***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.

Crime data assembled by census block group for the MSA from the Applied Geographic Solutions' (AGS) 1999 and 2005 'CrimeRisk' databases distributed by the Tetrad Computer Applications Inc. CrimeRisk is the result of an extensive analysis of FBI crime statistics. Based on detailed modeling of the relationships between crime and demographics, CrimeRisk provides an accurate view of the relative risk of specific crime types at the block group level. Data from 1990 - 1996,1999, and 2004-2005 were used to compute the attributes, please refer to the 'Supplemental Information' section of the metadata for more details. Attributes are available for two categories of crimes, personal crimes and property crimes, along with total and personal crime indices. Attributes for personal crimes include murder, rape, robbery, and assault. Attributes for property crimes include burglary, larceny, and mother vehicle theft. 12 block groups have no attribute information. CrimeRisk is a block group and higher level geographic database consisting of a series of standardized indexes for a range of serious crimes against both persons and property. It is derived from an extensive analysis of several years of crime reports from the vast majority of law enforcement jurisdictions nationwide. The crimes included in the database are the "Part I" crimes and include murder, rape, robbery, assault, burglary, theft, and motor vehicle theft. These categories are the primary reporting categories used by the FBI in its Uniform Crime Report (UCR), with the exception of Arson, for which data is very inconsistently reported at the jurisdictional level. Part II crimes are not reported in the detail databases and are generally available only for selected areas or at high levels of geography. In accordance with the reporting procedures using in the UCR reports, aggregate indexes have been prepared for personal and property crimes separately, as well as a total index. While this provides a useful measure of the relative "overall" crime rate in an area, it must be recognized that these are unweighted indexes, in that a murder is weighted no more heavily than a purse snatching in the computation. For this reason, caution is advised when using any of the aggregate index values. The block group boundaries used in the dataset come from TeleAtlas's (formerly GDT) Dynamap data, and are consistent with all other block group boundaries in the BES geodatabase. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

The World Crime Index 2023 dataset provides records of crime rankings for cities worldwide, along with associated information on their respective countries. This dataset is focused on the year 2023 and includes the following columns:

• Rank: The ranking of a city based on its crime index, with lower numbers indicating higher crime rates.
• City: The name of the city for which crime data is reported.
• Country: The country to which the city belongs.
• Crime Index: A numerical value representing the overall level of crime in a city, with higher values indicating higher crime rates.
• Safety Index: An index indicating the general level of safety in a city, derived from factors such as infrastructure, healthcare, and political stability.

This dataset enables data scientists to analyze and compare crime rankings across cities and countries, providing insights into the relative safety levels of different locations in the year 2023. By leveraging this dataset, researchers can conduct exploratory data analysis, perform comparative studies, and identify potential trends and patterns in crime rates globally for the specified year.

Crime isn't a topic most people want to use mental energy to think about. We want to avoid harm, protect our loved ones, and hold on to what we claim is ours. So how do we remain vigilant without digging too deep into the filth that is crime? Data, of course. The focus of our study is to explore possible trends between crime and communities in the city of Calgary. Our purpose is visualize Calgary criminal behaviour in order to help increase awareness for both citizens and law enforcement. Through the use of our visuals, individuals can make more informed decisions to improve the overall safety of their lives. Some of the main concerns of the study include: how crime rates increase with population, which areas in Calgary have the most crime, and if crime adheres to time-sensative patterns.

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.

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.

In 2023, the state with the highest crime rate in the United States per 100,000 inhabitants was New Mexico. That year, the crime rate was ******** crimes per 100,000 people. In comparison, New Hampshire had the lowest crime rate at ****** crimes per 100,000 people. Crime rate The crime rate in the United States has generally decreased over time. There are several factors attributed to the decrease in the crime rate across the United States. An increase in the number of police officers and an increase in income are some of the reasons for a decrease in the crime rate. Unfortunately, people of color have been disproportionately affected by crime rates, as they are more likely to be arrested for a crime versus a white person. Crime rates regionally The District of Columbia had the highest rate of reported violent crimes in the United States in 2023 per 100,000 inhabitants. The most common crime clearance type in metropolitan counties in the United States in 2020 was murder and non-negligent manslaughter. The second most dangerous city in the country in 2020 was Detroit. Detroit has faced severe levels of economic and demographic declines in the past years. Not only has the population decreased, the city has filed for bankruptcy. Despite the median household income increasing, the city still struggles financially.

