Data Activism
prettypara.site
Suck back your data from the giants
Role
Idea, Code, Founding
Website
prettypara.site
01
Idea
Suck back your data from the giants
prettypara.site encourages people to reclaim their data from the tech giants and discover their value, originality, and individual beauty.
02
Problem
300.000.000.000.000.000 Byte
The last time Zuck checked, Meta (Facebook, Instagram, WhatsApp) had hoarded 300 petabytes of user data. 56 MB of that was mine alone. How do I know? I asked for it and got it back. Any EU citizen can do this. Thanks to GDPR, tech giants are required to provide citizens with their data treasure with just a few clicks. Why don't more people do it? Firstly, those "few clicks" are often well hidden. And secondly: What should I do with it? Data sounds like "complicated" and "math."
03
Solution
prettypara.site is here to help
prettypara.site helps with both dilemmas. Firstly, the service reveals where Meta, TikTok, and others hide your data download. Secondly, prettypara.site shows the beautiful, emotional, and unique side of your data and quickly translates it into individual data art masterpieces. Individual in this case means: No one has the same data. So no one has the same artwork. It’s yours alone – as unique as your fingerprint.
04
Tech Stack
Python, p5, Processing and back
prettypara.site grows and thrives as a pet project alongside my job. It allows me to use my creative and coding skills for data literacy as a passion project. The project pushes me into areas outside my comfort zone. In the background, Python holds everything together. For generating graphics, a P5.js script works in the frontend. It works in perfect tandem with a Processing instance, which generates bitmaps for sharing and download images in the backend with almost identical code.
Architecture und components
05
Lean Startup
Build – Measure – Learn
There is no existing model for the success or failure of prettypara.site. Therefore, it is important to validate the idea, purpose, and impact. The project’s architecture follows Eric Ries’ Lean Startup method. Ries advocates a Build-Measure-Learn cycle: The product must be built quickly to find users quickly and measure their behavior and feedback. “If you don’t know who your customers are, you don’t know what quality means for them.” In small, organic iteration steps, the goal is to draw the right conclusions and incorporate the learnings into the next version. To simplify this, prettypara.site is built on a self-developed cohort system. In simple A/B tests, users are funneled through two different versions of the site to measure usage, drop-off, or conversion into other project parts.
