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.
Investigator(s): United Nations Office at Vienna, R.W. Burnham, Helen Burnham, Bruce DiCristina, and Graeme Newman The United Nations Surveys of Crime Trends and Operations of Criminal Justice Systems (formerly known as the United Nations World Crime Surveys) series was begun in 1978 and is comprised of five quinquennial surveys covering the years 1970-1975, 1975-1980, 1980-1986, 1986-1990, and 1990-1994. The project was supported by the United States Bureau of Justice Statistics, and conducted under the auspices of the United Nations Criminal Justice and Crime Prevention Branch, United Nations Office in Vienna. Data gathered on crime prevention and criminal justice among member nations provide information for policy development and program planning. The main objectives of the survey include: to conduct a more focused inquiry into the incidence of crime worldwide, to improve knowledge about the incidence of reported crime in the global development perspective and also international understanding of effective ways to counteract crime, to improve the dissemination globally of the information collected, to facilitate an overview of trends and interrelationships among various parts of the criminal justice system so as to promote informed decision-making in its administration, nationally and cross-nationally, and to serve as an instrument for strengthening cooperation among member states by putting the review and analysis of national crime-related data in a broader context. The surveys also provide a valuable source of charting trends in crime and criminal justice over two decades.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Analysis of ‘Uniform Crime Reporting Statistics - 2012’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/4f862b94-8345-4f7a-88b8-c88baaea19ab on 26 January 2022.
--- Dataset description provided by original source is as follows ---
A data extract of crime in Connecticut, by reporting agency from Uniform Crime Reporting Statistics - UCR Data Online. The UCR Program collects statistics on violent crime (murder and nonnegligent manslaughter, forcible rape, robbery, and aggravated assault) and property crime (burglary, larceny-theft, and motor vehicle theft). Notes: When data are unavailable, the cells are blank or the year is not presented. Variations in population coverage and reporting practices may cause differences in reporting from year to year. (See definitions) MSA and non-MSA county populations are not available. Rates are the number of reported offenses per 100,000 population. Crime rates are not available for agencies that report data for less than 12 months of a year. Sources: FBI, Uniform Crime Reports, prepared by the National Archive of Criminal Justice Data
--- Original source retains full ownership of the source dataset ---
https://data.syr.gov/pages/termsofusehttps://data.syr.gov/pages/termsofuse
This 2023 crime data is a list of Part 2 Offenses reported to the Syracuse Police Department (SPD), that were reported to have occurred in 2022. These records do not include rape offenses or 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 (UCR) 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 SPD records, rape offenses have been excluded due to victim privacy concerns. Part 2 crimes include all other offenses. A detailed list of Part 2 crimes is listed below. When using the data, the date and time provided are when the crime was actually reported. This means that though a larceny might b e 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.Quality of Life - True or False value stating whether this crime is part of the list of crimes that the City of Syracuse categorizes if these affect residents quality of life. DisclaimerData derived from the Syracuse Police Department record management system, any data not listed is not currently available.Part II Crime Definitions Part II crimes are those not included in the Part I section and are then grouped into the following categories KIDNAPPINGEXTORTION SIMPLE ASSAULTSALE/MANUFACTURE MARIJUANAFORGERY/COUNTERFEITOFFN AGAINST FAMILYSALE/MANUFACTURE CONTROLLED SUBSTANCEPROSTITUTION PATRON/PROMOTINGDRIVING UNDER INFLUENCEPOSSESSION/USE DRUGSTOLEN PROPERTYUNAUTHORIZED USE MVCOERCIONPOSSESSION BURGLAR TOOLSPOSSESSION/USE DANGEROUS WEAPONSCRIMINAL MISCHIEFLIQUOR LAW VIOLATIONSBRIBERYFRAUDDISORDERLY CONDUCTLOITERINGALL OTHER OFFENSESDataset Contact Information:Organization: Syracuse Police Department (SPD)Position: Data Program ManagerCity: Syracuse, NYE-Mail Address: opendata@syrgov.net
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.
http://opendatacommons.org/licenses/dbcl/1.0/http://opendatacommons.org/licenses/dbcl/1.0/
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.
https://data.cityofchicago.org/Public-Safety/Crimes-2001-to-present/ijzp-q8t2/data
https://www.icpsr.umich.edu/web/ICPSR/studies/38962/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/38962/terms
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.
