If written about creating a generic context engine for civic data, and also delved into the fact that private data is critical to understanding the world around us. in prep for the Knight-Mozilla-MIT “Story & Algorithm” Hack Day on Saturday, I wanted to lay out some specific manifestations of a general method developers could use to tell stories with existing words (aka data).
Take this building in New York City at 2192 Broadway.
They have a huge wallpaper of building permits:
But many of them are inconsequential (like the fencing around the construction site):
The really important ones talk about use:
In doing the research, take a look at how many stoppers I ran into:
The number one Web search result is a dead link:
And the post that the first post references is behind a firewall:
What I did glean from the story.
The narrative comes from pure entity extraction.
This story refs the possibility that CVS is going to put a store in this building:
That led me to check out the CVS Real Estate, which is understandably cagey about listing their future business plans and store openings on their Web site. One thing they do publish, though, is the opposite: a nifty spreadsheet of the 365 pieces of property they own but don’t want— “surplus properties“.