Remember SimCity 2000? That was a great game. That was probably the last computer game I played for any significant length of time, and if my Macbook Pro were able to read 5-inch floppies, I'd totally pop it in and build myself a city called Yau Town.
Put the look of SimCity 2000 together with Google Maps, and you get OnionMap. Most of the site is in Korean, but from what I gather it aims to be something of a tourist guide with a little bit of social network mixed in. That part of OnionMap is a little fuzzy, but it was worth the five minutes for the maps.
I've always liked twittervision. I'm not sure what it is, but it's strangely mesmerizing, getting a tiny peak into others' lives. This weekend, I recreated twittervision with a little bit of style for good measure. Say hello to Twitter World.
Twitter World shows updates from the Twitter public timeline, and makes use of the twittervision API for location. Until I get whitelisted for the Twitter API, I'm polling Twitter and twittervision every six minutes to keep things fresh. Hopefully neither putters out.
Like my visualization showing the spread of Walmart, I used Modest Maps (+ OpenStreetMap) to map things out, and I used TweenFilterLite to animate. I had all the gears in place and everything working nicely a couple of hours in - but that was with a flat XML file. The hard part was feeding the thing live data and then making sure everything was synchronized. That took, um, too much time.
Lee Byron, recent Carnegie Mellon grad and newly inducted New York Times graphics intern, maps walkability in San Francisco. He scraped Walk Score for uh, walk scores, which are scores from 0-100 based on the amenities around a location like "nearby stores, restaurants, schools, parks, etc" - how easy it is to live without a car.
Color was calculated on a per pixel basis using bicubic interpolation. From there he let Processing do the graphical labor to construct a map overlay. The result, which is accurate to the block, is a pretty one.
If you want data (sans map) for your own neighborhood, Lee has kindly provided the scraper.
The G-Econ (Geographically-based Economic data) group has worked on making economic data publicly available via Gross Cell Product (GCP). In other words, they've collected data for each 1x1 degree latitude by longitude cell on the globe. Above is a cell-by-cell globe mapping world population. Here's one that shows world rainfall.
This means you can use functionality from one API and apply it to another, or you can just put a whole bunch of synced maps on one page like above. Other features include geocoding, polylines, marker filters, and GeoRSS and KML, so go for it. Go map crazy.
Trulia, the real estate search site, launched Trulia Snapshot today in collaboration with Stamen Design. It's a pretty mapping interface that lets you view pictures of properties on a map in a very interactive way i.e. it's fun to use and super fluid.
First, you type a location you want to find properties at.
From there you can browse properties by newest/oldest or most/least expensive with the map or with the histogram at the bottom.
If you just want to sit back and watch, press play and the real estate properties will highlight automatically by the order you've selected, and the map will move back and forth by location. See something you like? Press pause. If not, just let the animations keep running - your own personal real estate agent.
My favorite part of the visualization is how the bottom images blur as you whiz by. It's a very small part and not the focal point, but it's one of those little design things that make it that much better. Nice touch.
Ultimately, success of such work is measured by (although it shouldn't need be) whether or not users would rather browse data with the visualization or with the usual listing pages. Give it a try - what would you rather use?
Bestiario, the group behind 6pli, recently put up their piece that maps informational distance between cities. At the base is a freely rotating globe. Arcs, whose strength and height represent strength of relationship, connect cities. The metric to determine strength of relationship takes several contexts into account - Google searches for individual cities, cities together, and geographical proximity. Bestiario implemented the piece in actionscript and used their own 3d framework (in Spanish).
Ben Fry maps every road segment in All Streets, according to the U.S. Census Bureau's TIGER/Line data. There's no actual map or drawn borders; instead Ben chooses to let the data do all the work, and the results are very pretty. Sometimes you don't need a map to map.
I was somewhat surprised to see California's low road density compared to the eastern half of the country, but I guess that's because of all the freeways. What's more surprising though is that line down the middle. Roads all of a sudden go dense somewhere around North Dakota. Is that really what it's like? Does farming suddenly stop and urban life begins in these areas?
Poor Alaska and Hawaii, with too few roads, were left out.
Paul gets into the mechanics of how you can use your own maps discussing the map stack - browser UI, tile cache, map server, and finally, the data. My favorite part though was his reasons for going with their own maps:
Ask yourself this question: why would you, as a website developer who controls all aspects of your site, from typography to layout, to color palette to photography, to UI functionality, allow a big, alien blob to be plopped down in the middle of your otherwise meticulously designed application? Think about it. You accept whatever colors, fonts, and map layers Google chooses for their map tiles. Sure, you try to rein it back in with custom markers and overlays, but at the root, the core componentâ€”the map itselfâ€”is out of your hands.
