Interactive dashboard for open data portal. Displays crimes by zip code.

Crime severity index (violent, non-violent, youth) and weighted clearance rates (violent, non-violent), Canada, provinces, territories and Census Metropolitan Areas, 1998 to 2024.

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.

This table contains data on the rate of violent crime (crimes per 1,000 population) for California, its regions, counties, cities and towns. Crime and population data are from the Federal Bureau of Investigations, Uniform Crime Reports. Rates above the city/town level include data from city, university and college, county, state, tribal, and federal law enforcement agencies. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Ten percent of all deaths in young California adults aged 15-44 years are related to assault and homicide. In 2010, California law enforcement agencies reported 1,809 murders, 8,331 rapes, and over 95,000 aggravated assaults. African Americans in California are 11 times more likely to die of assault and homicide than Whites. More information about the data table and a data dictionary can be found in the About/Attachments section.

The data provided in this dataset is preliminary in nature and may have not been investigated by a detective at the time of download. The data is therefore subject to change after a complete investigation. This data represents only calls for police service where a police incident report was taken. Due to the variations in local laws and ordinances involving crimes across the nation, whether another agency utilizes Uniform Crime Report (UCR) or National Incident Based Reporting System (NIBRS) guidelines, and the results learned after an official investigation, comparisons should not be made between the statistics generated with this dataset to any other official police reports. Totals in the database may vary considerably from official totals following the investigation and final categorization of a crime. Therefore, the data should not be used for comparisons with Uniform Crime Report or other summary statistics.Data is broken out by year into separate CSV files. Note the file grouping by year is based on the crime's Date Reported (not the Date Occurred).Older cases found in the 2003 data are indicative of cold case research. Older cases are entered into the Police database system and tracked but dates and times of the original case are maintained.Data may also be viewed off-site in map form for just the last 6 months on communitycrimemap.comData Dictionary:

Field Name

Field Description

Incident Number

the number associated with either the incident or used as reference to store the items in our evidence rooms

Date Reported

the date the incident was reported to LMPD

Date Occurred

the date the incident actually occurred

Badge ID

Badge ID of responding Officer

Offense Classification

NIBRS Reporting category for the criminal act committed

Offense Code Name

NIBRS Reporting code for the criminal act committed

NIBRS_CODE

the code that follows the guidelines of the National Incident Based Reporting System. For more details visit https://ucr.fbi.gov/nibrs/2011/resources/nibrs-offense-codes/view

NIBRS Group

hierarchy that follows the guidelines of the FBI National Incident Based Reporting System

Was Offense Completed

Status indicating whether the incident was an attempted crime or a completed crime.

LMPD Division

the LMPD division in which the incident actually occurred

LMPD Beat

the LMPD beat in which the incident actually occurred

Location Category

the type of location in which the incident occurred (e.g. Restaurant)

Block Address

the location the incident occurred

City

the city associated to the incident block location

Zip Code

the zip code associated to the incident block location

Contact:LMPD Open Records lmpdopenrecords@louisvilleky.gov

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

Update Frequency: Daily

Current year to date. The data included in this dataset has been reviewed and approved by a Milwaukee Police Department supervisor and the Milwaukee Police Department’s Records Management Division. This approval process can take a few weeks from the reported date of the crime. For preliminary crime data, please visit the Milwaukee Police Department’s Crime Maps and Statistics dashboard at https://city.milwaukee.gov/police/Information-Services/Crime-Maps-and-Statistics.

Wisconsin Incident Based Report (WIBR) Group A Offenses.

