INTEGRATINGOPEN DATA WITH OPERATIONSTO FIGHT BLIGHT
OLIVER WISEOffice of Performance & AccountabilityCity of New Orleans
In September 2010, roughly 25% addresses in NOLA looked like this
Source: David Grunfeld, Times-Picayune | nola.com
Source: Faubourg St. John Neighborhood Association. fsjna.org
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UPDATE #1:WE HIT OUR GOAL!
September 2010 Estimate (United States Postal Service data)
April 2013 Estimate (University of New Orleans survey data)
0
10,000
20,000
30,000
40,000
50,000
30% Reduction In Blighted Addresses In New Orleans:
More Than 10,000 Blighted Addresses Reduced
UPDATE #2:OPEN CODE AND OPEN DATA
Database
Flatfile export
Cleaning, manipulation, analysis
Visualization
Powerpoint for your
boss
Open data platform
Traditional BI in Public Sector
Open Code and Open Data for BI
Database
Open data platform
Cleaning, manipulation, and analysis coded in R
Reproducible, Sustainable,
Generalizable Reporting
UPDATE #3:ANALYTICS
11
Overview of the Blight Enforcement Process
LOT CLEARING
COMPLIANCE
JUDGMENT
3. RESEARCH
1. INTAKEAND INPUT
2. INSPECT 4. NOTICE
5. HEAR
Typical Blighted Property Blighted Property with <3 Violations
Blighted Property with <3 Violations in Strong Market
Cluster
0%
10%
20%
30%
40%
50%
60%
70%
19%
47%
58%
Compliance Rates for Different Types of Blighted Properties
