The study was a comprehensive analysis of felonious killings of officers. The purposes of the study were (1) to analyze the nature and circumstances of incidents of felonious police killings and (2) to analyze trends in the numbers and rates of killings across different types of agencies and to explain these differences. For Part 1, Incident-Level Data, an incident-level database was created to capture all incidents involving the death of a police officer from 1983 through 1992. Data on officers and incidents were collected from the Law Enforcement Officers Killed and Assaulted (LEOKA) data collection as coded by the Uniform Crime Reporting (UCR) program. In addition to the UCR data, the Police Foundation also coded information from the LEOKA narratives that are not part of the computerized LEOKA database from the FBI. For Part 2, Agency-Level Data, the researchers created an agency-level database to research systematic differences among rates at which law enforcement officers had been feloniously killed from 1977 through 1992. The investigators focused on the 56 largest law enforcement agencies because of the availability of data for explanatory variables. Variables in Part 1 include year of killing, involvement of other officers, if the officer was killed with his/her own weapon, circumstances of the killing, location of fatal wounds, distance between officer and offender, if the victim was wearing body armor, if different officers were killed in the same incident, if the officer was in uniform, actions of the killer and of the officer at entry and final stage, if the killer was visible at first, if the officer thought the killer was a felon suspect, if the officer was shot at entry, and circumstances at anticipation, entry, and final stages. Demographic variables for Part 1 include victim's sex, age, race, type of assignment, rank, years of experience, agency, population group, and if the officer was working a security job. Part 2 contains variables describing the general municipal environment, such as whether the agency is located in the South, level of poverty according to a poverty index, population density, percent of population that was Hispanic or Black, and population aged 15-34 years old. Variables capturing the crime environment include the violent crime rate, property crime rate, and a gun-related crime index. Lastly, variables on the environment of the police agencies include violent and property crime arrests per 1,000 sworn officers, percentage of officers injured in assaults, and number of sworn officers.

Law Enforcement Locations Any location where sworn officers of a law enforcement agency are regularly based or stationed. Law Enforcement agencies "are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Although TGS's intention is to only include locations associated with agencies that meet the above definition, TGS has discovered a few locations that are associated with agencies that are not publicly funded. TGS deleted these locations as we became aware of them, but some may still exist in this dataset. Personal homes, administrative offices, and temporary locations are intended to be excluded from this dataset; however, some personal homes of constables are included due to the fact that many constables work out of their homes. TGS has made a concerted effort to include all local police; county sheriffs; state police and/or highway patrol; Bureau of Indian Affairs; Bureau of Land Management; Bureau of Reclamation; U.S. Park Police; Bureau of Alcohol, Tobacco, Firearms, and Explosives; U.S. Marshals Service; U.S. Fish and Wildlife Service; National Park Service; U.S. Immigration and Customs Enforcement; and U.S. Customs and Border Protection. This dataset is comprised completely of license free data. FBI entities are intended to be excluded from this dataset, but a few may be included. The Law Enforcement dataset and the Correctional Institutions dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. With the merge of the Law Enforcement and the Correctional Institutions datasets, the NAICS Codes & Descriptions were assigned based on the facility's main function which was determined by the entity's name, facility type, web research, and state supplied data. In instances where the entity's primary function is both law enforcement and corrections, the NAICS Codes and Descriptions are assigned based on the dataset in which the record is located (i.e., a facility that serves as both a Sheriff's Office and as a jail is designated as [NAICSDESCR]="SHERIFFS' OFFICES (EXCEPT COURT FUNCTIONS ONLY)" in the Law Enforcement layer and as [NAICSDESCR]="JAILS (EXCEPT PRIVATE OPERATION OF)" in the Correctional Institutions layer). Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard fields that TGS populated. Double spaces were replaced by single spaces in these same fields. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based on the values in this field, the oldest record dates from 06/27/2006 and the newest record dates from 10/22/2009

Sadly, the trend of fatal police shootings in the United States seems to only be increasing, with a total 1,173 civilians having been shot, 248 of whom were Black, as of December 2024. In 2023, there were 1,164 fatal police shootings. Additionally, the rate of fatal police shootings among Black Americans was much higher than that for any other ethnicity, standing at 6.1 fatal shootings per million of the population per year between 2015 and 2024. Police brutality in the U.S. In recent years, particularly since the fatal shooting of Michael Brown in Ferguson, Missouri in 2014, police brutality has become a hot button issue in the United States. The number of homicides committed by police in the United States is often compared to those in countries such as England, where the number is significantly lower. Black Lives Matter The Black Lives Matter Movement, formed in 2013, has been a vocal part of the movement against police brutality in the U.S. by organizing “die-ins”, marches, and demonstrations in response to the killings of black men and women by police. While Black Lives Matter has become a controversial movement within the U.S., it has brought more attention to the number and frequency of police shootings of civilians.

Law Enforcement Locations Any location where sworn officers of a law enforcement agency are regularly based or stationed. Law Enforcement agencies "are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Although TGS's intention is to only include locations associated with agencies that meet the above definition, TGS has discovered a few locations that are associated with agencies that are not publicly funded. TGS deleted these locations as we became aware of them, but some may still exist in this dataset. Personal homes, administrative offices, and temporary locations are intended to be excluded from this dataset; however, some personal homes are included due to the fact that the New Mexico Mounted Police work out of their homes. TGS has made a concerted effort to include all local police; county sheriffs; state police and/or highway patrol; Bureau of Indian Affairs; Bureau of Land Management; Bureau of Reclamation; U.S. Park Police; Bureau of Alcohol, Tobacco, Firearms, and Explosives; U.S. Marshals Service; U.S. Fish and Wildlife Service; National Park Service; U.S. Immigration and Customs Enforcement; and U.S. Customs and Border Protection. This dataset is comprised completely of license free data. FBI entities are intended to be excluded from this dataset, but a few may be included. The Law Enforcement dataset and the Correctional Institutions dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. With the merge of the Law Enforcement and the Correctional Institutions datasets, the NAICS Codes & Descriptions were assigned based on the facility's main function which was determined by the entity's name, facility type, web research, and state supplied data. In instances where the entity's primary function is both law enforcement and corrections, the NAICS Codes and Descriptions are assigned based on the dataset in which the record is located (i.e., a facility that serves as both a Sheriff's Office and as a jail is designated as [NAICSDESCR]="SHERIFFS' OFFICES (EXCEPT COURT FUNCTIONS ONLY)" in the Law Enforcement layer and as [NAICSDESCR]="JAILS (EXCEPT PRIVATE OPERATION OF)" in the Correctional Institutions layer). Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard fields that TGS populated. Double spaces were replaced by single spaces in these same fields. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based on the values in this field, the oldest record dates from 08/14/2006 and the newest record dates from 10/23/2009

The primary table for all public data on complaints, including dates, locations and the outcomes of closed complaints received since the year 2000.

The dataset is part of a database of all public police misconduct records the Civilian Complaint Review Board (CCRB) maintains on complaints against New York Police Department uniformed members of service received in CCRB's jurisdiction since the year 2000, when CCRB's database was first built. This data is published as four tables:

Civilian Complaint Review Board: Police Officers Civilian Complaint Review Board: Complaints Against Police Officers Civilian Complaint Review Board: Allegations Against Police Officers Civilian Complaint Review Board: Penalties

A single complaint can include multiple allegations, and those allegations may include multiple subject officers and multiple complainants.

Public records exclude complaints and allegations that were closed as Mediated, Mediation Attempted, Administrative Closure, Conciliated (for some complaints prior to the year 2000), or closed as Other Possible Misconduct Noted.

This database is inclusive of prior datasets held on Open Data (previously maintained as "Civilian Complaint Review Board (CCRB) - Complaints Received," "Civilian Complaint Review Board (CCRB) - Complaints Closed," and "Civilian Complaint Review Board (CCRB) - Allegations Closed") but includes information and records made public by the June 2020 repeal of New York Civil Rights law 50-a, which precipitated a full revision of what CCRB data could be considered public.

This is five years of police use of force data for all 468 New Jersey municipal police departments and the New Jersey State Police compiled by NJ Advance Media for The Force Report.

When police punch, pepper spray or use other force against someone in New Jersey, they are required to fill out a form detailing what happened. NJ Advance Media filed 506 public records requests and received 72,607 forms covering 2012 through 2016. For more data collection details, see our Methodology here. Data cleaning details can be found here.

We then cleaned, analyzed and compiled the data by department to get a better look at what departments were using the most force, what type of force they were using, and who they were using it on. The result, our searchable database, can be found at NJ.com/force. But we wanted to make department-level results — our aggregate data — available in another way to the broader public.

Below you'll find two files:

• UOF_BY_DEPARTMENTS.csv, with every department's summary data, including the State Police. (This is important to note because the State Police patrols multiple towns and may not be comparable to other departments.)
• UOF_STATEWIDE.csv, a statewide summary of the same data.

For more details on individual columns, see the data dictionary for UOF_BY_DEPARTMENTS. We have also created sample SQL queries to make it easy for users to quickly find their town or county.

It's important to note that these forms were self-reported by police officers, sometimes filled out by hand, so even our data cleaning can't totally prevent inaccuracies from cropping up. We've also included comparisons to population data (from the Census) and arrest data (from the FBI Uniform Crime Report), to try to help give context to what you're seeing.

What about the form-level data?

We have included individual incidents on each department page, but we are not publishing the form-level data freely to the public. Not only is that data extremely dirty and difficult to analyze — at least, it took us six months — but it contains private information about subjects of force, including minors and people with mental health issues. However, we are planning to make a version of that file available upon request in the future.

Data analysis FAQ

What are rows? What are incidents?
Every time any police officer uses force against a subject, they must fill out a form detailing what happened and what force they used. But sometimes multiple police officers used force against the same subject in the same incident. "Rows" are individual forms officers filled out, "incidents" are unique incidents based on the incident number and date.

What are the odds ratios, and how did you calculate them?
We wanted a simple way of showing readers the disparity between black and white subjects in a particular town. So we used an odds ratio, a statistical method often used in research to compare the odds of one thing happening to another. For population, the calculation was (Number of black subjects/Total black population of area)/(Number of white subjects/Total white population of area). For arrests, the calculation was (Number of black subjects/Total number of black arrests in area)/(Number of white subjects/Total number of white arrests in area). In addition, when we compared anything to arrests, we took out all incidents where the subject was an EDP (emotionally disturbed person).

What are the NYC/LA/Chicago warning systems?
Those three departments each look at use of force to flag officers if they show concerning patterns, as way to select those that could merit more training or other action by the department. We compared our data to those three systems to see how many officers would trigger the early warning systems for each. Here are the three systems: - In New York City, officers are flagged for review if they use higher levels of force — including a baton, Taser or firearm, but not pepper spray — or if anyone was injured or hospitalized. We calculated this number by identifying every officer who met one or more of the criteria. - In Los Angeles, officers are compared with one another based on 14 variables, including use of force. If an officer ranks significantly higher than peers for any of the variables — technically, 3 standards of deviation from the norm — supervisors are automatically notified. We calculated this number conservatively by using only use of force as a variable over the course of a calendar year. - In Chicago, officers are flagged for review if force results in an injury or hospitalization, or if the officer uses any level of force above punches or kicks. We calculated this number by identifying every officer who met one or more of the criteria.

What are the different levels of force?
Each officer was required to include in the form what type of force they used against a subject. We cleaned and standardized the data to major categories, although officers could write-in a different type of force if they wanted to. Here are the major categories: - Compliance hold: A compliance hold is a painful maneuver using pressure points to gain control over a suspect. It is the lowest level of force and the most commonly used. But it is often used in conjunction with other types of force. - Takedown: This technique is used to bring a suspect to the ground and eventually onto their stomach to cuff them. It can be a leg sweep or a tackle. - Hands/fist: Open hands or closed fist strikes/punches. - Leg strikes: Leg strikes are any kick or knee used on a subject. - Baton: Officers are trained to use a baton when punches or kicks are unsuccessful. - Pepper spray: Police pepper spray, a mist derived from the resin of cayenne pepper, is considered “mechanical force” under state guidelines. - Deadly force: The firing of an officer's service weapon, regardless of whether a subject was hit. “Warning shots” are prohibited, and officers are instructed not to shoot just to maim or subdue a suspect.

Information found in this report follow the Uniformed Crime Reporting guidelines established by the FBI for LEOKA.

Key code for Race:

A- Asian/Pacific Island, Non-Hispanic B- African American, Non-Hispanic C- Hawaiian/Other Pacific Island, Hispanic H- Hawaiian/Other Pacific Island, Non-Hispanic I- Indian/Alaskan Native, Non-Hispanic K- African American, Hispanic L- Caucasian, Hispanic N- Indian/Alaskan Native, Hispanic P- Asian/Pacific Island, Hispanic S- Asian, Non-Hispanic T- Asian, Hispanic U- Unknown W- Caucasian, Non-Hispanic

Key Code for Reading Districts:

Example: LB519

L for Law call or incident B stands for Bloomington 5 is the district or beat where incident occurred All numbers following represents a grid sector.

Disclaimer: The Bloomington Police Department takes great effort in making open data as accurate as possible, but there is no avoiding the introduction of errors in this process, which relies on data provided by many people and that cannot always be verified. Information contained in this dataset may change over a period of time. The Bloomington Police Department is not responsible for any error or omission from this data, or for the use or interpretation of the results of any research conducted.

These data on 19th- and early 20th-century police department and arrest behavior were collected between 1975 and 1978 for a study of police and crime in the United States. Raw and aggregated time-series data are presented in Parts 1 and 3 on 23 American cities for most years during the period 1860-1920. The data were drawn from annual reports of police departments found in the Library of Congress or in newspapers and legislative reports located elsewhere. Variables in Part 1, for which the city is the unit of analysis, include arrests for drunkenness, conditional offenses and homicides, persons dismissed or held, police personnel, and population. Part 3 aggregates the data by year and reports some of these variables on a per capita basis, using a linear interpolation from the last decennial census to estimate population. Part 2 contains data for 267 United States cities for the period 1880-1890 and was generated from the 1880 federal census volume, REPORT ON THE DEFECTIVE, DEPENDENT, AND DELINQUENT CLASSES, published in 1888, and from the 1890 federal census volume, SOCIAL STATISTICS OF CITIES. Information includes police personnel and expenditures, arrests, persons held overnight, trains entering town, and population.

A list of all closed allegations made against uniformed members of the New York Police Department since the year 2000. A single complaint may include multiple allegations between multiple victims / alleged victims and multiple officers. A single allegation is between one complainant and one officer. The term "Victim / Alleged Victim" refers to the person claiming harm by at least one or more allegation(s) of police misconduct.

The dataset is part of a database of all public police misconduct records the Civilian Complaint Review Board (CCRB) maintains on complaints against New York Police Department uniformed members of service received in CCRB's jurisdiction since the year 2000, when CCRB's database was first built. This data is published as four tables:

Civilian Complaint Review Board: Police Officers Civilian Complaint Review Board: Complaints Against Police Officers Civilian Complaint Review Board: Allegations Against Police Officers Civilian Complaint Review Board: Penalties

A single complaint can include multiple allegations, and those allegations may include multiple subject officers and multiple complainants.

Public records exclude complaints and allegations that were closed as Mediated, Mediation Attempted, Administrative Closure, Conciliated (for some complaints prior to the year 2000), or closed as Other Possible Misconduct Noted.

This database is inclusive of prior datasets held on Open Data (previously maintained as "Civilian Complaint Review Board (CCRB) - Complaints Received," "Civilian Complaint Review Board (CCRB) - Complaints Closed," and "Civilian Complaint Review Board (CCRB) - Allegations Closed") but includes information and records made public by the June 2020 repeal of New York Civil Rights law 50-a, which precipitated a full revision of what CCRB data could be considered public.

A list of all NYPD officers, as reported to CCRB by NYPD based on NYPD's roster, and a count of any complaints they have received since the year 2000.

The dataset is part of a database of all public police misconduct records the Civilian Complaint Review Board (CCRB) maintains on complaints against New York Police Department uniformed members of service received in CCRB's jurisdiction since the year 2000, when CCRB's database was first built. This data is published as four tables:

Civilian Complaint Review Board: Police Officers Civilian Complaint Review Board: Complaints Against Police Officers Civilian Complaint Review Board: Allegations Against Police Officers Civilian Complaint Review Board: Penalties

A single complaint can include multiple allegations, and those allegations may include multiple subject officers and multiple complainants.

Public records exclude complaints and allegations that were closed as Mediated, Mediation Attempted, Administrative Closure, Conciliated (for some complaints prior to the year 2000), or closed as Other Possible Misconduct Noted.

This database is inclusive of prior datasets held on Open Data (previously maintained as "Civilian Complaint Review Board (CCRB) - Complaints Received," "Civilian Complaint Review Board (CCRB) - Complaints Closed," and "Civilian Complaint Review Board (CCRB) - Allegations Closed") but includes information and records made public by the June 2020 repeal of New York Civil Rights law 50-a, which precipitated a full revision of what CCRB data could be considered public.

Law Enforcement Locations Any location where sworn officers of a law enforcement agency are regularly based or stationed. Law Enforcement agencies "are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Although TGS's intention is to only include locations associated with agencies that meet the above definition, TGS has discovered a few locations that are associated with agencies that are not publicly funded. TGS deleted these locations as we became aware of them, but some may still exist in this dataset. Personal homes, administrative offices, and temporary locations are intended to be excluded from this dataset; however, some personal homes of constables are included due to the fact that many constables work out of their homes. TGS has made a concerted effort to include all local police; county sheriffs; state police and/or highway patrol; Bureau of Indian Affairs; Bureau of Land Management; Bureau of Reclamation; U.S. Park Police; Bureau of Alcohol, Tobacco, Firearms, and Explosives; U.S. Marshals Service; U.S. Fish and Wildlife Service; National Park Service; U.S. Immigration and Customs Enforcement; and U.S. Customs and Border Protection. This dataset is comprised completely of license free data. FBI entities are intended to be excluded from this dataset, but a few may be included. The Law Enforcement dataset and the Correctional Institutions dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. With the merge of the Law Enforcement and the Correctional Institutions datasets, the NAICS Codes & Descriptions were assigned based on the facility's main function which was determined by the entity's name, facility type, web research, and state supplied data. In instances where the entity's primary function is both law enforcement and corrections, the NAICS Codes and Descriptions are assigned based on the dataset in which the record is located (i.e., a facility that serves as both a Sheriff's Office and as a jail is designated as [NAICSDESCR]="SHERIFFS' OFFICES (EXCEPT COURT FUNCTIONS ONLY)" in the Law Enforcement layer and as [NAICSDESCR]="JAILS (EXCEPT PRIVATE OPERATION OF)" in the Correctional Institutions layer). Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard fields that TGS populated. Double spaces were replaced by single spaces in these same fields. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based on the values in this field, the oldest record dates from 08/10/2006 and the newest record dates from 10/22/2009

This dataset contains Use of Force (UOF) incidents (formerly referred to as "Response to Resistance" incidents) from January 2018 forward, including demographic information for officers as well as individuals. All incidents included in the UOF dataset have gone through a review process and have been completed and finalized. Incidents still in process are not included in the dataset until marked complete. Data is updated on the 1st of each month, with a 3-month lag time due to the reporting and review process.

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An Officer Involved Shooting (OIS) is the discharge of a firearm, whether accidental or intentional, by a police officer, whether on or off duty. For the purposes of this posting, an OIS will only refer to the instances in which an officer discharged a firearm at a person. CMPD posts Officer Involved Shootings in an effort to create greater transparency of the actions of our employees. It is important to us that members of the community are informed whenever an officer discharges his/her firearm at a person and whether the shooting follows department policies and procedures. We believe that your trust and confidence in the Charlotte-Mecklenburg Police Department will increase as you understand what our officers encounter and how we hold them accountable for their actions. The CMPD is continuously reviewing and improving our practices to reduce the likelihood of deadly force incidents.

Feature layer showing the locations of Sworn Law Enforcement Officer Locations in California.This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Although TGS's intention is to only include locations associated with agencies that meet the above definition, TGS has discovered a few locations that are associated with agencies that are not publicly funded. TGS deleted these locations as we became aware of them, but some may still exist in this dataset. Personal homes, administrative offices, and temporary locations are intended to be excluded from this dataset; however, some personal homes of constables are included due to the fact that many constables work out of their homes. This also applies to mounted police in New Mexico. TGS has made a concerted effort to include all local police; county sheriffs; state police and/or highway patrol; Bureau of Indian Affairs; Bureau of Land Management; Bureau of Reclamation; U.S. Park Police; Bureau of Alcohol, Tobacco, Firearms, and Explosives; U.S. Marshals Service; U.S. Fish and Wildlife Service; National Park Service; U.S. Immigration and Customs Enforcement; and U.S. Customs and Border Protection in the United States and its territories. This dataset is comprised completely of license free data. At the request of NGA, FBI entities are intended to be excluded from this dataset, but a few may be included. The HSIP Freedom Law Enforcement dataset and the HSIP Freedom Correctional Institutions dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. Please see the process description for the breakdown of how the records were merged. With the merge of the Law Enforcement and the Correctional Institutions datasets, the HSIP Themes and NAICS Codes & Descriptions were assigned based on the facility's main function which was determined by the entity's name, facility type, web research, and state supplied data. In instances where the entity's primary function is both law enforcement and corrections, the NAICS Codes and Descriptions are assigned based on the dataset in which the record is located (i.e., a facility that serves as both a Sheriff's Office and as a jail is designated as [NAICSDESCR]="SHERIFFS' OFFICES (EXCEPT COURT FUNCTIONS ONLY)" in the Law Enforcement layer and as [NAICSDESCR]="JAILS (EXCEPT PRIVATE OPERATION OF)" in the Correctional Institutions layer). Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard HSIP fields that TGS populated. Double spaces were replaced by single spaces in these same fields. At the request of NGA, text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. At the request of NGA, all diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based on the values in this field, the oldest record dates from 12/07/2004 and the newest record dates from 09/10/2009.Use Cases: Use cases describe how the data may be used and help to define and clarify requirements.1. An assessment of whether or not the total police capability in a given area is adequate. 2. A list of resources to draw upon in surrounding areas when local resources have temporarily been overwhelmed by a disaster - route analysis can help to determine those entities who are able to respond the quickest. 3. A resource for emergency management planning purposes. 4. A resource for catastrophe response to aid in the retrieval of equipment by outside responders in order to deal with the disaster. 5. A resource for situational awareness planning and response for federal government events.

This dataset contains Phoenix Police Department Officer-Involved Shooting (OIS) incidents from January 2017 forward, including demographic information for officers as well as individuals. Data is updated hourly; however, new OIS incidents are only displayed after information is compiled for all the fields displayed in the dataset, which may take several days following the incident.

More than one officer may discharge their weapon during the same incident. Accidental discharges, discharges at animals, and discharges at objects where there was not an active threat by a subject are not included in this data set.

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description: Law Enforcement Locations in Kansas Any location where sworn officers of a law enforcement agency are regularly based or stationed. Law enforcement agencies "are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Although TGS's intention is to only include locations associated with agencies that meet the above definition, TGS has discovered a few locations that are associated with agencies that are not publicly funded. TGS is deleting these locations as we become aware of them, but some probably still exist in this dataset. Personal homes, administrative offices and temporary locations are intended to be excluded from this dataset, but a few may be included. Personal homes of constables may exist due to fact that many constables work out of their home. FBI entites are intended to be excluded from this dataset, but a few may be included. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] attribute. Based upon this attribute, the oldest record dates from 2006/06/27 and the newest record dates from 2008/03/06; abstract: Law Enforcement Locations in Kansas Any location where sworn officers of a law enforcement agency are regularly based or stationed. Law enforcement agencies "are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Although TGS's intention is to only include locations associated with agencies that meet the above definition, TGS has discovered a few locations that are associated with agencies that are not publicly funded. TGS is deleting these locations as we become aware of them, but some probably still exist in this dataset. Personal homes, administrative offices and temporary locations are intended to be excluded from this dataset, but a few may be included. Personal homes of constables may exist due to fact that many constables work out of their home. FBI entites are intended to be excluded from this dataset, but a few may be included. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] attribute. Based upon this attribute, the oldest record dates from 2006/06/27 and the newest record dates from 2008/03/06

This dataset contains Phoenix Police Department officer demographics as of January 1st of each year starting in 2018. All ranks of sworn employees are included.

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Analysis of ‘US Police Shootings’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/ahsen1330/us-police-shootings on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

In the recent killings, a hot topic came into being, "Racism". So, I chose to gather some data to take out some insights and analyze the story around racism in America. I downloaded the raw data from kaggle and prepared it for visualization while correcting values, handling missing content, normalization and categorization

Content

It contains basic data about people like their name, age, gender and race. Along with it, is the shooting/killing information, like date of event, where it happened? how they were shot? did they attack? Were they holding weapons? Did they show any mental illness? Was the policeman wearing a camera/was the incident recorded? Did the suspect flee? Apart from that, a category column holds type of weapon used by the suspect

Acknowledgements

Kagglers

--- Original source retains full ownership of the source dataset ---

This dataset includes all valid felony, misdemeanor, and violation crimes reported to the New York City Police Department (NYPD) for all complete quarters so far this year (2017). For additional details, please see the attached data dictionary in the ‘About’ section.

Please review this brief video for a better understanding of how these data are created: https://www.youtube.com/watch?v=lvTCjVHxpAU

This data represents police response activity. Each row is a record of a Call for Service (CfS) logged with the Seattle Police Department (SPD) Communications Center. Calls originated from the community and range from in progress or active emergencies to requests for problem solving. Additionally, officers will log calls from their observations of the field.

Previous versions of this data set have withheld approximately 40% of calls. This updated process will release more than 95% of all calls but we will no longer provide latitude and longitude specific location data. In an effort to safeguard the privacy of our community, calls will only be located to the “beat” level. Beats are the most granular unit of management used for patrol deployment. To learn more about patrol deployment, please visit: https://www.seattle.gov/police/about-us/about-policing/precinct-and-patrol-boundaries.

As with any data, certain conditions and qualifications apply:

1) These data are queried from the Data Analytics Platform (DAP), and updated incrementally on a daily basis. A full refresh will occur twice a year and is intended to reconcile minor changes.

2) This data set only contains records of police response. If a call is queued in the system but cleared before an officer can respond, it will not be included.

3) These data contain administrative call types. Use the “Initial” and “Final” call type to identify the calls you wish to include in your analysis.

We invite you to engage these data, ask questions and explore.