July 23, 2013 – nextcity.org – Applying Big Data to Vacants, and Other Steps Taken By Chicago’s Land Bank

Imagine you’re an elected official in a city like Detroit, Philadelphia or Chicago — a place with so many vacant properties that one can only estimate, within two or three thousand, how many properties are not in productive use. Now, imagine someone hands you a sack of cash and instructs you to get as many properties as you can redeveloped, or at least make it so they aren’t serving as warrens of crime.

Do you focus on green space? Rehabbing empty homes? Demolitions? You only have so much money. Will you face political blowback if elected leaders see that you spend most of it in one part of town and not another? Redevelopment might not even be the ideal way to go. Sometimes neighborhoods with the strongest demand for space are best served when government steps in and saves a bit of land for everyone to use.

In the age of Big Data, these decisions are becoming less complicated. Last month, fellows with the University of Chicago’s Data Science for Social Good began working with the Chicago area’s newly born Cook County Land Bank Authority (CCLBA).

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Read more coverage of the developing land bank and ULI Chicago’s role in the process