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.

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.

Analysis of ‘Police Killings US’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/azizozmen/police-killings-us on 13 February 2022.

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

"In 2015, The Washington Post began to log every fatal shooting by an on-duty police officer in the United States. In that time there have been more than 5,000 such shootings recorded by The Post. After Michael Brown, an unarmed Black man, was killed in 2014 by police in Ferguson, Mo., a Post investigation found that the FBI undercounted fatal police shootings by more than half. This is because reporting by police departments is voluntary and many departments fail to do so. The Washington Post’s data relies primarily on news accounts, social media postings, and police reports. Analysis of more than five years of data reveals that the number and circumstances of fatal shootings and the overall demographics of the victims have remained relatively constant..." SOURCE ==> Washington Post Article

For more information about this story

This dataset has been prepared by The Washington Post (they keep updating it on runtime) with every fatal shooting in the United States by a police officer in the line of duty since Jan. 1, 2015.

2016 PoliceKillingUS DATASET
2017 PoliceKillingUS DATASET
2018 PoliceKillingUS DATASET
2019 PoliceKillingUS DATASET
2020 PoliceKillingUS DATASET

Features at the Dataset:

The file fatal-police-shootings-data.csv contains data about each fatal shooting in CSV format. The file can be downloaded at this URL. Each row has the following variables:

• id: a unique identifier for each victim
• name: the name of the victim
• date: the date of the fatal shooting in YYYY-MM-DD format
• manner_of_death: shot, shot and Tasered
• armed: indicates that the victim was armed with some sort of implement that a police officer believed could inflict harm
  • undetermined: it is not known whether or not the victim had a weapon
  • unknown: the victim was armed, but it is not known what the object was
  • unarmed: the victim was not armed
• age: the age of the victim
• gender: the gender of the victim. The Post identifies victims by the gender they identify with if reports indicate that it differs from their biological sex.
  • M: Male
  • F: Female
  • None: unknown
• race:
  • W: White, non-Hispanic
  • B: Black, non-Hispanic
  • A: Asian
  • N: Native American
  • H: Hispanic
  • O: Other
  • None: unknown
• city: the municipality where the fatal shooting took place. Note that in some cases this field may contain a county name if a more specific municipality is unavailable or unknown.
• state: two-letter postal code abbreviation
• signs of mental illness: News reports have indicated the victim had a history of mental health issues, expressed suicidal intentions or was experiencing mental distress at the time of the shooting.
• threat_level: The threat_level column was used to flag incidents for the story by Amy Brittain in October 2015. http://www.washingtonpost.com/sf/investigative/2015/10/24/on-duty-under-fire/ As described in the story, the general criteria for the attack label was that there was the most direct and immediate threat to life. That would include incidents where officers or others were shot at, threatened with a gun, attacked with other weapons or physical force, etc. The attack category is meant to flag the highest level of threat. The other and undetermined categories represent all remaining cases. Other includes many incidents where officers or others faced significant threats.
• flee: News reports have indicated the victim was moving away from officers
  • Foot
  • Car
  • Not fleeing

The threat column and the fleeing column are not necessarily related. For example, there is an incident in which the suspect is fleeing and at the same time turns to fire at gun at the officer. Also, attacks represent a status immediately before fatal shots by police while fleeing could begin slightly earlier and involve a chase. - body_camera: News reports have indicated an officer was wearing a body camera and it may have recorded some portion of the incident.

SOURCE

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

Since 2013, protests opposing police violence against Black people have occurred across a number of American cities under the banner of “Black Lives Matter.” We develop a new dataset of Black Lives Matter protests that took place in 2014–2015 and explore the contexts in which they emerged. We find that Black Lives Matter protests are more likely to occur in localities where more Black people have previously been killed by police. We discuss the implications of our findings in light of the literature on the development of social movements and recent scholarship on the carceral state’s impact on political engagement.

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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This set of raw data contains information from Bloomington Police Department cases, specifically it identified cases where officers have fired a gun at a suspect.

**Please note that this particular dataset contains no data. As of current date, the Bloomington Police Department has had no officer involved shootings to report. **

Key code for Race:

• A- Asian/Pacific Island, Non-Hispanic
• B- African American, 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
• 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.

