A S A B R I D G E T O B U I L D A D ATA E C O S Y S T E M T O D E L I V E R S E R V I C E T O R E S I D E N T S O P E N D ATA A S A B R I D G E T O B U I L D A D ATA E C O S Y S T E M T O D E L I V E R S E R V I C E T O R E S I D E N T S @CHICAGOCDO @CHICAGOCDO
At the national level, Chicago’s open data initiative has been held up as a model for cities that are seeking to start their own open data programs.” - National League of Cities, p. 22
can be downloaded to quickly deploy automated updates. It can be freely used by other governments and improvements can be submitted. ETL Utility Kit github.com/Chicago/open-data-etl-utility-kit
led by Chicago residents interested in technology and society. Smart Chicago Collaborative and non-profits provide assistance and city officials regularly engage in meetups and other activities. This group has produced several helpful apps. Community
a website using #opendata to help residents apply to the City of Chicago $1 lot program designed to encourage investment in struggling neighborhoods. largelots.org
across Chicago during the fall and winter months. This provides an easy-to-use central website built upon open data by a volunteer. chicagoflushots.org
is also based on the data portal. It provides summary statistics of potholes filled, graffiti removal, and other work completed by city council ward. chicagoworksforyou
partnered with multiple institutions to build a mesh network of small sensors, dubbed the Array of Things, that will frequently post data for public consumption. arrayofthings.github.io
local, temporal data on using a variety of sensors: §Sensors measuring sound and vibration §Low-resolution infrared cameras measuring sidewalk temperature §Climate and environmental data, such as air-quality and temperature
use data. Likewise, people wanted to sometimes correct our data. Data posted on GitHub can be edited by others and comes with a business-friendly MIT license. Open-source data github.com/Chicago/osd-street-center-line
projects which can be adopted by other cities or modified by outside developers. This allows a greater community to improve city projects. Open Source Projects github.com/Chicago/RSocrata
which we organize all of our work: Access to the Internet & technology, Skills to use technology once you've got access, and Data, which we construe as something meaningful to look at once you have access and skills.
tailored to encourage regular residents to provide feedback on applications, ensuring they reach beyond a technical audiences. Civic User Testing cutgroup.com
civic developers. However, these events rarely lead to “Learnathons” Weekend events dedicated to providing free workshops on introductory data analysis and advanced analysis. Using the data portal and open-source software tools.
situational awareness system that brings over a dozen data sources together into a single application. This year, it will be released as an open source project. WindyGrid
where rodent complaints are most likely in the next week. We used spatial- temporal relationships to create these predictions, which started as an investigation of over 350 different factors. Spatial Correlation Temporal Correlation
Alliance and Allstate Insurance Company’s data science team to help develop the predictive model. Data from the open data portal was used to develop the model. While other data were considered, almost all of the useful data was publicly available.
risk level Location of restaurant Nearby garbage and sanitation complaints Type of facility Nearby burglaries Whether the establishment has a tobacco or has an incidental alcohol consumption license. Length of time since last inspection. Length of time the restaurant has been inspecting. The model predicts the likelihood of a food establishment having a critical violation, a violation most likely to lead to food borne illnesses. Over a dozen data sources were used to help define the model. Ultimately, ten different variables proved to be useful predictors of critical violations. Significant Predictors:
70% The research revealed an opportunity to find deliver results faster. Within the first half of work, 69% of critical violations would have been found by inspectors using a data-driven approach. During the same period, only 55% of violations were found using the status quo method. Critical violations
rate of finding violations was accelerated by an average of 7.4 days in the 60 day pilot. That means more violations would be found sooner by CDPH’s inspectors. 7 days IMPROVEMENT The food inspection model is able to deliver results faster.
instructing others on the variables and statistical methodology used in the project. In addition to source code, the paper will help researchers adopt this approach. Technical Documentation
document, allowing other researchers to understand how summary numbers were calculated. Each statement in the project can be traced to an original source. Reproducible Research
source project on GitHub, allowing other cities to study or even adopt the model in their respective cities. No other city has released their analytic models before this release. #OPENSOURCE
Officer City of Chicago @ChicagoCDO [email protected] data.cityofchicago.org github.com/Chicago techplan.cityofchicago.org report.cityofchicago.org opengovhacknight.org arrayofthings.github.io datadictionary.cityofchicago.org digital.cityofchicago.org