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 2024.

Number and rate (per 100,000 population) of homicide victims, Canada and Census Metropolitan Areas, 1981 to 2024.

GapMaps offers advanced and reliable Crime Risk Location Data sourced from Applied Geographic Solutions (AGS), a trusted provider of premium demographic insights with over 20 years of experience. Leveraged by thousands of businesses, AGS use advanced statistical methodologies and a rolling seven-year database of FBI and local agency statistics to provide a highly accurate view of the relative risk of specific crime types for any geographic area empowering organizations to make informed decisions in areas such as insurance, urban planning, and real estate.

The AGS Crime Risk dataset includes: - Standardised indexes for a range of serious crimes against both persons and property such as murder, rape, robbery, assault, burglary, theft, and motor vehicle theft - Aggregate measures of crime risk, including crimes against persons, crimes against property, and overall crime risk, offering a comprehensive overview of an area’s safety. - 5-Year Projections: Added in 2020, these projections enhance the dataset by forecasting future crime risks, providing valuable insights for long-term planning. - High-Resolution Data: Crime risk indexes are available at the block group level, allowing insurers to identify variations in crime risk across specific land uses such as motor vehicle theft from parking structures.

Use cases: 1. Insurance underwriting and risk mitigation. 2. Evaluating the security measures needed to protect employees and customers at retail facilities. 3. The study of the effects of neighborhood crime on wellness and health care outcomes.

Methodology: Crime is tracked for multiple years using both FBI aggregate crime reports and for many parts of the country at the individual incident level. A complex set of statistical models are used to estimate and forecast risk of each individual crime type by using land use data in conjunction with demographic and business characteristics.

GapMaps offers an advanced and reliable Crime Risk dataset sourced from Applied Geographic Solutions (AGS), a trusted provider of premium demographic insights with over 20 years of experience. Leveraged by thousands of businesses, AGS use advanced statistical methodologies and a rolling seven-year database of FBI and local agency statistics to provide a highly accurate view of the relative risk of specific crime types for any geographic area empowering organizations to make informed decisions in areas such as insurance, urban planning, and real estate.

The AGS Crime Risk dataset includes: - Standardised indexes for a range of serious crimes against both persons and property such as murder, rape, robbery, assault, burglary, theft, and motor vehicle theft - Aggregate measures of crime risk, including crimes against persons, crimes against property, and overall crime risk, offering a comprehensive overview of an area’s safety. - 5-Year Projections: Added in 2020, these projections enhance the dataset by forecasting future crime risks, providing valuable insights for long-term planning. - High-Resolution Data: Crime risk indexes are available at the block group level, allowing insurers to identify variations in crime risk across specific land uses such as motor vehicle theft from parking structures.

Use cases for Crime Risk data in Insurance include: 1) Help determine the likelihood of policyholders filing claims. This information allows them to price policies appropriately. Higher crime risk areas typically result in higher premiums to account for the increased likelihood of claims. 2) Provide recommendations for loss prevention measures based on crime risk assessments. This could include installing security systems, using better lighting, or employing security personnel. Effective loss prevention can reduce the frequency and severity of claims. 3) Insurance underwriters can establish sufficient premiums to cover potential claims. Misjudging crime risk could lead to financial losses if claims exceed the collected premiums. This stability is essential for the insurer's long-term viability. 4) Offer competitive premiums while maintaining profitability. This can attract more customers and increase market share.

Methodology: The primary source of CrimeRisk is a careful compilation and analysis of the FBI Uniform Crime Report databases. On an annual basis, the FBI collects data from each of about 16,000 separate law enforcement jurisdictions at the city, county, and state levels and compiles these into its annual Uniform Crime Report (UCR). While useful, the UCR provides detailed data only for the largest cities, counties, and metropolitan areas. A complex set of statistical models are used to estimate and forecast risk of each individual crime type by using land use data in conjunction with demographic and business characteristics.