A map of the five districts can be located on Raidsonline.com, under the tab labeled ‘Agency Layers’.

Disclaimer: The Bloomington Police Department takes great effort in making all sets of data as accurate as possible, but there is no avoiding the introduction of errors in this process. 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.

Bloomington Police Department cases where officers have fired a gun at an individual.

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.

Note: Due to the RMS change for CPS, this data set stops on 6/2/2024. For records beginning on 6/3/2024, please see the dataset at this link: https://data.cincinnati-oh.gov/safety/Reported-Crime-STARS-Category-Offenses-/7aqy-xrv9/about_data

The combined data will be available by 3/10/2025 at the linke above.

Data Description: This data represents reported Crime Incidents in the City of Cincinnati. Incidents are the records, of reported crimes, collated by an agency for management. Incidents are typically housed in a Records Management System (RMS) that stores agency-wide data about law enforcement operations. This does not include police calls for service, arrest information, final case determination, or any other incident outcome data.

Data Creation: The Cincinnati Police Department's (CPD) records crime incidents in the City through Records Management System (RMS) that stores agency-wide data about law enforcement operations.

Data Created By: The source of this data is the Cincinnati Police Department.

Refresh Frequency: This data is updated daily.

CincyInsights: The City of Cincinnati maintains an interactive dashboard portal, CincyInsights in addition to our Open Data in an effort to increase access and usage of city data. This data set has an associated dashboard available here: https://insights.cincinnati-oh.gov/stories/s/8eaa-xrvz

Data Dictionary: A data dictionary providing definitions of columns and attributes is available as an attachment to this dataset.

Processing: The City of Cincinnati is committed to providing the most granular and accurate data possible. In that pursuit the Office of Performance and Data Analytics facilitates standard processing to most raw data prior to publication. Processing includes but is not limited: address verification, geocoding, decoding attributes, and addition of administrative areas (i.e. Census, neighborhoods, police districts, etc.).

Data Usage: For directions on downloading and using open data please visit our How-to Guide: https://data.cincinnati-oh.gov/dataset/Open-Data-How-To-Guide/gdr9-g3ad

Disclaimer: In compliance with privacy laws, all Public Safety datasets are anonymized and appropriately redacted prior to publication on the City of Cincinnati’s Open Data Portal. This means that for all public safety datasets: (1) the last two digits of all addresses have been replaced with “XX,” and in cases where there is a single digit street address, the entire address number is replaced with "X"; and (2) Latitude and Longitude have been randomly skewed to represent values within the same block area (but not the exact location) of the incident.

This is a set of csv files including a number of variables including fatal police shootings and other crime and socioeconomic covariates at different levels of geographical aggregation from 2013-2016. Five of the files use only the Washington Post data covering years 2015 and 2016, whereas the other five files utilize fatal police shootings of civilians for years 2013-2016, combining the Lott & Moody (2016) data for years 2013-2015 and Washington Post data for 2016. Other variables are included from the American Community Survey (ACS), the FBI's Uniform Crime Reports (UCR), the Law Enforcement Management and Administrative Statistics (LEMAS), Stanford Education Data Archive (SEDA), the US Census, and the Local Area Unemployment Statistics (LAUS) provided by the Bureau of Labor Statistics (BLS). The base file is the county-level data. The two files labelled "tenk" consist of regions with at least 10,000 residents. Counties with fewer than 10,000 residents are combined with adjacent counties, ranked by population in ascending order, so that counties with fewer than 10,000 residents are iteratively combined with adjacent neighbors with the fewest residents until they reach the threshold of 10,000 residents. The same algorithm is used to produce regions with 100,000 and 1 million residents. The final two files are state-level aggregations.

Bloomington Police Department Calls for Service that reported an accident.

Note that this is every call for service that documents an accident, regardless of the outcome of the accident. Not all accidents become State Crash Reports, and, therefore, the data contained in this set will not match accident data supplied by the Indiana State Police.This set of raw data contains information from Bloomington Police Department Calls for Service that reported an accident.

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.