The Crime Data represents incident level data defined by Wisconsin Incident Based Reporting System (WIBRS) codes. WIBRS reporting is a crime reporting standard and can not be compared to any previous UCR report. Therefore, the Crime Data may reflect:

• Information not yet verified by further investigation
• Preliminary crime classifications that may be changed at a later date based upon further investigation
• Information that may include mechanical or human error

Neither the City of Milwaukee nor the Milwaukee Police Department guarantee (either express or implied) the accuracy, completeness, timeliness, or correct sequencing of the Crime Data. The City of Milwaukee and the Milwaukee Police Department shall have no liability for any error or omission, or for the use of, or the results obtained from the use of the Crime Data. In addition, the City of Milwaukee and the Milwaukee Police Department caution against using the Crime Data to make decisions/comparisons regarding the safety of or the amount of crime occurring in a particular area. When reviewing the Crime Data, the site user should consider that:

• The information represents only police services where a report was made and does not include other calls for police service
• The information does not reflect or certify "safe" or "unsafe" areas
• The information will sometimes reflect where the crime was reported versus where the crime occurred

This data is not intended to represent a total number/sum of crimes, rather 1 = True and 0 = False.

The use of the Crime Data indicates the site user's unconditional acceptance of all risks associated with the use of the Crime Data.

To download XML and JSON files, click the CSV option below and click the down arrow next to the Download button in the upper right on its page. XY fields in data is in projection Wisconsin State Plane South NAD27 (WKID 32054).

The Division of Criminal Justice Services (DCJS) collects crime reports from more than 500 New York State police and sheriffs' departments. DCJS compiles these reports as New York's official crime statistics and submits them to the FBI under the National Uniform Crime Reporting (UCR) Program. UCR uses standard offense definitions to count crime in localities across America regardless of variations in crime laws from state to state. In New York State, law enforcement agencies use the UCR system to report their monthly crime totals to DCJS. The UCR reporting system collects information on seven crimes classified as Index offenses which are most commonly used to gauge overall crime volume. These include the violent crimes of murder/non-negligent manslaughter, forcible rape, robbery, and aggravated assault; and the property crimes of burglary, larceny, and motor vehicle theft. Police agencies may experience reporting problems that preclude accurate or complete reporting. The counts represent only crimes reported to the police but not total crimes that occurred. DCJS posts preliminary data in the spring and final data in the fall.

***Starting on March 7th, 2024, the Los Angeles Police Department (LAPD) will adopt a new Records Management System for reporting crimes and arrests. This new system is being implemented to comply with the FBI's mandate to collect NIBRS-only data (NIBRS — FBI - https://www.fbi.gov/how-we-can-help-you/more-fbi-services-and-information/ucr/nibrs). During this transition, users will temporarily see only incidents reported in the retiring system. However, the LAPD is actively working on generating new NIBRS datasets to ensure a smoother and more efficient reporting system. *** **Update 1/18/2024 - LAPD is facing issues with posting the Crime data, but we are taking immediate action to resolve the problem. We understand the importance of providing reliable and up-to-date information and are committed to delivering it. As we work through the issues, we have temporarily reduced our updates from weekly to bi-weekly to ensure that we provide accurate information. Our team is actively working to identify and resolve these issues promptly. We apologize for any inconvenience this may cause and appreciate your understanding. Rest assured, we are doing everything we can to fix the problem and get back to providing weekly updates as soon as possible. ** This dataset reflects incidents of crime in the City of Los Angeles dating back to 2020. This data is transcribed from original crime reports that are typed on paper and therefore there may be some inaccuracies within the data. Some location fields with missing data are noted as (0°, 0°). Address fields are only provided to the nearest hundred block in order to maintain privacy. This data is as accurate as the data in the database. Please note questions or concerns in the comments.

