The dataset contains a subset of locations and attributes of incidents reported in the ASAP (Analytical Services Application) crime report database by the District of Columbia Metropolitan Police Department (MPD). Visit crimecards.dc.gov for more information. This data is shared via an automated process where addresses are geocoded to the District's Master Address Repository and assigned to the appropriate street block. Block locations for some crime points could not be automatically assigned resulting in 0,0 for x,y coordinates. These can be interactively assigned using the MAR Geocoder.On February 1 2020, the methodology of geography assignments of crime data was modified to increase accuracy. From January 1 2020 going forward, all crime data will have Ward, ANC, SMD, BID, Neighborhood Cluster, Voting Precinct, Block Group and Census Tract values calculated prior to, rather than after, anonymization to the block level. This change impacts approximately one percent of Ward assignments.

Records from the Crimes - 2001 to Present dataset for the indicated year.

Please see the description section of the full dataset for further information about the data.

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

The Crime Reports 2024 dataset is a filtered view of the Crime Reports dataset.

Crime Reports dataset: https://datahub.austintexas.gov/d/fdj4-gpfu

2024 NIBRS crime data for St. Louis County Police Department and additional St. Louis County Municipalities. Data is subject to change.

***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.

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.

Drinking alcohol on the street was the most common offense witnessed by people in Mexico in 2024. When asked which type of crime or antisocial activity they had witnessed, over 63 percent of respondents said alcohol consumption. The second most reported kind of crime was drug consumption, whereas 50 percent of the people surveyed said they had seen this type of crime.

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.

This dataset, curated by the Los Angeles Police Department (LAPD), provides detailed records of crime incidents reported across Los Angeles from 2020 to 2023. It reflects the LAPD’s commitment to transparency and public safety, offering insights into crime trends, enforcement actions, and neighborhood-specific challenges. The data serves as a critical resource for researchers, policymakers, and residents to understand urban safety dynamics.

🔗 Source

Directly sourced from the LAPD’s Public Data Portal on Data.gov.

💡 Inspiration

Public Accountability: Empower communities to track crime trends in their neighborhoods.

Policy & Prevention: Aid law enforcement and city planners in resource allocation and hotspot intervention.

Research: Enable academics to study socio-economic factors, seasonal patterns, and the impact of policing strategies.

🔍 Key Attributes

Temporal: Incident date/time (DATE OCC), report date (Date Rptd).

Geospatial: Latitude/longitude 🌐, cross streets, police precinct (AREA NAME).

Crime Details: Type (Crm Cd Desc), weapon used 🔫, premise (e.g., street, store 🏪).

Victim Data: Age, gender ♀️♂️, descent.

Case Status: Arrests 🚨, investigations 🕵️, court outcomes ⚖️.

This 2024 crime data is the list of calls for service that the Syracuse Police Department responded to in 2024. These records does not include rape offenses as well as any crimes that have been sealed by the court. These records are derived from the records management system utilized by the SPD. The data is then anonymized by SPD Crime Analysts weekly.After this data is received weekly from the SPD, this data is then mapped to the approximate location of that incident, using the 100 block level and a Geolocator File from Onondaga County GIS Department. This data is then updated on the Open Data Portal. The points should not be construed to be the exact point this incidents were reported to occur, rather the block where these incident is reported to occur.Crimes are reported to the FBI in two major categories under the Uniform Crime Reports specification: Part 1 and Part 2 crimes. Part 1 crimes include criminal homicide, forcible rape, robbery, aggravated assault, burglary, larceny-theft, and motor vehicle theft. In these records, rape offenses have been excluded due to victim privacy concerns.Part 2 crimes include all other offenses. A more detailed guide to Part 1 crimes is listed below. More details about Part 2 Crimes is listed in the Part 2 Crimes Dataset.When using the data, the date and time provided are when the crime was actually reported. This means that though a larceny might be reported at noon, the actual crime could have happened at 8am, but was not realized until someone noticed hours later. Similarly, if a home break-in happens during a holiday weekend when the owners are out of town, the crime report may not come in until they return home and notice the crime took place previously. The address in the dataset is where the crime occurred. The location is also anonymized to the block level, so a crime that occurred at 123 Main St. will appear as occurring on the 100 block of Main St. This is to protect the privacy of all involved. Finally, information about crimes is fluid, and details about the crime could change.Data DictionaryDate End -Date that the crime was reported. It could have happened earlier. This is in the format of DD-MON-YY (Ex. 01-Jan-22).Time start and time end -Listed in military time (2400) - Burglaries and larcenies are often a time frame.Address- Where the crime occurred. All addresses are in the 100’s because the Syracuse Police Department allows privacy for residents and only lists the block number.Code Defined-Offense names are listed as crime categories group for ease of understanding. There may have been other offenses also, but the one displayed is the highest Unified Crime Reporting (UCR) category.Arrest- Means that there was an arrest, but not necessarily for that crime.Larceny Code- Indicates the type of larceny (Example: From Building or From Motor Vehicle).LAT - The approximate latitude (not actual) that this call for service occurred.LONG- The approximate latitude (not actual) that this call for service occurred.DisclaimerData derived from the Syracuse Police Department record management system, any data not listed is not currently available.Part I Crime DefinitionsCriminal homicide—a.) Murder and non-negligent manslaughter: the willful (non-negligent) killing of one human being by another. Deaths caused by negligence, attempts to kill, assaults to kill, suicides, and accidental deaths are excluded. The program classifies justifiable homicides separately and limits the definition to: (1) the killing of a felon by a law enforcement officer in the line of duty; or (2) the killing of a felon, during the commission of a felony, by a private citizen. b.) Manslaughter by negligence: the killing of another person through gross negligence. Deaths of persons due to their own negligence, accidental deaths not resulting from gross negligence, and traffic fatalities are not included in the category Manslaughter by Negligence.Robbery—The taking or attempting to take anything of value from the care, custody, or control of a person or persons by force or threat of force or violence and/or by putting the victim in fear.Aggravated assault—An unlawful attack by one person upon another for the purpose of inflicting severe or aggravated bodily injury. This type of assault usually is accompanied by the use of a weapon or by means likely to produce death or great bodily harm. Simple assaults are excluded.Burglary(breaking or entering)—The unlawful entry of a structure to commit a felony or a theft. Attempted forcible entry is included.Larceny-theft (except motor vehicle theft)—The unlawful taking, carrying, leading, or riding away of property from the possession or constructive possession of another. Examples are thefts of bicycles, motor vehicle parts and accessories, shoplifting, pocket picking, or the stealing of any property or article that is not taken by force and violence or by fraud. Attempted larcenies are included. Embezzlement, confidence games, forgery, check fraud, etc., are excluded.Motor vehicle theft—The theft or attempted theft of a motor vehicle. A motor vehicle is self-propelled and runs on land surface and not on rails. Motorboats, construction equipment, airplanes, and farming equipment are specifically excluded from this category.Dataset Contact Information:Organization: Syracuse Police Department (SPD)Position: Data Program ManagerCity: Syracuse, NYE-Mail Address: opendata@syrgov.net

