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 study was designed to explore the relationship between employment and involvement with the criminal justice system. Males arrested primarily for felony offenses were interviewed at the central booking agency in Brooklyn, New York, at the time of their arrests in 1979. A subsample of 152 arrestees was reinterviewed in 1980. The data include information on labor market participation, arrests, periods of incarceration, and the respondents' demographic characteristics. The labor market information spans a two-year period prior to those arrests. Arrest history and other criminal justice data cover the two years prior to arrest and one year following the arrest. Additional variables supply information on employment and occupation, social and neighborhood characteristics, and perceptions of the risk of committing selected crimes.

This map shows the incidence of seven major felonies -- burglary, felony assault, grand larceny, grand larceny of a motor vehicle, murder, rape, and robbery -- in New York City over the past year. Data can be mapped in aggregate at the precinct level, as a heat map showing concentration of crimes, or as individual incident points.

All BPD data on Open Baltimore is preliminary data and subject to change. The information presented through Open Baltimore represents Part I victim based crime data. The data do not represent statistics submitted to the FBI's Uniform Crime Report (UCR); therefore any comparisons are strictly prohibited. For further clarification of UCR data, please visit http://www.fbi.gov/about-us/cjis/ucr/ucr. Please note that this data is preliminary and subject to change. Prior month data is likely to show changes when it is refreshed on a monthly basis. All data is geocoded to the approximate latitude/longitude location of the incident and excludes those records for which an address could not be geocoded. Any attempt to match the approximate location of the incident to an exact address is strictly prohibited.

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 (2016). Offenses occurring at intersections are represented at the X Coordinate and Y Coordinate of the intersection. Crimes occurring anywhere other than an intersection are geo-located to the middle of the block. For additional details, please see the attached data dictionary in the ‘About’ section.

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 (2019). For additional details, please see the attached data dictionary in the ‘About’ section.

All BPD data on Open Baltimore is preliminary data and subject to change. The information presented through Open Baltimore represents Part I victim based crime data. The data do not represent statistics submitted to the FBI's Uniform Crime Report (UCR); therefore any comparisons are strictly prohibited. For further clarification of UCR data, please visit http://www.fbi.gov/about-us/cjis/ucr/ucr. Please note that this data is preliminary and subject to change. Prior month data is likely to show changes when it is refreshed on a monthly basis. All data is geocoded to the approximate latitude/longitude location of the incident and excludes those records for which an address could not be geocoded. Any attempt to match the approximate location of the incident to an exact address is strictly prohibited.

In 2023, the City of New York experienced a total of 1,455 rapes. This was a significant decrease from 2001 when 1,981 rapes were reported. These figures include all crimes as defined in the FBI Uniform Crime Reporting definition of rape.

Since 1998, the New York City Police Department (NYPD) has been tasked with the collection and maintenance of crime data for incidents that occur in New York City public schools. The NYPD has provided this data for the 2010-2011 school year to the New York City Department of Education (DOE), covering the period from July 1, 2010-June 30, 2011. The DOE has compiled this data by schools and locations for the information of our parents and students, our teachers and staff, and the general public. In some instances, several Department of Education learning communities co-exist within a single building. In other instances, a single school has locations in several different buildings. In either of these instances, the data presented here is aggregated by building location rather than by school, since safety is always a building-wide issue. We use “consolidated locations” throughout the presentation of the data to indicate the numbers of incidents in buildings that include more than one learning community.

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. This study contains data from a project by the New York City Police Department (NYPD) involving GIS data on environmental risk factors that correlate with criminal behavior. The general goal of this project was to test whether risk terrain modeling (RTM) could accurately and effectively predict different crime types occurring across New York City. The ultimate aim was to build an enforcement prediction model to test strategies for effectiveness before deploying resources. Three separate phases were completed to assess the effectiveness and applicability of RTM to New York City and the NYPD. A total of four boroughs (Manhattan, Brooklyn, the Bronx, Queens), four patrol boroughs (Brooklyn North, Brooklyn South, Queens North, Queens South), and four precincts (24th, 44th, 73rd, 110th) were examined in 6-month time periods between 2014 and 2015. Across each time period, a total of three different crime types were analyzed: street robberies, felony assaults, and shootings. The study includes three shapefiles relating to New York City Boundaries, four shapefiles relating to criminal offenses, and 40 shapefiles relating to risk factors.

