This dataset contains county-level totals for the years 2002-2014 for eight types of crime: murder, rape, robbery, aggravated assault, burglary, larceny, motor vehicle theft, and arson. These crimes are classed as Part I criminal offenses by the United States Federal Bureau of Investigations (FBI) in their Uniform Crime Reporting (UCR) program. Each record in the dataset represents the total of each type of criminal offense reported in (or, in the case of missing data, attributed to) the county in a given year.

Serious violent crimes consist of Part 1 offenses as defined by the U.S. Department of Justice’s Uniform Reporting Statistics. These include murders, nonnegligent homicides, rapes (legacy and revised), robberies, and aggravated assaults. LAPD data were used for City of Los Angeles, LASD data were used for unincorporated areas and cities that contract with LASD for law enforcement services, and CA Attorney General data were used for all other cities with local police departments. This indicator is based on location of residence. Single-year data are only available for Los Angeles County overall, Service Planning Areas, Supervisorial Districts, City of Los Angeles overall, and City of Los Angeles Council Districts.Neighborhood violence and crime can have a harmful impact on all members of a community. Living in communities with high rates of violence and crime not only exposes residents to a greater personal risk of injury or death, but it can also render individuals more susceptible to many adverse health outcomes. People who are regularly exposed to violence and crime are more likely to suffer from chronic stress, depression, anxiety, and other mental health conditions. They are also less likely to be able to use their parks and neighborhoods for recreation and physical activity.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. The study integrated neighborhood-level data on robbery and burglary gathered from local police agencies across the United States, foreclosure data from RealtyTrac (a real estate information company), and a wide variety of social, economic, and demographic control variables from multiple sources. Using census tracts to approximate neighborhoods, the study regressed 2009 neighborhood robbery and burglary rates on foreclosure rates measured for 2007-2008 (a period during which foreclosure spiked dramatically in the nation), while accounting for 2007 robbery and burglary rates and other control variables that captured differences in social, economic, and demographic context across American neighborhoods and cities for this period. The analysis was based on more than 7,200 census tracts in over 60 large cities spread across 29 states. Core research questions were addressed with a series of multivariate multilevel and single-level regression models that accounted for the skewed nature of neighborhood crime patterns and the well-documented spatial dependence of crime. The study contains one data file with 8,198 cases and 99 variables.

The Part 1 crime rate captures incidents of homicide, rape, aggravated assault, robbery, burglary, larceny, and auto theft that are reported to the Police Department. These incidents are per 1,000 residents in the neighborhood to allow for comparison across areas. Source: Baltimore Police Department Years Available: 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023

Toronto Neighbourhoods Boundary File includes Crime Data by Neighbourhood. Counts are available at the offence and/or victim level for Assault, Auto Theft, Bike Theft, Break and Enter, Robbery, Theft Over, Homicide, Shootings and Theft from Motor Vehicle. Data also includes crime rates per 100,000 people by neighbourhood based on each year's Projected Population by Environics Analytics.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.

The primary purpose of the second wave of the National Neighborhood Crime Study (NNCS2) was to develop a panel dataset of serious reported crimes in urban neighborhoods circa two time points - 2000 and 2010. These data offer the opportunity to assess the sources and consequences of neighborhood crime change for "communities" of different ethno-racial and economic compositions across the United States. The study also sought to examine the role of a neighborhood's broader ecology on crime levels and crime change by integrating indicators of city and/or metropolitan conditions. The NNCS2 includes two datasets. The first dataset, the NNCS2-Panel file (NNCS2-P), contains information on the Federal Bureau of Investigation's (FBI) Part 1 Index crimes (except arson), socioeconomic and demographic characteristics, and a variety of other neighborhood and city level controls for circa 2000 and 2010 for tracts in 81 of the 91 cities in the NNCS, wave 1. The second dataset, the NNCS2-Cross-Sectional file (NNCS2-CS), allows for examination of the local and contextual sources of neighborhood crime inequality circa 2010. The NNCS2-CS incorporates parallel data for census tracts and cities as in the Panel file, but includes a few additional cities for which panel data could not be compiled, as well information on the metropolitan areas within which cities are located.

In February 2019, we updated the neighborhood assignment with regards to the new police record system.

