Angel investors can be a Godsend… and not just because they can help fund your business. When I founded Mosaic, I spent a lot of time meeting with Angel investors and telling then about how my company helps photographer’s better access and store their photos. I did too much telling and not enough listening.
I was in full sales mode. I believed it was my job to convince them that Mosaic was a great investment and that together we were going to make boatloads of money. That was part of my job. But an even bigger part of my job was actually building Mosaic into a successful company.
Angel investors are really smart. A lot of them got their wings by building businesses themselves. They also get thrown more pitches than Kevin Youkilis.
I believe your should ask them for advice first and money second. If you start to hear the same types of questions from the investors, you have two options. 1) Go out and do research on the question and come back with answers. Ask them if this new data satisfies their question and if not what data would. 2) If the answer to their question isn’t good, then it is time to think about a pivot.
A pivot isn’t a bad thing. If you listened to your advisors early at the very least it will save you from a lot of wasted energy and resources. As a startup by definition you are trying to do a lot with few resources – so waste is evil. It might even save your business.
Balance your gut with what investors say. Be a harsh critic of your answers before you give them to potential investors. If you aren’t satisfied with your own answers to questions, neither will potential investors.
It is easy to get lazy with answers as being good enough. Quickly identify your startups fundamental business assumptions and figure out how you can test these assumptions as quickly (and cheaply) as possible. Angels bullshit meters are remarkably well tuned.
There is no right way to do any of this stuff. If you ask 20 Angel investors the same question, you will get 20 answers. The trick is to listen to all of them and figure out the right path for your business.
In this way, Angels are very similar to customers. Remarkably, investors and customers were giving us similar advice; it took us too long to realize this. Once we did, Mosaic started gaining customers more quickly and we had better luck with investors.
We were blessed with great mentors (many from The Capital Network) like Ben Littauer who saw our potential and worked with us to build a stronger business. (And yes, he ultimately invested.)
Ultimately if you listened to the investors needs and answered their questions, they will invest. I would rather err on the side of treating potential investors too much as advisors than too little. This might even slow down your fundraising efforts.
But even if those Angels don’t invest, you will have gained a lot.
About Gerard Murphy: Gerard is the CEO/Co-Founder of Mosaic Storage Systems. You can connect with him on Twitter or Google Plus.
from BostInno http://bostinno.com/channels/how-angels-can-make-your-company-better-without-...

You know what makes me sad? Nobody gives a shit about space anymore. When I was growing up space was exciting, now you can't have a decent space conversation with someone at the bar without them excusing themselves to go to the restroom THEN BLATANTLY NOT GOING AND STARTING TO TALK TO SOMEONE ELSE . That's how fights happen. This is a picture of a 30-foot rock that rolled across the lunar surface some 50-100 million years ago. You can still see it's tracks. The ones my truck left in the mud when I went to burn down my ex's house? I covered those. It's believed the rock got rolling from the impact of a meteor crash. Ugh, look at you -- you don't even care. Listen, here's what I want you to do: I want you to look at the moon tonight. And while you're staring at it, I want you to say OUT LOUD: "holy shit, we've put people up there". Then keep repeating it until you realize just how amazing that really is. Space: let's bring it back. Then start a cult.
Picture shows clear evidence of rock 'n' roll on the moon [dvice]
Thanks to Billy, who still wants to be an astronaut even though he got really claustrophobic and started crying that time I locked him in the closet. The right stuff: I'm not sure you have it.
from Geekologie - Gadgets, Gizmos, and Awesome http://www.geekologie.com/2012/02/dont-stop-there-keep-going-this-rock-rol.php
When we read something silently we are, essentially, saying it to ourselves in our internal monologue. Psychology researchers at Britain's University of Nottingham wanted to know whether the voice that reads in our heads matches the voice that we read aloud in. In other words, does your internal monologue have an accent?
It's an interesting question. Although you might think it's a given, previous studies have suggested that the voice you speak with and the voice you think with might not be pronouncing words quite the same. This newer study, published in PLOS last fall, found the opposite—that there is at least some level of match between audible and silent pronunciation.
