The FBI's Uniform Crime Reporting (UCR) system accepts voluntary crime data from nearly 17,000 domestic law enforcement agencies. This data, collected since the 1920s, is the cornerstone for national crime statistics and is used by law enforcement, resea

In response to a growing concern about hate crimes, the United States Congress enacted the Hate Crime Statistics Act of 1990. The Act requires the attorney general to establish guidelines and collect, as part of the Uniform Crime Reporting (UCR) Program, data "about crimes that manifest evidence of prejudice based on race, religion, sexual orientation, or ethnicity, including where appropriate the crimes of murder and non-negligent manslaughter, forcible rape, aggravated assault, simple assault, intimidation, arson, and destruction, damage or vandalism of property." Hate crime data collection was required by the Act to begin in calendar year 1990 and to continue for four successive years. In September 1994, the Violent Crime Control and Law Enforcement Act amended the Hate Crime Statistics Act to add disabilities, both physical and mental, as factors that could be considered a basis for hate crimes. Although the Act originally mandated data collection for five years, the Church Arson Prevention Act of 1996 amended the collection duration "for each calendar year," making hate crime statistics a permanent addition to the UCR program. As with the other UCR data, law enforcement agencies contribute reports either directly or through their state reporting programs. Information contained in the data includes number of victims and offenders involved in each hate crime incident, type of victims, bias motivation, offense type, and location type.

The study was a comprehensive analysis of felonious killings of officers. The purposes of the study were (1) to analyze the nature and circumstances of incidents of felonious police killings and (2) to analyze trends in the numbers and rates of killings across different types of agencies and to explain these differences. For Part 1, Incident-Level Data, an incident-level database was created to capture all incidents involving the death of a police officer from 1983 through 1992. Data on officers and incidents were collected from the Law Enforcement Officers Killed and Assaulted (LEOKA) data collection as coded by the Uniform Crime Reporting (UCR) program. In addition to the UCR data, the Police Foundation also coded information from the LEOKA narratives that are not part of the computerized LEOKA database from the FBI. For Part 2, Agency-Level Data, the researchers created an agency-level database to research systematic differences among rates at which law enforcement officers had been feloniously killed from 1977 through 1992. The investigators focused on the 56 largest law enforcement agencies because of the availability of data for explanatory variables. Variables in Part 1 include year of killing, involvement of other officers, if the officer was killed with his/her own weapon, circumstances of the killing, location of fatal wounds, distance between officer and offender, if the victim was wearing body armor, if different officers were killed in the same incident, if the officer was in uniform, actions of the killer and of the officer at entry and final stage, if the killer was visible at first, if the officer thought the killer was a felon suspect, if the officer was shot at entry, and circumstances at anticipation, entry, and final stages. Demographic variables for Part 1 include victim's sex, age, race, type of assignment, rank, years of experience, agency, population group, and if the officer was working a security job. Part 2 contains variables describing the general municipal environment, such as whether the agency is located in the South, level of poverty according to a poverty index, population density, percent of population that was Hispanic or Black, and population aged 15-34 years old. Variables capturing the crime environment include the violent crime rate, property crime rate, and a gun-related crime index. Lastly, variables on the environment of the police agencies include violent and property crime arrests per 1,000 sworn officers, percentage of officers injured in assaults, and number of sworn officers.

The Uniform Crime Reporting Program Data, Police Employee Data, 2010 file contains monthly data on felonious or accidental killings and assaults upon United States law enforcement officers acting in the line of duty. The Federal Bureau of Investigation (FBI) assembled the data and processed them from UCR Master Police Employee (LEOKA) data tapes. Each agency record included in the file includes the following summary variables: state code, population group code, geographic division, Metropolitan Statistical Area code, and agency name. These variables afford considerable flexibility in creating subsets or aggregations of the data. Since 1930, the Federal Bureau of Investigation has compiled the Uniform Crime Reports (UCR) to serve as a periodic nationwide assessment of reported crimes not available elsewhere in the criminal justice system. Each year, this information is reported in four types of files: (1) Offenses Known and Clearances by Arrest, (2) Property Stolen and Recovered, (3) Supplementary Homicide Reports (SHR), and (4) Police Employee (LEOKA) Data. The Police Employee (LEOKA) Data provide information about law enforcement officers killed or assaulted (hence the acronym, LEOKA) in the line of duty. The variables created from the LEOKA forms provide in-depth information on the circumstances surrounding killings or assaults, including type of call answered, type of weapon used, and type of patrol the officers were on.

