Over the years of working on Qri's product, the team's vision and purpose of Qri was beginning to take a backseat to feature development.
Qri experienced a general issue of having a platform that was difficult to get sucked into. Months of feature accretion without a wholistic vision lead to fat tab bars, buttons with difficult to understand names, and icons that didn't quite line up to expectations.
On top of this, Qri is a fairly complicated product built upon decentralization technologies.
Qri is the authority over sharing and validating large datasets.
This writing exercise intends to capture the optimal promoter's profile.
The goal of this exercise was to both inspire the developers and align on who our user was.
I search Qri first when trying to find any kind of open data, because Qri is the fastest, most reliable, and easiest tool to use for retrieving data and experimenting with in the tools I'm already using.
Unlike other repository browsers, when I open Qri, I am inspired to make new observations about the world. I think to myself "I wonder if crime and energy consumption have anything in common by areas" or "I wonder if there is a correlation between gun legislation and officer safety in the United States". Qri can take any question in and help me find robust and verifiable data that can help me indulge my curiosity.
I was first introduced to Qri during my math class in third grade at Kickapoo high school, where we learned about plotting animal data on a plot. Our assignment was to open a dataset showing how high a ball reached on each successive bounce, but it was honestly pretty boring. I may or may not have been goofing off when I came across a map of shark attack occurrences and compared them to the shoot locations of my favorite shark movies. I wonder why so many shark attacks happen in Australia, yet so few shark movies are based there?
I don't use Qri much anymore, but every so often a special dataset catches my eye in their monthly newsletter, and I indulge myself in making another /r/DataIsBeautiful post. To this day, I am a proud peer of the network, and I have helped seed more than 2TB of data. Look at my github
Work began with user research, rough sketches, and gist-of-it designs.
Through competitive research and user interviews, we identified several additional problems in the data stewardship space that could be natural fits for Qri to address.