I made a few tweaks and our humanflows visualization prototypes are now online. There’s a bit of information on how humanflows came about, who was involved, and a day-by-day recap of the design process. Once you get to the prototypes section, give the applets a few seconds to load and hopefully you’re not disappointed. The interaction is pretty intuitive. All you have to do is click and hold to browse the flow lines and the map. Also, if you can, go full screen on your browser. It looks much better that way (and how it was intended to be shown).
Again, I’d like to thank Miguel, Iman, and Monica for making my trip to Spain and the Visualizar workshop a memorable experience. Thank you!
The New York Times recently put up a cool data exploration tool to sift through the transcript of the most recent Republican debate. They call it the transcript analyzer. There are three key features:
View where candidates put in their two cents indicated by the blue, highlighted rectangles
Read the actual chunks of transcript for each block
Search the transcript to see when specific words and phrases were used indicated by the smaller gray highlighted rectangles
My particular favorite is the search feature because it really allows readers to dig into the transcript or a reader can find out which candidate is (or isn’t) talking about his or her point of interest and when in the debate the topic was discussed. The intuitive text scrolling is pretty awesome too. Good job, New York Times!
After two weeks at Visualizar, I’m back in the United States. It’s good to be back. I don’t know how many people know this (because I certainly didn’t), but the people in Madrid (or all of Spain?) eat a ridiculous number of sandwiches. I spoke to a couple of locals who said it’s pretty common to eat two sandwiches a day every day. I’m all sandwiched out.
Anyways, the Visualizar symposium / workshop was a lot of fun, really interesting, and I ended up learning a lot more than I expected from some incredibly talented people. During my two weeks, I had the opportunity to work with designers Miguel Cabanzo, Iman Moradi, and Monica Sanchez and we managed to build a visualization framework that shows migration data with economic indicators. We call the piece humanflows.
Human Flows, the Piece
I just tried putting humanflows online, but of course it’s not working on my server right now (because all computers are against me), so I settled for a couple of screencasts. You’ll just have to take my word for it that the whole thing came together really nicely with a kiosk-looking type setup and a designer’s touch (three of them, actually). The visualization itself was done in Processing.
Here’s the first one that just shows the flows. Right off bat, you can see the huge rush to the United States (especially immigrants from Mexico).
This one shows the flows with unemployment rate.
We also did one with GDP, but you get the idea.
Of course, now that we have a framework, there’s so many other things that I can think of adding. Functionality like specific country selection and the ability to browse through other indicators would really allow some serious data exploration and since we were working with data form the United Nations Common Database, which has a hundreds of publicly available datasets, there’s a lot to work with.
So there it is. Humanflows.
Through the development process, I learned a lot about what I can do with Processing as well as gained an entirely different perspective on data visualization — a designer’s perspective. Simple concepts like color and more complex ideas like how to approach a large dataset are some of the things that I learned that I think are important for statisticians and the more technically-involved data people to know. I’ll cover that stuff in later posts though.
For now, I’d appreciate any comments on our visualization and any ideas on how to improve it. How would you visualize migration data?
I feel like it’s been forever since my last post, so I just wanted to let everyone know that I am not dead.
It’s the last few days here at Visualizar so I’ve got a couple of late nights ahead to make sure we get our project done, and on Wednesday, we set things up for the one-month exhibition. That should be fun. It’ll be especially nice to see everyone else’s work out on display.
The most interesting part about this workshop has probably been working and talking to designers about data visualization. I’m a statistician. Everyone else is a designer of some sort. With a statistics background and just coming off my New York Times internship, it felt really strange for the first week to go from the very literal and straightforward representation of data to the artsy, metaphorical data visualizations.
The defining moment — when I saw a huge difference between designers and statisticians’ views on visualization — was what followed after a talk from someone from the GapMinder foundation.
I’ll get into all of this stuff I’ve learned once I return to the lovely United States of America. In the meantime though, there was short blurb about the Visualizar workshop on We Make Money Not Art. There’s a picture of my back. I’m famous.
Oh, and if you’re really bored, the MediaLab has a Flickr stream. They’ve been taking tons of photos.
I’m staying in a hostel here in Madrid and am currently in the “Internet Room.” I’m on my laptop, but there are six desktop computers in front of me, all of which are occupied. Three of the six people have Facebook open plus myself. It’s come to the point that Facebook has so many ways to share information, that almost everyone can find some use for it. Is there some way to share data in some similar social way?
I know there’s some data blogging available and a few social data sites, but they don’t have the same feel as Facebook. I think the main reason people like Facebook (other than an entertaining way to waste a few hours) is because they personally relate to the information displayed and there’s some kind of connection between friends and strangers. Read More
It’s been a couple of days here in Madrid. It’s about 6:00am in the morning and I really should get back to bed. I’m incredibly jet lagged though, so that’s not really an option. The past couple of nights I’ve woken up at 4:30am and have had trouble falling back asleep. Anyone who knows me, knows that I’m very much a night person and always wake up late, so obviously, I’ve been feeling a little off the past couple of days.