Context

Introduction: The dataset used for this experiment is real and authentic. The dataset is acquired from UCI machine learning repository website [13]. The title of the dataset is ‘Crime and Communities’. It is prepared using real data from socio-economic data from 1990 US Census, law enforcement data from the 1990 US LEMAS survey, and crimedata from the 1995 FBI UCR [13]. This dataset contains a total number of 147 attributes and 2216 instances.

The per capita crimes variables were calculated using population values included in the 1995 FBI data (which differ from the 1990 Census values).

Content

The variables included in the dataset involve the community, such as the percent of the population considered urban, and the median family income, and involving law enforcement, such as per capita number of police officers, and percent of officers assigned to drug units. The crime attributes (N=18) that could be predicted are the 8 crimes considered 'Index Crimes' by the FBI)(Murders, Rape, Robbery, .... ), per capita (actually per 100,000 population) versions of each, and Per Capita Violent Crimes and Per Capita Nonviolent Crimes)

predictive variables : 125 non-predictive variables : 4 potential goal/response variables : 18

Acknowledgements

http://archive.ics.uci.edu/ml/datasets/Communities%20and%20Crime%20Unnormalized

U. S. Department of Commerce, Bureau of the Census, Census Of Population And Housing 1990 United States: Summary Tape File 1a & 3a (Computer Files),

U.S. Department Of Commerce, Bureau Of The Census Producer, Washington, DC and Inter-university Consortium for Political and Social Research Ann Arbor, Michigan. (1992)

U.S. Department of Justice, Bureau of Justice Statistics, Law Enforcement Management And Administrative Statistics (Computer File) U.S. Department Of Commerce, Bureau Of The Census Producer, Washington, DC and Inter-university Consortium for Political and Social Research Ann Arbor, Michigan. (1992)

U.S. Department of Justice, Federal Bureau of Investigation, Crime in the United States (Computer File) (1995)

Inspiration

Your data will be in front of the world's largest data science community. What questions do you want to see answered?

Data available in the dataset may not act as a complete source of information for identifying factors that contribute to more violent and non-violent crimes as many relevant factors may still be missing.

However, I would like to try and answer the following questions answered.

1. Analyze if number of vacant and occupied houses and the period of time the houses were vacant had contributed to any significant change in violent and non-violent crime rates in communities

2. How has unemployment changed crime rate(violent and non-violent) in the communities?

3. Were people from a particular age group more vulnerable to crime?

4. Does ethnicity play a role in crime rate?

5. Has education played a role in bringing down the crime rate?

A. SUMMARY These data represent hate crimes reported by the SFPD to the California Department of Justice. Read the detailed overview of this dataset here. What is a Hate Crime? A hate crime is a crime against a person, group, or property motivated by the victim's real or perceived protected social group. An individual may be the victim of a hate crime if they have been targeted because of their actual or perceived: (1) disability, (2) gender, (3) nationality, (4) race or ethnicity, (5) religion, (6) sexual orientation, and/or (7) association with a person or group with one or more of these actual or perceived characteristics. Hate crimes are serious crimes that may result in imprisonment or jail time. B. HOW THE DATASET IS CREATED How is a Hate Crime Processed? Not all prejudice incidents including the utterance of hate speech rise to the level of a hate crime. The U.S. Constitution allows hate speech if it does not interfere with the civil rights of others. While these acts are certainly hurtful, they do not rise to the level of criminal violations and thus may not be prosecuted. When a prejudice incident is reported, the reporting officer conducts a preliminary investigation and writes a crime or incident report. Bigotry must be the central motivation for an incident to be determined to be a hate crime. In that report, all facts such as verbatims or statements that occurred before or after the incident and characteristics such as the race, ethnicity, sex, religion, or sexual orientations of the victim and suspect (if known) are included. To classify a prejudice incident, the San Francisco Police Department’s Hate Crimes Unit of the Special Investigations Division conducts an analysis of the incident report to determine if the incident falls under the definition of a “hate crime” as defined by state law. California Penal Code 422.55 - Hate Crime Definition C. UPDATE PROCESS These data are updated monthly. D. HOW TO USE THIS DATASET This dataset includes the following information about each incident: the hate crime offense, bias type, location/time, and the number of hate crime victims and suspects. The data presented mirrors data published by the California Department of Justice, albeit at a higher frequency. The publishing of these data meet requirements set forth in PC 13023. E. RELATED DATASETS California Department of Justice - Hate Crimes Info California Department of Justice - Hate Crimes Data