The data set is refreshed on the third day of the month at 8:45 AM. The website will reflect the last time the data set was updated and the total count of rows. The grid on the “Data” tab will display the up to date data. However, in certain situations there is a delay in the refresh of the downloadable data file. Sometimes the downloadable file does not reflect the updates to the data in the portal. After a delay (duration has been variable; up to 30 minutes), the file will be updated on the server and then downloads will include the updated data.

This study explores the relationship between crime and neighborhood deterioration in eight neighborhoods in Chicago. The neighborhoods were selected on the basis of slowly or rapidly appreciating real estate values, stable or changing racial composition, and high or low crime rates. These data provide the results of a telephone survey administered to approximately 400 heads of households in each study neighborhood, a total of 3,310 completed interviews. The survey was designed to measure victimization experience, fear and perceptions of crime, protective measures taken, attitudes toward neighborhood quality and resources, attitudes toward the neighborhood as an investment, and density of community involvement. Each record includes appearance ratings for the block of the respondent's residence and aggregate figures on personal and property victimization for that city block. The aggregate appearance ratings were compiled from windshield surveys taken by trained personnel of the National Opinion Research Center. The criminal victimization figures came from Chicago City Police files.

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 map shows a comparable measure of crime in the United States. The crime index compares the average local crime level to that of the United States as a whole. An index of 100 is average. A crime index of 120 indicates that crime in that area is 20 percent above the national average.The crime data is provided by Applied Geographic Solutions, Inc. (AGS). AGS created models using the FBI Uniform Crime Report databases as the primary data source and using an initial range of about 65 socio-economic characteristics taken from the 2000 Census and AGS’ current year estimates. The crimes included in the models include murder, rape, robbery, assault, burglary, theft, and motor vehicle theft. The total crime index incorporates all crimes and provides a useful measure of the relative “overall” crime rate in an area. However, these are unweighted indexes, meaning that a murder is weighted no more heavily than a purse snatching in the computations. The geography depicts states, counties, Census tracts and Census block groups. An urban/rural "mask" layer helps you identify crime patterns in rural and urban settings. The Census tracts and block groups help identify neighborhood-level variation in the crime data.------------------------The Civic Analytics Network collaborates on shared projects that advance the use of data visualization and predictive analytics in solving important urban problems related to economic opportunity, poverty reduction, and addressing the root causes of social problems of equity and opportunity. For more information see About the Civil Analytics Network.

All crime data for Vital Signs indicators are provided by the Baltimore City Police Department. BNIA-JFI normalizes this data by population to establish crime rates. Normalizing data allows for the rates to reflect the concentration of the crime relative to the population in the area and allows for comparison between areas of different populations.

The property crime rate measures the number of Part 1 crimes identified as being property-based (burglary and auto theft) that are reported to the Police Department. These incidents are per 1,000 residents in the neighborhood to allow for comparison across areas. Source: Baltimore Police Department Years Availabile: 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023

This table contains figures on the number of registered crimes per month and per year. These are broken down by type of crime and by district and neighbourhood. Attempts are also included in the recorded crimes. For some crimes (e.g. murder/homicide), this results in a much higher number than just the number of completed crimes. The data per district and neighbourhood are presented for all years according to the classification of 1 January 2024.

Since July 2018, it is no longer possible to record multiple offences, which are related to each other (concurrence), in one registration. An example of this is a street robbery in which a firearm (gun possession) is used. If several offences occur in one registration, only the most serious offence was counted before July 2018. As a result of this adjustment, a number of offences show an increase compared to 2018. This mainly concerns trespassing, special laws including money laundering, arms trafficking including possession of weapons, drug trafficking, violation of public order and other social integrity including insults. The increase was therefore mainly visible in the last 6 months of 2018. This adjustment has only a limited impact on the total number of crimes. For the whole of 2018, this causes an increase of approximately 1.0%. Since 30 April 2020, it is possible to report WhatsApp fraud via the Internet (also known as friend-in-emergency fraud). This was immediately used extensively. In the months of May to December 2020, approximately 20,000 reports of WhatsApp fraud were made.

The number of registered crimes fireworks 2023 is not final. In the first half of 2024, many incidents with retroactive effect will still be classified as a criminal offence and included in the census.

Declarations concern registered crimes for which a Pv of declarations has been drawn up. Several reports can be made per crime. Internet reporting can only be done for a selected number of offences and only if there is no detection indication.

