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

This project's main goal was to develop an analytical framework that could be used for analysis of rare crimes observed at local (intra-city) levels of geographic aggregation. To demonstrate the application of this framework to a real-world issue, this project analyzed the occurrence of different types of homicide at both the census tract and neighborhood cluster level in Chicago. Homicide counts for Chicago's 865 census tracts for 1989-1991 were obtained from HOMICIDES IN CHICAGO, 1965-1995 (ICPSR 6399), Part 1: Victim Level Data. The types of homicide examined were gang-related, instrumental, family-related expressive, known person expressive, stranger expressive, and other. Demographic and socioeconomic data at the census tract level for the year 1990 were obtained from the Neighborhood Change Database (NCDB) at the Urban Institute. Part 1 contains these data, as initially obtained, at the census tract level. Part 2 contains an aggregated version of the same data for Chicago's 343 neighborhood clusters as defined by the Project on Human Development in Chicago's Neighborhoods.

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.

The purpose of the study was to examine homicide trends in Chicago neighborhoods from 1980-2000 using HOMICIDES IN CHICAGO, 1965-1995 (ICPSR 6399), 1980-2000 Census data, and PROJECT ON HUMAN DEVELOPMENT IN CHICAGO NEIGHBORHOODS: COMMUNITY SURVEY, 1994-1995 (ICPSR 2766). Drawing on the social disorganization and concentrated disadvantage literature, this study used growth-curve modeling and semi-parametric group-based trajectory modeling to: (1) assess neighborhood variation in homicide trends; (2) identify the particular types of homicide trajectory that Chicago neighborhoods follow; (3) assess whether structural characteristics of neighborhoods influence homicide trends and trajectories; and (4) determine the extent to which the influence of structural characteristics is mediated by neighborhood levels of collective efficacy. This project extended prior research by not only describing the homicide trends and trajectories of Chicago neighborhoods, but also identifying the neighborhood characteristics that directly and indirectly influence those trends.

This dataset contains individual-level homicide and non-fatal shooting victimizations, including homicide data from 1991 to the present, and non-fatal shooting data from 2010 to the present (2010 is the earliest available year for shooting data). This dataset includes a "GUNSHOT_INJURY_I " column to indicate whether the victimization involved a shooting, showing either Yes ("Y"), No ("N"), or Unknown ("UKNOWN.") For homicides, injury descriptions are available dating back to 1991, so the "shooting" column will read either "Y" or "N" to indicate whether the homicide was a fatal shooting or not. For non-fatal shootings, data is only available as of 2010. As a result, for any non-fatal shootings that occurred from 2010 to the present, the shooting column will read as “Y.” Non-fatal shooting victims will not be included in this dataset prior to 2010; they will be included in the authorized-access dataset, but with "UNKNOWN" in the shooting column.

Each row represents a single victimization, i.e., a unique event when an individual became the victim of a homicide or non-fatal shooting. Each row does not represent a unique victim—if someone is victimized multiple times there will be multiple rows for each of those distinct events.

The dataset is refreshed daily, but excludes the most recent complete day to allow the Chicago Police Department (CPD) time to gather the best available information. Each time the dataset is refreshed, records can change as CPD learns more about each victimization, especially those victimizations that are most recent. The data on the Mayor's Office Violence Reduction Dashboard is updated daily with an approximately 48-hour lag. As cases are passed from the initial reporting officer to the investigating detectives, some recorded data about incidents and victimizations may change once additional information arises. Regularly updated datasets on the City's public portal may change to reflect new or corrected information.

A version of this dataset with additional crime types is available by request. To make a request, please email dataportal@cityofchicago.org with the subject line: Violence Reduction Victims Access Request. Access will require an account on this site, which you may create at https://data.cityofchicago.org/signup.

How does this dataset classify victims?

The methodology by which this dataset classifies victims of violent crime differs by victimization type:

Homicide and non-fatal shooting victims: A victimization is considered a homicide victimization or non-fatal shooting victimization depending on its presence in CPD's homicide victims data table or its shooting victims data table. A victimization is considered a homicide only if it is present in CPD's homicide data table, while a victimization is considered a non-fatal shooting only if it is present in CPD's shooting data tables and absent from CPD's homicide data table.

