Oaklandexter stores the streets of Oakland / Alameda County and the connections between them.
You use the website to add data, and the API to get maps and network analysis out.
The examples below can be reworked to show how neighborhoods are served by local libraries, farmers' markets, or hackerspaces.
This is all very experimental, so I might not accept data forever. If you're interested in the project for your own city or projects, grab the source code on Github.
I added a 'bart' tag to all of the streets with BART stations. Then I went to /access/bart to get rules for each street in Carto for TileMill.
Another Code for America fellow (Jessica Lord) told me that choice was a major factor in urban planning, so I also added a /choice/TAGNAME endpoint. This is a /choice map representing your two nearest libraries.
I loaded 15 years of housing data from the City of Macon into another instance of this project. If you look at individual streets, it's hard to tell the worst streets (those with demolitions) from the rest of the pack. The distribution of these streets is just a dropoff:
When statistics branch out to include connecting streets, you get more than just higher numbers. You get a better idea of a neighborhood. Most housing violations occur in neighborhoods with few demolitions, but houses that get demolished happen in neighborhoods peaking around 10-12 demolished neighbors
These aren't the greatest diagrams, so I'd be happy to share the data with people with better maths.
Go to /tags to see what tags exist, and create a new one.
The map will be empty at first. Follow directions to add streets.
The Github Readme has API documentation.
Tweet to @mapmeld once you've got a map started, or if you run into trouble.