There has been little research on United States homicide rates from a long-term perspective, primarily because there has been no consistent data series on a particular place preceding the Uniform Crime Reports (UCR), which began its first full year in 1931. To fill this research gap, this project created a data series on homicides per capita for New York City that spans two centuries. The goal was to create a site-specific, individual-based data series that could be used to examine major social shifts related to homicide, such as mass immigration, urban growth, war, demographic changes, and changes in laws. Data were also gathered on various other sites, particularly in England, to allow for comparisons on important issues, such as the post-World War II wave of violence. The basic approach to the data collection was to obtain the best possible estimate of annual counts and the most complete information on individual homicides. The annual count data (Parts 1 and 3) were derived from multiple sources, including the Federal Bureau of Investigation's Uniform Crime Reports and Supplementary Homicide Reports, as well as other official counts from the New York City Police Department and the City Inspector in the early 19th century. The data include a combined count of murder and manslaughter because charge bargaining often blurs this legal distinction. The individual-level data (Part 2) were drawn from coroners' indictments held by the New York City Municipal Archives, and from daily newspapers. Duplication was avoided by keeping a record for each victim. The estimation technique known as "capture-recapture" was used to estimate homicides not listed in either source. Part 1 variables include counts of New York City homicides, arrests, and convictions, as well as the homicide rate, race or ethnicity and gender of victims, type of weapon used, and source of data. Part 2 includes the date of the murder, the age, sex, and race of the offender and victim, and whether the case led to an arrest, trial, conviction, execution, or pardon. Part 3 contains annual homicide counts and rates for various comparison sites including Liverpool, London, Kent, Canada, Baltimore, Los Angeles, Seattle, and San Francisco.

Victims of gang-related homicides (total number of homicide victims; number of homicide victims - unknown gang-relation; number of homicide victims - known gang relation; number of gang-related homicide victims; percentage of gang-related homicide victims; rate (per 100,000 population) of gang-related homicide victims), Canada and regions, 1999 to 2024.

This dataset includes all Major Crime Indicators (MCI) occurrences by reported date and related offences since 2014.Major Crime Indicators DashboardDownload DocumentationThe Major Crime Indicators categories include Assault, Break and Enter, Auto Theft, Robbery and Theft Over (Excludes Sexual Violations). This data is provided at the offence and/or victim level, therefore one occurrence number may have several rows of data associated to the various MCIs used to categorize the occurrence.The downloadable datasets display the REPORT_DATE and OCC_DATE fields in UTC timezone.This data does not include occurrences that have been deemed unfounded. The definition of unfounded according to Statistics Canada is: “It has been determined through police investigation that the offence reported did not occur, nor was it attempted” (Statistics Canada, 2020).**The dataset is intended to provide communities with information regarding public safety and awareness. The data supplied to the Toronto Police Service by the reporting parties is preliminary and may not have been fully verified at the time of publishing the dataset. The location of crime occurrences have been deliberately offset to the nearest road intersection node to protect the privacy of parties involved in the occurrence. All location data must be considered as an approximate location of the occurrence and users are advised not to interpret any of these locations as related to a specific address or individual.NOTE: Due to the offset of occurrence location, the numbers by Division and Neighbourhood may not reflect the exact count of occurrences reported within these geographies. Therefore, the Toronto Police Service does not guarantee the accuracy, completeness, timeliness of the data and it should not be compared to any other source of crime data.By accessing these datasets, the user agrees to full acknowledgement of the Open Government Licence - Ontario.In accordance with the Municipal Freedom of Information and Protection of Privacy Act, the Toronto Police Service has taken the necessary measures to protect the privacy of individuals involved in the reported occurrences. No personal information related to any of the parties involved in the occurrence will be released as open data. ** Statistics Canada. 2020. Uniform Crime Reporting Manual. Surveys and Statistical Programs. Canadian Centre for Justice Statistics.

Number and percentage of homicide victims, by type of firearm used to commit the homicide (total firearms; handgun; rifle or shotgun; fully automatic firearm; sawed-off rifle or shotgun; firearm-like weapons; other firearms, type unknown), Canada, 1974 to 2018.

Number of homicide victims, by method used to commit the homicide (total methods used; shooting; stabbing; beating; strangulation; fire (burns or suffocation); other methods used; methods used unknown), Canada, 1974 to 2024.