This dataset is for RMS Crime Incidents for 2024. For the comprehensive dataset which includes all records please refer to the RMS Crime Incidents dataset. The RMS Crime Incidents dataset consists of crime reports from the Detroit Police Department Records Management System (RMS). This data reflects reported criminal offenses that have occurred in the City of Detroit. Incident-based offense data is extracted from the Detroit Police Department's records management system hourly. This data set contains the most recent data available and is updated anytime DPD sends official crime records contributing to the Michigan Incident Crime Reporting (MICR) or the National Incident Based Reporting systems (reflected by the IBR Date field). It should be noted that some incidents involve the commission of multiple offenses, such as a domestic assault where property was also vandalized. In such cases, there is a row in the dataset for each offense, and the related offenses share a common Crime ID and Report Number.

In 2024, about 64 percent of Americans felt there is more crime now in the United States than there was a year ago. A further 29 percent of survey respondents said that there was less crime in the U.S. in 2024 than there was the year previous.

In January 2024, the most usual type of crime reported in Mexico was domestic violence. In that month, the cases of this type of violence amounted to around 20,814 cases. Regarding property crimes, the highest number of occurrences were vehicle thefts, with nearly 11,887 reported crimes.

Domestic violence Domestic violence stands out as the crime with the highest incidence and, paradoxically, one of the least attended to by the government. Public spending allocated to combat domestic violence has been dismally low, with a value only around 25 percent of the spending on the military. Adding to the concern, this budget has witnessed a consistent decrease each year since 2015. This decline in resources has had severe consequences, leading to a surge in domestic violence crimes, with many resulting in homicides. It's noteworthy that the majority of registered femicides occur within the confines of closed domestic spaces and are often committed by the partners of the victims. This paints a concerning picture of the challenges faced in addressing and preventing domestic violence.

Mexico and the most violent cities in the world
Mexico hosts seven of the most dangerous cities globally, with Celaya ranking as the number one in terms of murder rate, registering a staggering 109.39 homicides per 100,000 inhabitants and the most of these other cities are concentrated in the upper region of the country, highlighting the significant regional variations in safety and security. On the other hand, the capital, Mexico City, has experienced a decreasing trend in crime incidence, with a notable decrease from 2018 to 2022, nonetheless, the crime rate is still high. As a result, crime and insecurity have become the primary concern for nearly half of the country's population, underscoring the pressing need for addressing these issues.

This dataset reflects reported incidents of crime that have occurred in the City of Chicago over the past year, minus the most recent seven days of data. 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. Any use of the information for commercial purposes is strictly prohibited. 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.

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

This dataset includes all criminal offenses reported to the Colorado Springs Police Department. Each case report (incident) may have several offenses. Each offense may have multiple suspects and/or victims.

Important: This dataset provided by CSPD does not apply the same counting rules as official data reported to the Colorado Bureau of Investigations and the Federal Bureau of Investigation. This means comparisons to those datasets would be inaccurate.

This dataset contains detailed records of reported criminal incidents in Washington, D.C., providing valuable insights for spatial and temporal crime analysis. Potential Use Cases Exploratory Data Analysis (EDA) of crime patterns. Spatial econometric modeling and geospatial analysis. Urban planning and public safety strategies. Time-series analysis of criminal activity.