To determine the IUCR code of homicide and non-fatal shooting victimizations, we defer to the incident IUCR code available in CPD's Crimes, 2001-present dataset (available on the City's open data portal). If the IUCR code in CPD's Crimes dataset is inconsistent with the homicide/non-fatal shooting categorization, we defer to CPD's Victims dataset. For a criminal homicide, the only sensible IUCR codes are 0110 (first-degree murder) or 0130 (second-degree murder). For a non-fatal shooting, a sensible IUCR code must signify a criminal sexual assault, a robbery, or, most commonly, an aggravated battery. In rare instances, the IUCR code in CPD's Crimes and Victims dataset do not align with the homicide/non-fatal shooting categorization:

1. In instances where a homicide victimization does not correspond to an IUCR code 0110 or 0130, we set the IUCR code to "01XX" to indicate that the victimization was a homicide but we do not know whether it was a first-degree murder (IUCR code = 0110) or a second-degree murder (IUCR code = 0130).
2. When a non-fatal shooting victimization does not correspond to an IUCR code that signifies a criminal sexual assault, robbery, or aggravated battery, we enter “UNK” in the IUCR column, “YES” in the GUNSHOT_I column, and “NON-FATAL” in the PRIMARY column to indicate that the victim was non-fatally shot, but the precise IUCR code is unknown.

Other violent crime victims: For other violent crime types, we refer to the IUCR classification that exists in CPD's victim table, with only one exception:

1. When there is an incident that is associated with no victim with a matching IUCR code, we assume that this is an error. Every crime should have at least 1 victim with a matching IUCR code. In these cases, we change the IUCR code to reflect the incident IUCR code because CPD's incident table is considered to be more reliable than the victim table.

Note: The definition of “homicide” (shooting or otherwise) does not include justifiable homicide or involuntary manslaughter. This dataset also excludes any cases that CPD considers to be “unfounded” or “noncriminal.” Officer-involved shootings are not included.

Note: The initial reporting officer usually asks victims to report demographic data. If victims are unable to recall, the reporting officer will use their best judgment. “Unknown” can be reported if it is truly unknown.

Note: In some instances, CPD's raw incident-level data and victim-level data that were inputs into this dataset do not align on the type of crime that occurred. In those instances, this dataset attempts to correct mismatches between incident and victim specific crime types. When it is not possible to determine which victims are associated with the most reliable crime determination, the dataset will show empty cells in the respective demographic fields (age, sex, race, etc.).

Note: Homicide victims names are delayed by two weeks to allow time for the victim’s family to be notified of their passing.

Note: The initial reporting officer usually asks victims to report demographic data. If victims are unable to recall, the reporting officer will use their best judgment. “Unknown” can be reported if it is truly unknown.

Note: This dataset includes variables referencing administrative or political boundaries that are subject to change. These include Street Outreach Organization boundary, Ward, Chicago Police Department District, Chicago Police Department Area, Chicago Police Department Beat, Illinois State Senate District, and Illinois State House of Representatives District. These variables reflect current geographic boundaries as of November 1st, 2021. In some instances, current boundaries may conflict with those that were in place at the time that a given incident occurred in prior years. For example, the Chicago Police Department districts 021 and 013 no longer exist. Any historical violent crime victimization that occurred in those districts when they were in existence are marked in this dataset as having occurred in the current districts that expanded to replace 013 and 021."

The overall goal of this study was to acquire a greater understanding of the development of adolescent antisocial behavior using data from the Project on Human Development in Chicago Neighborhoods (PHDCN). Longitudinal cohort data from PHDCN were analyzed to assess patterns of substance use and delinquency across three waves for three age cohorts and 78 neighborhoods. This analysis of existing PHDCN data used multiple cohort and multilevel latent growth models as well as several ancillary approaches to answer questions pertinent to the development of adolescent antisocial behavior.

The Project on Human Development in Chicago Neighborhoods (PHDCN) is a large-scale, interdisciplinary study of how families, schools, and neighborhoods affect child and adolescent development. The crosswalk file contains census tract to neighborhood cluster level data, enabling researchers to merge and aggregate additional crime and census data with the PHDCN data. Access to these data is restricted. Users must provide justification for their request to access the crosswalk file, as well as a description of any datasets they plan to link to the PHDCN data.

This data collection was designed to evaluate the effects of disorderly neighborhood conditions on community decline and residents' reactions toward crime. Data from five previously collected datasets were aggregated and merged to produce this collection: (1) REACTIONS TO CRIME PROJECT, 1977 [CHICAGO, PHILADELPHIA, SAN FRANCISCO]: SURVEY ON FEAR OF CRIME AND CITIZEN BEHAVIOR (ICPSR 8162), (2) CHARACTERISTICS OF HIGH AND LOW CRIME NEIGHBORHOODS IN ATLANTA, 1980 (ICPSR 8951), (3) CRIME FACTORS AND NEIGHBORHOOD DECLINE IN CHICAGO, 1979 (ICPSR 7952), (4) REDUCING FEAR OF CRIME PROGRAM EVALUATION SURVEYS IN NEWARK AND HOUSTON, 1983-1984 (ICPSR 8496), and (5) a survey of citizen participation in crime prevention in six Chicago neighborhoods conducted by Rosenbaum, Lewis, and Grant. Neighborhood-level data cover topics such as disorder, crime, fear, residential satisfaction, and other key factors in community decline. Variables include disorder characteristics such as loitering, drugs, vandalism, noise, and gang activity, demographic characteristics such as race, age, and unemployment rate, and neighborhood crime problems such as burglary, robbery, assault, and rape. Information is also available on crime avoidance behaviors, fear of crime on an aggregated scale, neighborhood satisfaction on an aggregated scale, and cohesion and social interaction.