What I really like, though, is how they constructed the study. After all, you can't just ask people how they pronounce words in their heads. Like the question of whether you say "soda" or "pop" or "coke", once you start thinking about it hard enough to answer, you suddenly lose all ability to know what you do when you aren't paying attention. (Note: That soda/pop thing hasn't actually been scientifically demonstrated. It's just a bit of personal anecdata that I thought was relevant here.) In order to get around that problem, the Nottingham researchers had subjects read limericks while carefully monitoring their eye movements. The subjects were chosen based on their accents—one group pronounced their "a" sounds so that "path" would rhyme with "Kath". To the other group, that rhyme wouldn't rhyme at all. Instead, for them, "path" rhymed with "Garth".
The subjects read the limericks silently to themselves. But when they got to rhymes that didn't make sense with their spoken accent, there was a distinct disruption in eye movement. Basically, the physiological equivalent of the subjects having to stop and think, "Wait. That doesn't rhyme."
The other really cool thing I found in this paper: The fact that what we know about he author of the piece can influence how we read it.
... some previous studies have presented evidence to suggest that ‘person-particular’ knowledge of the author of a piece of text can influence reading of that piece of text. For example, it has been demonstrated that knowledge of the presumed author's speaking speed can influence how quickly people read aloud a passage of text [32]. This finding has also been replicated, and extended to silent reading [33]. Findings from other studies examining auditory imagery during reading have suggested that readers simulate aspects of the voices of the characters featured in the text (see [34], and also [35], for related findings). The current research supports, and extends these findings, by demonstrating that in the absence of information about the writer's voice, or that of characters involved in the text, inner speech during silent reading resembles the reader's own voice.
Henceforth, I shall refer to this as "The Just-Read-Trainspotting Effect", in honor of the three weeks during college when I couldn't get my inner monologue to stop drifting into an approximation of a heavy Scottish accent.
Via Stan Carey
Image: Eight-Minute Mouth Move, a Creative Commons Attribution Share-Alike (2.0) image from bruce-asher's photostream
  
from Boing Boing http://boingboing.net/2012/02/13/what-the-voices-in-your-head-s.html?utm_sour...
The machines that made the Jet Age
By Tim Heffernan - Share this article
This is a companion piece to Iron Giant: One of America’s great machines comes back to life, a feature by Tim published in The Atlantic
Germany, June 1945. The Nazi regime has been toppled; the war in Europe is over. But the Allied victory is largely the result of sheer overwhelming force, not technological superiority — and the victors know it. Most glaringly, while the Allies still rely on propeller-driven aircraft, the Luftwaffe has put three jets successfully into service.
 A Messerschmitt Me 262, the first military jet to enter service. Brought to you by Krupp’s magnesium forging division. Photo: USAF
 A Boeing B-29, the first bomber with pressurized crew compartments. Brought to you by Rosie the Riveter. Source: USAF
The reasons for German air superiority were several, of course, but a key one was their mastery of light-metal forging. While the Allies were still bolting together their planes out of steel plate, a slow, labor-intensive process ripe for error and unsuited to design optimization, the Germans were stamping and squeezing out complex structural elements from magnesium and aluminum alloys.
Not surprisingly, after Germany surrendered, both the U.S. and the USSR sought to take control of its forging facilities.
The Soviets got the good stuff.
In so doing they got a head start on the Cold War race for supersonic air superiority. Unwittingly, they also set in motion a larger, and largely forgotten, industrial revolution that shaped the second half of the 20th century and will shape the 21st. This is the story of the birth of the Jet Age — but it’s anchored firmly to the ground.
 Photo: Library of Congress
The magnificent machine pictured above is a closed-die forging press, one of the biggest in the world. (For reference, check out the men standing at its foot, down there on the left.) It and nine other huge forges were built in 1950s by the U.S. government, in a long-forgotten endeavor called the Heavy Press Program. I wrote about the press and the program in the March Atlantic, and Maggie kindly invited me to write a bit more here, because — well, first of all, because just look at that thing. It stands nine stories tall (four of them are hidden under the floor), weighs 16 million pounds, exerts 50,000 tons of compressive force, and, like Vulcan’s own waffle iron, squeezes ingots of solid metal between its jaws until they flow like batter.
