If you are a city official looking to improve public safety through better use of data and analysis, there are many resources available to help you get started.

In 2009, the U.S. Department of Justice introduced the Smart Policing Initiative (“SPI”), a program to fund and train over 30 law enforcement agencies in evidence-based, data-driven policing. Through partnerships between local jurisdictions and researchers, SPI has collected an impressive set of case studies and resources, all available on its website. SPI also hosts an ongoing webinar series—this month: Randomized Controlled Trials in Criminal Justice.

The White House launched the Police Data Initiative in April 2015, assembling a network of law enforcement agencies, researchers, and tech leaders to explore how data can be used to better the relationship between police and communities by increasing transparency, strengthening trust, and improving accountability. A year later, the White House described the progress made by the 50+ member jurisdictions, which could serve as an inspiration for cities looking to begin using data within their own police departments. Esri, The Police Foundation, and Code for America partnered with law enforcement agencies to build the Public Safety Open Data Portal, a great example and visualization of how open data can be used for public safety purposes.

Similarly, the Center for Policing Equality collaborates with law enforcement, researchers, and other key stakeholders to improve community relationships and build accountability in policing with data. The site has resources for both researchers and law enforcement looking to tackle public safety problems with data.

IBM Center for the Business of Government released a comprehensive report on predictive policing theory and practice. In addition to descriptions of various analytical strategies and case studies, the report offers the following advice to police departments:

1. Implement predictive policing strategies (“Do it!”)

2. Treat predictive policing as an addition to, not a substitute for, tradi­tional policing methods.

3. Avoid top-down implementation.

4. Keep the software accessible to officers on the beat.

5. Consider the geographic and demographic nature of the jurisdiction.

6. Collect accurate and timely data.

7. Designate leaders committed to the use of analytics.

The RAND Corporation published “Predictive Policing: The Role of Crime Forecasting in Law Enforcement Operations,” a free eBook sponsored by the National Institute of Justice. The authors give useful implementation advice in Chapter 5, including a Buyer’s Guide for those of you looking to upgrade your system (page 125). RAND characterizes successful predictive policy implementation as having the following attributes (page 137):

1. There is substantial top-level support for the effort.

2. Resources are dedicated to the task.

3. The personnel involved are interested and enthusiastic.

4. Efforts are made to ensure good working relationships between analysts and officers.

5. The predictive policing systems and other department resources provide the shared situational awareness needed to make decisions about where and how to take action.

6. Synchronized support is provided when needed.

7. Responsible officers have the freedom to carry out interventions, combined with accountability for solving crime problems.

8. The interventions are based on building good relationships with the community and good information (intelligence).

The Data & Society Research Institute released a 2015 report on predictive policing and civil rights, examining the current state of predictive policing and exploring unanswered questions. The report includes differences between predictive policing in theory and practice, an explanation of how rhetoric can affect and bias our view of predictive policing, and a rundown of key organizations and companies working on predictive policing. Four open questions, which the report argues are pressing and need to be addressed, are posed:

1. How and where does biased data shape these systems?

2. How do different policing tools perform, relative to each other and relative to earlier methods?

3. How can Fourth Amendment protections be preserved in the context of these new tools?

4. How will predictive policing affect the overall dynamic between police and the communities they serve?

Smart Cities Council has a number of white papers, case studies, and articles on how smart technologies can help cities better respond to public safety concerns. The topics range from streamlining fire department operations to implementing audible crosswalk signals to keep pedestrians safe; the featured cities vary in size and location as well, providing realistic analysis of how smart technologies can be still be applied in different types of cities.

Enigma, a data analytics startup that helped the city of New Orleans bring analytics into their fire prevention programs, developed Smoke Signals, a tool that offers block-level risk assessment for 178 American cities and is available as an interactive map and downloadable CSV files. Cities can also upload their own historical fire incident data to improve the model for their area.

The Vision Zero Initiative works with cities to help reduce traffic fatalities and accidents. First launched in Sweden in 1997, the project has spread to cities in the United States including Boston, Chicago, and Austin. Vision Zero has a toolbox explaining the initiative’s goal, demonstrating successful implementations in cities, and providing information for how new cities can get involved.

Data.Gov, the US federal government’s primary open data site, has a collection of data, apps, resources, and other materials related to public safety and disasters, all of which could be useful for cities examining how to best leverage their own data.

And of course, for ongoing updates, subscribe to Data-Smart City Solutions: Public Safety.