Following up on last month's map of the world's friendships on Facebook, we've released another visualization of relationships across social networks today. Called "Photo-sharing Explosions," these visualizations look at the different ways that photos shared on George Takei's Facebook page go viral once he's posted them.
Each visualization is made up of a series of branches, starting from George. As each branch grows, re-shares split off onto their own arcs. Sometimes, these re-shares spawn a new generation of re-shares, and sometimes they explode in short-lived bursts of activity. The two different colors show gender, and each successive generation becomes lighter as time goes by. And the curves are just for snazz.
The visualizations are live at facebookstories.com.
A lot of what we do at Stamen is inventing things that haven't been done before; pushing the technical envelope on something like scary cartography, or inventing new techniques to animate the effects of climate change due to global warming. It's fun, and it's definitely a big part of what keeps my creative juices flowing: Hey, look at that shiny new thing! Are they really paying us to do this? Awesome! But it can also be stressful, particularly when you're planning your time and running the day-to-day operations of a studio, because fundamentally: if it's new, it's hard to figure out how long it's going to take. We have various mechanisms for accounting for this (including taking a loss on a project because we just can't help ourselves), but every once in a good while while we get lucky enough to take a second pass at something that smart people have laid a foundation for. This kind of work comes with its own satisfactions: polishing something to a high sheen, making it great instead of just good, really taking the time to pay attention to every detail and make sure that it comes out just right.
We're proud to announce today, along with our friends at Yandex, a redesign of the online maps for Russia's most popular search engine.
We have done the important stage of the project. We talked to designers, engineers and other smart guys during all time of the project. We achieved a lot of experience of mapping design.
For example, at the the begining of the project we collaborated with Stamen. These cool guys helped us pick main issue definitions, refine ideas, get important recommendations what to improve. We implemented it into final design.
What follows are some before and after comparisons of the various design changes we recommended to Yandex.
Many maps account for many different kinds of roads: freeways, business routes, on ramps, off ramps, service roads, residential streets - and show those roads as different kinds of strips on the map. We reduced the number of roads to three, greatly simplifying the display:
District names are always tricky to label; you've got to decide how take into account things like major railway stations, and how they'e going to interact with one another. These choices have been improved:
Zooming in a bit, we brought down the emphasis on the subway labels themselves, and made sure to label them for easy legibility:
Zooming in further, we paid attention to the routes that the subway lines take under Moscow. Not having been there before, we needed to rely on our friends at Yandex for confirmation as to whether this looked right given insider knowledge of Moscow, but it turned out nicely:
One more zoom level in and there's enough detail for the subway icons to be colored according to which line they're on:
We did recommend a few new features, in this case one-way arrows indicating the directions that cars are allowed to travel in on different streets:
And finally we improved the rendering of freeway interchanges, which if you've ever tried it yourself, is no joke:
You can see the results for yourself at http://maps.yandex.ru/. And it's generally a good sign when your client, in town from Russia, comes to visit. Thanks Andrey, Alexander, Julia and team Yandex!
The Map to Image bit of maps.stamen.com has seen steady use since we launched it in September: close to six thousand images made, about half of those watercolor, a third toner, about one every ten minutes. We've made some adjustments and improvements to it that should make it even easier to use, and easier to see what other people have made.
For starters, the results page has been reworked so it's a bit more navigable: where there used to be one long infinitely scrolling page with all the maps on it, each day now gets it's own page that fills up over a 24 hour period, so if you made an image on September 18, you're covered. There's also a graph at the top so you can see usage over time.
Each generated image also gets its own page now, and we've included Pinterest buttons so the images are easier to share.
Since launching maps.stamen.com and making the maps available for purchase in select cities on 20x200 we've been lucky enough to receive a steady trickle of interest from people who want to print the maps themselves. For those unlucky enough to have missed the watercolor letterpress map that went out with Jason Kottke's marvelous Quarterly.co subscription service, we're pleased to announce the beta version of M2I, a service that lets you print out larger static versions of the maps on maps.stamen.com. Now you can generate those long images on pinterest, chop chop!
The maximum size you can currently generate is 2000x2000 pixels. This is to keep the servers happy; depending on how they run we'll likely increase these limits in the coming weeks.
