Thursday, April 22nd is Earth Day. The weather is looking to be sunny and 65 degrees in New York City. Sounds like a perfect day to ride your bike (or walk, run or whatever you like to do outside). Since you’re already going to be out there, why not log the trip, help me with my thesis, and have your data made into some visualizations I’m preparing for the project?
It’s pretty simple…download Mobile Logger from the App Store (iPhone 3G/3GS), open it, then tap Logging switch to begin. Put the phone in your pocket, bag, mounted to handlebars, or wherever is convenient and go. You can double-tap the screen to disable the display, but shouldn’t lock the phone.
When you’ve reached your destination, tap the logging switch again to stop and you’re done! The log data is automatically uploaded to the Mobile Logger server and will be included in my research (this uploading can be disabled if you’d like to use the app without contributing to the project, too).
What I’m really interested in exploring is a sense of connection between us by sharing our experiences. I ride a bike daily through NYC, and encounter many other cyclists, walkers and drivers. We pass each other in a moment, or perhaps share a lane for a bit and then continue on our separate ways. How does my 5 mile, 25 minute ride from Greenpoint to the East Village compare to someone riding from Queens? What does a ride around Prospect Park share with one in Central Park? What’s the loudest part of the city for a cyclist? Where are the most frequently ridden routes?
I’ll be working with the contributed data to create visualizations which attempt to answer these questions. The “dashboard” of the system will be present at mobilelogger.robertcarlsen.net. More info about the app is available on it’s documentation page.
Times UP! is also organizing a ride at 7pm from Union Square if you still need another excuse to get on a bike, skates or a board. It would be neat to see a bunch of riders converge on a location, then ride together in a group. I really want to see what that visualization would look like…
Thanks, and enjoy the ride!
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