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
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Analysis of ‘Baton Rouge Crime Incidents’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/2c991bb1-eec4-4ebd-9506-75dbf8b74b45 on 13 February 2022.
--- Dataset description provided by original source is as follows ---
Crime incident reports as of beginning on January 1, 2021. Includes records for all crimes such as burglaries (vehicle, residential and non-residential), robberies (individual and business), auto theft, homicides and other crimes against people, property and society which occurred within the City of Baton Rouge.
Please see the disclaimer attachment in the About section of the primer page.
For Crime Incidents prior to 1/1/2021 visit the Legacy Baton Rouge Crime Incident dataset at https://data.brla.gov/Public-Safety/Legacy-Baton-Rouge-Crime-Incidents/fabb-cnnu.
--- Original source retains full ownership of the source dataset ---
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
The data tables contain figures for:
There are counting rules for recorded crime to help to ensure that crimes are recorded consistently and accurately.
These tables are designed to have many uses. The Home Office would like to hear from any users who have developed applications for these data tables and any suggestions for future releases. Please contact the Crime Analysis team at crimeandpolicestats@homeoffice.gov.uk.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Analysis of ‘NYPD Criminal Court Summons Incident Level Data (Year To Date)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/ead9efa5-3aef-426c-96e6-165f086eb09f on 13 February 2022.
--- Dataset description provided by original source is as follows ---
List of every criminal summons issued in NYC during the current calendar year.
This is a breakdown of every criminal summons issued in NYC by the NYPD during the current calendar year. This data is manually extracted every quarter and reviewed by the Office of Management Analysis and Planning before being posted on the NYPD website. Each record represents a criminal summons issued in NYC by the NYPD and includes information about the type of crime, the location and time of enforcement. In addition, information related to suspect demographics is also included. This data can be used by the public to explore the nature of police enforcement activity. Please refer to the attached data footnotes for additional information about this dataset.
--- Original source retains full ownership of the source dataset ---
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Analysis of ‘CVS11 - Extent crime in their local area has impacted on persons life in the last 12 months’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/b616e393-7225-48bf-a2cb-6333c49a2928 on 19 January 2022.
--- Dataset description provided by original source is as follows ---
Extent crime in their local area has impacted on persons life in the last 12 months
--- Original source retains full ownership of the source dataset ---
The Detection of Crime, Resource Deployment, and Predictors of Success: A Multi-Level Analysis of Closed-Circuit Television (CCTV) in Newark, NJ collection represents the findings of a multi-level analysis of the Newark, New Jersey Police Department's video surveillance system. This collection contains multiple quantitative data files (Datasets 1-14) as well as spatial data files (Dataset 15 and Dataset 16). The overall project was separated into three components: Component 1 (Dataset 1, Individual CCTV Detections and Calls-For-Service Data and Dataset 2, Weekly CCTV Detections in Newark Data) evaluates CCTV's ability to increase the "certainty of punishment" in target areas; Component 2 (Dataset 3, Overall Crime Incidents Data; Dataset 4, Auto Theft Incidents Data; Dataset 5, Property Crime Incidents Data; Dataset 6, Robbery Incidents Data; Dataset 7, Theft From Auto Incidents Data; Dataset 8, Violent Crime Incidents Data; Dataset 9, Attributes of CCTV Catchment Zones Data; Dataset 10, Attributes of CCTV Camera Viewsheds Data; and Dataset 15, Impact of Micro-Level Features Spatial Data) analyzes the context under which CCTV cameras best deter crime. Micro-level factors were grouped into five categories: environmental features, line-of-sight, camera design and enforcement activity (including both crime and arrests); and Component 3 (Dataset 11, Calls-for-service Occurring Within CCTV Scheme Catchment Zones During the Experimental Period Data; Dataset 12, Calls-for-service Occurring Within CCTV Schemes During the Experimental Period Data; Dataset 13, Targeted Surveillances Conducted by the Experimental Operators Data; Dataset 14, Weekly Surveillance Activity Data; and Dataset 16, Randomized Controlled Trial Spatial Data) was a randomized, controlled trial measuring the effects of coupling proactive CCTV monitoring with directed patrol units. Over 40 separate four-hour tours of duty, an additional camera operator was funded to monitor specific CCTV cameras in Newark. Two patrol units were dedicated solely to the operators and were tasked with exclusively responding to incidents of concern detected on the experimental cameras. Variables included throughout the datasets include police report and incident dates, crime type, disposition code, number of each type of incident that occurred in a viewshed precinct, number of CCTV detections that resulted in any police enforcement, and number of schools, retail stores, bars and public transit within the catchment zone.
