Monthly Archives October 2011

How to Survive the Zombie Apocalypse [Infographic]

Photo on 2011 10 31 at 15.00 3 300x225 How to Survive the Zombie Apocalypse [Infographic]Greetings fair blog readers. You are looking mighty… tasty today. Uhm, I mean… I hope you all had an excellent Halloween weekend. As you may have noticed, I’m looking a bit under the weather today. Craziest thing – I was out with some friends on 6th Street and was accosted and bitten by a particular rowdy gentleman dressed as a farmer.  At least, I think he was a farmer… his fingertips were worked down to the bone and for some reason, he kept repeating the world “grains” over and over again.  ”Graaains…. Graaaaains…. GRAAAAINS”!  That man must really love his barley and wheat!

Whew, I’m starting to feel a little feverish again.  Maybe I should head home for some rest… mmm, but the data mine is looking pretty tasty. All those engineers… so full of big, fat, juicy brains! Mmmm…

zombieinfographic thumb How to Survive the Zombie Apocalypse [Infographic]

(via Nether Noir)

Happy 7 Billion Day!

Today, October 31, 2011, has been declared 7 Billion Day by the UNFPA, United Nations Population Fund.  Yes, despite lacking a complete census of the world’s population, today has been declared a milestone date in human history and to celebrate, the UNFPA launched 7 Billion Actions, where they are encouraging people to participate in their communities, both online and offline.

Our favorite part of this whole campaign?  The header link that says “Data” on the 7 Billion Actions page.  Here you’ll find a slick interactive visualization of the world’s current and projected demographics and population data.  Some of the most fascinating insights are documented in the videos at the bottom of the page, including this one, which illustrated the paradox of the current world’s population, which is both getting younger and older at the same time.

Hey Baby, What’s Your Number?

Hello!  From now on, you can call me #4,770,751,276.

Tomorrow is 7 Billion Day and to celebrate, Population Action International has created a little web app that calculates your number amongst the nearly 7 billion people alive today. Nearly 2.3 billion people have been born since the early 80s, which, as noted in the chart in yesterday’s post, was approximately the world’s population in the 50s (when my parents were born).  Find out your number by clicking the image below and let us know what your thoughts are on reaching 7 billion.

populationaction Hey Baby, Whats Your Number?

When I Was a Kid, the Earth Only Had 5 Billion People…

On Monday, October 31st, the UN has declared “7 Billion Day“, the day when the world population will reach 7 billion people.  While believing Halloween 2011 is the exact date of the world population crossing the 7 billion threshold is a bit naive, it is interesting to consider the significance of this milestone.  I recall as a child in pre-K celebrating the Day of 5 Billion (July 11, 1987), which got me thinking – has the world population really grown by 40% in my brief lifetime?  And the answer is amazingly – yes.  While it took until from the start of human history til 1804 for humans to reach our first billion, the growth since has been astronomical.  The first doubling after reaching our first billion took 123 years, while the next doubling only took 47 and we’re adding an additional billion people approximately every 13 years.

I’ll be curious to see how world population growth plays out over the course of my lifetime.  If the last 28 years have been any indication, we’re in for a wild ride.

World population milestones (USCB estimates)
Population
(in billions)
1 2 3 4 5 6 7 8 9
Year 1804 1927 1960 1974 1987 1999 2012 2027 2046
Years elapsed - 123 33 14 13 12 13 15 19

Source: Wikipedia

 

 

 

 

 

 

 

Where Does The Weather (Data) Come From? Visualizations of Worldwide Weather Stations

This post was written by Hohyon Ryu, who interned with us this past summer as a Catalog Engineer.  He’s currently pursuing a PhD at the University of Texas’ School of Information.