Please let us know what you think; we're looking into ways that people can order physical products from the site, because watercolor blankets and toner scarves are where it's at this season (and should be available from Soft Cities this fall).
In 2008 we designed a hurricane tracker for MSNBC, right as Irene was "bearing down on Louisiana like a shotgun full of wind and rain." The project worked fine for several seasons of hurricanes and tropical storms, until Apple killed Flash in 2011 and the world of interactive mapping and data visualization turned its attention to HTML5 and mobile platforms.
Here's what I said about it at the time:
I'm really pleased with how this project's turned out; in particular I've not seen a map like this before that gives a sense of the relative speed that a storm moves at (take a look at how Gustav slows down as it passes over the southwest coast of Haiti). It's not something I've really ever thought about before, but now that I've seen it, I'll be looking for it in every other map like this I see—which is just how I like to change the world. Congratulations to Tom and Geraldine for pulling this one together.
This is the first time that we've released something this concrete. At dinner last night Lane told me that it was the first time he'd seen something that Stamen had done that was going to really matter to him in 72 hours. We've historically shied away from doing work that's overly predictive and analytical, preferring to focus on the lyrical and metaphorical aspects of visualization. This is the first time you can make a decision based on something we've built, and I'm glad we seem to have crossed that barrier without fretting too much about it. Just about every big decision I've ever made that's turned out well has been made in lightness and in haste; no sense stopping now!
Much of this carries through in the new version of the hurricane tracker that we released earlier this week. What I said about making important decisions in lightness and in haste still stands (if anything it's gotten worse), but there are a couple different things about this project worth drawing attention to:
- The client is the Weather Channel (previous work for them here), and we're working directly with meteorologists to ensure that the representations meet their standards.
- It's in HTML5, so you can view it on an iPad. Which is good!
- We've made some improvements to the interaction that I never got to take care of in the previous version. The entire histogram (chart at the top) is an active thing you can roll over, for example; the previous version only popped the rollover when you were over the lines.
- The histogram and the map have a much tighter relationship now. If the whole hurricane path is visible on the map, you'll see the whole thing on the histogram, and visey versey. Conversely, if you change the map so that 1/2 the hurricane is visible, you see 1/2 of it on the histogram. You can see this happening in the images below.
Every year around this time in San Francisco things start to feel a little rushed, and there's anticipation in the air as a whole slice of society hauls itself out to the middle of the Nevada desert for the annual Burning Man festival. I'm not going myself this year, but my good friend Zach Coffin has been working out of an office here at Stamen on his latest song in steel and stone, The Universe Revolves Around YOU and it's been great fun seeing it come together:
Given all the Burning Man energy in town, it's probably no coincidence that our latest exercise in pushing the boundaries of online mapping would tend towards the, well, combustible side of things. We've pulled together the latest in web browser capabilities and layered them on top of toner-lines from Citytracking, and it's called Burningmap.
Here's Black Rock City:
It works in New York as well:
And pretty much anywhere else in the world you'd like to point it. Enjoy!
This is a followup to yesterday's post on the visualization of a day's worth of trading data on the NASDAQ stock exchange. We've taken another look at the same dataset a bit more closely. In the examples that follow, each of which represents a single minute of trading, the image on the left uses a unique color to represent each trader, and the image on the right uses a unique color to represent each stock. So on the left hand (trader) side, a big grouping of the same color means that a single trader is buying or selling stocks. And on the right hand (stock) side, a big color block means a single stock being purchased in lots of different transactions.
In this first example, we see that a single trader (UBS, in this case) is responsible for the majority of the shares in this minute:
and that they're regularly trading a single stock at a single price at the same amounts (the yellow dots in a row):
Here we see that UBS buys a fixed amount of a stock at a fixed price, very steadily, stops abruptly, and then starts trading a different stock at a slightly lower price (the dark green and then blue dots on the right):
Here we see a single trader (the orangish square at left) perform a burst of concentrated activity within precisely deliniated margins, making small trades across a wide range of stocks (the kaleidosopic square on the right)
And here we see a similarly trader-centric burst (in blue, at left) spread across a multiplicity of small stock trades, just before the market closes for the day.
Earlier this year Zach Watson and I spent some time visualizing financial data. It's time to make that work public. The following images represent visualization of buy/sell data during a single day of NASDAQ trades.
