Note: Due to the RMS change for CPS, this data set stops on 6/2/2024. For records beginning on 6/3/2024, please see the dataset at this link: https://data.cincinnati-oh.gov/safety/Reported-Crime-STARS-Category-Offenses-/7aqy-xrv9/about_data

The combined data will be available by 3/10/2025 at the linke above.

Data Description: This data represents reported Crime Incidents in the City of Cincinnati. Incidents are the records, of reported crimes, collated by an agency for management. Incidents are typically housed in a Records Management System (RMS) that stores agency-wide data about law enforcement operations. This does not include police calls for service, arrest information, final case determination, or any other incident outcome data.

Data Creation: The Cincinnati Police Department's (CPD) records crime incidents in the City through Records Management System (RMS) that stores agency-wide data about law enforcement operations.

Data Created By: The source of this data is the Cincinnati Police Department.

Refresh Frequency: This data is updated daily.

CincyInsights: The City of Cincinnati maintains an interactive dashboard portal, CincyInsights in addition to our Open Data in an effort to increase access and usage of city data. This data set has an associated dashboard available here: https://insights.cincinnati-oh.gov/stories/s/8eaa-xrvz

Data Dictionary: A data dictionary providing definitions of columns and attributes is available as an attachment to this dataset.

Processing: The City of Cincinnati is committed to providing the most granular and accurate data possible. In that pursuit the Office of Performance and Data Analytics facilitates standard processing to most raw data prior to publication. Processing includes but is not limited: address verification, geocoding, decoding attributes, and addition of administrative areas (i.e. Census, neighborhoods, police districts, etc.).

Data Usage: For directions on downloading and using open data please visit our How-to Guide: https://data.cincinnati-oh.gov/dataset/Open-Data-How-To-Guide/gdr9-g3ad

Disclaimer: In compliance with privacy laws, all Public Safety datasets are anonymized and appropriately redacted prior to publication on the City of Cincinnati’s Open Data Portal. This means that for all public safety datasets: (1) the last two digits of all addresses have been replaced with “XX,” and in cases where there is a single digit street address, the entire address number is replaced with "X"; and (2) Latitude and Longitude have been randomly skewed to represent values within the same block area (but not the exact location) of the incident.

Description Crime incidents starting with those reported in 2016. The data provided is the latest available information and is updated regularly as statistics change. For access to comprehensive reports, kindly submit a public record request here.Note: Crimes that occurred before 2016 are included if the date reported was in 2016 or later.

Disclaimer: The City strives to provide the highest-quality information on this platform. The content on this website is provided as a public service, on an ‘as is’ basis. The City makes no warranty, representation, or guarantee of any type as to the content, accuracy, timeliness, completeness, or fitness for any particular purpose or use of any public data provided on this portal; nor shall any such warranty be implied, including, without limitation, the implied warranties of merchantability and fitness for a particular purpose. The City assumes no liability by making data available to the public or other departments.This dataset is featured in the following app(s): Cleveland Division of Police Crime DashboardCrime Incidents MapData GlossarySee the Attributes section below for details about each column in this dataset.Update Frequency Daily around 8 AM EST

