Time taken for first arriving apparatus to arrive on the scene of an emergency. Does not include non-emergent calls.

This data set includes type of request, nature of request, date request was received, and the date of the event or response to request.

A summary of all the concrete sidewalk repair and reconstruction projects that occurred during 2017. This includes work done in association with the City's Sidewalk Assistance Program, as well as general maintenance, repair and reconstruction to sidewalk segments, driveway entrances, curbs and ramps

This summary includes all projects that were completed both by City of Bloomington Street Department crews and those that were performed by personnel from Groomer Construction, which was contracted by the City of Bloomington to assist with sidewalk and ramp repair work in 2017.

This data set includes type of request, nature of request, date request was received, and the date of the event or response to request.

This data set includes incident number, nature of call, area, date, time, month, day of week, disposition, and how the call was received. Each case was identified as Domestic Battery using the State Statue definition of 'domestic'.

This data set includes type of request, nature of request, date request was received, and the date of the event or response to request.

This data set includes type of request, nature of request, date request was received, and the date of the event or response to request.

Emergency responses by area served. Includes within City limits, IU, and mutual aid responses.

After coming across the open source data analysis tool created by Enigma, Bloomington FD (BFD) decided to pursue this data driven prevention project. After uploading 16 years of fire response data, the department was given a spreadsheet with our data analysis. The complexity of the project exceeded internal Fire Department capabilities and quickly moved to the collaborative project list established by our interdisciplinary team. This team based out of Indiana University includes data science researchers from the School of Informatics and Computing, leading technologists from the University’s Information Technology Services (UITS), and BFD members. The mapped data was created by Logan Paul, a graduate researcher in Prof. David Wild’s Integrative Data Science Laboratory and is much easier to use than the raw data. BFD plans to use the data to help focus smoke detector installations to areas that will have the biggest impact. If Bloomington's results are similar to other Cities across the nation, this data driven approach will increase our accuracy of smoke detector installations from 5-8 percent to nearly 65 percent. This represents a more efficient delivery of service that will also save lives.

How it works:

Open Source algorithm: