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

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

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.

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.

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 (2019). For additional details, please see the attached data dictionary in the ‘About’ section.

Context

This dataset contains information about fatal shooting of civilians by police officers in the US since Jan 1st, 2015. The data about the shootings was collected by the Washington Post in their fatal police shootings dataset. The city locations were geocoded using OpenStreetMap Nominatim.

Content

fatal-police-shootings-data.csv contains information about each shooting. Each row is a shooting, and columns contain information about

• Name of the individual shot
• Date of the shooting
• Manner of death of the individual shot
• If and how the individual shot was armed
• Age of the individual shot
• Gender of the individual shot
• Race of the individual shot
• Whether the individual shot displayed signs of mental illness
• To what level the individual shot was attacking when shot
• If and how the individual shot was fleeing from police
• If an officer present for the shooting was wearing a body camera

CityLocations.csv contains the latitude and longitude for each city present in fatal-police-shootings-data.csv.

Acknowledgements and Licenses

The data in fatal-police-shootings-data.csv was collected by the Washington Post, and is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License.

The data in CityLocations.csv was geocoded using OpenStreetMap Nominatim, and is licensed under the Open Database License.

Cover image by Spenser.

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.

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.

Use of force is a sometimes necessary, yet often controversial, police power. Attempts to understand and explore police use of force have often been hampered by a lack of data, both nationally and internationally, with much research reliant on a very small number of datasets, often in the United States of America. This new data, collected by police forces in England and Wales and collated and published by the Home Office, represents an exciting new resource. According to the Home Office, 'these statistics cover incidents where police officers have used force and includes: the tactics used, the reason for force, the outcome, any injuries (to the officers and or the subject) and subject information (age, gender, ethnicity and disability, as perceived by the reporting officer). From April 2017, all police forces in the UK have been required to record this data. The use of force data collection is intended to hold police forces to account and to provide the public with greater information on the different types of force used and the context in which this occurs' https://www.gov.uk/government/collections/police-use-of-force-statistics.This project (ES/N016564/1, Less Lethal Force in Law Enforcement) involved, in part, working with various stakeholders to help advise on the creation and maintenance of a new template form for police officers to record their use of force, which in turn has resulted in the collection of new use of force data. A subset of this information, which is generated by the police and published by the Home Office, is routinely made publicly available and this record has been set up to help signpost researchers towards this resource. Further details about the broader ESRC funded project is below: Use of force by law enforcement officials, including police and correctional officers, is a highly important issue. Yet whilst the situations in which these officials use firearms, and the effects of this use, are relatively well documented and understood, this is not the case with 'less lethal' weapons and 'less lethal' force. At least three key topics around less lethal weapons remain under-researched, and this project will tackle all three directly. First we lack a basic understanding of when, why, on whom, and how often, less lethal weapons are used - and whether certain groups of people (those of a particular gender, ethnic minority, mental health status or geographical origin) are more or less likely to have less lethal force used on them. This project will see the PI work closely with the National Police Chief's Council, the Home Office and UK police forces, utilizing datasets previously unavailable to academic researchers to answer such questions. Such issues are also relevant internationally, as shown by recent debates on police less lethal force in countries as varied as Armenia, Hungary and New Zealand. Second, whilst these weapons are associated with saving lives, they have also been associated with serious injuries and fatalities. In the UK alone, several high profile deaths-including that of Ian Tomlinson and Jordan Begley-have occurred following police use of less lethal weapons. There are key questions around how so called less lethal force can impact the right to life, and their association with fatalities worldwide. Building on my PhD work focusing on injuries associated with Taser, this project will see the PI work with the UN Special Rapporteur to research the impact less lethal force has on the right to life in the UK and globally. Third, if it is important to attend to the situations in which force is used, it is also important to look at how such force is monitored and governed. This requires working with police and government to help understand what data on less lethal force should be gathered and analyzed, and working with the independent oversight bodies that monitor places of detention (including police custody) to ensure that they have the necessary research to enable them to document the LLF used by state authorities. The UN Subcommittee for the Prevention of Torture has highlighted the need for research to assist them in addressing and monitoring less lethal weapons and other physical infrastructure found in places of detention. The PI will work with key decision makers on these issues; with the UK government on reporting, and with oversight bodies via the SPT and its network of over 40 national bodies. According to the Home Office's User Guide to Use of Force Statistics, https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/945436/user-guide-police-use-of-force-dec20.pdf (pages 4 - 5): 'Officers must complete a ‘use of force report’ each time they use force tactics on an individual. The use of force reports also allow for other information to be recorded... The publication does not include force used in designated public order events, where officers may use force over a period of time against a person(s) not subsequently apprehended. In these situations, it is not feasible for officers to provide the same level of detail as for individual use of force incidents. Police forces may collect additional information at a local level, with further detail or including designated public order events".

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

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.

About this dataset

The Washington Post compiled a dataset of every fatal shooting in the United States by a police officer in the line of duty since Jan. 1, 2015.

In 2015, The Post began tracking more than a dozen details about each killing by culling local news reports, law enforcement websites and social media and by monitoring independent databases such as Killed by Police and Fatal Encounters. The available features are: - Race of the deceased; - Circumstances of the shooting; - Whether the person was armed; - Whether the victim was experiencing a mental-health crisis; - Among others.

In 2016, The Post is gathering additional information about each fatal shooting that occurs this year and is filing open-records requests with departments. More than a dozen additional details are being collected about officers in each shooting.

The Post is documenting only those shootings in which a police officer, in the line of duty, shot and killed a civilian — the circumstances that most closely parallel the 2014 killing of Michael Brown in Ferguson, Mo., which began the protest movement culminating in Black Lives Matter and an increased focus on police accountability nationwide. The Post is not tracking deaths of people in police custody, fatal shootings by off-duty officers or non-shooting deaths.

The FBI and the Centers for Disease Control and Prevention log fatal shootings by police, but officials acknowledge that their data is incomplete. In 2015, The Post documented more than two times more fatal shootings by police than had been recorded by the FBI. Last year, the FBI announced plans to overhaul how it tracks fatal police encounters.

How to use this dataset

• Understanding US Police Shootings by Curtis Thompson
• Dataset Questions and Suggestions
• More datasets

Acknowledgements

If you use this dataset in your research, please credit the authors.

BibTeX

@misc{wapo-police-shootings-bot , author = {The Washington Post}, title = {data-police-shootings}, month = jan, year = 2015, publisher = {Github}, url = {https://github.com/washingtonpost/data-police-shootings} }

License

CC BY NC SA 4.0

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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 04/26/2006 and the newest record dates from 10/19/2009

List of every shooting incident that occurred in NYC during the current calendar year.

This is a breakdown of every shooting incident that occurred in NYC during the current calendar year. This data is manually extracted every quarter and reviewed by the Office of Management Analysis and Planning before being posted on the NYPD website. Each record represents a shooting incident in NYC and includes information about the event, the location and time of occurrence. In addition, information related to suspect and victim demographics is also included. This data can be used by the public to explore the nature of police enforcement activity. Please refer to the attached data footnotes for additional information about this dataset.

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 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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We will build you a custom US crime dataset based on your needs. Data points may include date, time, location, crime type, crime description, victim demographics, offender demographics, arrest records, charges filed, court outcomes, police department response time, incident outcome, weapon used, property stolen or damaged, crime location type, and other related data.

Use our US crime datasets for a range of applications to enhance public safety and policy effectiveness. Analyzing these datasets can help organizations understand crime patterns and trends across different regions of the United States, enabling them to tailor their strategies and interventions accordingly. Depending on your needs, you may access the entire dataset or a customized subset.

Popular use cases include: improving public safety measures, designing targeted crime prevention programs, resource allocation for law enforcement, and more.

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.

This dataset sets forth the Police Retirement System holdings (both equity and fixed income) of the identified pension/retirement system as of the close of the fiscal year.

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.