This API is available at https://data.police.uk It contains crimes at street-level; either within a 1 mile radius of a single point, or within a custom area. The street-level crimes returned in the API are only an approximation of where the actual crimes occurred, they are not the exact locations. See the about page for more information about location anonymisation. https://data.police.uk/about/

The dataset contains a subset of locations and attributes of incidents reported in the ASAP (Analytical Services Application) crime report database by the District of Columbia Metropolitan Police Department (MPD). Visit crimecards.dc.gov for more information. This data is shared via an automated process where addresses are geocoded to the District's Master Address Repository and assigned to the appropriate street block. Block locations for some crime points could not be automatically assigned resulting in 0,0 for x,y coordinates. These can be interactively assigned using the MAR Geocoder.On February 1 2020, the methodology of geography assignments of crime data was modified to increase accuracy. From January 1 2020 going forward, all crime data will have Ward, ANC, SMD, BID, Neighborhood Cluster, Voting Precinct, Block Group and Census Tract values calculated prior to, rather than after, anonymization to the block level. This change impacts approximately one percent of Ward assignments.

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.

The dataset contains a subset of locations and attributes of incidents reported in the ASAP (Analytical Services Application) crime report database by the District of Columbia Metropolitan Police Department (MPD). Visit crimecards.dc.gov for more information. This data is shared via an automated process where addresses are geocoded to the District's Master Address Repository and assigned to the appropriate street block. Block locations for some crime points could not be automatically assigned resulting in 0,0 for x,y coordinates. These can be interactively assigned using the MAR Geocoder.On February 1 2020, the methodology of geography assignments of crime data was modified to increase accuracy. From January 1 2020 going forward, all crime data will have Ward, ANC, SMD, BID, Neighborhood Cluster, Voting Precinct, Block Group and Census Tract values calculated prior to, rather than after, anonymization to the block level. This change impacts approximately one percent of Ward assignments.

In 2022, the New Orleans-Metairie, LA metro area recorded the highest homicide rate of U.S. cities with a population over 250,000, at **** homicides per 100,000 residents, followed by the Memphis, TN-MS-AR metro area. However, homicide data was not recorded in all U.S. metro areas, meaning that there may be some cities with a higher homicide rate. St. Louis St. Louis, which had a murder and nonnegligent manslaughter rate of **** in 2022, is the second-largest city by population in Missouri. It is home to many famous treasures, such as the St. Louis Cardinals baseball team, Washington University in St. Louis, the Saint Louis Zoo, and the renowned Gateway Arch. It is also home to many corporations, such as Monsanto, Arch Coal, and Emerson Electric. The economy of St. Louis is centered around business and healthcare, and boasts ten Fortune 500 companies. Crime in St. Louis Despite all of this, St. Louis suffers from high levels of crime and violence. As of 2023, it was listed as the seventh most dangerous city in the world as a result of their extremely high murder rate. Not only does St. Louis have one of the highest homicide rates in the United States, it also reports one of the highest numbers of violent crimes. Despite high crime levels, the GDP of the St. Louis metropolitan area has been increasing since 2001.

The RMS Crime Incidents dataset consists of crime reports from the Detroit Police Department Records Management System (RMS). This data reflects reported criminal offenses that have occurred in the City of Detroit. Incident-based offense data is extracted from the Detroit Police Department's records management system hourly. This data set contains the most recent data available and is updated anytime DPD sends official crime records contributing to the Michigan Incident Crime Reporting (MICR) or the National Incident Based Reporting systems (reflected by the IBR Date field). It should be noted that some incidents involve the commission of multiple offenses, such as a domestic assault where property was also vandalized. In such cases, there is a row in the dataset for each offense, and the related offenses share a common Crime ID and Report Number.

This dataset, curated by the Los Angeles Police Department (LAPD), provides detailed records of crime incidents reported across Los Angeles from 2020 to 2023. It reflects the LAPD’s commitment to transparency and public safety, offering insights into crime trends, enforcement actions, and neighborhood-specific challenges. The data serves as a critical resource for researchers, policymakers, and residents to understand urban safety dynamics.

🔗 Source

Directly sourced from the LAPD’s Public Data Portal on Data.gov.

💡 Inspiration

Public Accountability: Empower communities to track crime trends in their neighborhoods.

Policy & Prevention: Aid law enforcement and city planners in resource allocation and hotspot intervention.