Here’s another picture for scale:
 Each casting was loaded individually onto a specially built train car and carried from Pittsburgh to Cleveland. Photo: USAF Air Force Material Command
Those are just four of the 14 steel castings that make up the Fifty, as the press is known, and they aren’t even the biggest ones. Those would be the twin 250-ton upper stationary crossheads, shown in Figures 5 and 6 of this document— also a good source for more technical details about the press.
And here’s a before-and-after of the Fifty’s handiwork:

 Press-forging minimizes waste metal compared to machining, and by realigning the metal’s internal crystalline structure along natural lines of stress, results in much stronger parts than casting would produce. Photos: Library of Congress
That’s a piece of titanium about 15 feet wide and a foot thick, in its raw state and after being forged in a single stroke between the Fifty’s hardened steel dies under 100 million pounds of pressure.
Though they were built nearly 60 years ago, the ten machines of the Heavy Press Program — four forging presses, the waffle irons, and six extrusion presses, basically giant caulking guns except the “caulk” is solid metal — are still among the most powerful ever made. Even more impressively, at least eight of the ten are still in use.
 Extruded aluminum parts (not parts from Heavy Press Program machines). Photo courtesy Dalcio Metal
So, what do they do? Well, in strict terms, they make heavy components for aircraft, spacecraft, and power-generation facilities. That chunk of titanium, for example, became one of the bulkheads that anchor the engines, fuselage, and wings of an F-15. More familiarly, every time you fly on a Boeing or Airbus, you’re relying on parts made by the Heavy Press Program machines to keep you aloft—things like the wing spars, which connect the wings to the plane’s chassis.
But in broader terms, what the machines do is make the Jet Age possible. On a plane, a pound of weight saved is a pound of thrust gained—or a pound of lift, or a pound of cargo. A lighter plane also puts less stress on its chassis when it goes through maneuvers. Supersonic military jets are optimized for speed and strength. Subsonic passenger and cargo jets are optimized for fuel efficiency and load capacity. Without the ultra-strong, ultra-light components that only forging can produce, they’d all be pushing much smaller envelopes.
Dawn of the Military-Industrial Complex
Back to 1945 for moment. The Soviet acquisition of Germany’s biggest forges made it all but inevitable that the U.S. would build its own heavy presses—but it’s important to note that it did not make the Heavy Press Program inevitable. Private industry could have built its own machines. The government could have built them, too, and indeed early plans called for the military to construct a “pilot plant” and dole out chunks of time to the air industry to experiment on government-run machines. The idea that it was in the public’s interest to pay for the machines but cede their control to industry was a controversial one, and many leaders in Congress strongly resisted it as a dangerous blurring of private and civic concerns.
On the other hand, with millions of WWII servicemen and women being demobilized, mass unemployment was a threat, and shoring up the aerospace industry was an attractive way to stave it off and harness wartime technology to the peacetime economy. Cold War policy also encouraged massive defense spending, but (as ever) a secondary war was being waged by the military branches for funding, and heavy forging wasn’t of much use to the Army or Navy. It was a complex situation, and one that could have been resolved in several ways. But by 1949 it had been decided that the government would build a number of heavy forging machines and the factories to support them, and that these facilities would be leased to the great metals companies of the day on very generous terms. The Heavy Press Program had begun.
Nifty Fifty
The Fifty was installed at Alcoa’s Cleveland Works facility and began operations on May 5, 1955. A complementary 35,000-ton press was installed shortly after. I have their initial production list, and it reads like catalog of American military air power of the age: wing roots for the Republic F-105, wing spars for the Convair B-58, landing gear trunions for the Boeing B-52, bulkheads for the Lockheed C-130—in all, hundreds of items. From the start, the forges were busy machines.