This study examined the relationship between legal pressure and drug treatment retention by assessing perceptions of legal pressure held by two groups of legally-mandated treatment clients: (1) participants of the Drug Treatment Alternative to Prison (DTAP) program operated by the Kings County (Brooklyn) District Attorney in New York City, and (2) a matched group of probationers, parolees, Treatment Alternatives to Street Crime (TASC) participants, and other court-mandated offenders attending the same community-based treatment programs used by DTAP. The Brooklyn DTAP was selected for study because of the program's uniquely coercive program components, including the threat of a mandatory prison term for noncompliance. The goals of this project were (1) to test whether DTAP participants would show significantly higher retention rates when compared to a matched sample of other legally-mandated treatment clients, and (2) to assess the role of perceived legal pressure in predicting retention for both of these groups. Data were collected from program participants through interviews conducted at admission to treatment and follow-up interviews conducted about eight weeks later. Intake interviews were conducted, on average, one week after the client's admission to treatment. The one-to-one interviews, which lasted up to two hours, were administered by trained researchers in a private location at the treatment site. The intake interview battery included a mixture of standardized measures and those developed by the Vera Institute of Justice. Data in Part 1 were collected with the Addiction Severity Index and include age, sex, race, religion, and education. Additional variables cover medical problems, employment history, detailed substance abuse and treatment history, number of times arrested for various crimes, history of incarceration, family's substance abuse and criminal histories, relationships with family and friends, psychological problems such as depression, anxiety, and suicide, current living arrangements, and sources of income. Part 2, Supplemental Background and Retention Data, contains treatment entry date, number of days in treatment, age at treatment entry, termination date, treatment condition, arrest date, detention at arrest, date released on probation/parole, violation of probation/parole arrest date and location, problem drug, prior drug treatment, as well as age, gender, race, education, and marital status. Part 3, Division of Criminal Justice Services Data, includes data on the number of arrests before and after program entry, and number of total misdemeanor and felony arrests, convictions, and sentences. Part 4, Chemical Use, Abuse, and Dependence Data, contains information on type of substance abuse, intoxication or withdrawal at work, school, or home, effects of abuse on social, occupational, or recreational activities, and effects of abuse on relationships, health, emotions, and employment. Parts 5 and 6 contain psychiatric data gathered from the Symptom Checklist-90-Revised and Beck's Depression Inventory, respectively. Part 7 variables from the Circumstances, Motivation, Readiness, and Suitability scale include family's attitude toward treatment, subject's need for treatment, subject's desire to change life, and legal consequences if subject did not participate in treatment. Part 8, Stages of Change Readiness and Treatment Eagerness scale, contains data on how the subject viewed the drug problem, desire to change, and history of dealing with substance abuse. Part 9, Motivational/Program Supplement Data, includes variables on the subject's need for treatment, attitudes toward treatment sessions, the family's reaction to treatment, and a likelihood of completion rating. Part 10, Perceived Legal Coercion Data, gathered information on who referred the subject to the treatment program, who was keeping track of attendance, whether someone explained the rules of participation in the program and the consequences if the subject failed the program, whether the rules and consequences were put in writing, who monitored program participants, the likelihood of using drugs while in treatment, the likelihood of leaving the program before completion, whether the subject understood the legal consequences of failing the program, the type and frequency of reports and contacts with the criminal justice system, and the subject's reaction to various penalties for not completing the program. Part 11 contains data from the Community Oriented Programs Environment Scale (COPES). Part 12, Treatment Services Review Data, includes data on the number of times the subject received medical attention, days in school, days employed, days intoxicated, days in substance abuse treatment, days tested for drugs, number of contacts with the criminal justice system, days treated for psychological problems, and time spent at recreational activities. Additional variables include the number of individual and group treatment sessions spent discussing medical problems, education and employment, substance abuse, legal problems, and psychological and emotional problems.