Much research has examined how crime rates vary across urban neighborhoods, focusing particularly on community-level demographic and social characteristics. A parallel line of work has treated crime at the individual level as an expression of certain behavioral patterns (e.g., impulsivity). Little work has considered, however, whether the prevalence of such behavioral patterns in a neighborhood might be predictive of local crime, in large part because such measures are hard to come by and often subjective. The Facebook Advertising API offers a special opportunity to examine this question as it provides an extensive list of "interests'' that can be tabulated at various geographic scales. Here we conduct an analysis of the association between the prevalence of interests among the Facebook population of a ZIP code and the local rate of assaults, burglaries, and robberies across 9 highly populated cities in the US. We fit various regression models to predict crime rates as a function of the Facebook and census demographic variables. In general, models using the variables for the interests of the whole adult population on Facebook perform better than those using data on specific demographic groups (such as Males 18-34). In terms of predictive performance, models combining Facebook data with demographic data generally have lower error rates than models using only demographic data. We find that interests associated with media consumption and mating competition are predictive of crime rates above and beyond demographic factors. We discuss how this might integrate with existing criminological theory.

This statistic shows the crime severity index value of metropolitan areas in Canada in 2023. As of 2023, the crime severity index in Saskatoon, Saskatchewan, stood at 116.31.

This is the most current information as of the date of upload. This provides the user the ability to view the most current crime information within Kansas City, Missouri. The displayed information is the most current information from the data source as of the date of upload. The data source is dynamic and therefore constantly changing. Changes to the information may occur, as incident information is refined. While the Board of Police Commissioners of Kansas City, Missouri (Board) makes every effort to maintain and distribute accurate information, no warranties and/or representations of any kind are made regarding information, data or services provided. The Board is not responsible for misinterpretation of this information and makes no inference or judgment as to the relative safety to any particular area or neighborhood. In no event shall the Board be liable in any way to the users of this data. Users of this data shall hold the Board harmless in all matters and accounts arising from the use and/or accuracy of this data.

The Division of Prevention and Early Intervention (PEI) was created to consolidate child abuse prevention and juvenile delinquency prevention and early intervention programs within the jurisdiction of a single state agency. Consolidation of these programs is intended to eliminate fragmentation and duplication of contracted prevention and early intervention services for at-risk children, youth, and families: Community Youth Development (CYD) - The CYD program contracts with community-based organizations to develop juvenile delinquency prevention programs in ZIP codes with high juvenile crime rates. Approaches used by communities to prevent delinquency have included mentoring, youth employment programs, career preparation, youth leadership development and recreational activities. Communities prioritize and fund specific prevention services according to local needs. CYD services are available in 15 targeted Texas ZIP codes. Family and Youth Success Program (FAYS) (formerly Services to At-Risk Youth (STAR)) - The FAYS program contracts with community agencies to offer family crisis intervention counseling, short- term emergency respite care, and individual and family counseling. Youth up to age 17 and their families are eligible if they experience conflict at home, truancy or delinquency, or a youth who runs away from home. FAYS services are available in all 254 Texas counties. Each FAYS contractor also provides universal child abuse prevention services, ranging from local media campaigns to informational brochures and parenting classes. Statewide Youth Services Network (SYSN) - The SYSN program contracts provide community and evidence-based juvenile delinquency prevention programs focused on youth ages 10 through 17, in each DFPS region. NOTE: For FY15, as a result of a new procurement, the overall number of youth served decreased however the service requirements were enhanced with additional programmatic components. Data as of December 11, 2024.

Data for violent crimes per Police Incident Data taken from the records managment sysmte

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.