The Heavy Press Program also supplied Wyman-Gordon of Grafton, Massachusetts, with a 50,000- and 35,000-ton pair of forging presses. Here’s their 50K, nicknamed Major (yep, the 35K is Minor), and again, note the man standing at its foot for scale:
 The two 50,000-ton presses were of very different design — those interested can compare them here and here — but their dies were made to be interchangeable, so that production would not be disrupted if one of the machines broke down or was attacked during war. Photo: Library of Congress
To these four were added the six huge extrusion presses: a 12,000-tonner for Curtiss-Wright in Buffalo; twin 8,000-tonners for Kaiser in Halethorpe, Maryland; a 14,000-tonner for Alcoa in Davenport, Iowa; and an 8,000- and a 12,000-tonner for Harvey Aluminum in Torrance, California, just south of L.A. With stroke lengths of up to 92 feet, the extruders were used to produce long, hollow structures like aluminum missile bodies and wing struts in a single, seamless piece, saving time, weight, and material. Here’s the Harvey 12K, which went into service in August 1957:
 Though it was nearly 300 feet long and weighed 8 million pounds, the maximum variance along the Harvey 12K’s chassis was just 0.004 inches. Source: USAF Materiel Command
This iron giant—which reminds me somehow of a steam train—is the one Heavy Press Program machine that definitely no longer exists: it was cut up for scrap in the 1990s. And I haven’t been able to confirm the fate of the 8,000-tonner at Harvey—though it may have been shipped to Korea or China.
As for the other eight machines, they’re still working. Curtiss-Wright’s extruder ultimately was bought by Precision Castparts and moved to Houston, and Kaiser’s pair was taken over by Alcoa, but their jobs haven’t changed. They make the things that make us fly, and they’ll be doing so for decades yet.
A Stamp on History
I see three main legacies of the Heavy Press Program.
First, of course, is the aeronautics industry as it now exists. We are accustomed to talking about the ways abstractions like “technology” or “Washington” have affected life the world over. But the machines of the Heavy Press Program are a concrete—well, an iron-and-steel—example of how industry and politics can collide with enormous yet unpredictable effect. The civilian air industry was an afterthought when the program was conceived, yet it is arguably the program’s signal achievement. Again, every Boeing and Airbus jet you’ve ever flown, every one that has carried mail or freight across the oceans, on was built around vital structural components made by these huge machines. Their impact on global society and commerce has been incalculably great. But every American military jet that has fired a gun or dropped a bomb in war was also built around Heavy Press parts—and thus the greatness of the program’s impact is morally blurred.
 You can’t have this...
 ...without this.
Second is the military-industrial complex. I don’t believe it’s possible to place its origin in any single spot. But I am also not aware of any defense program since the HPP that was meaningfully opposed by Congress on the grounds that it threatened the functioning of American democracy. That a given project was “wasteful” or “bloated,” sure—but that’s just bookkeeping. The Heavy Press Program was in many ways the test case for the proper division between private and public interest, and it was decided in favor of what amounts to a mutual aid society between American industry, the American military, and Congress. The consequences are plain, and not often pretty.
Lastly is a legacy of absence. Today, America lacks the ability to make anything like the Heavy Press Program machines. The Fifty, to pick the one I’m most familiar with, was made by the Mesta Machine Company of West Homestead, PA, just outside of Pittsburgh. Mesta built the machines that built Steeltown — the furnaces, the blowers, the rolling mills and the forges. Mech-heads will want to check out this digitized Mesta brochure of 1919, a kind of Whole Earth Catalog for the iron industry. The less avid can just enjoy the picture below, from the same era. Then imagine what Mesta Machine could do by 1950, with three decades worth of further innovation under its belt.
 Mesta could mold, cast, forge, machine and field-test huge components under one roof — literally — a full-service shop of the sort that no longer exists in the U.S. Photo: Carnegie Museum of Art.