Since 1930, the Federal Bureau of Investigation has compiled the Uniform Crime Reports (UCR) to serve as a periodic nationwide assessment of reported crimes not available elsewhere in the criminal justice system. Each year, this information is reported in four types of files: (1) Offenses Known and Clearances by Arrest, (2) Property Stolen and Recovered, (3) Supplementary Homicide Reports (SHR), and (4) Police Employee (LEOKA) Data. The Supplementary Homicide Reports provide incident-based information on criminal homicides reported to the police. These homicides consist of murders, non-negligent manslaughter, and justifiable homicides. The data, provided monthly by UCR agencies, contain information describing the victim of the homicide, the offender, and the relationship between victim and offender.

Federal Bureau of Investigation, Department of Justice - Extraction of crime related data from the FBI's Uniform Crime Reporting (UCR) Program

Abstract (en): Since 1930, the Federal Bureau of Investigation has compiled the Uniform Crime Reports (UCR) to serve as a periodic nationwide assessment of reported crimes not available elsewhere in the criminal justice system. Each year, this information is reported in four types of files: (1) Offenses Known and Clearances by Arrest, (2) Property Stolen and Recovered, (3) Supplementary Homicide Reports (SHR), and (4) Police Employee (LEOKA) Data. The Police Employee (LEOKA) Data provide information about law enforcement officers killed or assaulted (hence the acronym, LEOKA) in the line of duty. The variables created from the LEOKA forms provide in-depth information on the circumstances surrounding killings or assaults, including type of call answered, type of weapon used, and type of patrol the officers were on. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Performed consistency checks.; Checked for undocumented or out-of-range codes.. Law enforcement officers killed or assaulted as reported by law enforcement agencies. 2005-11-04 On 2005-03-14 new files were added to one or more datasets. These files included additional setup files as well as one or more of the following: SAS program, SAS transport, SPSS portable, and Stata system files. The metadata record was revised 2005-11-04 to reflect these additions.2001-10-31 The SPSS data definition statements were replaced to correct inaccurate title and study number information. Funding insitution(s): United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics. The codebook for this collection is provided as a Portable Document Format (PDF) file. The PDF file format was developed by Adobe Systems Incorporated and can be accessed using PDF reader software, such as the Adobe Acrobat Reader. Information on how to obtain a copy of the Acrobat Reader is provided on the ICPSR Web site.

These data provide incident-level information on criminal homicides including date, location, circumstances, and method of offense, as well as demographic characteristics of victims and perpetrators and the relationship between the two. For this dataset, the original Uniform Crime Reports data were completely restructured into a nested, or hierarchical, form with repeating records. Specifically, the file contains one record for each agency per year (record type "A"), nested within which is one record per incident (record type "I"). Victim records (record type "V") are in turn nested within incident records, and offender data are repeated for all offenders on each victim record. Part 3, ORI List, contains Originating Agency Identifier (ORI) codes used by the FBI and the corresponding agency name.