The Shootings dashboard contains information on shooting incidents where a victim was struck by a bullet, either fatally or non-fatally; that occurred in the City of Boston and fall under Boston Police Department jurisdiction. The dashboard does not contain records for self-inflicted gunshot wounds or shootings determined to be justifiable. Information on the incident, and the demographics of victims are included. This information is updated based on analysis conducted by the Boston Regional Intelligence Center under the Boston Police Department Bureau of Intelligence and Analysis. The data is for 2015 forward, with a 7 day rolling delay to allow for analysis and data entry to occur.

Analysis of ‘Accidents’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/fa755bd7-3f21-4683-848a-add535d21101 on 13 February 2022.

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

Bloomington Police Department Calls for Service that reported an accident.

Note that this is every call for service that documents an accident, regardless of the outcome of the accident. Not all accidents become State Crash Reports, and, therefore, the data contained in this set will not match accident data supplied by the Indiana State Police.This set of raw data contains information from Bloomington Police Department Calls for Service that reported an accident.

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.

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

Number, percentage and rate (per 100,000 population) of homicide victims, by racialized identity group (total, by racialized identity group; racialized identity group; South Asian; Chinese; Black; Filipino; Arab; Latin American; Southeast Asian; West Asian; Korean; Japanese; other racialized identity group; multiple racialized identity; racialized identity, but racialized identity group is unknown; rest of the population; unknown racialized identity group), gender (all genders; male; female; gender unknown) and region (Canada; Atlantic region; Quebec; Ontario; Prairies region; British Columbia; territories), 2019 to 2023.

This dataset consists of gun violence within Jefferson county that may fall within LMPDs radar, including non-fatal shootings, homicides, as well as shot-spotter data. The mapping data points where there are victims have been obfuscated to maintain privacy, while still being accurate enough to be placed in its correct boundaries, particularly around, neighborhoods, ZIP Codes, Council districts, and police divisions. The data also excludes any victim information that could be used to identify any individual. this data is used to make the public aware of what is going on in their communities. The data consists of only criminal incidents, excluding any cases that are deemed non-criminal.Field NameField DescriptionCase numberPolice report number. For ShotSpotter detections, it is the ShotSpotter ID.DateTimeDate and time in which the original incident occurred. Time is rounded down.AddressAddress rounded down to the one hundred block of where the initial incident occured. Unless it is an intersection.NeighborhoodNeighborhood in which the original incident occurred.Council DistrictCouncil district in which the original incident occurred.LatitudeLatitude coordinate used to map the incidentLongitudeLongitude coordinate used to map the incidentZIP CodeZIP Code in which the original incident occurred.Crime Typea distinction between incidents, whether it is a non-fatal shooting, homicide, or a ShotSpotter detection.CauseUsed to differentiate on the cause of death for homicide victims.SexGender of the victim of the initial incident.RaceRace/Ethnicity of the victim in a given incident.Age GroupCategorized age groups used to anonymize victim information.Division NamePolice division or department where the initial incident occurred.Crime report data is provided for Louisville Metro Police Divisions only; crime data does not include smaller class cities, unless LMPD becomes involved in smaller agency incident.The data provided in this dataset is preliminary in nature and may have not been investigated by a detective at the time of download. The data is therefore subject to change after a complete investigation. This data represents only calls for police service where a police incident report was taken. Due to the variations in local laws and ordinances involving crimes across the nation, whether another agency utilizes Uniform Crime Report (UCR) or National Incident Based Reporting System (NIBRS) guidelines, and the results learned after an official investigation, comparisons should not be made between the statistics generated with this dataset to any other official police reports. Totals in the database may vary considerably from official totals following the investigation and final categorization of a crime. Therefore, the data should not be used for comparisons with Uniform Crime Report or other summary statistics.Contact:Ivan Benitez, Ph.D.Gun Violence Data FellowOffice for Safe and Healthy Neighborhoodsivan.benitez@louisvilleky.gov