The National Crime Victimization Survey (NCVS), previously called the National Crime Survey (NCS), has been collecting data on personal and household victimization through an ongoing survey of a nationally-representative sample of residential addresses since 1973. The NCVS was designed with four primary objectives: (1) to develop detailed information about the victims and consequences of crime, (2) to estimate the number and types of crimes not reported to the police, (3) to provide uniform measures of selected types of crimes, and (4) to permit comparisons over time and types of areas. Beginning in 1992, the survey categorizes crimes as "personal" or "property." Personal crimes include rape and sexual assault, robbery, aggravated and simple assault, and purse-snatching/pocket-picking, while property crimes include burglary, theft, motor vehicle theft, and vandalism. Each respondent is asked a series of screen questions designed to determine whether she or he was victimized during the six-month period preceding the first day of the month of the interview. A "household respondent" is also asked to report on crimes against the household as a whole (e.g., burglary, motor vehicle theft). The data include type of crime, month, time, and location of the crime, relationship between victim and offender, characteristics of the offender, self-protective actions taken by the victim during the incident and results of those actions, consequences of the victimization, type of property lost, whether the crime was reported to police and reasons for reporting or not reporting, and offender use of weapons, drugs, and alcohol. Basic demographic information such as age, race, gender, and income is also collected, to enable analysis of crime by various subpopulations. This dataset represents the concatenated version of the NCVS on a collection year basis for 1992-2022. A collection year contains records from interviews conducted in the 12 months of the given year. Under the collection year format, victimizations are counted in the year the interview is conducted, regardless of the year when the crime incident occurred.For additional information on the dataset, please see the documentation for the data from the most current year of the NCVS, ICPSR Study 38603.

Beginning in 1993, the Chicago Police Department has been committed to implementing a comprehensive community policing strategy – CAPS – that is designed to make residents an active partner in preventing and reducing crime in all of Chicago’s neighborhoods. That strategy recognizes that police, residents and other neighborhood stakeholders, and other City agencies must work together to address all the conditions that can lead to crime. No one stands alone; each of us has a role to play in improving the quality of life in our communities.This application shows upcoming community engagement events. The map can be filtered by type, timeframe and several other geographies like District & Ward.

Despite much recent attention devoted to understanding the ramifications of residential mobility, especially negative consequences for youth, there is scant research exploring how inner-city mobility impacts youth violence and victimization among minorities and immigrants. Leaving the city imparts benefits: decreasing deviance and improving youth outcomes. Considering that many are unable to "escape" the city, clarifying what effects, if any, inner-city mobility has is critical. Destination neighborhoods for youth who move in the city are either contextually the same, better, or worse than their original neighborhood. Evidence suggests that immigrant families are more likely to move as are racial minorities. Because of this, the researchers examined the extent to which moving within a city affects minority and immigrant youth experiences, particularly in relation to changes in neighborhood collective efficacy; a major characteristic shaping community crime rates and youth violence. This project involved four main goals: identify key characteristics of the destination neighborhoods and those who are moving within the city of Chicago; understand how inner-city mobility of minority and immigrant youth affects engagement in violence and victimization; determine whether vertical or horizontal mobility with respect to key neighborhood factors differentially influences minority and immigrant youth outcomes; assess who fares better - youth who vertically move (to better or worse neighborhoods), those who do not move, or those who horizontally move (to equivalent neighborhoods). This research used data from the Project on Human Development in Chicago Neighborhoods (PHDCN). Data were drawn from both the Longitudinal Cohort Study (N=1,611) and Community Survey (N=97). The rich data from the Community Survey affords the opportunity to examine how community characteristics like collective efficacy, disorder, and indicators of social disorganization can impact a variety of youth behaviors among at-risk youth over time between Wave 1 and Wave 2 and Wave 2 and Wave 3. The Longitudinal Cohort Study provides data on youth characteristics and experiences with violence, and ecological information on family and peer relationships. The investigators focused primarily on three of the seven youth cohorts from the Longitudinal Cohort Study: 9, 12, and 15. The ages of these youth during the study period place them at increased risk for exposure to community violence, and place them in range for aging into, peaking, or aging out of crime and delinquency. The Longitudinal Cohort Study respondents are nested in neighborhood clusters and multilevel models are employed to assess the outcomes victimization and violence within neighborhood context. The researchers employed a series of hierarchical generalized linear models using HLM 7 in addition to running several analyses of variance (ANOVA) permitting examinations between groups of interest.