Research: Enable academics to study socio-economic factors, seasonal patterns, and the impact of policing strategies.

🔍 Key Attributes

Temporal: Incident date/time (DATE OCC), report date (Date Rptd).

Geospatial: Latitude/longitude 🌐, cross streets, police precinct (AREA NAME).

Crime Details: Type (Crm Cd Desc), weapon used 🔫, premise (e.g., street, store 🏪).

Victim Data: Age, gender ♀️♂️, descent.

Case Status: Arrests 🚨, investigations 🕵️, court outcomes ⚖️.

The dataset contains a subset of locations and attributes of incidents reported in the ASAP (Analytical Services Application) crime report database by the District of Columbia Metropolitan Police Department (MPD). Visit https://crimecards.dc.gov for more information. This data is shared via an automated process where addresses are geocoded to the District's Master Address Repository and assigned to the appropriate street block. Block locations for some crime points could not be automatically assigned resulting in 0,0 for x,y coordinates. These can be interactively assigned using the MAR Geocoder.On February 1 2020, the methodology of geography assignments of crime data was modified to increase accuracy. From January 1 2020 going forward, all crime data will have Ward, ANC, SMD, BID, Neighborhood Cluster, Voting Precinct, Block Group and Census Tract values calculated prior to, rather than after, anonymization to the block level. This change impacts approximately one percent of Ward assignments.

This API is available at https://data.police.uk

It contains crimes at street-level; either within a 1 mile radius of a single point, or within a custom area.

The street-level crimes returned in the API are only an approximation of where the actual crimes occurred, they are not the exact locations. See the about page for more information about location anonymisation. https://data.police.uk/about/

2025 NIBRS crime data for St. Louis County Police Department and additional St. Louis County Municipalities. Data is subject to change.

Updated daily postings on Montgomery County’s open data website, dataMontgomery, provide the public with direct access to crime statistic databases - including raw data and search functions – of reported County crime. The data presented is derived from reported crimes classified according to the National Incident-Based Reporting System (NIBRS) of the Criminal Justice Information Services (CJIS) Division Uniform Crime Reporting (UCR) Program and documented by approved police incident reports. The data is compiled by “EJustice”, a respected law enforcement records-management system used by the Montgomery County Police Department and many other law enforcement agencies. To protect victims’ privacy, no names or other personal information are released. All data is refreshed on a quarterly basis to reflect any changes in status due to on-going police investigation.

dataMontgomery allows the public to query the Montgomery County Police Department's database of founded crime. The information contained herein includes all founded crimes reported after July 1st 2016 and entered to-date utilizing Uniform Crime Reporting (UCR) rules. Please note that under UCR rules multiple offenses may appear as part of a single founded reported incident, and each offense may have multiple victims. Please note that these crime reports are based on preliminary information supplied to the Police Department by the reporting parties. Therefore, the crime data available on this web page may reflect:

-Information not yet verified by further investigation -Information that may include attempted and reported crime -Preliminary crime classifications that may be changed at a later date based upon further investigation -Information that may include mechanical or human error -Arrest information [Note: all arrested persons are presumed innocent until proven guilty in a court of law.]

Update Frequency: Daily

This dataset contains on street crimes provided by the Police via their API (https://data.police.uk/docs/). The data is clipped to the London Borough of Camden boundary, and can contain up to fifteen types of street crime including bicycle theft, shoplifting and criminal damage. The London Borough of Camden does not maintain the content of this dataset.

These data were collected to examine the relationships among crime rates, residents' attitudes, physical deterioration, and neighborhood structure in selected urban Baltimore neighborhoods. The data collection provides both block- and individual-level neighborhood data for two time periods, 1981-1982 and 1994. The block-level files (Parts 1-6) include information about physical conditions, land use, people counts, and crime rates. Parts 1-3, the block assessment files, contain researchers' observations of street layout, traffic, housing type, and general upkeep of the neighborhoods. Part 1, Block Assessments, 1981 and 1994, contains the researchers' observations of sampled blocks in 1981, plus selected variables from Part 3 that correspond to items observed in 1981. Nonsampled blocks (in Part 2) are areas where block assessments were done, but no interviews were conducted. The "people counts" file (Part 4) is an actual count of people seen by the researchers on the sampled blocks in 1994. Variables for this file include the number, gender, and approximate age of the people seen and the types of activities they were engaged in during the assessment. Part 5, Land Use Inventory for Sampled Blocks, 1994, is composed of variables describing the types of buildings in the neighborhood and their physical condition. Part 6, Crime Rates and Census Data for All Baltimore Neighborhoods, 1970-1992, includes crime rates from the Baltimore Police Department for aggravated assault, burglary, homicide, larceny, auto theft, rape, and robbery for 1970-1992, and census information from the 1970, 1980, and 1990 United States Censuses on the composition of the housing units and the age, gender, race, education, employment, and income of residents. The individual-level files (Parts 7-9) contain data from interviews with neighborhood leaders, as well as telephone surveys of residents. Part 7, Interviews with Neighborhood Leaders, 1994, includes assessments of the level of involvement in the community by the organization to which the leader belongs and the types of activities sponsored by the organization. The 1982 and 1994 surveys of residents (Parts 8 and 9) asked respondents about different aspects of their neighborhoods, such as physical appearance, problems, and crime and safety issues, as well as the respondents' level of satisfaction with and involvement in their neighborhoods. Demographic information on respondents, such as household size, length of residence, marital status, income, gender, and race, is also provided in this file.

This 2025 crime data is the list of calls for service that the Syracuse Police Department responded to in 2025. These records does not include rape offenses as well as any crimes that have been sealed by the court. These records are derived from the records management system utilized by the SPD. The data is then anonymized by SPD Crime Analysts weekly.After this data is received weekly from the SPD, this data is then mapped to the approximate location of that incident, using the 100 block level and a Geolocator File from Onondaga County GIS Department. This data is then updated on the Open Data Portal. The points should not be construed to be the exact point this incidents were reported to occur, rather the block where these incident is reported to occur.Crimes are reported to the FBI in two major categories under the Uniform Crime Reports specification: Part 1 and Part 2 crimes. Part 1 crimes include criminal homicide, forcible rape, robbery, aggravated assault, burglary, larceny-theft, and motor vehicle theft. In these records, rape offenses have been excluded due to victim privacy concerns.Part 2 crimes include all other offenses. A more detailed guide to Part 1 crimes is listed below. More details about Part 2 Crimes is listed in the Part 2 Crimes Dataset.When using the data, the date and time provided are when the crime was actually reported. This means that though a larceny might be reported at noon, the actual crime could have happened at 8am, but was not realized until someone noticed hours later. Similarly, if a home break-in happens during a holiday weekend when the owners are out of town, the crime report may not come in until they return home and notice the crime took place previously. The address in the dataset is where the crime occurred. The location is also anonymized to the block level, so a crime that occurred at 123 Main St. will appear as occurring on the 100 block of Main St. This is to protect the privacy of all involved. Finally, information about crimes is fluid, and details about the crime could change.Data DictionaryDate End -Date that the crime was reported. It could have happened earlier. This is in the format of DD-MON-YY (Ex. 01-Jan-22).Time start and time end -Listed in military time (2400) - Burglaries and larcenies are often a time frame.Address- Where the crime occurred. All addresses are in the 100’s because the Syracuse Police Department allows privacy for residents and only lists the block number.Code Defined-Offense names are listed as crime categories group for ease of understanding. There may have been other offenses also, but the one displayed is the highest Unified Crime Reporting (UCR) category.Arrest- Means that there was an arrest, but not necessarily for that crime.Larceny Code- Indicates the type of larceny (Example: From Building or From Motor Vehicle).LAT - The approximate latitude (not actual) that this call for service occurred.LONG- The approximate latitude (not actual) that this call for service occurred.DisclaimerData derived from the Syracuse Police Department record management system, any data not listed is not currently available.Part I Crime DefinitionsCriminal homicide—a.) Murder and non-negligent manslaughter: the willful (non-negligent) killing of one human being by another. Deaths caused by negligence, attempts to kill, assaults to kill, suicides, and accidental deaths are excluded. The program classifies justifiable homicides separately and limits the definition to: (1) the killing of a felon by a law enforcement officer in the line of duty; or (2) the killing of a felon, during the commission of a felony, by a private citizen. b.) Manslaughter by negligence: the killing of another person through gross negligence. Deaths of persons due to their own negligence, accidental deaths not resulting from gross negligence, and traffic fatalities are not included in the category Manslaughter by Negligence.Robbery—The taking or attempting to take anything of value from the care, custody, or control of a person or persons by force or threat of force or violence and/or by putting the victim in fear.Aggravated assault—An unlawful attack by one person upon another for the purpose of inflicting severe or aggravated bodily injury. This type of assault usually is accompanied by the use of a weapon or by means likely to produce death or great bodily harm. Simple assaults are excluded.Burglary(breaking or entering)—The unlawful entry of a structure to commit a felony or a theft. Attempted forcible entry is included.Larceny-theft (except motor vehicle theft)—The unlawful taking, carrying, leading, or riding away of property from the possession or constructive possession of another. Examples are thefts of bicycles, motor vehicle parts and accessories, shoplifting, pocket picking, or the stealing of any property or article that is not taken by force and violence or by fraud. Attempted larcenies are included. Embezzlement, confidence games, forgery, check fraud, etc., are excluded.Motor vehicle theft—The theft or attempted theft of a motor vehicle. A motor vehicle is self-propelled and runs on land surface and not on rails. Motorboats, construction equipment, airplanes, and farming equipment are specifically excluded from this category.Dataset Contact Information:Organization: Syracuse Police Department (SPD)Position: Data Program ManagerCity: Syracuse, NYE-Mail Address: opendata@syrgov.net