List of every criminal summons issued in NYC during the current calendar year.

This is a breakdown of every criminal summons issued in NYC by the NYPD during the current calendar year. This data is manually extracted every quarter and reviewed by the Office of Management Analysis and Planning before being posted on the NYPD website. Each record represents a criminal summons issued in NYC by the NYPD and includes information about the type of crime, the location and time of enforcement. In addition, information related to suspect demographics is also included. This data can be used by the public to explore the nature of police enforcement activity. Please refer to the attached data footnotes for additional information about this dataset.

This data collection is one of three quantitative databases comprising the Commercial Theft Studies component of the Study of the Causes of Crime for Gain, which focuses on patterns of commercial theft and characteristics of commercial thieves. This data collection contains information on methods used to commit commericial thefts involving cargo. The data include incident and missing cargo characteristics, suspect characteristics and punishments, and type and value of stolen property. Cargo thefts that occurred at John F. Kennedy International Airport, LaGuardia Airport, Newark International Airport, and the New York Marine Terminals at Brooklyn, Port Elizabeth, and Port Newark were included in the data, which were collected from the Crime Analysis Unit files of the Port Authorities of New York and New Jersey.

The Motor Vehicle Collisions crash table contains details on the crash event. Each row represents a crash event. The Motor Vehicle Collisions data tables contain information from all police reported motor vehicle collisions in NYC. The police report (MV104-AN) is required to be filled out for collisions where someone is injured or killed, or where there is at least $1000 worth of damage (https://www.nhtsa.gov/sites/nhtsa.dot.gov/files/documents/ny_overlay_mv-104an_rev05_2004.pdf). It should be noted that the data is preliminary and subject to change when the MV-104AN forms are amended based on revised crash details.For the most accurate, up to date statistics on traffic fatalities, please refer to the NYPD Motor Vehicle Collisions page (updated weekly) or Vision Zero View (updated monthly).

Due to success of the CompStat program, NYPD began to ask how to apply the CompStat principles to other problems. Other than homicides, the fatal incidents with which police have the most contact with the public are fatal traffic collisions. Therefore in April 1998, the Department implemented TrafficStat, which uses the CompStat model to work towards improving traffic safety. Police officers complete form MV-104AN for all vehicle collisions. The MV-104AN is a New York State form that has all of the details of a traffic collision. Before implementing Trafficstat, there was no uniform traffic safety data collection procedure for all of the NYPD precincts. Therefore, the Police Department implemented the Traffic Accident Management System (TAMS) in July 1999 in order to collect traffic data in a uniform method across the City. TAMS required the precincts manually enter a few selected MV-104AN fields to collect very basic intersection traffic crash statistics which included the number of accidents, injuries and fatalities. As the years progressed, there grew a need for additional traffic data so that more detailed analyses could be conducted. The Citywide traffic safety initiative, Vision Zero started in the year 2014. Vision Zero further emphasized the need for the collection of more traffic data in order to work towards the Vision Zero goal, which is to eliminate traffic fatalities. Therefore, the Department in March 2016 replaced the TAMS with the new Finest Online Records Management System (FORMS). FORMS enables the police officers to electronically, using a Department cellphone or computer, enter all of the MV-104AN data fields and stores all of the MV-104AN data fields in the Department’s crime data warehouse. Since all of the MV-104AN data fields are now stored for each traffic collision, detailed traffic safety analyses can be conducted as applicable.

Calls for Service to NYPD's 911 system
This dataset documents entries into the NYPD 911 system, ICAD. The data is collected from the ICAD system which call takers and dispatchers use to communicate with callers and the NYPD. Each record represents an entry into the system. The data includes entries generated by members of the public as well as self-initiated entries by NYPD Members of Service. The data can be used for issues being responded to by the NYPD.