Neal | December 16, 2016
Hey Housing Insights team!
Thanks for everyone that came last night! All the sketches from last night have been scanned and I’ve put them in the ‘/mockups’ folder in our Github repo. You can view them on the Github website (the dec15-hacknight.pdf file is the file with all of last nights ideas.
As I said last night, our next step is to sift through these ideas, and turn them into a clear plan of what to build for our first prototype. Based on the Doodle poll, we will do this at a design session on Tuesday, Dec. 20, 6:30-9:00 at the NY Code and Design Academy (*tentatively confirmed). For ongoing work in the month of January, I’m proposing splitting the group into 4 teams (see descriptions below).
How you can participate:
1) [Most important] Tell me whether or not you plan to come on Tuesday. At the same time, tell me which team(s) you are interested in joining. Take 1 minute to fill in your preferences on this sheet.
**More stuff: **
2) Draw more one-page design ideas before our Tuesday meeting, like the ones we did last night. Scan them or take a picture and add them to this Github issue.
3) Explore our data.
Port: 5432
Don’t know how to use this? We can help you get set up next time. Also, please don’t drop our tables :)
Thanks! I hope to see many of you on Tuesday; if you can’t make it or just want to wait to see the plan, I’ll be in touch re: teams before the new year.
Prototype Team:
We’ll use Google Slides and Tableau to make a fake (but real-looking) version of our proposed design, or potentially 2-3 different versions. We’ll show this to some affordable housing users and watch their interactions with it.
General Data Team:
Responsible for wrangling and locating our data sources, making sure we can link them, and writing Python / SQL code to analyze them. Also can do some data exploration to find interesting stories.
Location Data Team:
Writing code to do spatial-analysis related data. For example, this team would start working on putting affordable buildings on a map and calculating the distance to public transit, or find the other buildings within X miles. Most likely will do this client-side via Mapbox GL JS and the Directions API (open to alternatives), but could also use Python SDK if it makes sense.
Javascript/D3 Team:
Setting up the core structure of our main page code. For now this will focus on the nuts-and-bolts part of the project that we will use no matter what the design, learning about using D3, and how we connect to our data.