Contacts

 City of Cleveland, Division of Police

The Urban Institute undertook a comprehensive assessment of communities approaching decay to provide public officials with strategies for identifying communities in the early stages of decay and intervening effectively to prevent continued deterioration and crime. Although community decline is a dynamic spiral downward in which the physical condition of the neighborhood, adherence to laws and conventional behavioral norms, and economic resources worsen, the question of whether decay fosters or signals increasing risk of crime, or crime fosters decay (as investors and residents flee as reactions to crime), or both, is not easily answered. Using specific indicators to identify future trends, predictor models for Washington, DC, and Cleveland were prepared, based on data available for each city. The models were designed to predict whether a census tract should be identified as at risk for very high crime and were tested using logistic regression. The classification of a tract as a "very high crime" tract was based on its crime rate compared to crime rates for other tracts in the same city. To control for differences in population and to facilitate cross-tract comparisons, counts of crime incidents and other events were converted to rates per 1,000 residents. Tracts with less than 100 residents were considered nonresidential or institutional and were deleted from the analysis. Washington, DC, variables include rates for arson and drug sales or possession, percentage of lots zoned for commercial use, percentage of housing occupied by owners, scale of family poverty, presence of public housing units for 1980, 1983, and 1988, and rates for aggravated assaults, auto thefts, burglaries, homicides, rapes, and robberies for 1980, 1983, 1988, and 1990. Cleveland variables include rates for auto thefts, burglaries, homicides, rapes, robberies, drug sales or possession, and delinquency filings in juvenile court, and scale of family poverty for 1980 through 1989. Rates for aggravated assaults are provided for 1986 through 1989 and rates for arson are provided for 1983 through 1988.

Incidents are the records, of reported crimes, collated by an agency for management. Incidents are typically housed in a Records Management System (RMS) that stores agency-wide data about law enforcement operations.

DISCLAIMER: In compliance with privacy laws, all Public Safety datasets are anonymized and appropriately redacted prior to publication on the City of Cincinnati’s Open Data Portal. This means that for all public safety datasets: (1) the last two digits of all addresses have been replaced with “XX,” and in cases where there is a single digit street address, the entire address number is replaced with "X"; and (2) Latitude and Longitude have been randomly skewed to represent values within the same block area (but not the exact location) of the incident.

The purpose of the study was to evaluate the implementation of the Safe City crime prevention model that was implemented in designated retail areas in jurisdictions across the United States. The model involved frequent meetings and information-sharing among the police, Target, and neighboring retailers, along with the implementation of enhanced technology. The first step in the Safe City evaluation involved selecting evaluation sites. The final sites selected were Chula Vista, California, and Cincinnati, Ohio. Next, for each of the two sites, researchers selected a site that had a potential for crime displacement caused by the intervention area, and a matched comparison area in another jurisdiction that would likely have been selected as a Safe City site. For Chula Vista, the displacement area was 2 miles east of the intervention area and the comparison area was in Houston, Texas. For Cincinnati, the displacement area was 1.5 miles north of the intervention area and the comparison area was in Buffalo, New York. In Chula Vista, the Safe City intervention activities were focused on gaining a better understanding of the nature and underlying causes of the crime and disorder problems occurring in the designated Safe City site, and strengthening pre-existing partnerships between law enforcement and businesses affected by these problems. In Cincinnati, the Safe City intervention activities centered on increasing business and citizen awareness, communication, and involvement in crime control and prevention activities. The research team collected pre- and post-intervention crime data from local police departments (Part 1) to measure the impact of the Safe City initiatives in Chula Vista and Cincinnati. The 981 records in Part 1 contain monthly crime counts from January 2004 to November 2008 for various types of crime in the retail areas that received the intervention in Chula Vista and Cincinnati, and their corresponding displacement zones and matched comparison areas. Using the monthly crime counts contained in the Safe City Monthly Crime Data (Part 1) and estimations of the total cost of crime to society for various offenses from prior research, the research team calculated the total cost of crimes reported during the month/year for each crime type that was readily available (Part 2). The 400 records in the Safe City Monthly Cost Benefit Analysis Data (Part 2) contain monthly crime cost estimates from January 2004 to November 2008 for assaults, burglaries, larcenies, and robberies in the retail areas that received the intervention in Chula Vista and Cincinnati, and their corresponding displacement zones and matched comparison areas. The research team also received a total of 192 completed baseline and follow-up surveys with businesses in Chula Vista and Cincinnati in 2007 and 2008 (Part 3). The surveys collected data on merchants' perceptions of crime and safety in and around businesses located in the Safe City areas. The Safe City Monthly Crime Data (Part 1) contain seven variables including the number of crimes in the target area, the month and year the crime was committed, the number of crimes in the displacement area, the number of crimes in a comparable area in a comparable city, the city, and the crime type. The Safe City Monthly Cost Benefit Analysis Data (Part 2) contain seven variables including the cost of the specified type of crime occurring in the target area, the month and year the cost was incurred, the cost of the specified type of crime in the displacement area, the cost of the specified type of crime in a matched comparison area, the city, and the crime type. The Safe City Business Survey Data (Part 3) contain 132 variables relating to perceptions of safety, contact with local police, experience and reporting of crime, impact of crime, crime prevention, community connections, and business/employee information.