Crime is a significant social, economic, and legal issue. This paper presents an open-access spatiotemporal repository of street and neighborhood crime data, comprising approximately one million records of crimes in China, with specific geographic coordinates (latitude and longitude) and timestamps for each incident. The dataset is based on publicly available law court judgment documents. Artificial intelligence (AI) technologies are employed to extract crime events at the neighborhood or even building level from vast amounts of unstructured judicial text. This dataset enables more precise spatial analysis of crime incidents, offering valuable insights across interdisciplinary fields such as economics, sociology, and geography. It contributes significantly to the achievement of the United Nations Sustainable Development Goals (SDGs), particularly in fostering sustainable cities and communities, and plays a crucial role in advancing efforts to reduce all forms of violence and related mortality rates.

Historical dataset showing St. Martin (French part) crime rate per 100K population by year from 2011 to 2016.

Web app displaying 2021-YTD NIBRS crime data. Data is included for all areas that the St. Louis County Police Department and the St. Louis County Park Rangers patrol. Additionally, data is included for the following police departments in St. Louis County: Ballwin, Bel Nor, Bel Ridge, Bella Villa, Bellefontaine Neighbors, Breckenridge Hills, Brentwood, Bridgeton, Country Club Hills, Chesterfield, Clayton, Crestwood, Creve Coeur, Des Peres, Ellisville, Eureka, Frontenac, Hillsdale, Kirkwood, Ladue, Lakeshire, Moline Acres, Maplewood, Normandy, Olivette, Overland, Pagedale, Riverview, Richmond Heights, Rock Hill, Saint Louis County, Shrewsbury, St. John, Sunset Hills, Town & Country, Velda City, Webster Groves, and Woodson Terrace.The data in this map should not be compared to previous UCR Part 1 crime data provided by the department. NIBRS data is counted differently, and comparisons made between the data will not be accurate.

Crime data and neighbourhood policing information from all forces in England and Wales to the Public. This data is what is behind the police.uk website.

The Police API allows you to retrieve information about neighbourhood areas in all 43 English & Welsh police forces. All forces are required to keep this data accurate and up to date, so the API provides a rich and definitive data source for crime statistics at both street and neighourhood level.

The API is implemented as a standard XML REST web service using HTTP GET/POST requests.

The monthly data dumps can be downloaded using URLs structured consistently in the following format: https://data.police.uk/data/archive/[year]-[month].zip However because the data file is over 19 million rows, we also provide Custom CSV Download and JSON API helper interfaces so you can easily access subsets of the data. Generally, we recommend working with one of these interfaces instead of the full data dump.

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

*This dataset is updated nightly. Crime data represents the initial information that is provided by individuals calling for police assistance. Please note that the dataset only contains the last 5 years. Remaining information is often amended for accuracy after an Officer arrives and investigates the reported incident. Most often, the changes are made to more accurately reflect the official legal definition of the crimes reported. An example of this is for someone to report that they have been "robbed," when their home was broken into while they were away. The official definition of "robbery" is to take something by force. An unoccupied home being broken into, is actually defined as a "burglary," or a "breaking and entering." While there are mechanisms in place to make each initial call as accurate as possible, some events require evaluation upon arrival. Caution should be used when making assumptions based solely on the data provided, as they may not represent the official crime reports.