40 datasets found
  1. d

    DC Crime Cards

    • catalog.data.gov
    • opendata.dc.gov
    Updated Feb 5, 2025
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    City of Washington, DC (2025). DC Crime Cards [Dataset]. https://catalog.data.gov/dataset/dc-crime-cards
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    Dataset updated
    Feb 5, 2025
    Dataset provided by
    City of Washington, DC
    Area covered
    Washington
    Description

    An interactive public crime mapping application providing DC residents and visitors easy-to-understand data visualizations of crime locations, types and trends across all eight wards. Crime Cards was created by the DC Metropolitan Police Department (MPD) and Office of the Chief Technology Officer (OCTO). Special thanks to the community members who participated in reviews with MPD Officers and IT staff, and those who joined us for the #SaferStrongerSmarterDC roundtable design review. All statistics presented in Crime Cards are based on preliminary DC Index crime data reported from 2009 to midnight of today’s date. They are compiled based on the date the offense was reported (Report Date) to MPD. The application displays two main crime categories: Violent Crime and Property Crime. Violent Crimes include homicide, sex abuse, assault with a dangerous weapon (ADW), and robbery. Violent crimes can be further searched by the weapon used. Property Crimes include burglary, motor vehicle theft, theft from vehicle, theft (other), and arson.CrimeCards collaboration between the Metropolitan Police Department (MPD), the Office of the Chief Technology Officer (OCTO), and community members who participated at the #SafterStrongerSmarterDC roundtable design review.

  2. Crime Incidents in the Last 30 Days

    • catalog.data.gov
    • opendata.dc.gov
    • +4more
    Updated Aug 20, 2025
    + more versions
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    Metropolitan Police Department (2025). Crime Incidents in the Last 30 Days [Dataset]. https://catalog.data.gov/dataset/crime-incidents-in-the-last-30-days
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    Dataset updated
    Aug 20, 2025
    Dataset provided by
    Metropolitan Police Department of the District of Columbiahttps://mpdc.dc.gov/
    Description

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

  3. d

    Crime Incidents in 2020

    • opendata.dc.gov
    • catalog.data.gov
    • +3more
    Updated Jan 1, 2020
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    City of Washington, DC (2020). Crime Incidents in 2020 [Dataset]. https://opendata.dc.gov/datasets/crime-incidents-in-2020
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    Dataset updated
    Jan 1, 2020
    Dataset authored and provided by
    City of Washington, DC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

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

  4. Reported violent crime rate U.S. 2023, by state

    • statista.com
    Updated Nov 14, 2024
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    Statista (2024). Reported violent crime rate U.S. 2023, by state [Dataset]. https://www.statista.com/statistics/200445/reported-violent-crime-rate-in-the-us-states/
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    Dataset updated
    Nov 14, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, the District of Columbia had the highest reported violent crime rate in the United States, with 1,150.9 violent crimes per 100,000 of the population. Maine had the lowest reported violent crime rate, with 102.5 offenses per 100,000 of the population. Life in the District The District of Columbia has seen a fluctuating population over the past few decades. Its population decreased throughout the 1990s, when its crime rate was at its peak, but has been steadily recovering since then. While unemployment in the District has also been falling, it still has had a high poverty rate in recent years. The gentrification of certain areas within Washington, D.C. over the past few years has made the contrast between rich and poor even greater and is also pushing crime out into the Maryland and Virginia suburbs around the District. Law enforcement in the U.S. Crime in the U.S. is trending downwards compared to years past, despite Americans feeling that crime is a problem in their country. In addition, the number of full-time law enforcement officers in the U.S. has increased recently, who, in keeping with the lower rate of crime, have also made fewer arrests than in years past.

  5. District Gun Violence Dashboards

    • catalog.data.gov
    • opendata.dc.gov
    • +1more
    Updated Mar 18, 2025
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    Office of Gun Violence Prevention (2025). District Gun Violence Dashboards [Dataset]. https://catalog.data.gov/dataset/district-gun-violence-dashboards
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    Dataset updated
    Mar 18, 2025
    Dataset provided by
    White House Office of Gun Violence Prevention
    Description

    The Office of Gun Violence Prevention (OGVP) shares real-time gun violence data to increase government transparency, improve the public's awareness, and support community-based gun violence prevention and reduction partners. All District crime data is available through Crime Cards. The dashboards below focus on gun violence only. The data in these dashboards is updated daily at 7:40AM with the incidents from the day before. View data covering 7-Day Look-back of Gun Violence and Year-to-date Gun Violence.All statistics presented here are based on preliminary DC criminal code offense definitions. The data do not represent official statistics submitted to the FBI under the Uniform Crime Reporting program (UCR) or National Incident Based Reporting System (NIBRS). All preliminary offenses are coded based on DC criminal code and not the FBI offense classifications. Please understand that any comparisons between MPD preliminary data as published on this website and the official crime statistics published by the FBI under the Uniform Crime Reporting Program (UCR) are inaccurate and misleading. The MPD does not guarantee (either expressed or implied) the accuracy, completeness, timeliness, or correct sequencing of the information. The MPD will not be responsible for any error or omission, or for the use of, or the results obtained from the use of this information. Read complete data notes at buildingblocks.dc.gov/data.