This data collection was designed to test the "incivilities thesis": that incivilities such as extant neighborhood physical conditions of disrepair or abandonment and troubling street behaviors contribute to residents' concerns for personal safety and their desire to leave their neighborhood. The collection examines between-individual versus between-neighborhood and between-city differences with respect to fear of crime and neighborhood commitment and also explores whether some perceived incivilities are more relevant to these outcomes than others. The data represent a secondary analysis of five ICPSR collections: (1) CHARACTERISTICS OF HIGH AND LOW CRIME NEIGHBORHOODS IN ATLANTA, 1980 (ICPSR 7951), (2) CRIME CHANGES IN BALTIMORE, 1970-1994 (ICPSR 2352), (3) CITIZEN PARTICIPATION AND COMMUNITY CRIME PREVENTION, 1979: CHICAGO METROPOLITAN AREA SURVEY (ICPSR 8086), (4) CRIME, FEAR, AND CONTROL IN NEIGHBORHOOD COMMERCIAL CENTERS: MINNEAPOLIS AND ST. PAUL, 1970-1982 (ICPSR 8167), and (5) TESTING THEORIES OF CRIMINALITY AND VICTIMIZATION IN SEATTLE, 1960-1990 (ICPSR 9741). Part 1, Survey Data, is an individual-level file that contains measures of residents' fear of victimization, avoidance of dangerous places, self-protection, neighborhood satisfaction, perceived incivilities (presence of litter, abandoned buildings, vandalism, and teens congregating), and demographic variables such as sex, age, and education. Part 2, Neighborhood Data, contains crime data and demographic variables from Part 1 aggregated to the neighborhood level, including percentage of the neighborhood that was African-American, gender percentages, average age and educational attainment of residents, average household size and length of residence, and information on home ownership.

The Project on Human Development in Chicago Neighborhoods is an interdisciplinary study aimed at deepening society's understanding of the causes and pathways of juvenile delinquency, adult crime, substance abuse, and violence. In particular, it is a study of children's social and psychological development from birth to young adulthood in urban neighborhoods. This collection contains data from a cross-sectional survey of Chicago residents in 1994 and is the first product of an eight-year project. The survey gathered information from adult residents of Chicago on their perceptions of the neighborhoods in which they live. The survey questionnaire was a multidimensional assessment of the structural conditions and organization of the neighborhoods. Data collection consisted of a household interview of residents aged 18 and older to assess key neighborhood dimensions, including the dynamic structure of the local community, organizational and political structure, cultural values, informal social control, formal social control, and social cohesion. Variables include measures of the best and worst aspects of living in Chicago, how long residents had lived in a particular neighborhood, characteristics of their neighborhood, including types of social service agencies available, and if they would consider moving to a different neighborhood and why. Other community variables measure the relationships among neighbors, including how many neighbors a respondent would recognize, how often neighbors socialized, and how often neighbors participated in other activities together. Variables that capture neighborhood social order include respondents' perceptions of neighborhood problems such as litter, graffiti, drinking, drugs, and excessive use of force by police. Respondents were also asked about their normative beliefs regarding violence, money, and various children's behaviors. Victimization variables cover how often the respondent was the victim of a fight with a weapon, a violent argument, a gang fight, sexual assault, robbery, theft, or vandalism. Other variables measure fear of crime and attitudes toward the police. Demographic variables include age, gender, education, living arrangement, national origin, and employment status. In addition, a number of scales created by the study's scientific directors are included such as social disorder, perceived neighborhood danger, and neighborhood activism. Part 1 of this study contains individual responses to survey questions. Part 2 contains data aggregated to the neighborhood cluster (NC) level (see Study Design for explanation of NC).

The data contain records of charges filed against defendants whose cases were filed by United States attorneys in United States district court during fiscal year 2000. The data are charge-level records, and more than one charge may be filed against a single defendant. The data were constructed from the Executive Office for United States Attorneys (EOUSA) Central Charge file. The charge-level data may be linked to defendant-level data (extracted from the EOUSA Central System file) through the CS_SEQ variable, and it should be noted that some defendants may not have any charges other than the lead charge appearing on the defendant-level record. The Central Charge and Central System data contain variables from the original EOUSA files as well as additional analysis variables, or "SAF" variables, that denote subsets of the data. These SAF variables are related to statistics reported in the Compendium of Federal Justice Statistics. Variables containing identifying information (e.g., name, Social Security Number) were replaced with blanks, and the day portions of date fields were also sanitized in order to protect the identities of individuals. These data are part of a series designed by the Urban Institute (Washington, DC) and the Bureau of Justice Statistics. Data and documentation were prepared by the Urban Institute.