The company went under in the mid-1980s. It is not unambiguously bad that it and the rest of American ultra-heavy manufacturing are gone. But it’s not unambiguously good, either. Conventional wisdom would say that the industry went to less-developed nations, freeing American resources for higher-tech pursuits. In fact, the only companies today capable of producing Heavy Press-size equipment are in the backwaters known as Germany and Japan, with companies in Russia, Korea, and China rapidly catching up and the UK actively rebuilding its top firm, Sheffield Forgemasters, through cheap government loans. Just last year four Japanese companies joined forces to build a new 50,000-ton press for the aerospace and power industries, and while I was working on this piece China Erzhong, a nationalized conglomerate, announced that it will build an 80,000-ton press — the biggest ever — to support its nascent aerospace industry.
Now is not the time for America to build new forges: eight really is enough. But the original heavy presses, which have lived far longer and spurred far more innovation than was ever imagined, set an example that I think might yet be followed. Big machines are the product of big visions, and they make big visions real. How about a Heavy Fusion Program?
  
from Boing Boing http://boingboing.net/2012/02/13/machines.html?utm_source=feedburner&utm_medi...
We need a word that captures the specific sort of pain entrepreneurs feel when their carefully developed startup ideas are met with blank indifference. All that time. All that effort. And it adds up to ... this?
"Running Lean" author Ash Maurya (@ashmaurya) doesn't have that word, but he may have something better: a method for avoiding the pain altogether. In the following interview, Maurya explains how the Running Lean process helps startups iterate from flawed "Plan A" ideas to products people want.
What is Running Lean?
Ash Maurya: Running Lean is a systematic process for quickly vetting and building successful products. Most entrepreneurs start with an initial vision: their "Plan A." Unfortunately, most Plan A ideas don't work. Running Lean helps entrepreneurs iterate from their initial Plan A to one that works — before running out of resources.
What are the early signs that a Plan A idea isn't working?
Ash Maurya: A startup is about bringing bold, new ideas to the world. That naturally works to your advantage. Your initial goal is getting a strong signal (positive or negative) from customers. This typically doesn't require a large sample size. So, for instance, if you can't even get 10 strangers to say they want your product (or better yet, pay for your product), this problem is not going to go away by targeting 1,000 people. A strong negative signal indicates that your bold hypothesis most likely won't work. It lets you quickly refine or abandon it.
On the other hand, a strong positive signal doesn't necessarily mean it will scale up to a significant business. But it does give you permission to move forward on the hypothesis until it can be verified later through quantitative means.
Is there any value to writing a business plan?
Ash Maurya: Before you can start the process of iteration, you have to draw a line in the sand. You have to start by documenting your initial vision (or Plan A) and sharing it with at least one other person. Otherwise, it's too easy to endlessly iterate in your head and never be wrong.
Traditionally, business plans have been used for this purpose. But while writing a business plan is a good exercise for the entrepreneur, a business plan falls short of its intended purpose. Few people take the time to actually read business plans. More importantly, since many Plan As are likely to be proven wrong anyway, spending several weeks or months writing a 60-page business plan largely built on untested hypotheses is a form of waste.
I instead recommend using a one-page business model format called Lean Canvas. It captures the same core elements you find on a business plan, but because it fits on one page, it's a lot more concise, portable and readable.
Running Lean — This book demonstrates ways to apply and test techniques from the Customer Development, Lean Startup, and bootstrapping methods. Learn how to engage customers throughout the development cycle so you can build a product people will actually buy. (Note: This digital early release edition includes the author's raw and unedited content. You'll receive updates when significant changes are made, as well as the final ebook version.)
Why is it a bad idea to build products in stealth?
Ash Maurya: There is a fear, especially common among first-time entrepreneurs, that their great idea will be stolen by someone else. The truth is two-fold: First, most people are not capable of visualizing the potential of an idea at such an early stage; and second, they won't care. The initial challenge for most startups is getting noticed at all.
There is also a difference between stealth and obscurity. Stealth is bad because you build products in complete isolation only to find out later that you were optimizing a product no one wanted. On the other hand, obscurity is a gift. It allows you to test your product at micro-scale, getting it right, before attracting a lot of attention and scaling out.