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.

In the late 1970s, the Rand Corporation pioneered a method of collecting crime rate statistics. They obtained reports of offending behavior--types and frequencies of crimes committed--directly from offenders serving prison sentences. The current study extends this research by exploring the extent to which variation in the methodological approach affects prisoners' self-reports of criminal activity. If the crime rates reported in this survey remained constant across methods, perhaps one of the new techniques developed would be easier and/or less expensive to administer. Also, the self-reported offending rate data for female offenders in this collection represents the first time such data has been collected for females. Male and female prisoners recently admitted to the Diagnostic Unit of the Colorado Department of Corrections were selected for participation in the study. Prisoners were given one of two different survey instruments, referred to as the long form and short form. Both questionnaires dealt with the number of times respondents committed each of eight types of crimes during a 12-month measurement period. The crimes of interest were burglary, robbery, assault, theft, auto theft, forgery/credit card and check-writing crimes, fraud, and drug dealing. The long form of the instrument focused on juvenile and adult criminal activity and covered the offender's childhood and family. It also contained questions about the offender's rap sheet as one of the bases for validating the self-reported data. The crime count sections of the long form contained questions about motivation, initiative, whether the offender usually acted alone or with others, and if the crimes recorded included crimes against people he or she knew. Long-form data are given in Part 1. The short form of the survey had fewer or no questions compared with the long form on areas such as the respondent's rap sheet, the number of crimes committed as a juvenile, the number of times the respondent was on probation or parole, the respondent's childhood experiences, and the respondent's perception of his criminal career. These data are contained in Part 2. In addition, the surveys were administered under different conditions of confidentiality. Prisoners given what were called "confidential" interviews had their names identified with the survey. Those interviewed under conditions of anonymity did not have their names associated with the survey. The short forms were all administered anonymously, while the long forms were either anonymous or confidential. In addition to the surveys, data were collected from official records, which are presented in Part 3. The official record data collection form was designed to collect detailed criminal history information, particularly during the measurement period identified in the questionnaires, plus a number of demographic and drug-use items. This information, when compared with the self-reported offense data from the measurement period in both the short and long forms, allows a validity analysis to be performed.

Incident-based crime statistics (actual incidents, rate per 100,000 population, percentage change in rate, unfounded incidents, percent unfounded, total cleared, cleared by charge, cleared otherwise, persons charged, adults charged, youth charged / not charged), by detailed violations (violent, property, traffic, drugs, other Federal Statutes), police services in Ontario, 1998 to 2023.

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

Suburb-based crime statistics for crimes against the person and crimes against property. The Crime statistics datasets contain all offences against the person and property that were reported to police in that respective financial year. The Family and Domestic Abuse-related offences datasets are a subset of this, in that a separate file is presented for these offences that were flagged as being of a family and domestic abuse nature for that financial year. Consequently the two files for the same financial year must not be added together.

Recorded crime figures for CSP areas. Number of offences for the last two years, percentage change, and rates per 1,000 population for the latest year.

This dataset reflects reported incidents of crime (with the exception of murders where data exists for each victim) 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. 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://bit.ly/rk5Tpc.

Disclaimer: Crime Responses is provided by the Gainesville Police Department (GPD) to document initial details surrounding an incident to which GPD officers respond. This dataset contains crime incidents from 2011 to present and includes a reduced set of fields focused on capturing the type of incident as well when and where an incident occurred. The Incident location addresses have been rounded off and are not the exact location due to the constitutional amendment known as "Marsy's Law".