Data available from: 2012

Status of figures: The figures in this table are regularly updated. This may result in minor differences with previous publications. Updating the figures is necessary, for example, in order to be able to retroactively process the reclassification of municipalities or the adjustment of coding.

Changes as of 15 November 2024: Figures for October have been added.

When will there be new figures? The figures for November are added on 16 December.

Data is no longer provided by the Calgary Police Service. To access latest data click here. This data is considered cumulative as late-reported incidents are often received well after an offence has occurred. Therefore, crime counts are subject to change as they are updated. Crime count is based on the most serious violation (MSV) per incident. Violence: These figures include all violent crime offences as defined by the Centre for Canadian Justice Statistics Universal Crime Reporting (UCR) rules. Domestic violence is excluded. Break and Enter: Residential B&E includes both House and ‘Other’ structure break and enters due to the predominantly residential nature of this type of break in (e.g. detached garages, sheds). B&Es incidents include attempts.

In 2023, around 3,640.56 violent crimes per 100,000 residents were reported in Oakland, California. This made Oakland the most dangerous city in the United States in that year. Four categories of violent crimes were used: murder and non-negligent manslaughter; forcible rape; robbery; and aggravated assault. Only cities with a population of at least 200,000 were considered.

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.

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.citation: Zhang Y, Kwan M P, Fang L. An LLM driven dataset on the spatiotemporal distributions of street and neighborhood crime in China[J]. Scientific Data, 2025, 12(1): 467.关于该数据的问题可以访问我的个人网站获取我的联系方式：https://www.giserzhang.xyz/

This table contains figures on property, destruction and public order and violent crimes recorded by the police. In addition to absolute numbers, some types of crime include the numbers per 1000 inhabitants. The figures are broken down by municipality of committing, neighborhood and neighborhood. Crimes whose foster location cannot be attributed to a neighborhood are not counted in this table.

Data available on: 2018

Status of the figures: The figures are final.

Amendments as of 18 February 2021: None, this table has been discontinued.

When will there be new figures? No longer applicable.

Criminality rates per neighborhood can be found on the Police Data Portal. See paragraph 3.

This dataset reflects reported incidents of crime (with the exception of murders where data exists for each victim) that occurred in the City of Chicago from 2001 to present, minus the most recent seven days. Data is extracted from the Chicago Police Department's CLEAR (Citizen Law Enforcement Analysis and Reporting) system. In order to protect the privacy of crime victims, addresses are shown at the block level only and specific locations are not identified. Should you have questions about this dataset, you may contact the Research & Development Division of the Chicago Police Department at 312.745.6071 or RandD@chicagopolice.org. Disclaimer: These crimes may be based upon preliminary information supplied to the Police Department by the reporting parties that have not been verified. The preliminary crime classifications may be changed at a later date based upon additional investigation and there is always the possibility of mechanical or human error. Therefore, the Chicago Police Department does not guarantee (either expressed or implied) the accuracy, completeness, timeliness, or correct sequencing of the information and the information should not be used for comparison purposes over time. The Chicago Police Department will not be responsible for any error or omission, or for the use of, or the results obtained from the use of this information. All data visualizations on maps should be considered approximate and attempts to derive specific addresses are strictly prohibited. The Chicago Police Department is not responsible for the content of any off-site pages that are referenced by or that reference this web page other than an official City of Chicago or Chicago Police Department web page. The user specifically acknowledges that the Chicago Police Department is not responsible for any defamatory, offensive, misleading, or illegal conduct of other users, links, or third parties and that the risk of injury from the foregoing rests entirely with the user. The unauthorized use of the words "Chicago Police Department," "Chicago Police," or any colorable imitation of these words or the unauthorized use of the Chicago Police Department logo is unlawful. This web page does not, in any way, authorize such use. Data is updated daily Tuesday through Sunday. The dataset contains more than 65,000 records/rows of data and cannot be viewed in full in Microsoft Excel. Therefore, when downloading the file, select CSV from the Export menu. Open the file in an ASCII text editor, such as Wordpad, to view and search. To access a list of Chicago Police Department - Illinois Uniform Crime Reporting (IUCR) codes, go to http://data.cityofchicago.org/Public-Safety/Chicago-Police-Department-Illinois-Uniform-Crime-R/c7ck-438e

In 2020, the number of robberies known to law enforcement in suburban areas in the United States amounted to 43,096 cases. There were more than 1.8 million property crimes known to law enforcement in suburban areas in that year.