So avoid stealth, but embrace obscurity.
Do the techniques in your book only apply to tech-centric startups?
Ash Maurya: Even though a lot of these concepts were recently popularized by tech-centric startups, I believe the principles they embody are universally applicable to products ranging from high-tech to no-tech. Several core principles in "Running Lean" date back to the last century when Taiichi Ohno and Shigeo Shingo were laying out the early groundwork for the Toyota Production System, which later became "lean manufacturing." I used these same techniques in the writing of my book, which I share as a case study in the book along with several other non-tech products.
What's the connection between Running Lean and the Lean Startup?
Ash Maurya: Running Lean is a synthesis of three methodologies: Lean Startup, Customer Development, and Bootstrapping. Of the three, Running Lean draws the most from Lean Startup. While the Lean Startup, created by Eric Ries, codifies the core principles, my goal with Running Lean was to create an actionable how-to guide for taking these principles to practice.
[Note: Eric Ries is the editor of the Lean Startup Series, which includes "Running Lean."]
Why did you decide to apply Lean Startup methods to your own work?
Ash Maurya: When I was first exposed to Lean Startup, I was already running a company and on my fifth product at the time. I had built products in stealth; attempted building a platform; dabbled with open sourcing; practiced release-early, release-often; embraced "less is more"; and even tried "more is more" — all with varying degrees of success.
I saw that acting on a vision can easily consume years of your life, and I was in search of a better, faster way of vetting and building products.
The key idea from Lean Startup that resonated with me was that of rapid iteration around customer learning. Specifically, that you could almost always test the riskiest parts of a vision without having to build the product first.
As I started internalizing these principles, I had more questions than answers. That prompted my own rigorous testing and application of these principles, which led to the book "Running Lean" and several other software products I am now building.
This interview was edited and condensed.
"Running Lean" author Ash Maurya will discuss the Running Lean methods in a free webcast on Feb. 14 at 10 am PT / 1 pm ET. Register to attend.
Related: 
from O'Reilly Radar - Insight, analysis, and research about emerging technologies. http://radar.oreilly.com/2012/02/running-lean-startups.html?utm_source=feedbu...
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Rise of the Independents (Bryce Roberts) -- companies that don't take VC money and instead choose to grow organically: indies. +1 for having a word for this.
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The Performance Golden Rule (Steve Souders) -- 80-90% of the end-user response time is spent on the frontend. Check out his graphs showing where load times come from for various popular sites. The backend responds quickly, but loading all the Javascript and images and CSS and embedded autoplaying videos and all that kerfuffle takes much much longer.
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Starry Night Comes to Life -- wow, beautiful, must-see.
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MapReduce Patterns, Algorithms, and Use Cases -- In this article I digest a number of MapReduce patterns and algorithms to give a systematic view of the different techniques that can be found in the web or scientific articles. Several practical case studies are also provided. All descriptions and code snippets use the standard Hadoop’s MapReduce model with Mappers, Reduces, Combiners, Partitioners, and sorting.

from O'Reilly Radar - Insight, analysis, and research about emerging technologies. http://radar.oreilly.com/2012/02/four-short-links-13-february-2.html?utm_sour...
Over the last few years I've created a few popular visualizations, a lot of duds, and I've learned a few lessons along the way. For my latest analysis of where Facebook users go on vacation, I decided to document the steps I follow to build my visualizations . It's a very rough guide, these are just stages I've learned to follow by trial and error, but following these guidelines is a good way to start if you're looking to create your first visualization.
Play with your data
I was lucky enough to spend a few hours with Andreas Weigend recently, head of the Stanford Social Data lab. He has nine rules of data, and the first is "Start with the problem, not the data." What struck me about visualizations is that I actually take the opposite approach. I find the only way to begin is to explore what information is available and get a feeling for what stories it can tell.