The idea for this project started from one of the simplest and most essential questions in computer science. How close is the nearest X from where I stand?  To explore how to answer this question, I used our NCDC Weather Station API and attempted to answer, “What is the closest weather station from where I stand”?

stations map left 1024x517 Where Does The Weather (Data) Come From?  Visualizations of Worldwide Weather Stations

A brute force algorithm that calculates distances from all the weather stations will have to go through 2.5 million weather stations. It works but it just takes long long time.

mapgrid Where Does The Weather (Data) Come From?  Visualizations of Worldwide Weather Stations

One better solution is dividing the earth by grids. We may divide the globe into small tiles and find the closest station in the grid that I’m standing in. This solution is very fast, but there’s another problem. In the map below, let’s say I’m standing in New Orleans. There are 2 stations: one in Baton Rouge and one in Slidell. The closest station would be the one in Slidell, it is in a different tile. So this algorithm would find the one in Baton Rouge as the closest point.

voronoi 1024x560 Where Does The Weather (Data) Come From?  Visualizations of Worldwide Weather Stations

So, came up with this solution, a Voronoi diagram for all the stations in the world! It looks like a very complex calculation should be involved to generate a map like the following, but it takes only a few minutes to build the world scale map with 2.5 million points. Each station has a polygon that indicates the range it covers.

The best solution for us was grid + Voronoi lattice. Now let’s go back to the New Orleans problem. We’re in New Orleans and it is in the grid that intersects with the Voronoi polygons of Slidell and Baron Rouge. So now, we know that we have 2 candidate stations and the one in Slidell is the closest one.

Want to try out making your own visualization of our weather station data?  You can find the NCDC Weather Stations API here and the Voronoi Lattice library written in Python is available at Github.

What Paying Off Credit Card Debt Really Looks Like

According to CardWeb.com, the average American household with at least one credit card has nearly $10,700 in credit-card debt with an average interest rate that runs in the mid- to high teens at any given time.

How do we get ourselves in so deep?  This infographic from Visualizing Economics reminds us of the power of a little thing called compound interest and how it can have you spending in upwards of 50% more than the original purchase price of the item you put on your credit card. While in the short run, it may seem like a good idea to just make your minimum monthly payment, it’s pretty evident that such a decision can haunt you for long after you swipe your card (in this case, over seven years!).

PayoffYourDebt 650x944 What Paying Off Credit Card Debt Really Looks Like

(via Visualizing Economics)

Mining Google for Market Research: The Tablet Market & What We Really Want

What People Want From Tablets Full Mining Google for Market Research: The Tablet Market & What We Really Want

When Apple first introduced the iPad in 2010, there was no small amount of skepticism. However, the product’s initial mixed reaction did not stop it from selling over 14.8 million units and being named as one of Time Magazine‘s 50 Best Inventions of the Year 2010.  The iPad now takes approximately 83% of the total tablet market.

So, how will folks like Amazon Fire and Samsung Galaxy possibly compete?  Dell asked themselves the same question and hired design and branding agency, Method to do research on the tablet market.  The hope?  To uncover some new insights to help Dell design a product to compete with the iPad behemoth.  So, what did Method find?

Method proposed a novel approach to better understanding the tablet market.  Rather than conducting focus groups and customer interviews, the company mined Google to figure out what people were searching for.  Exploring exact-match search volumes, they produced a mind-map-like infographic that showcased what folks actually cared about.

The bigger the black circles (which represent tablet properties), the more it was searched for.  The darker the color of the colored nodes coming off the black circles, the higher the search activity was there.

What this data visualization uncovers are some interesting dimensions of how people search for products in this market.  Speed, memory, screen size and weight – four factors that we’ve grown accustomed to believing play a heavy role in purchase decisions for laptops – are hugely important factors for tablets.  Storage, battery life and interestingly enough, depth were the three key components.  Diving into these three dimensions a little bit more deeply, you’ll see that folks are looking to maximize battery life, want lots of storage and are generally looking for a model that is on moderately thin side.

What does this all mean?  In the pool of current and potential tablet users, it’s more important for the device to be easy to use (lots of storage, not going to die on you easily, reasonably light) and not necessarily powerful (memory, speed, etc).  I’d be curious to track these searches over time to see if folks’ expectations of these products ramp up or if we really are reasonably content with how powerful our tablets are.

