TypeDrawing is a fun applicaiton avalaible on the web, iPhone, and iPad. I like the idea of word forming images like in the expression: “an image worth 1000 words”. It is very user based. It is more a tool and the user have to interact with it to see the artwork. The application me of those drawing applications such as Paint MS or any web-based one such as a oekaki board. But instead of choosing a brush size/shape, you are choosing the letters you want to use. The aesthetic of the application is simple, yet effective, and the aesthetic of the artwork depends of the user’s talent. After that, you can save what you did, which is a good thing since it involves the user till the end by rewarding him with the possibility to keep his piece.
Typorganism is a cute animation using typography. Typography’s components are represented here as a bacterial culture seen trough a microscope. The user interactivity is limited to mouse over the particules to see the description. So no, this piece does not require a lot of participation from the user and there is possibility to change the component that you see on the screen. You can click on the description each component is linked to others applications related to that. I do not consider them as the same piece though. However, the aesthetic of it is more researched that the one of TypeDrawing and there is also more movement into that piece.
files are the same as 2.3
For the prototype and the final, I used a software called Hype, developed by Tumult. The idea was to document my reading process using articles from Wikipedia, recording the links that I clicked on. With that information, I wanted to create some kind of note sheets where the links that I clicked on while reading the articles would be written. I add the possibility to save the still image of a particular note sheet since it could be useful. A lot of times when you searched on Wikipedia, you click on links and you end up with too many tabs opened without remembering the initial article that you were reading. The next step would be developed on the same idea, but instead of using already retrieved data, using live data (retrieved from Wikipedia’s api).