Data Description: This data represents reported Crime incidents separated by offense in the City of Cincinnati. Incidents are the records, of reported crimes, collated by an agency for management. Incidents are typically housed in a Records Management System (RMS) that stores agency-wide data about law enforcement operations. This does not include police calls for service, arrest information, final case determination, or any other incident outcome data.

Data Creation: The Cincinnati Police Department's (CPD) records crime incidents in the City through Records Management System (RMS) that stores agency-wide data about law enforcement operations.

NOTE: CPD transitioned to a new RMS on June 3rd, 2024. Columns may differ before or after that date due to differences in the way the RMS stores the information. To view Records from before 6/3/2024 visit this link: https://data.cincinnati-oh.gov/safety/PDI-Police-Data-Initiative-Crime-Incidents/k59e-2pvf/about_data

Data Created By: The source of this data is the Cincinnati Police Department.

Refresh Frequency: This data is updated daily.

CincyInsights: The City of Cincinnati maintains an interactive dashboard portal, CincyInsights in addition to our Open Data in an effort to increase access and usage of city data. This data set has an associated dashboard available here: https://insights.cincinnati-oh.gov/stories/s/8eaa-xrvz

Data Dictionary: A data dictionary providing definitions of columns and attributes is available as an attachment to this dataset.

Processing: The City of Cincinnati is committed to providing the most granular and accurate data possible. In that pursuit the Office of Performance and Data Analytics facilitates standard processing to most raw data prior to publication. Processing includes but is not limited: address verification, geocoding, decoding attributes, and addition of administrative areas (i.e. Census, neighborhoods, police districts, etc.).

Data Usage: For directions on downloading and using open data please visit our How-to Guide: https://data.cincinnati-oh.gov/dataset/Open-Data-How-To-Guide/gdr9-g3ad

Disclaimer: In compliance with privacy laws, all Public Safety datasets are anonymized and appropriately redacted prior to publication on the City of Cincinnati’s Open Data Portal. This means that for all public safety datasets: (1) the last two digits of all addresses have been replaced with “XX,” and in cases where there is a single digit street address, the entire address number is replaced with "X"; and (2) Latitude and Longitude have been randomly skewed to represent values within the same block area (but not the exact location) of the incident.

Incidents are the records, of reported crimes, collated by an agency for management. Incidents are typically housed in a Records Management System (RMS) that stores agency-wide data about law enforcement operations.

DISCLAIMER: In compliance with privacy laws, all Public Safety datasets are anonymized and appropriately redacted prior to publication on the City of Cincinnati’s Open Data Portal. This means that for all public safety datasets: (1) the last two digits of all addresses have been replaced with “XX,” and in cases where there is a single digit street address, the entire address number is replaced with "X"; and (2) Latitude and Longitude have been randomly skewed to represent values within the same block area (but not the exact location) of the incident.