In my case, we have a Cassandra cluster with information on more than 350 million photos shared on Facebook. I've been running Pig analytics jobs regularly to get a view of what we have in there. One of the reports we generate is a count of how many photos and users we have for particular places:
 Click to enlarge.
I was chatting with my colleague Chris Raynor about this, and he asked me if we could tell where all the visitors to those places were coming from. This was something that had been at the back of my mind for a long time. Seeing how much information we had on each destination made me realize we had enough data to produce significant and meaningful answers.
When I was learning engineering, one of my favorite case studies was an investigation into an air-traffic control system. Software engineers couldn't understand why fully-computerized control rooms were actually less efficient and safe than more old-fashioned sites. What the researchers discovered was that the old process of passing around and arranging small cards that each represented a plane gave controllers a much stronger awareness of the situation than a screen that didn't require their involvement for tasks, such as handing an aircraft to a colleague. I think the same is true of data. The more time you spend manipulating and examining the raw information, the more you understand it at a deep level. Knowing your data is the essential starting point for any visualization.
Pick a question
Now that I had a rough idea for what I wanted to visualize, I really needed to focus on what I would be doing. The best way to do that is to chose the exact title you want to give your visualization. I actually messed this up on one early map I created, giving the blog post the title "How to split up the US." Everyone subsequently described it as "The Five Nations of Facebook." Since then, I've tried very hard to pick the most natural title for what I'm going to be presenting, and then ensure I can deliver on the promise of the headline.
In this case I had a clear idea of the question at the start, it was going to be "Where do people go on vacation?". However, as I thought about it, I realized it needed to be a lot more specific and concrete. There's already a lot of "top travel destinations" lists out there, so what made mine different? It was the use of Facebook to gather much richer and more detailed information, so I refined it to "Where do Facebook users go on vacation?".
Sketch out your presentation
I now had the data and a question I wanted to answer. The next step was figuring out how to show the information in a visual form. I'm in love with network diagrams showing connections between thousands of objects, but so often they are completely baffling to the rest of the world. I still remember David Cohen threatening to strangle me if I showed him another one of "those damn spider webs" instead of a business plan. However, network diagrams are a good way of hinting at how much data is available for querying; they can really give an idea of the sheer scale of what's there.
One of my favorite recent visualizations was Paul Butler's map of friendships on Facebook, so I decided to use that as a visual reference:
 See the full version of Paul Butler's "Visualizing Friendships" visualization.
I borrowed a couple of key ideas from his work: the general color palette of the blue lines on a dark background and the use of great circles to create flowing arcs for all connections.
As I thought about the presentation, I realized that I had to simplify what it would be showing. With sources and destinations plotted all over the world, both the visual look and the querying interface would be overwhelming. Our user-base is primarily American thanks to our reliance on English-only natural language processing, so with that in mind I decided to make life simpler by only showing data from people who lived in the U.S. Accordingly, I changed the question in my title to "Where do American Facebook users go on vacation?".
While I'm mostly presenting this as a linear, waterfall process, what I've just described is a good example of how iterative cycles drive the real workflow. It's hard to know how well a lot of things will work until you try them. As you're still making some progress, don't worry if you find yourself going in circles.
Crunch the data
If you know your data, and you have a good idea of the question you're trying to answer, this should be the simplest stage. You'll hopefully have a clear set of requirements and it's just a matter of executing the right queries over your data.
In this case I already had some Pig scripts asking similar questions, so I was able to adapt one of those. The biggest surprise was when I ran into issues with some of the joins. The hard part was running the Hadoop job to gather the raw data from our Cassandra cluster, and that worked. I was able to output smaller files containing the gathered data, and then run a local Pig job to do the joins I needed.
The next stage was turning the raw information into a form that could be displayed. For example, I needed to take all of the user locations from the unstructured text strings that Facebook gave me, and convert them into latitude-longitude coordinates for plotting on a map. For this sort of work I usually turn to a general-purpose scripting language, and most of Jetpac is already written in Ruby, so that was an easy choice. I wrote a script that walked through the data, using the Data Science Toolkit to match coordinates with names, and then output it into a file containing a JSON array of all the information.