Alaska crime data from 2000 to present from the FBI Uniform Crime Reporting (UCR) program. Information includes data on both violent and property crime.The UCR Program's primary objective is to generate reliable information for use in law enforcement administration, operation, and management; over the years, however, the data have become one of the country’s leading social indicators. The program has been the starting place for law enforcement executives, students of criminal justice, researchers, members of the media, and the public at large seeking information on crime in the nation. The program was conceived in 1929 by the International Association of Chiefs of Police to meet the need for reliable uniform crime statistics for the nation. In 1930, the FBI was tasked with collecting, publishing, and archiving those statistics.Source: US Federal Bureau of Investigation (FBI)This data has been visualized in a Geographic Information Systems (GIS) format and is provided as a service in the DCRA Information Portal by the Alaska Department of Commerce, Community, and Economic Development Division of Community and Regional Affairs (SOA DCCED DCRA), Research and Analysis section. SOA DCCED DCRA Research and Analysis is not the authoritative source for this data. For more information and for questions about this data, see: FBI UCR Program.
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.
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
https://www.icpsr.umich.edu/web/ICPSR/studies/4447/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/4447/terms
The National Crime Victimization Survey: Unbounded Data (also referred to as the All Rotations Data) are now being made available to the public for analytic use. These data differ from the "regular" National Crime Victimization Survey (NCVS) data in that they contain the first interview with respondents. The National Crime Victimization Survey 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 dynamic analysis tool allows you to examine National Crime Victimization Survey (NCVS) data on both violent and property victimization by select victim, household, and incident characteristics. The NCVS is the nation's primary source of information on criminal victimization. It is an annual data collection conducted by the U.S. Census Bureau for the Bureau of Justice Statistics. The NCVS collects information from a nationally representative sample of U.S. households on nonfatal crimes, reported and not reported to the police, against persons age 12 or older. Violent crimes measured by the NCVS include rape and sexual assault, robbery, aggravated assault, and simple assault. Property crimes include burglary/trespassing, motor-vehicle theft, and theft.
The purpose of the study was to investigate the role and impact of forensic science evidence on the criminal justice process. The study utilized a prospective analysis of official record data that followed criminal cases in five jurisdictions (Los Angeles County, California; Indianapolis, Indiana; Evansville, Indiana; Fort Wayne, Indiana; and South Bend, Indiana) from the time of police incident report to final criminal disposition. The data were based on a random sample of the population of reported crime incidents between 2003 and 2006, stratified by crime type and jurisdiction. A total of 4,205 cases were sampled including 859 aggravated assaults, 1,263 burglaries, 400 homicides, 602 rapes, and 1,081 robberies. Descriptive and impact data were collected from three sources: police incident and investigation reports, crime lab reports, and prosecutor case files. The data contain a total of 175 variables including site, crime type, forensic variables, criminal offense variables, and crime dispositions variables.
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.