In 2021, Florida reporting of crime data began a transition from Summary Reporting System (SRS) to National Incident-Based Reporting System (NIBRS), causing an effect on crime statistics reported by Law Enforcement Agencies such as the Gainesville Police Department who made this transition on November 16, 2021. The effect would be an increase in crime due to the elimination of the SRS Hierarchy Rule which collected only the most serious offense in an incident while NIBRS will now capture up to 10 offenses per incident and specifies more offense categories than SRS. The inclusion of these crimes, particularly property crimes, will reflect an increase in crime when switching from SRS reporting to NIBRS' reporting. The apparent increase (usually not greater than 2.7%) is simply due to the difference between how crimes are counted in NIBRS versus the SRS and its application of the Hierarchy Rule. More information regarding NIBRS effect on crime statistics can be found on the following link: https://ucr.fbi.gov/nibrs/2014/resource-pages/effects_of_nibrs_on_crime_statistics_final.pdf.

Incident-based crime statistics (actual incidents, rate per 100,000 population, percentage change in rate, unfounded incidents, percent unfounded, total cleared, cleared by charge, cleared otherwise, persons charged, adults charged, youth charged / not charged), by detailed violations (violent, property, traffic, drugs, other Federal Statutes), Canada, provinces, territories, Census Metropolitan Areas and Canadian Forces Military Police, 1998 to 2023.

AUSTIN POLICE DEPARTMENT DATA DISCLAIMER Please read and understand the following information.

This dataset contains a record of incidents that the Austin Police Department responded to and wrote a report. Please note one incident may have several offenses associated with it, but this dataset only depicts the highest level offense of that incident. Data is from 2003 to present. This dataset is updated weekly. Understanding the following conditions will allow you to get the most out of the data provided. Due to the methodological differences in data collection, different data sources may produce different results. This database is updated weekly, and a similar or same search done on different dates can produce different results. Comparisons should not be made between numbers generated with this database to any other official police reports. Data provided represents only calls for police service where a report was written. Totals in the database may vary considerably from official totals following investigation and final categorization. Therefore, the data should not be used for comparisons with Uniform Crime Report statistics. The Austin Police Department does not assume any liability for any decision made or action taken or not taken by the recipient in reliance upon any information or data provided. Pursuant to section 552.301 (c) of the Government Code, the City of Austin has designated certain addresses to receive requests for public information sent by electronic mail. For requests seeking public records held by the Austin Police Department, please submit by utilizing the following link: https://apd-austintx.govqa.us/WEBAPP/_rs/(S(0auyup1oiorznxkwim1a1vpj))/supporthome.aspx

Dundee City's crime rate of 847 crimes per 10,000 people was the highest of any region of Scotland in 2023/24. The rate for the whole of Scotland was 550 per 10,000 people, which appears to be driven by low crime in places such as the Orkney and Shetland Islands, with almost all Scottish cities reporting higher than average crime rates. In Glasgow, Scotland's largest city, the crime rate was 812 crimes per 10,000 people, while in the Scottish capital, Edinburgh, the crime rate was 679 per 10,000 population. Comparisons with the rest of the UK When compared with the rest of the United Kingdom, Scotland has experienced a noticeable decline in its overall crime rate. In 2008/09 for example, Scotland's crime rate was higher than that of England and Wales, as well as Northern Ireland, the other two jurisdictions in the UK. In 2022/23, however, Scotland's crime rate was the lowest in the UK, with the crime rate in England and Wales rising noticeably during the same period. Scotland's homicide rate has also fallen, from being the highest in the UK in 2002/03, to the lowest as of 2022/23. Theft and fraud drive recent crime uptick There was a slight increase in the number of crimes recorded by the Scottish police in 2023/24, when compared with the previous year. Although many other types of crimes declined during this reporting year, the number of theft offences has increased, reaching 111,054 offences in 2023/24. Fraud crime has also increased significantly in recent years, with 16,789 offences in 2022/23, compared with just 6,913 in 2014/15. The recent uptick in fraud and theft offences is also reflected in the jurisdiction England and Wales.

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