Anyways, the past couple of days have been interesting. I flew in on Wednesday, and was extremely tired. I only slept maybe an hour on the plane. Once I came in, I got lost for several hours looking for the hostel and then the Medialab. That was fun.
I’ve joined this group of three graphic designers / media artists. We’re dealing with a good bit of migration data in a project now known as Humanflows, and a good bit of data means a lot of Statistics fun.
OK, I’m finding myself in a bit of a daze at the moment, so I think I’ll pause it here, and resume a coherent thought later…
Have a good weekend :)
On a completely unrelated note, I just had real hot chocolate for the first time. I mean, it was like melted chocolate with cream. Delicious.
I was about to click away, but then I saw movement on the map. In addition to recent incidents, the map also has police unit tracking. You can see where certain units are at any given time as well as a video feed. That’s pretty cool. However, it doesn’t seem live, because every car is Officer Heinz, every car shows the same video, and the timestamp on the video shows November 2004. I guess it’s just a demo or prototype right now.
How cool would it be if that were live though? I can imagine plasma screens on the walls of every gang’s central control station. Crime could be transformed forever.
We all know fast food is incredibly bad for us and yet we still eat it. Why? Because it has tons of fat and tastes delicious. Nevermind that we will die a few days earlier for every French fry we eat.
Over at Calorie Counter, they try to make us feel guilty with numbers. Check out the Carl’s Jr. Double Six Double Dollar Burger with 1,520 Calories and a delicious 111 grams of fat. I’m a little surprised that it beat out the Burger King Triple Whopper with cheese. I shudder just thinking about eating one of those.
Anyways, there’s a whole lot of numbers here but not an incredible amount of meaning. How bad is bad? How much fat should I consume per day? Is 111 grams of fat bad? If yes, how will it directly affect me? Yes, 111 grams of fat is bad for you. You will directly feel the effects as you sit on the toilet in the morning wondering why it is taking you so long to take a dump. Now that’s context.
Also, with all the numbers, I bet all the tables would benefit from some kind of chart or, at the least, a simple infographic. Any takers? We should have a contest for who can make fast food the least appealing using nutritional data and without bending the truth.
Every day during the summer I walked past “Moveable Type” in The New York Times lobby. Since my adviser was one of the people working on it, I had the privilege to see it up close before the actual opening.
The picture is nice, but it’s nothing like standing there and experiencing the news. It’s especially nice to be in the middle of the two walls of panels (there’s a panel behind the photographer) and you get bits and pieces of the day’s paper and archive coming at you visually and um, auditorily. These bits and pieces are coming parsed from the paper in an intelligent (statistical) way. Listen to the NPR clip below to find out more. There’s also a video on The Times page.
Really, really great. Or as my adviser would say, “so sexy.” If you’re ever in the area, you should definitely take a look.
Many Eyes now has more detailed mapping functionality with the help of ESRI data. It was really only a matter of time before this happened. It’s come to the point where I almost instantly think ESRI when I think maps–that and The Times maps department (who frequently uses ESRI data :). Anyways, this is pretty nice looking stuff. They’ve got bubbles, color coding, and multiple maps in matrix form (to compare).
I didn’t get a chance to look at the maps in depth, but one thing that I noticed is that the region bubbles are only labeled if they’re at least a certain size. If they’re smaller than that threshold, then it’s just the bubble. I’m not sure what the threshold is, but I feel that it could be a bit lower so that more labeling can happen.
There’s also (of course) zoom-in, zoom-out, and panning– features we have come to expect from online mapping applications. Zoom and pan gets a little sluggish when there are multiple maps, but the feature still feels pretty useful.
When people I know can’t decide whether or not go to graduate school, I always encourage them to do so, because cool stuff like this happens. First I get to intern at The New York Times and now I’m headed to Madrid, Spain for two weeks to attend the Visualizar workshop. As you might have guessed, it’s a visualization workshop, and it’s headed by Benjamin Fry, Bestiario and Adrian Holovaty. I’m not sure who Bestiario and Adrian (although I will soon), but Ben is most recently known, or I guess most widely known for his work on Processing with Casey Reas.
There are ten projects, of which one I think I will be collaborating on. I’m not really sure how it’s going to work yet. Unfortunately I’m going to miss the conference part of Visualizar, because I couldn’t get to Spain soon enough on such short notice. I’m headed back to Buffalo on Monday (I’m in Los Angeles for the week) and then my flight to Spain is on Tuesday.
Sorry in Advance
Sorry in advance as my posts on FlowingData become a little sporadic during these two weeks, but I’ll be sure to write about the goings on in Spain while I’m there. I’m pretty sure it’s going to be really interesting and extremely educational.
Graphwise launched a few weeks ago, but I’m just hearing about it now, so I guess there hasn’t been a whole lot of buzz about this new application.
The Graphwise group has got a spider crawling the Web for data in HTML data tables and as a result, has accumulated a pretty big data warehouse. There’s currently 2,766,560 extracted tables in the Graphwise database. That’s pretty good, and I think they’re building on a pretty good idea. However, Graphwise advertises itself as three pieces of a three-piece puzzle — get data, visualize, and share.