As a first step in understanding law enforcement agencies' use and knowledge of crime mapping, the Crime Mapping Research Center (CMRC) of the National Institute of Justice conducted a nationwide survey to determine which agencies were using geographic information systems (GIS), how they were using them, and, among agencies that were not using GIS, the reasons for that choice. Data were gathered using a survey instrument developed by National Institute of Justice staff, reviewed by practitioners and researchers with crime mapping knowledge, and approved by the Office of Management and Budget. The survey was mailed in March 1997 to a sample of law enforcement agencies in the United States. Surveys were accepted until May 1, 1998. Questions asked of all respondents included type of agency, population of community, number of personnel, types of crimes for which the agency kept incident-based records, types of crime analyses conducted, and whether the agency performed computerized crime mapping. Those agencies that reported using computerized crime mapping were asked which staff conducted the mapping, types of training their staff received in mapping, types of software and computers used, whether the agency used a global positioning system, types of data geocoded and mapped, types of spatial analyses performed and how often, use of hot spot analyses, how mapping results were used, how maps were maintained, whether the department kept an archive of geocoded data, what external data sources were used, whether the agency collaborated with other departments, what types of Department of Justice training would benefit the agency, what problems the agency had encountered in implementing mapping, and which external sources had funded crime mapping at the agency. Departments that reported no use of computerized crime mapping were asked why that was the case, whether they used electronic crime data, what types of software they used, and what types of Department of Justice training would benefit their agencies.

The National Incident-Based Reporting System (NIBRS) is a part of the Uniform Crime Reporting Program (UCR), administered by the Federal Bureau of Investigation (FBI). In the late 1970s, the law enforcement community called for a thorough evaluative study of the UCR with the objective of recommending an expanded and enhanced UCR program to meet law enforcement needs into the 21st century. The FBI provided its support, formulating a comprehensive redesign effort. Following a multiyear study and in consultation with local and state law enforcement executives, new guidelines for the Uniform Crime Reports were created. The National Incident-Based Reporting System (NIBRS) is being implemented to meet these guidelines. NIBRS data are archived at ICPSR as 13 separate data files, which may be merged by using linkage variables. The data focus on a variety of aspects of a crime incident. The Batch Header Segment (Parts 1-3) separates and identifies individual police agencies by Originating Agency Identifier (ORI). Batch Header information, which is contained on three records for each ORI, includes agency name, geographic location, and population of the area. Part 4, Administrative Segment, offers data on the incident itself (date and time). Each crime incident is delineated by one administrative segment record. Also provided are Part 5, Offense Segment (offense type, location, weapon use, and bias motivation), Part 6, Property Segment (type of property loss, property description, property value, drug type and quantity), Part 7, Victim Segment (age, sex, race, ethnicity, and injuries), Part 8, Offender Segment (age, sex, and race), and Part 9, Arrestee Segment (arrest date, age, sex, race, and weapon use). Part 10, Group B Arrest Report Segment, includes arrestee data for Group B crimes. Window Segments files (Parts 11-13) pertain to incidents for which the complete Group A Incident Report was not submitted to the FBI. In general, a Window Segment record will be generated if the incident occurred prior to January 1 of the previous year or if the incident occurred prior to when the agency started NIBRS reporting. As with UCR, participation in NIBRS is voluntary on the part of law enforcement agencies. The data are not a representative sample of crime in the United States. For 1998, 17 states, fully or partially participating in NIBRS, were included in the dataset.

Since 1930, the Federal Bureau of Investigation has compiled the Uniform Crime Reports (UCR) to serve as periodic nationwide assessments of reported crimes not available elsewhere in the criminal justice system. Law enforcement agencies contribute reports either directly or through their state reporting programs. Each year, summary data are reported in four types of files: (1) Offenses Known and Clearances by Arrest, (2) Property Stolen and Recovered, (3) Supplementary Homicide Reports (SHR), and (4) Police Employee (LEOKA) Data. The Offenses Known and Clearances by Arrest data files include monthly data on the number of Crime Index offenses reported and the number of offenses cleared by arrest or other means. The counts include all reports of Index crimes (excluding arson) received from victims, officers who discovered infractions, or other sources.