Report Volume Data The report counts in this data set are broken down by activity sector, report type, the year and month of receipt, and reporting entity location. The reporting entity location is represented by the forward sortation area (FSA) component of the Canadian postal code (i.e. the first three characters of the Canadian postal code, e.g. “K1P”) that designates the postal district where the reporting entity is located. ##Modernization of Reporting Forms The Financial Transactions and Reports Analysis Centre of Canada (FINTRAC) is engaged in a multi-year initiative to implement important changes to its reporting forms. Part of this modernization now allows reporting entities to submit reports containing transactions from multiple locations, increasing efficiency and reducing burden. This will change how FINTRAC publishes statistics for reports that have been modernized. FINTRAC implemented the new Large Cash Transaction Report in October 2023. As such, reporting volume statistics for the Large Cash Transaction Report will be published at a national level for quarters 3 and 4 of 2023-2024 (from October to December, and January to March, respectively). The publication of this dataset has been temporarily paused to accommodate the transition to new reporting forms. This transition is part of our ongoing efforts to enhance the quality and consistency of the data we collect. ##Protecting the Identity of Reporting Entities By law, FINTRAC must protect the identity of the persons and entities that are required to submit financial transaction reports to the Centre under the Proceeds of Crime (Money Laundering) and Terrorist Financing Act. In keeping with this responsibility to protect information, FINTRAC cannot provide more specific geographic data than is contained in this data set. Whenever possible, the data set includes the full FSA to identify the location of reporting entities submitting reports to FINTRAC. However, in any case where a certain location contains fewer than five reporting entities, or fewer than five reports submitted, only partial characters of the FSA are shown. This means that certain FSAs may contain only one or two characters (e.g., K or K1) instead of the standard three characters (e.g., K1P). In rare cases, it was not possible to provide a reporting entity location or report count without risking revealing the identity of reporting entities in a given activity sector or identifying a specific report, and so the data is provided at a national level only. All FSA levels are hierarchically inclusive. This means, for example, that the total number of report counts for K1 includes all reports submitted within all FSAs that start with K1 (i.e. K1A, K1B, K1C), including those that may not be visible because they include fewer than five reporting entities in a given activity sector. E&OE

Prevention and Early Intervention (PEI) was created to consolidate child abuse prevention and juvenile delinquency prevention and early intervention programs within the jurisdiction of a single state agency. To provide services for at-risk children, youth, and families.

Community Youth Development (CYD) - The CYD program contracts services in 15 targeted Texas ZIP codes with community-based organizations to develop juvenile delinquency prevention programs in areas with high juvenile crime rates. Approaches used by communities to prevent delinquency include mentoring, youth employment programs, career preparation, youth leadership development and recreational activities. Communities prioritize and fund specific prevention services according to local needs.

Family and Youth Success Program (FAYS) (Formerly Services to At-Risk Youth (STAR)) - The FAYS program contracts with community agencies to offer family crisis intervention counseling, short- term emergency respite care, individual and family counseling, and universal child abuse prevention services, ranging from local media campaigns to informational brochures and parenting classes in all counties in Texas. Youth up to age 17 and their families are eligible if they experience conflict at home, truancy or delinquency, or a youth who runs away from home. In FY2018, contracts for the FAYS program were re-procured and started on December 1, 2017. Under these contracts, families could be served through traditional FAYS services or through one-time focused skills training. In some cases, families participating in skills training also chose to enroll in traditional FAYS services. Programmatically, these families are counted uniquely in both programs; for DFPS Data Book purposes, they are reported unduplicated.

Statewide Youth Services Network (SYSN) - The SYSN program contracts provide community and evidence-based juvenile delinquency prevention programs focused on youth ages 10 through 17, in each DFPS region.

This is a data set built in the fall of 2004 of the addresses of know spammers that have been identified by Spamhaus. Specifically the data comes from their Registry of Known Spam Operations - http://www.spamhaus.org/Rokso/. Street addresses were culled from the the database then geocoded to a zip code level of accuracy.

The NCREDC in conjunction with Hobbs, Upchurch & Associates developed the digital `P' Sewer System as mapped by individual system owners as required by contract. The data collected will facilitate planning, siting and impact analysis in the 70 individual counties of North Carolina. This file enables the user to make various county-level determinations when used in conjunction with other data layers. This data contains information onP' Sewer systems which are planned or proposed public community system service areas are outside of current service area boundaries where public systems do not currently exist. Type P systems are areas which have been identified as having sufficient need and population density to support viable public systems and which have an existing minimum potential user density of 40 existing potential connections per mile of wastewater collection line. Information includes: system ID, parent system ID, cost estimate to implement. Other coverages exist with sewer lines and other appurtenances. This data was created to assist governmental agencies and others in making resource management decisions through use of a Geographic Information System (GIS).