Because it's so easy to put in Google Maps instead of make your own (although it is getting a little easier), everything starts to look and feel the same and we get stuck in this Google Maps-confined interaction funk. Don't get me wrong. Google Maps does have its uses and it is a great application. I look up directions with it all the time, but we should also keep in mind that there's more to mapping than bubble markers all in the color of the Google flag.
Wilson provides a tutorial for horizontal bar charts and sparklines with nothing but HTML and CSS. Why would you want to do this when you could use some fancy graphing API? Using Everyblock as an example, data visualization can serve as part of a navigation system as opposed to a standalone graphic:
Sometimes the visualization isn't at the center of attention.
Make sure you check out Everyblock, a site that is all about the data in your very own neighborhood, to see these maps and graphs in action.
For each sin we stretched our imagination to find a workable proxy--murder rates for wrath, per capita billionaires for avarice--then culled the available data sources to rank the cities. Some of the results were surprising: Salt Lake City as America's Vainest City. Some were not: Detroit as America's Most Murderous.
It's always good to remember to take these with a grain of salt, since you don't really know much about the metrics used and how useful these metrics really are. Usually, rankings like these involve a lot of assumptions about the data.
They are of course still interesting and fun to look at though. Apparently, I moved from one America's most gluttonous cities to one of the most violent and lustful.
Chris Harrison put together a series of Internet maps that show how cities are interconnected by router configuration. Similar to Aaron Koblin's Flight Patterns, Chris chose to map only the data, which makes an image that looks a lot like strands of silk stretched from city to city. With these maps, viewers gain a sense of connectivity in the world - and as expected the U.S. and Europe are a lot brighter than the rest. Continue Reading
I just created a new Twitter account, and it got me to thinking about all the data visualization I've seen for Twitter tweets. I felt like I'd seen a lot, and it turns out there are quite a few. Here they are grouped into four categories - network diagrams, maps, analytics, and abstract.
Twitter is a social network with friends (and strangers) linking up with each other and sharing tweets aplenty. These network diagrams attempt to show the relationships that exist among users.
Twitter Social Network Analysis
The ebiquity group did some cluster analysis and managed to group tweets by topic.
Twitter in Red
I'm not completely sure how to read this one. I looks like it starts from a single user and then shoots out into the network.
I thought this map was amusing. As you can see, Mr. Bridges prefers those in the southeast and northeast according to his 2001 hit single, Area Codes in which he raps about all the female friends he has made.
This is yet another example of the ubiquity of data. If you can find hoe data in Ludacris' Area Codes, you can find data anywhere. Here's the large version of the above map. By the way, I'm sorry if I've offended anyone with this hoe data. Hoe data.
New York Talk Exchange - Illustrates the global exchange of information in real time by visualizing volumes of long distance telephone and IP (Internet Protocol) data flowing between New York and cities around the world.
A Week In the Life - A data sculpture made out of cardboard representing movement and communication from a cell phone in one week to increase awareness of the German Telecommunications Data Retention Act.
National Gruntledness Index - A heat map showing where in the United States most people are, um, gruntled. Is this for real? Somehow I don't think the entire country is pissed off.
BreathingEarth is an animated map that represents death rate data from September 2005 and birth rate data from August 2006 compiled by the World Factbook and 2002 carbon dioxide emission rates from the United Nations. The frying sound is kind of a nice touch.
Pretty But Not Very Useful
I think that BreathingEarth, like manymapsbeforeit, communicates an important point (in this case, CO2 emissions), but doesn't particularly do a good job of showing it. I watched BreathingEarth for a few minutes, but I didn't get much of a sense of what country had more deaths, had more births, or created more CO2 emissions. It's one those projects when a statistician could have lent a useful hand.
So to answer the question - What Impact Does Our Country Have on Climate Change? - I'm not sure. It is a pretty map though.
Manhattan Timeformations looks like a series of interactive schematics from a video game, but really it's a computer model that allows you to look at the relationships between the developments of the lower Manhattan skyline and other urban factors like farms, urban renewal, subways, and commercial zones. The visualization provides different views in the form of the traditional 2-dimensional map views as well as rotations, fly-throughs, and layers.
It's nice to step out of that Google mashup look every once in a while.
There's a nice real-time (?) map on (suit)men Entertainment. Click the black rectangle on the bottom left-hand corner to see the entire map. Supposedly the map is powered by Google, so I want to say it's showing search data or something of that sort. To be honest though, I have no clue.
Whenever a number pops up, there's a line that connects some country to Japan (the site's origin), so I'm guessing they're mapping something like accesses to the (suit)men site from whatever country. Oh well, no matter. Look how pretty. It's entertainment, and it managed to entertain me for a good few minutes (which says alot with my short attention span :). Does anyone know what they're showing?
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 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.