(Infographic by Method via Fast Co Design)

When the Data is More Valuable Than the Device

water view When the Data is More Valuable Than the Device

I came across this Wall Street Journal article last week which included a blurb about a company, Liquid Robotics Inc. They make unmanned water vehicles with some pretty impressive technology.

By continuously harvesting energy from the environment, Wave Gliders are able to travel long distances, hold station, and monitor vast areas without ever needing to refuel. A unique two-part architecture and wing system directly converts wave motion into thrust, and solar panels provide electricity for sensor payloads. This means that Wave Gliders can travel to a distant area, collect data, and return for maintenance without ever requiring a ship to leave port.

Others have also been impressed by the company and they recently raised $22 million. This news is fairly interesting to a VC geek like me, but the thing that really caught my attention was their recent pivot. At Infochimps our data suppliers typically fall into one of two categories: 1) companies in the business of selling data (eg AggData), and 2) companies in the business of selling something else, but that want to monetize their data byproduct (see: Twitter). Liquid Robotics is an example of the latter. In the course of making unmanned water vehicles, they recognized their data byproduct was more valuable than what they were selling.

73955v1 max 250x250 When the Data is More Valuable Than the DeviceLiquid Robotics is sending a fleet of four of their unmanned water vehicles across the Pacific (PacX) to collect over 2 million data points on salinity and water temperature, waves, weather, fluorescence, and dissolved oxygen. They are making this data accessible to scientists, but I am sure there are many companies chomping at the bit for it.

Many companies use their own data to gain insight into their operations, but more and more companies are using third party data to go way beyond that. Quentin Hardy posits in this New York Times article whether we’re in a big data bubble. He says yes, but I say no. The big data stack is maturing and the tools available enable companies to ask myriad questions to both their own data, as well as data from third parties. This marriage provides additional insight and begets many more questions.

As more and more companies recognize the value of their data and seek to monetize it, and as more and more companies use third party data to gain insight, Infochimps will be there to provide liquidity in the emerging data marketplace.

A Marketer Learns How to Program

Okay, I have a confession to make. Though I’ve helped write example queries, created wireframes for webpages and heck, even toyed around with our API Explorer, I’ve never written a single line of code. Not terribly surprising for a marketer; however, after hanging out with the chimps for the past six months, I felt like it was finally about time to learn something. But where to start? Would I really have the time to commit to a regular weekly class? Could I make myself curl up with an O’Reilly book on PHP or Ruby with other more pressing projects looming? Clearly, the only way I could make this a priority is for it to be fun!

codecademy A Marketer Learns How to Program

Meet Codecademy, which I’ve been nerding out on all morning.  In fact, in the last hour, I’ve learned how to define variables and starting working with strings, substrings, arrays and if/else.  The best part of the whole thing?  It’s been absolutely delightful.  Much of this comes from the amazingly simple layout, which takes students through progressive lessons on the basics of programming and JavaScript in a command line setting.  The initial concepts are easy to grok and they build beautifully on each other, until suddenly, whoa – did I just define variables, prompt a user for input and create different returns based on user input?

While, this might not sound like much to the hardcore programmers out there, for a marketer who had never written a lick of code in her life as of an hour ago, Codecademy is a pretty rad resource.  Share it with your programming-novice friends and see what they think.  Or, contribute to their lesson plans and get more folks coding!

Data Visualization as Art: I Want You to Want Me

2 Data Visualization as Art: I Want You to Want Me3 Data Visualization as Art: I Want You to Want Me2 Data Visualization as Art: I Want You to Want Me

On February 14, 2008, Jonathan Harris and Sep Kamvar unveiled “I Want You To Want Me“, an interactive art installation, commissioned by the Museum of Modern Art, for their “Design and the Elastic Mind” exhibition. Using data collected from dating sites every few hours, the project explored the search for love and identity in the world of online dating.  Using balloons to represent individuals, the piece is divided into movements, each expressing a different elements of a user’s profile, translated into a balloon’s path of travel and grouping. While this exhibit has long left the halls of the MOMA, you can still enjoy a bit of the magic captured here. This interactive work reaches a level that most data visualization strives for: beauty and clear expression of the underlying data.