This is a side project that I worked on for a little over a year. Our goal was to collect and visualize a data set more complex and popular than the ones we were getting from clients. We kept coming back to it when client work was slow, but have realized that we don’t have the time to really give it the love it deserves. We still believe in the idea, and I know there’s so much more that could be done that I never would have thought of, so I’m opening the source and the data.
The Interactive Visualization
This is a prototype that we put together that I just kept adding features to. At this point, all it really does is allow you to view a scatter plot of projects and change what is on each axis. Just click the label to change. You can also click Zoom and Categories in the corner to change the axis ranges, or filter a certain project category.
The code is dirty and thrown together, but was fun to play with. If you’ve got Unity 3D installed, you should be able get it going right away. If you don’t, check out the builds. More details on the Github readme.
Framework: Unity 3D
Windows: Google Drive Link
Mac: Google Drive Link
Unity Package: Google Drive Link
Note: I haven’t tested the windows build. Just built it from mac. Let me know if you have problems, and I’ll boot into windows.
If you want to get started quickly or aren’t familiar with mySQL, I’ve provided an excel file and a csv. The excel file has some charts and pivot tables so you can see some of the arm chair analysis that’s been done. The SQL dump has a lot more data, like description text, and full rewards and backers data.
I tried to upload the csv as a google fusion table but was having trouble with quotes I think. It only took the first 6 records. If anyone else can get it to work, let me know.
Since Kickstarter does not open up their data, I had to write a scraper to collect what I could from the website itself. I couldn’t find a suitable scraper out of the box, so I wrote one myself. I wanted to learn Python better anyway. Again, a lot more details on the Github readme.
As a bonus, here’s a video of me presenting the data using a rockband controller