The November issue of Popular Science is a special on data. There are a couple of original graphics by Jer Thorp and Jan Willem Tulp, along with a handful of interesting articles. I also got to put together a gallery of some of favorite visualization projects over the past few years.

A couple of infographic résumé sites, vizualize.me and re.vu, sprouted up that use your LinkedIn data to show your career stats. Just create an account, connect it to LinkedIn, and you get some graphs that show when and where you worked. It’s a visual form of your LinkedIn profile with a goal to replace the “old” and “boring” résumé that uses just text.

Is this the best way to go though, if you’re applying for a job?
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Designer Stefanie Posavec talks about her process of data collection, analysis, and design. There’s a lot of advantages to knowing how to program, but there can also be value in meticulous manual discovery if you’re willing to put in that extra time.
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Lulu Pinney goes over the subtle art of working with significant digits:

When we say on the phone “I’ll be there in half an hour” it’s quite likely we’ll arrive sometime in the next 25 to 35 minutes. But for the context of meeting up with a friend “half an hour” will do. If you said “see you in 27 minutes” that would raise a laugh being an odd level of precision for the given context. The same ideas apply to numbers in journalism.

Important in both accurate representation of data and readability.

A fun map by Jamie Popkin of Little Earth that animates the use of the F-bomb, C-word, and “regular swear word” over a month. There isn’t much information about where the data comes from, but I’m guessing Twitter. Each circle represents the use of a swear word, and the intensity grows as time passes. Too bad it doesn’t cover the world or the entire United States.

[PottyMouth via @awoodruff]

Note from Nathan: Last week, visualization researchers from all over gathered in Providence, Rhode Island for VisWeek 2011. One of the workshops, Telling Stories with Data, focused on data as narrative and what that means for visualization. This is a guest post by the organizers: Nick Diakopoulos, Joan DiMicco, Jessica Hullman, Karrie Karahalios, and Adam Perer.

“Data storytelling” is all the rage on websites ranging from international news outlets, to political and economic organizations, to personal blogs. Indeed, this trend has captured the attention of those who research and work in information visualization. Scores of both aspiring and seasoned visual storytellers descended on the Telling Stories with Data workshop that we organized this year (the 2nd installment of the workshop) to discuss and learn about visualization storytelling tools, issues, and contexts. The workshop took place in Providence, Rhode Island on October 23rd and was part of the yearly international VisWeek conference which itself drew about 1,000 attendees.

As in many technological fields, those interested in “narrative visualization” face the challenge of connecting with like-minded others across the oft un-negotiated boundary between academic research and practical applications or designs. Yet these groups have much to learn from one another. To bring visualization research in contact with visualization practice, we structured the workshop line-up of speakers to include both academicians (e.g. from Harvard, UC Berkeley, UIUC) and people from industry (e.g. New York Times, Microsoft Research, OECD, Workbook Project). The talks were organized into three blocks: (1) tools for structuring and sharing, (2) communicating with visualization, and (3) storytelling in context.
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In a follow-up to last year’s visions of the future, Microsoft imagines interacting with data and information in 2020. It is the land of big displays, linked devices, and projections in the real world. It’s mostly from a productivity standpoint, but there’s crossover to the everyday.

To be honest though, all I really want are power laces, a self-drying coat, a flying car, and rehydrating pizza. I wouldn’t mind a hover board either, but it’s not urgent. I don’t think that’s too much to ask. I can deal with not being able to flick graphs in the air if it means getting the important things sooner.

[Video Link via @juiceanalytics]

NPR explains how we reached a population of 7 billion. Simply put, the world is making babies faster than people are dying, and with improved medicine and agriculture, people are living longer than before. The video above demonstrates the different birth and mortality rates, where each container represents a continent.

There has been a shift in recent years:

Much of that growth has happened in Asia — in India and China. Those two countries have been among the world’s most populous for centuries. But a demographic shift is taking place as the countries have modernized and lowered their fertility rates. Now, the biggest growth is taking place in sub-Saharan Africa.