The Tempe Police Department prides itself in its continued efforts to reduce harm within the community and is providing this dataset on hate crime incidents that occur in Tempe.This data compares hate crimes in the City of Tempe and the State of Arizona. The data source is from the Federal Bureau of Investigation (FBI) and the Department of Justice (DOJ) at both the national and state level: FBIhttps://www.fbi.gov/services/cjis/ucr/publications#Hate-Crime%20StatisticsDOJhttps://www.justice.gov/hatecrimes/facts-and-statisticsInformation about Tempe Police Department's collection and reporting process for possible hate crimes is included in the story map Projecting Our Community form Hate at https://storymaps.arcgis.com/stories/a963e97ca3494bfc8cd66d593eebabafAdditional InformationSource: Federal Bureau of Investigation (FBI) and the Department of Justice (DOJ) https://www.fbi.gov/services/cjis/ucr/publications#Hate-Crime%20Statistics, https://www.justice.gov/hatecrimes/facts-and-statisticsContact: Angelique BeltranContact E-Mail: angelique_beltran@tempe.govData Source Type: TabularPreparation Method: Data extracted from sources, reformatted in Excel and uploaded.Publish Frequency: AnnualPublish Method: ManualData Dictionary

The Crime Statistics Agency (CSA) is responsible for processing, analysing and publishing Victorian crime statistics, independent of Victoria Police.\r
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The CSA aims to provide an efficient and transparent information service to assist and inform policy makers, researchers and the Victorian public.\r
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The legal basis for the Crime Statistics Agency is the Crime Statistics Act 2014, which provides for the publication and release of crime statistics, research into crime trends, and the employment of a Chief Statistician for that purpose.\r
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Under the provisions of the Act, the Chief Statistician is empowered to receive law enforcement data from the Chief Commissioner of Police and is responsible for publishing and releasing statistical information relating to crime in Victoria.\r
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The number and rate of recorded offences in Victoria.\r
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Data Classification - http://www.crimestatistics.vic.gov.au/home/about+the+data/classifications/\r
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Glossary and Data Dictionary - http://www.crimestatistics.vic.gov.au/home/about+the+data/data+dictionary/\r

Since 1930, the Federal Bureau of Investigation has compiled the Uniform Crime Reports (UCR) to serve as periodic nationwide assessments of reported crime not available elsewhere in the criminal justice system. Each year, this information is reported in four types of files: (1) Offenses Known and Clearances by Arrest, (2) Property Stolen and Recovered, (3) The Supplementary Homicide Reports (SHR), and (4) Police Employee (LEOKA) data. This collection contains Offenses Known and Clearances by Arrest data and includes monthly information on the number of Crime Index offenses reported, the number of offenses cleared by arrest or other means, and the number of adults and juveniles arrested in cities with populations over 250,000. The counts include all reports of Index Crimes (excluding arson) received from victims, from officers who discovered infractions, or from other sources.

The National Crime Victimization Survey (NCVS) Series, previously called the National Crime Surveys (NCS), has been collecting data on personal and household victimization through an ongoing survey of a nationally-representative sample of residential addresses since 1973. The NCVS was designed with four primary objectives: (1) to develop detailed information about the victims and consequences of crime, (2) to estimate the number and types of crimes not reported to the police, (3) to provide uniform measures of selected types of crimes, and (4) to permit comparisons over time and types of areas. The survey categorizes crimes as "personal" or "property." Personal crimes include rape and sexual attack, robbery, aggravated and simple assault, and purse-snatching/pocket-picking, while property crimes include burglary, theft, motor vehicle theft, and vandalism. Each respondent is asked a series of screen questions designed to determine whether she or he was victimized during the six-month period preceding the first day of the month of the interview. A "household respondent" is also asked to report on crimes against the household as a whole (e.g., burglary, motor vehicle theft). The data include type of crime, month, time, and location of the crime, relationship between victim and offender, characteristics of the offender, self-protective actions taken by the victim during the incident and results of those actions, consequences of the victimization, type of property lost, whether the crime was reported to police and reasons for reporting or not reporting, and offender use of weapons, drugs, and alcohol. Basic demographic information such as age, race, gender, and income is also collected, to enable analysis of crime by various subpopulations. This version of the NCVS, referred to as the collection year, contains records from interviews conducted in the 12 months of the given year.