Build an interface
A lot of the best visualizations have no interactivity. They just tell a story with a static image. That's why it's worth considering whether you need an interface at all. I actually had the interactive site that I used to create the "Five Nations of Facebook" visualization up for several weeks before that post, and nobody used it because it was too confusing. It was only when I boiled it down into a single picture with labels that it became a hit.
My problem is that I want other people to have as much fun exploring the data as I've had, so I couldn't resist adding some interaction to the vacation visualization. I still wanted to retain the immediate visual appeal of a static image, so I decided to create a background showing the full data to introduce the visualization at a first glance, and then overlay an interactive foreground once the user started exploring it more deeply.
In most cases you're better off using one of the excellent off-the-shelf visualization frameworks like D3. Since I needed something client-side for interaction, and was working with both geographic and network rendering, I couldn't find anything that met my requirements. Instead I cannibalized one of my own projects, the jQuery component from OpenHeatMap, and combined it with HTML5 canvas rendering to produce a custom JavaScript renderer. I used it to pre-render a background containing all the possible connections between home towns and travel destinations, and saved that off as a static image. That's useful to save rendering time on page load, and lets me fall back to a static visualization on older browsers that don't support Canvas.
 Click to enlarge.
I then tied in rendering the connections of any places that the user was hovering their cursor over, so that they could quickly get a feel for the relationships expressed in the data. I also wanted to display the details underlying the picture, so to drill down I added a dialog listing the raw statistics about a place. Users can bring this dialog up by clicking.
 Click to enlarge.
One problem with that interaction is that a lot of different cities are in a very small area, so it becomes extremely difficult to pick the one you want with the mouse cursor. To make that a little better, I prioritized the most popular U.S. cities so that in case of a conflict, they're chosen over their smaller neighbors. I realized I also needed to add a search box. Thankfully we're heavy users of Twitter's Bootstrap framework, so it was a simple matter to add a search field and tie it in with Twitter's excellent autocomplete component.
Find the surprises!
I build these visualizations so I can explore them myself, so my favorite part of the whole process is the chance to sit and play with the results. There's always unexpected stories hidden in there, and I love uncovering them. For example, who knew that the city that had the most visitors to Paris was West Hollywood? When I lived in Los Angeles I used to love popping by the wonderful patisseries. Now I know why they're so good! These little details are the stories that catch people's imagination and cause them to spread the word, so think about writing a few of them up to help visitors understand what the page can tell them.
You'll never know whether one of your visualizations will become popular ahead of time, but the real reward is enjoying your own work. I hope this short guide gives you some ideas for visualizations you want to build. I look forward to seeing what you come up with.
 See the full visualization.
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from O'Reilly Radar - Insight, analysis, and research about emerging technologies. http://radar.oreilly.com/2012/02/how-to-create-visualization-facebook-vacatio...
Social Media Week is upon us, so we thought it would be appropriate to delve into the social media industry and see how its salaries stack up. Social media is an evolving and cutting-edge field, so it should come as no surprise that you can make a great living managing a brand’s presence on Twitter, Facebook, YouTube, Tumblr, LinkedIn, Google+, Pinterest, Instagram, Foursquare and other social platforms.
In the infographic below, produced by OnwardSearch, you can see where the social media jobs are concentrated, the breakdown of job titles in the industry, and how much dough the average social mediate is bringing home each year. (The graphic shows the 25th and 75th percentiles for salary, pulled from Indeed).
Does this stack up with what you’ve seen in the industry? Do you think these positions and the salaries make sense, given the rise of social media? Let us know in the comments.
Infographic courtesy of OnwardSearch
Social Media Job Listings
Every week we post a list of social media and web job opportunities. While we publish a huge range of job listings, we’ve selected some of the top social media job opportunities from the past two weeks to get you started. Happy hunting!
More About: community management, infographics, job search series, salary, Social Media, trending 
from Mashable! http://mashable.com/2012/02/12/social-media-salary-infographic/?utm_source=fe...
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