To say the least, the visualize and share portions need work. Here’s a visualization from the front page:
Am I being too harsh? My conscious is yelling at me for calling the graphs regurgitated food.
OK, OK. So to sum things up — the data warehousing and Web crawling are great. The spiders are clearly doing their job, so thumbs up for that. As for the visualizations, I, well, uh, it needs work (along with all the other junk that comes with running these types of data-centric applications).
When I talk about data, people often zone out or don’t really see the interest. Why does this happen? People just don’t understand the wonder that is data and how much of their life is led by data. With that in mind, why would people share their data? You can’t share something you don’t know exists. Off the top of my head, here’s 100 reasons to be interested in, want to share, and get excited about data. Read More
While on the topic of maps here’s a Microsoft Virtual Earth mashup — US Demographics Visualizer. It allows the user to map US census data by county. Map population, age, ethnicity, election results, and income. It’s not quite as responsive as the Competitive Edge Explorer, but if you’re looking to explore country-wide census data, then it’s worth taking a look at.
I have not yet achieved that elusive zero-byte graphics program, but I do believe that bulk, in programming or in writing, can sometimes be an inverse measure of clarity and thought. Users dislike “bloatware” not only because it is a pig that wastes their computers’ resources but also because they know it usually reflects design-by-committee and sloppy thinking.
GOOD Magazine is really growing on me. Have you subscribed yet? All of your subscription costs go to the charity of your choice, and by all, I mean 100%. My subscription money went to Ashoka.
In their most recent awareness animation, GOOD Magazine takes you inside the business of death.
Throughout the developed world the business surrounding death has often been an uneasy topic of discussion. Originating in the mid-19th Century, the modern funeral has evolved into an economic and cultural monster, with a vast network of supporting industries and myriad options for your earthly remains.
The amount of money put into casket, tombstone, plot etc. is kind of frightening. As if a death in the family isn’t troubling enough.
Eyebeam, an art and technology research center, has posted two eco-viz challenges to get artists and technologists thinking about data visualization and the role it plays in raising environmental awareness. The first challenge is to create an eco-icon that signals something about the environment. It might be displayed as a sign or on a cell phone. The second challenge is to create an eco-viz that focuses on a data set and displays the data in a novel way.
This is exactly why eco-viz has become so important. Consumers (myself included) don’t know how they’re wasting resources and the effect they’re having on the environment. All consumers know is that the longer they leave the lights on or the higher they turn up the heat, the more money they have to pay at the end of the month. If consumers are consistently wasteful, then a high bill won’t seem that unusual. A few more dollars per month isn’t enough to get someone to turn the thermostat down a few degrees.
As Peter B. Crabb put it in Control of Energy-depleting Behavior (1992)
[P]eople do not use energy; they use devices and products. How devices and products are designed determines how we use them, which in turn determines rates of energy depletion.
The deadline for the eco-icon challenge is coming up soon — November 5. There’s more time until the eco-viz deadline — December 8.
Despite being surrounded with ads, this money clock was kind of, um, interesting. Put in how much you earn hourly, monthly, or annually, and it displays a running clock of dollars and cents for how much you’ve earned while watching the clock. It was amusing at first, and then kind of depressing after a few seconds.
Tom from Stamen Design and Hadley from the GGobi group kindly pointed me to the recently ported Flare visualization toolkit. Developed by Berkeley’s Jeffrey Heer, Flare looks extremely useful for anyone who is interested in developing interactive visualizations (e.g. time series, stacked bar, pie charts, graph) for the Web that run in the Adobe Flash player.
There’s a pretty good tutorial that I, as a beginner, found straightforward. I ran into some problems when I was trying to “import a library into another project,” but per Jeffrey’s suggestion, I upgraded to Adobe Flex 3 beta (currently a free download). That cured my problems. Adobe Flex is apparently still a little rough around the edges. Oh right, and the tutorial provides instructions on how to develop with Flare in the Flex Builder environment.
I’m currently going through the demos to gain a better understanding of both Flare and Actionscript, and it looks very promising. I’m pretty excited about what I can do once I’ve improved my Actionscript programming skills.
Check out some screenshots from the Flare demo reel after the jump.
On Last.fm, someone took snapshots of some Linkin Park songs, compared them, and concluded that all Linkin Park songs look are the same. I guess at a glance, the songs might appear the same because of the dark chunk towards middle left, but it kind of stops there. Sure, there’s some loud to soft and soft to loud alternation, but who likes songs who are loud (or soft) throughout?
The beginning of the post:
Each image above shows the audio level in (roughly) the first 90 seconds of a Linkin Park song. The tempo has been adjusted for a few tracks for better visual alignment.
Wait a minute. The tempo was adjusted for better visual alignment? If you’re adjusting the tempo, then really, all songs can be made to look the same. On top of that, we don’t know the x-axis or y-axis units. Finally, there’s a lot more to a song other than dynamics — such as key, tempo, rhythm, and lyrics.