another yearly report on his own life that is a series of infographics:

For nearly a decade, designer Nicholas Felton has tracked his interests, locations, and the myriad beginnings and ends that make up a life in a series of sumptuously designed “annual reports.” The upcoming edition, looking back at 2013, uses 94,824 data points: 44,041 texts, 31,769 emails, 12,464 interpersonal conversations, 4,511 Facebook status updates, 1,719 articles of snail mail, and assorted notes to tell the tale of a year that started with his departure from Facebook and ended with the release of his app, called Reporter…

New types of data forced Felton to experiment with novel visualizations. One of Felton’s favorite graphics from this report is a “topic graph” that plots the use and frequency of specific phrases over time. It started as a tangled mess of curves, but by parsing his conversation data using the Natural Language Toolkit and reducing the topics to flat lines, a coherent picture of his year emerges a few words at a time.

After nine years of fastidious reporting, Felton has an unparalleled perspective on his changing tastes, diets, and interests. Despite a trove of historical data, Felton has found few forward-looking applications for the data. “The purpose of these reports has always been exploration rather than optimization,” he says. “Think of them more as data travelogues than report cards.”…

Felton says it’s relatively easy for companies to make sense of physical data, but properly quantifying other tasks like email is much harder. Email can be a productivity tool or a way to avoid the real work at hand making proper quantification fuzzy. “The next great apps in this space will embrace the grayness of personal data,” says Felton. “They will correlate more dimensions and recognize that life is not merely a continuum of exercising versus not exercising.”

Fascinating project and you can see images from the report at the link.

I like the conclusion: even all of this data about a single year lived requires a level of interpretation that involves skills and nuance. Quantification of some tasks or information could be quite helpful – like health data – but even that requires useful interpretation because numbers don’t speak for themselves. Even infographics need to address this issue: do they help viewers make sense of a year or do they simply operate as flashy graphics?

The factors behind the rise of viral maps

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Here is a short look at how viral maps (“graphic, easy to read, and they make a quick popular point”) are put together by one creator:

When I need to find a particular data set, it’s often as straightforward as a search for the topic with the word “shapefile” or “gis” attached. There’s so much data just sitting on servers that if you can imagine it, it’s probably out there somewhere (often for free). Sometimes though, finding data requires a deeper search. A lot of government-provided data sits inside un-indexed data portals or clearinghouses. Depending on the quality of the portal, these can be tedious to sort through…

Simplicity and ease-of-use: Interactive maps are great, but I want the maps I make to be straightforward to read and understand. I don’t want viewers to have to figure out how to use the map; they should just be able to look at it and figure out what’s going on.

Projections: Typical web maps are limited to the Web Mercator projection. I don’t have any objection to Mercator in principle (in fact it’s brilliant for what it does), but I can’t in good conscience use it for maps at a continental or global scale. Sticking to static maps allows me to choose more appropriate projections for the data and region I’m depicting.

Uniformity: I want everyone who visits my maps to be presented with the same information. I don’t want some algorithm deciding that one visitor is shown a particular view while another visitor gets a different one.

These principles sound similar to what one would expect for any sort of online chart or infographic. There is plenty of data available online but it takes some skill in order to present the data clearly and then market the map to the appropriate audience.

Now that I think about it, it is a little surprising that it took this long for viral maps to catch on. First, the Internet makes a lot of geographic data easily accessible. Two, it is a visual medium and maps are essentially graphics (audio is another story). Third, geographic data seems to feed into a lot of hot-button topics of conversation these days as people of different races (residential segregation), cultural viewpoints (think the American South or the Bible Belt), education (think the Creative Callas looking for exciting urban neighborhoods), and other groupings tend to live in different places.

I wonder if the real story here isn’t the technology that makes mapping on a large-scale relatively easy today. GIS software has been around for a while but it generally pretty expensive and has a learning curve. Now, there are numerous websites that offer access to data and mapping capability (think the Census or Social Explorer). Shapefiles are used by a variety of local governments and researchers and can be downloaded. There are good freeware GIS programs like GeoDa. You need some bandwidth and computing power to get the data and crunch the numbers. All together, the pieces have now come together for more people to access, manipulate, and publish maps in a way that wasn’t possible even just 5 years ago.

 

Tree diagrams as important tool in human approach to big data

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Big data may seem like a recent phenomenon but for centuries tree diagrams have helped people make sense of new influxes of data:

The Book of Trees: Visualizing Branches of Knowledge catalogs a stunning diversity of illustrations and graphics that rely on arboreal models for representing information. It’s a visual metaphor that’s found across cultures throughout history–a data viz tool that has outlived empires and endured huge upheavals in the arts and sciences…

For the first several hundred years at least, the use of the tree metaphor is largely literal. A graphic from 1552 classifies parts of the Code of Justinian–a hugely important collection of a thousand years of Roman legal thought–as a trunk with a dense tangle of leafless branches. An illustration from Liber Floridus, one of the best-known encyclopedias from the Middle Ages, lays out virtues as fronds of a palm. In the early going, classifying philosophical knowledge and delineating the moral world were frequent use cases. In nearly every case, foliage abounds…

At some point in the 18th or 19th century, the tree model made the leap to abstraction. This led to much more sophisticated visuals, including complex organization charts and dense genealogies. One especially influential example arrived with Darwin’s On the Origin of Species, in 1859…

While the impulse to visualize is more alive today than ever, our increasingly technological society may be outgrowing this enduring representational model. “Trees are facing this paradigm shift,” Lima says. “The tree, as a representational hierarchy, cannot accommodate things like the web and Wikipedia–things with linkage. The network is replacing the tree as the new visual metaphor.” In fact, the idea to do a collection solely on trees was born during Lima’s research on his first book–a collection of visualizations based on the staggering complexity of networks.

A few quick thoughts:

1. We talk a lot now about being in a visual age (why can’t audio clips go viral?) yet humans have a long history of utilizing visuals to help them understand the world.

2. We’ve seen big leaps forward in data dissemination in the past – think the invention of writing, the printing press, the telegraph, etc. The leap forward to the Internet may seem quite monumental but such shifts have been tackled before.

3. Designing infographics took skill in the past just as it does today. The tree is a widely understood symbol that lends itself to certain kinds of data. Throw in some color and flair and it can work well. Yet, it can also be done poorly and detract from its ability to convey information quickly.

Infographic: “Gender Inequality in [Hollywood] Film”

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Check out this infographic from the New York Film Academy on gender inequality in American films. A few of the facts involved:

-“Women purchase half of the movie tickets sold in the U.S.” but “28.8% of women wore sexually revealing clothes as opposed to 7.0% of men” in the top 500 films from 2007 to 20012 and the “average ratio of male actors to females is 2.25:1” in these same films.

-The number of men and women working behind the scene in major roles of the top 250 films of 2012 is pretty unequal: women are 9% of directors, 15% of writers, 17% of executive producers, 25% of producers, 20% of editors, and 2% of cinematographers.

-“Forbes 2013 list of the top ten highest paid actresses made a collective $181 million versus $465 million made by the top ten male actors” and “In 2013 the highest paid female actor, Angelina Jolie, made $33 million, roughly the same amount as the two lowest-ranked men. Furthermore, age appears to be a dominant factor in an actress’s monetary success compared to men.”

So much for progressive Hollywood? The infographic also suggests the depth of the inequality goes beyond just star actors and actresses; it applies to numerous important roles and how characters are regularly portrayed.

Another aspect of this is to think about using infographics for social activism. In one big graphic, this group has presented a lot of data regarding gender in American films. Is it more effective to present the data in (1) a splashy way – infographics are hot these days and (2) to overwhelm people with data?