NewsWare was launched yesterday on msnbc.com. It's a set of apps, games, and widgets to interact with the news. The three main points of interest are the Spectra (pictured above) and two games that resemble a couple of popular arcade games infused with news.
In a deviation from the usual pie chart and standard tree map, this graphic from The New York Times resembles something of a stained glass window - a really pretty piece of work. Amanda Cox, with Matthew Bloch and Shan Carter, designed the interactive graphic that lets you explore how American consumers spend their money.
Inspired by Jonathan Harris and Sep Kamvar's We Feel Fine, and using data from summize, twistori shows what people love, hate, think, believe, feel, and wish for on Twitter. Given the conversational feel of Twitter, twistori shows an almost natural flow of emotion and like Twittervision, is sort of mesmerizing.
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.
Dan Beech represents worldwide poverty in this video, which is actually a 3-dimensional bar chart with some flare:
Welcome to Povertyville, Slumtown, and Low Income city. I'm not sure what to think. Should I laugh? Should I cry? I don't know. What do you think?
In this genre of over-produced graphs, Povertyville reminds me of the real estate roller coaster, a dramatic 3-D time series plot:
Why Not Go With Google Maps?
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.
Remember: a little bit of design goes a long way.
Data Visualization with Web Standards
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.
Moritz has been working on visualization of a hierarchical glossary carefully named "Glossary Visualization" versions 2-5. Not sure where version 1 is. Being a network graph, I can see this getting chaotic when there are more words (or categories) involved, but then again, maybe that's all the words. In either case, it beats browsing through words in a dictionary; although, these prototypes don't include definitions yet.
In the most recent version, words are represented as a DOI tree showing only the categories. Click on a category and view the sub-categories.
All four versions were implemented using the recently-mentioned Flare visualization toolkit.
What do you think - cluttered or just right?
Facebook recently released Lexicon which is like a Google Trends or Technorati for wall posts. Type in a word or a group of words, and you can see the buzz for those terms in a time series plot. Daniel sent me this excellent example. Type in party tonight, hangover and you'll get the above graph. Notice the Saturday spikes for party tonight and the Sunday spikes for hangover? Here's another one for finals:
It's interesting to see what people are talking about, and being Facebook walls, there's this realness to the charts (or maybe that's just me).
Go ahead. Give Lexicon a try. What interesting queries can you find?
P.S. You have to be logged in to use it.
Reduce Multidimensional Data
After showing many thread arc versions, Kerr says that when you are dealing with multidimensional data, pick two variables; otherwise, you're going to end up with a big mess. He says this literally, but don't forget that you can also reduce dimensionality with super special and magical statistical methods.
Use Real Data
You won't know what you're really dealing with until you have the real data. You can spend lots of time guessing what the data are going to be, but it's the real data that will eventually drive your design. This goes for statistics too. Real data leads to real analysis.
Try Adobe Illustrator
What rules of thumb do you follow?
Here's the talk in full. It's pretty interesting, if you've got about 25 minutes to spare.
We all know about information aesthetics, but what other visualization blogs are out there? While writing for FlowingData I've come across some good ones as people send me links (hint) or that I've just randomly found. Here are some of the visualization (and mapping) blogs that I enjoy.
- Strange Maps - Lots of unique maps from ads, books, papers, etc with very informed commentary.
- Well-formed Data - Moritz is interested in interface design, visualization, statistics and data mining and is a freelance visualizer.
- Random Etc. - Tom occasionally updates his blog with thoughts, resources, and, well, random etc.
- Serial Consign - Greg talks about design and research with some visualization mixed in.
- AnyGeo - Covers everything geospatial, although I do wish Glenn would switch to full feeds.
What are some of your favorites that others might not know about?
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.
Transactions Graph, by Burak Arikan, is a piece placing personal transactions in network graph. Each node represents a transaction while connections (or edges) shows a relationship between transactions based on time and spending category. The thicker the edge the greater the total of the two connected transactions. Viewers are also able to scroll through time to watch how transactions evolve.
Stefanie Posavec, maps literary works at the Sheffield Galleries On the Map exhibit. There are several parts to Stefanie's piece mapping sentence length, writing style, and structure. From the looks of things, it looks like the parsing process was manual and involved a lot of highlighting and circling of things. I could be wrong though. For some reason, long and manual labor makes me appreciate things more.
Check out this lovely use of Chernoff Faces by Steve Wang of Swarthmore College. This method of visualization was developed by none other than mathematician-statistician-physicist Herman Chernoff in 1973. These faces were designed on the premise that people could easily understand facial expressions. With that in mind, Chernoff used facial characteristics to represent multivariate data.
If you like, you can make your own Chernoff faces with this R library.
Energy consumption grows more and more concern, and with the popularity of Mr. Gore's An Inconvenient Truth, just about everyone is at the very least, semi-aware of energy consumption. These 21 visualizations and designs were created to increase that awareness, so that maybe, a few more people will turn off the light when they leave a room. I think Peter Crabb said it best (which I borrowed from Tiffany Holmes' ecoviz paper):
[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.
Here they are - 21 dashboards, ambient devices, games, and calculators. Continue Reading
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.
Nexus, by Ivan Kozik, lets you explore your Facebook social network and find out what your friends have in common. Nexus kind of caught me off guard, because it actually does a decent job of showing you commonalities. I was expecting something like Friend Wheel or Friends Density, which are Facebook bling more than anything else.
If I've learned anything about designing information graphics, it's that attention to detail and small changes make a mediocre graphic into a really useful and usually more attractive one. It's what sets New York Times graphics apart from those in other publications and especially those in academic papers. Something like a short annotation can add context or a line shifted slightly to the left can make data look less cluttered.
Google recently released a visualization API that allows you to share embeddable visualization on your website, create Google Gadgets that can be shared and reused, and create extensions for existing Google products. Andrew asks, "Will this shape the future of data visualization online?"
On one side, this is exciting for the visualization field, because when Google talks, everyone listens. On the opposing side, could this be another Google Maps type of thing? Google Maps was cool at first, but now, mashup after mashup has left me bored and disillusioned. Ultimately though, I like to think that this API is going to benefit all of us.
What the API Offers
There's a slew of charts, graphs, gidgets, and gadgets available that you'll see in the gallery.
I'm sure this Google Finance-looking graph will make a lot of people happy.
These are, um, interesting.
We've seen this before, but the difference here is that it's now in widget form, which means a hook into Google Docs and other apps.
How We Will Benefit
If Google visualization becomes popular, visualization, in general, grows in popularity. People who weren't exposed will now know more, and if all goes according to plan, data awareness has a chance to develop.
As an example, Google Maps made online mapping what it is now - commonplace. Remember when online mapping was only limited to the big boys? Now everyone can mashup to their heart's content. People know how to use it and similar mapping applications and because of that, more "idea people" ask for mapping. As a result there is more opportunity.
Similarly, with the data viz API, we'll see data mashups outside of the map. Data visualization will no longer just be for the big boys, but at the same time, we'll still be able to make our own designs with a wider audience ready to experiment and play.
Good or Bad?
What do you think? Is the Google visualization API going to limit our imagination where we get stuck in a Google-ish funk; or is data and visualization awareness ready to rise to a point where we all benefit?