We mapped a small subset of the variables for each transaction:
- time of the transaction, to the second
- whether it was buy or sell
- price of the transaction
- number of shares traded
Each of these variables is represented in the diagrams below. Each image represents a minute of time, and shows every trade that happens in that minute. Each trade is shown as a circle:
- Every vertical row is a second in time. So the left hand side of the screen is the beginning of the minute, the middle of the screen is 15 seconds in, and the right hand side of the screen is the end of the minute, with 60 seconds in between.
- Blue dots are buys, yellow dots are sells
- The vertical axis is the price of the transaction; the top of the screen is cheaper stocks and the bottom is more expensive stocks.
- The size of the dot is the number of shares traded; small dots are for a few shares and larger dots are for a larger number of shares.
NASDAQ opens for pre-trading hours at 7am, and for public trading at 9:30am.
The market opens. Fairly light activity in the first minute. Most of it is contained within the middle band.
Slightly more trades are happening, and they're for smaller amounts.
Someone seems to be buying shares at a low and high price, simultaneously - hence the lines at the top and bottom of the screen that match each other perfectly. We're not representing who's making these simultaneous buy/sell moves, but it would be easy to find that out or build it in.
This is about the pace we see for the next 2 hours, with the exception of a few bursts like this one right at 8:30am.
There's an incredible burst of activity just before public trading starts. It's completely unlike anything that comes before it. Our theory is that these are algorithms getting in one last set of tiny flurrying trades before the great unwashed masses come on board.
Right at launch, there's a giant burst of selling and trading, within seconds of the bell ringing.
And then the day starts:
Here's a video of what the data looks like when it's animated:
Untitled from Stamen on Vimeo.
There are literally thousands more where these came from. It's surprising us how much loveliness is in this financial data, which is generally perceived dry and boring, only interesting to bean counters.
What I like most about what's come out of this exercise is this idea that you can visually start to detect a difference between normal and anomalous data, even for what's normally considered data that lay people can't understand. If we could find a way to make it easier to understand what's happening in the markets, there's potential here for a kind of literacy in financial data that could help to offset some of the damage done by unscrupulous experts over the past few years.
The first thing I thought after we hung a copy of London's Kerning, a printed map showing only the street names in London, in the studio, was: I want one of those for the rest of the world. "How hard can it be to just (people here love that) show the streets?"
As part of the CityTracking project, we've released six new map flavors that get pretty close: Terrain and Toner both now include layers with streets only, labels only, and background only.
Toner: just streets
Those finding Toner
a little too, well, stark
for their purposes (it can be a bit heavy on the printer cartridges, we've heard) will hopefully find Toner Lite
a bit easier to work with.
Terrain: just streets
Terrain: just labels
Terrain: just background
We'll follow up with some more detail about how to incorporate these into existing projects soon—many of the styles have transparent backgrounds, for example, so they can be used as layers on other maps—but for now: enjoy!
We've got some new additions to Toner, the black and white style that Geraldine started and that Nathaniel and Mike have been gradually improving this year. There are some fairly significant changes to the cartography stack all the way through, which you can read about in detail at the project's visual changelog on GitHub. And of course everything's open source and available for download as per the terms of the Citytracking grant.
We promised to do this work in public, so here goes. One significant thing we've decided to do is to keep older versions of the project around, so that we (and, hopefully, you) can compare the different versions of the maps. So when Nathaniel talks in his post about "shaving San Francisco's Mohawk" from how it looked in 2010:
to how it looks in 2012, with a better coastline:
you can see it in situ. It's pretty simple to change the urls:
The changes can be fairly visually dramatic, as in the addition of non-Roman scripts to places like Tokyo:
The thing about designing maps is that you're never designing just one view. For one thing, it's important to account for all the different zoom levels: it's about showing more as you zoom in, but it's also about showing different things at different scales. Choices need to be made at every level about the thicknesses of streets, which buildings to show, which city name to show, and so forth. Different places have different characteristics spatially; some are more dense than others, and you have to keep the whole system in mind. These two versions of the zoom into DC, from different years, gives a sense of the range of choices involved:
I'm not aware of any other mapping projects that let you look back in time as a design evolves this way.