The data provided in this dataset is preliminary in nature and may have not been investigated by a detective at the time of download. The data is therefore subject to change after a complete investigation. This data represents only calls for police service where a police incident report was taken. Due to the variations in local laws and ordinances involving crimes across the nation, whether another agency utilizes Uniform Crime Report (UCR) or National Incident Based Reporting System (NIBRS) guidelines, and the results learned after an official investigation, comparisons should not be made between the statistics generated with this dataset to any other official police reports. Totals in the database may vary considerably from official totals following the investigation and final categorization of a crime. Therefore, the data should not be used for comparisons with Uniform Crime Report or other summary statistics.Data is broken out by year into separate CSV files. Note the file grouping by year is based on the crime's Date Reported (not the Date Occurred).Older cases found in the 2003 data are indicative of cold case research. Older cases are entered into the Police database system and tracked but dates and times of the original case are maintained.Data may also be viewed off-site in map form for just the last 6 months on communitycrimemap.comData Dictionary:Field NameField DescriptionIncident Numberthe number associated with either the incident or used as reference to store the items in our evidence roomsDate Reportedthe date the incident was reported to LMPDDate Occurredthe date the incident actually occurredBadge IDBadge ID of responding OfficerOffense ClassificationNIBRS Reporting category for the criminal act committedOffense Code NameNIBRS Reporting code for the criminal act committedNIBRS_CODEthe code that follows the guidelines of the National Incident Based Reporting System. For more details visit https://ucr.fbi.gov/nibrs/2011/resources/nibrs-offense-codes/viewNIBRS Grouphierarchy that follows the guidelines of the FBI National Incident Based Reporting SystemWas Offense CompletedStatus indicating whether the incident was an attempted crime or a completed crime.LMPD Divisionthe LMPD division in which the incident actually occurredLMPD Beatthe LMPD beat in which the incident actually occurredLocation Categorythe type of location in which the incident occurred (e.g. Restaurant)Block Addressthe location the incident occurredCitythe city associated to the incident block locationZip Codethe zip code associated to the incident block locationContact:LMPD Open Records lmpdopenrecords@louisvilleky.gov

Dallas Police Public Data - Officer Involved Shootings City Of Dallas

Police-reported hate crime, by type of motivation (race or ethnicity, religion, sexual orientation, language, disability, sex, age), selected regions and Canada (selected police services), 2014 to 2023.

Following racially charged events, individuals often diverge in perceptions of what happened and how justice should be served. Examining data gathered shortly after the 2014 shooting of Michael Brown in Ferguson, Missouri alongside reactions to a novel officer-involved shooting, we unpack the processes by which racial divisions emerge. Even in a controlled information environment, White Americans preferred information that supported claims of a justified shooting. Conversely, Black Americans preferred information that implied the officer behaved inappropriately. These differences stemmed from two distinct processes: we find some evidence for a form of race-based motivated reasoning and strong evidence for belief updating based on racially distinct priors. Differences in summary judgments were larger when individuals identified strongly with their racial group or when expectations about the typical behaviors of Black Americans and police diverged. The findings elucidate processes whereby individuals in different social groups come to accept differing narratives about contentious events. (2020-09-04)

***Starting on March 7th, 2024, the Los Angeles Police Department (LAPD) will adopt a new Records Management System for reporting crimes and arrests. This new system is being implemented to comply with the FBI's mandate to collect NIBRS-only data (NIBRS — FBI - https://www.fbi.gov/how-we-can-help-you/more-fbi-services-and-information/ucr/nibrs). During this transition, users will temporarily see only incidents reported in the retiring system. However, the LAPD is actively working on generating new NIBRS datasets to ensure a smoother and more efficient reporting system. ***

******Update 1/18/2024 - LAPD is facing issues with posting the Crime data, but we are taking immediate action to resolve the problem. We understand the importance of providing reliable and up-to-date information and are committed to delivering it.

As we work through the issues, we have temporarily reduced our updates from weekly to bi-weekly to ensure that we provide accurate information. Our team is actively working to identify and resolve these issues promptly.

We apologize for any inconvenience this may cause and appreciate your understanding. Rest assured, we are doing everything we can to fix the problem and get back to providing weekly updates as soon as possible. ******

This dataset reflects incidents of crime in the City of Los Angeles dating back to 2020. This data is transcribed from original crime reports that are typed on paper and therefore there may be some inaccuracies within the data. Some location fields with missing data are noted as (0°, 0°). Address fields are only provided to the nearest hundred block in order to maintain privacy. This data is as accurate as the data in the database. Please note questions or concerns in the comments.