Abstract (en): This study investigated changes in the geographic concentration of drug crimes in Cleveland from 1990 to 2001. The study looked at both the locations of drug incidents and where drug offenders lived in order to explore factors that bring residents from one neighborhood into other neighborhoods to engage in drug-related activities. This study was based on data collected for the 224 census tracts in Cleveland, Ohio, in the 1990 decennial Census for the years 1990 to 1997 and 1999 to 2001. Data on drug crimes for 1990 to 1997 and 1999 to 2001 were obtained from Cleveland Police Department (CPD) arrest records and used to produce counts of the number of drug offenses that occurred in each tract in each year and the number of arrestees for drug offenses who lived in each tract. Other variables include counts and rates of other crimes committed in each census tract in each year, the social characteristics and housing conditions of each census tract, and net migration for each census tract. This study investigated changes in the geographic concentration of drug crimes in Cleveland from 1990 to 2001. The main objectives of the study were: (1) to identify neighborhoods in which drug crimes were concentrated and neighborhoods where persons arrested for drug crimes resided, (2) to describe changes in concentrations of drug offending over time, and (3) to explain changes in patterns of drug offending in relation to changes in the social and physical structure of neighborhoods. The study looked at both the locations of drug incidents and where drug offenders lived in order to explore factors that bring residents from one neighborhood into other neighborhoods to engage in drug-related activities. This study used data collected for the 224 census tracts in Cleveland, Ohio, in the 1990 decennial census for the years 1990 to 1997 and 1999 to 2001. All of the data other than the United States Census data and the drug crime data are available on-line from the Center on Urban Poverty and Social Change's community database, Cleveland Area Network for Data and Organizing (CAN DO). Data on drug crimes for 1990 to 1997 and 1999 to 2001 were obtained from Cleveland Police Department (CPD) arrest records. These records provided the address of the incident and the residential address of the person arrested. These addresses were geocoded into their 1990 census tracts, with a match rate of over 95 percent, to produce counts of the number of drug trafficking and possession incidents occurring within each tract in each year and the number of arrestees for drug trafficking and possession living in each tract. (Users should note that no geocoded data are included in this dataset.) In 1998 the CPD changed the way that drug crimes were recorded, and the accuracy with which types of drug crimes were reported was significantly reduced. As a result, while data on the total number of drug incidents in census tracts were available for the entire length of the study, data on whether these incidents involved drug trafficking or possession were only available for 1990 to 1997. CPD arrest records for non-drug crimes and Cuyahoga County Juvenile Court data were used to produce count and rate data on non-drug crimes for each census tract. Data on the social characteristics and housing conditions of each census tract were gathered from the 1990 and 2000 Censuses. Migration into and out of each tract between 1990 and 2000 was estimated using 1990 and 2000 Census population counts and Ohio Department of Health vital statistics data on births and deaths from 1990 to 2000. Data on the number of schools in each census tract were obtained from the Cleveland Municipal School District. Several sources of data were used to develop measures of the physical characteristics of areas. These included the Cuyahoga County Auditor's parcel-level data (from 1990 to 2000) on land-use patterns, characteristics of dwellings, tax delinquencies, and assessed value, and the Home Mortgage Disclosure Act data (for 1992 to 2001) on home purchase loans and home improvement loans. Variables include 1990 census tract number, year, the City of Cleveland Statistical Planning Area that each census tract belonged to, counts and rates of violent crimes, robberies, robberies with firearms, burglaries committed by adults in each census tract in each year, robberies and violent crimes committed by juveniles in each census tract in each year, number of drug trafficking and possession in...

California reported the largest number of homicides to the FBI in 2023, at 1,929 for the year. Texas recorded the second-highest number of murders, with 1,845 for the year. Homicide victim demographics There were a total of 19,252 reported homicide cases in the U.S. in 2023. When looking at murder victims by gender and ethnicity, the vast majority were male, while just over half of the victims were Black or African American. In addition, homicide victims in the United States were found most likely to be between the ages of 20 and 34 years old, with the majority of victims aged between 17 to 54 years old. Are murders up? In short, no – since the 1990s the number of murders in the U.S. has decreased significantly. In 1990, the murder rate per 100,000 people stood at 9.4, and stood at 5.7 in 2023. It should be noted though that the number of homicides increased slightly from 2014 to 2017, although figures declined again in 2018 and 2019, before ticking up once more in 2020 and 2021. Despite this decline, when viewed in international comparison, the U.S. murder rate is still notably high. For example, the Canadian homicide rate stood at 1.94 in 2023, while the homicide rate in England and Wales was even lower.