My job has me file design patents on all sorts of retarded things. A piece of me dies every time I get a patent cube. I can’t wait till the entire software IP system goes down the drain. The only fun part of it is the drawing. I’ve always liked the patent drawing style. Being both explanatory and expressive with black and white is challenging. And fun.
Anyways, I felt bored over the New Year’s break. I recreated some Minecraft textures as an experiment:
Since they don’t look too bad, I went on to rebuild some Minecraft machines in Rhino. The result is two fake patent filings by Steve. One for automatic chicken cooker (click to enlarge):
Another one for charcoal cooker:
Both configurations are fully tested in game. The lava block in the chicken cooker is destroying cooked meat (while leaving the feathers) in 1.8.9. Bummer, it used to work for me in earlier versions. For now, I’d substitute lava with water.
What’s next? I’ve no idea, Monday is on the horizon, I need a beer. Let me know what you think.
I’m not associated with Mojang nor Minecraft, nor am I the original inventor of the machines illustrated above. You may use the images freely as long as I’m credited. I’m in no way responsible for any damage caused by my illustrations, including but not limited to in-game death, loss of sleep and antisocial behavior. If you’re a nice human, friend @Pessimistress on all the game-y-internets.
Tools: Rhino, Illustrator, Minecraft
This is just a side project. So the 6 of us have been working some internal project on TFS (5 devs and I. Sorry for all the destructive check-ins guys. Don’t lose your faith in designers because of me). One night I extracted the version histories and had some fun with it.
The visual is inspired by Context Free. I first played with the tool in ’07 and was impressed by the powerful outcome of combining recursion and randomness. In this visualization each curve(represents a file or a folder) wanders freely in space and gradually fades out until it gets some attention. Each is colored by the last person who made changes. A curve branches when something derives from it (files added to folder; branching versions; etc.) The tree does get out of structure and less readable after some time. I’ll try some improved concept when I have the time.
Full view (click to enlarge):
With my contribution highlighted:
Click here to play with the visualization. It should work with all decent browsers that support canvas. You can highlight the map by contributor or file. Hover over a node to see detail information. I did mess up the file names so (hopefully) I’m not violating any company policy. Please don’t get me in trouble. :-p
Tools: R, HTML5
Well, not real colors of the sky – but you get the idea.
The dominant influence factor is the climate. Winter is the most polluted season because of thermal inversion and less rainfall. Spring in northern China suffers from sandstorm. Still, you can easily identify the effect of government intervention, such as the significant improvement in Taiyuan. And look how amazingly Beijing performed in 2008 August through September for the Olympics. Click the image below to zoom in.
Tools used: R
Dedicated to my endearing home city.
[Looking into the Forbidden City from Jingshan – BJNews, March 21, 2011]
Update: Images now available as Flickr photostream
On April 10th, 2011 MIT held the Next Century Convocation as a centerpiece of its 150 anniversary celebration. 10,000 people attended the event at the Boston Convention and Exhibition Center. Before the program began guests participated in a trivia game designed by our team.
The game was a crowdsourcing experience, with participants asking their own questions to the crowd. Participants sent text messages to a short number through Ken’s awesome mSurvey system. Messages ending with “?” were recognized as questions and appeared on the screen with a sequential number. Messages started with “Q+number” followed by a space are recognized as answers to that question. Questions and answers were displayed in real-time, on a 90-foot screen.
My goal in designing this vis was to enable direct feedback to the users, invoke conversation among them and encourage participation. Considering the dimensions of the space, it was critical to keep the interface simple and learnable. Our team came up with this idea of “questions competing for answers” – each question moved from the left edge of screen to the right, gradually accelerating if nobody responded to it, till it was out of sight. When an answer came in, it was attached to the target question and therefore slowed it down. Each question left a trail behind it, whose width was related to speed. So the more popular questions would stay longer on the screen. It was a competition for both good questions and interesting answers.
Screenshot from the game:
Picture at the event:
I was a bit unhappy that the video staff insisted on adding moving backgrounds to the visualization. Then during the real run, we encountered some technical problem , causing the answers mismatched for a while (in fact a bug in the setup-at-the-last-minute message censorship system – censorship sucks, I knew it better than anyone). Anyway both the team and the guests had a lot of fun with the game. Some of us were sleepless for a few days to make this work, especially our great leader Ken, who’s been suffering from a fever since then – I hope he gets better now. ♥
Tools used: Processing
Visualization: Xiaoji Chen, Yanni Loukissas
Backend: Kenfield Griffith, Reid Williams
And thanks to the rest of the team: Michael Berry, Kristyn Maiorca, Ella Peinovich who made this happen
Economist just posts an interactive visualization Chinese Equivalents on their website. It’s a very interesting approach. (Somehow I feel it has an psychological side-effect by saying one province is equivalent to France while it’s neighbor is equivalent to Kenya, though noted in terms of population.)
I got curious how we can visualize how actually important the Chinese provinces are. I was reading Gastner & Newman’s paper Diffusion-based method for producing density-equalizing maps (PNAS 2004) at the time. So I set out to make my first density-equalizing map.
Newman’s code on his website deals with raster image only. I also tried to implement a diffusion simulator in Processing, but it was hard to preserve all the details of a vector map. Below is my first shot. It took (quite) some manual effort to remove the bad points. Still seeking solutions. Anyway, enjoy.
You can recognize in this map how unbalanced China is – the west is barely occupied due to challenging natural environment, and population keeps flowing from the middle towards the economic centers (Beijing and the southeast coast). They become both productivity and pressure for big cities.
What about looking at the provinces from a social network’s perspective? In the following graph I measured how often each two provinces appear in the same media coverage. It is clear now that Beijing is the absolute, mono-center of all China. The social power is not proportional to a province’s population. The south and the east coast get far more attention than inland provinces, which is a sad fact.
Tools used: Processing, Tulip, Illustrator