These data provide information on the number of arrests reported to the Federal Bureau of Investigation's Uniform Crime Reporting (UCR) Program each year by police agencies in the United States. These arrest reports provide data on 43 offenses including violent crime, drug use, gambling, and larceny. The data received by ICPSR were structured as a hierarchical file containing, per reporting police agency: an agency header record, and 1 to 43 detail offense records containing the counts of arrests by age, sex, and race for a particular offense. ICPSR restructured the original data to logical record length format with the agency header record variables copied onto the detail records. Consequently, each record contains arrest counts for a particular agency-offense.

This subsample of the national crime surveys consists of data on personal and household victimization for persons aged 12 and older in 26 major United States cities in the period 1972-1975. The National Crime Surveys were designed by the Bureau of Justice Statistics to meet three primary objectives: (1) to develop detailed information about the victims and consequences of crime, (2) to estimate the numbers and types of crimes not reported to police, and (3) to provide uniform measures of selected types of crimes in order to permit reliable comparisons over time and between areas. The surveys provide measures of victimization on the basis of six crimes (including attempts): rape, robbery, assault, burglary, larceny, and motor vehicle theft. The total National Crime Survey employed two distinct samples: a National Sample, and a Cities Sample. The cities sample consists of information about victimization in 26 major United States cities. The data collection was conducted by the United States Census Bureau, initial processing of the data and documentation was performed by the Data Use and Access Laboratories (DUALabs), and subsequent processing was performed by the ICPSR under grants from the Bureau of Justice Statistics (BJS). This Cities Attitude Sub-Sample study also includes information on personal attitudes and perceptions of crime and the police, the fear of crime, and the effect of this fear on behavioral patterns such as choice of shopping areas and places of entertainment. Data are provided on reasons for respondents' choice of neighborhood, and feelings about neighborhood, crime, personal safety, and the local police. Also specified are date, type, place, and nature of the incidents, injuries suffered, hospital treatment and medical expenses incurred, offender's personal profile, relationship of offender to victim, property stolen and value, items recovered and value, insurance coverage, and police report and reasons if incident was not reported to the police. Demographic items cover age, sex, marital status, race, ethnicity, education, employment, family income, and previous residence and reasons for migrating. This subsample is a one-half random sample of the Complete Sample, NATIONAL CRIME SURVEYS: CITIES, 1972-1975 (ICPSR 7658), in which an attitude questionnaire was administered. The subsample contains data from the same 26 cities that were used in the Complete Sample.

Since 1930, the Federal Bureau of Investigation has compiled the Uniform Crime Reports (UCR) to serve as periodic nationwide assessments of reported crimes not available elsewhere in the criminal justice system. By 1985, there were approximately 17,000 law enforcement agencies contributing reports either directly or through their state reporting programs. Each year, this information is reported in four types of files: (1) Offenses Known and Clearances by Arrest, (2) Property Stolen and Recovered, (3) Supplementary Homicide Reports (SHR), and (4) Police Employee (LEOKA) Data. Offenses Known and Clearances by Arrest data files include monthly data on the number of Crime Index offenses reported and the number of offenses cleared by arrest or other means. The counts include all reports of Index Crimes (excluding arson) received from victims, officers who discovered infractions, or other sources. The Property Stolen and Recovered data are collected on a monthly basis by all UCR contributing agencies. These data, aggregated at the agency level, report on the nature of the crime, the monetary value of the property stolen, and the type of property stolen. Similar information regarding recovered property is also included in the data. The Supplementary Homicide Reports provide incident-based information on criminal homicides. Further, the data, provided monthly by UCR agencies, contain information describing the victim of the homicide, the offender, and the relationship between victim and offender. The Police Employee (LEOKA) Data provide information about law enforcement officers killed or assaulted (hence the acronym, LEOKA) in the line of duty. The variables created from the LEOKA forms provide in-depth information on the circumstances surrounding killings or assaults, including type of call answered, type of weapon used, and type of patrol the officers were on.