[NPR via Graphic Sociology]

Another month, another crazy circular discussion on the chances of answering a question correctly. Thanks again for sharing and tweeting. Always appreciated.

1. Best statistics question ever
2. Where people don’t use Facebook
3. The Venn Piagram
4. Bible sentiment analysis
5. Language communities of Twitter
6. #thankyousteve
7. All numbers lead to one
8. Kill Math makes math more meaningful
9. Nobel laureates by country and prize
10. Venn diagram: Platypus playing a keytar

According to estimates from the United Nations Population Division, there are now over seven billion people in the world. That’s enough people to fill, like, an entire room. Yeah. Visualization firm Bestiario, for The Guardian, shows this growth by country, using their home-brewed visual programming language, Impure.

There are a few options to play with. You can click on the bubble for a country to see the time series on the bottom for population from 1950 to 2010, through a projected 2100 population. Life expectancy for the same range is also shown. To compare geographically, you can also choose the year filters in the bottom right to compare, say, population in 1950 to that of 2010.

India and China of course pop out in that range, whereas many African populations are expected to increase a lot, percentage-wise, during the next century.

[The Guardian]

So many movies, so many creepy crawlies that go bump in the night. Very Small Array continues its ongoing run of charts about movies with this map, just in time for Halloween. Watch out Indiana. Daylight Saving Time is coming to get you.

Speaking of Halloween, my wife bought two bags of handout candy from Costco this year. I predict ten pounds will be going in my stomach next month.

[Very Small Array]

By way of Raymond Johnson, the best statistics multiple choice question ever written on a chalkboard. Try not to think too hard. [via]

The word you’re looking for is epic. From Tenso graphics, maker of amusing t-shirt sketches. [via]

Posts and links get shared over and over again, but we usually don’t know how. We get counts, but who shares what and how far do does a link reach? Google+ Ripples gives you a peak into the process. A link or status is posted, and like when a pebble is dropped in a pond, a pattern forms outwards.
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Eric Fischer maps language communities on Twitter using Chrome’s open-source language detector. Each color, chosen to make differences more visibly obvious, represents a language. English is represented in dark gray, which is used just about everywhere, so it doesn’t obscure everything else.

The emergence of borders without actually drawing them in is interesting. There’s a little bit of blending, but the splits are pretty well-defined. Especially in the Netherlands, where the tweet dispersal seems to be abnormally dense in that area. What’s going on over there?

There’s also a world version, but Europe is where all the action’s at.

[Language communities via @enf]

Casey Reas and Chandler McWilliams asked visual designers why they write their own software and how it affects their process:

The answers reflect the individuality of the designers and their process, but some ideas are persistent. The most consistent answer is that custom software is written because it gives more control. This control is often expressed as individual freedom. Another thread is writing custom software to create a precise realization for a precise idea. To put it another way, writing custom code is one way to move away from generic solutions; new tools can create new opportunities.

Most of the interviewees are media artists, but there are a couple of names you’ll recognize. My favorite, Amanda Cox, uses a Mad Libs metaphor:

Mad Libs is a game where key words in a short story have been replaced with blanks. Players fill in the blanks with designated parts of speech (“noun”, “adverb”) or types of words (“body part”, “type of liquid”), without seeing the rest of the story. Occasionally, hilarity ensues, but no one really believes that this is an effective method for generating great literature.

I’m looking at you, non-programming statistician.

Update: The article isn’t there anymore, so you can read the cached page for now.

Apple has a page dedicated to Steve Jobs that displays messages from friends, colleagues, and fans. Neil Kodner downloaded those messages and extracted overall themes:

I wanted to see what how people were speaking about Steve Jobs and especially what terms were being used to describe him. There was no point in performing sentiment analysis on this text as all of the texts were not only obviously positive but were also vetted by Apple for content. Using NLTK, I performed part-of-speech tagging on every word in each tribute message and then wrote some code to total the adjectives and adverbs used in the tribute messages.

The top descriptors? Not surprisingly: great, many, first, sad, better, best, and visionary. About one in five messages referenced an Apple product.

The message data and Kodner’s code is available on github.

[Thanks, Guy]