  6. d

    Crime Incidents in 2022

    • opendata.dc.gov
    • catalog.data.gov
    • +3more
    Updated Jan 1, 2022
    + more versions
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    City of Washington, DC (2022). Crime Incidents in 2022 [Dataset]. https://opendata.dc.gov/maps/crime-incidents-in-2022
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    Dataset updated
    Jan 1, 2022
    Dataset authored and provided by
    City of Washington, DC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

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

  7. Felony Crime Incidents in 2016

    • catalog.data.gov
    • opendata.dc.gov
    • +5more
    Updated Feb 5, 2025
    + more versions
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    Metropolitan Police Department (2025). Felony Crime Incidents in 2016 [Dataset]. https://catalog.data.gov/dataset/felony-crime-incidents-in-2016-02202
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    Dataset updated
    Feb 5, 2025
    Dataset provided by
    Metropolitan Police Department of the District of Columbiahttps://mpdc.dc.gov/
    Description

    The dataset contains records of felony crime incidents recorded by the District of Columbia Metropolitan Police Department in 2016. Visit mpdc.dc.gov/page/data-and-statistics for more information.

  8. Data from: Uniform Crime Reports: Monthly Weapon-Specific Crime and Arrest...

    • catalog.data.gov
    • icpsr.umich.edu
    Updated Mar 12, 2025
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    Bureau of Justice Statistics (2025). Uniform Crime Reports: Monthly Weapon-Specific Crime and Arrest Time Series, 1975-1993 [National, State, and 12-City Data] [Dataset]. https://catalog.data.gov/dataset/uniform-crime-reports-monthly-weapon-specific-crime-and-arrest-time-series-1975-1993-natio-09efd
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    Bureau of Justice Statisticshttp://bjs.ojp.gov/
    Description

    These data were prepared in conjunction with a project using Bureau of Labor Statistics data (not provided with this collection) and the Federal Bureau of Investigation's Uniform Crime Reporting (UCR) Program data to examine the relationship between unemployment and violent crime. Three separate time-series data files were created as part of this project: a national time series (Part 1), a state time series (Part 2), and a time series of data for 12 selected cities: Baltimore, Buffalo, Chicago, Columbus, Detroit, Houston, Los Angeles, Newark, New York City, Paterson (New Jersey), and Philadelphia (Part 3). Each data file was constructed to include 82 monthly time series: 26 series containing the number of Part I (crime index) offenses known to police (excluding arson) by weapon used, 26 series of the number of offenses cleared by arrest or other exceptional means by weapon used in the offense, 26 series of the number of offenses cleared by arrest or other exceptional means for persons under 18 years of age by weapon used in the offense, a population estimate series, and three date indicator series. For the national and state data, agencies from the 50 states and Washington, DC, were included in the aggregated data file if they reported at least one month of information during the year. In addition, agencies that did not report their own data (and thus had no monthly observations on crime or arrests) were included to make the aggregated population estimate as close to Census estimates as possible. For the city time series, law enforcement agencies with jurisdiction over the 12 central cities were identified and the monthly data were extracted from each UCR annual file for each of the 12 agencies. The national time-series file contains 82 time series, the state file contains 4,083 time series, and the city file contains 963 time series, each with 228 monthly observations per time series. The unit of analysis is the month of observation. Monthly crime and clearance totals are provided for homicide, negligent manslaughter, total rape, forcible rape, attempted forcible rape, total robbery, firearm robbery, knife/cutting instrument robbery, other dangerous weapon robbery, strong-arm robbery, total assault, firearm assault, knife/cutting instrument assault, other dangerous weapon assault, simple nonaggravated assault, assaults with hands/fists/feet, total burglary, burglary with forcible entry, unlawful entry-no force, attempted forcible entry, larceny-theft, motor vehicle theft, auto theft, truck and bus theft, other vehicle theft, and grand total of all actual offenses.

  9. d

    Crime Incidents in 2009

    • opendata.dc.gov
    • catalog.data.gov
    • +2more
    Updated Jan 1, 2009
    + more versions
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    City of Washington, DC (2009). Crime Incidents in 2009 [Dataset]. https://opendata.dc.gov/datasets/crime-incidents-in-2009/api
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    Dataset updated
    Jan 1, 2009
    Dataset authored and provided by
    City of Washington, DC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

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

  10. d

    Bias Crime

    • catalog.data.gov
    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    • +2more
    Updated May 28, 2025
    + more versions
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    Metropolitan Police Department (2025). Bias Crime [Dataset]. https://catalog.data.gov/dataset/bias-crime
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    Dataset updated
    May 28, 2025
    Dataset provided by
    Metropolitan Police Department
    Description

    It is important for the community to understand what is – and is not – a hate crime. First and foremost, the incident must be a crime. Although that may seem obvious, most speech is not a hate crime, regardless of how offensive it may be. In addition, a hate crime is not a crime, but a possible motive for a crime.It can be difficult to establish a motive for a crime. Therefore, the classification as a hate crime is subject to change as an investigation proceeds – even as prosecutors continue an investigation. If a person is found guilty of a hate crime, the court may fine the offender up to 1½ times the maximum fine and imprison him or her for up to 1½ times the maximum term authorized for the underlying crime.While the District strives to reduce crime for all residents of and visitors to the city, hate crimes can make a particular community feel vulnerable and more fearful. This is unacceptable, and is the reason everyone must work together not just to address allegations of hate crimes, but also to proactively educate the public about hate crimes.The figures in this data align with DC Official Code 22-3700. Because the DC statute differs from the FBI Uniform Crime Reporting (UCR) and National Incident-Based Reporting System (NIBRS) definitions, these figures may be higher than those reported to the FBI.Each month, an MPD team reviews crimes that have been identified as potentially motivated by hate/bias to determine whether there is sufficient information to support that designation. The data in this document is current through the end of the most recent month.The hate crimes dataset is not an official MPD database of record and may not match details in records pulled from the official Records Management System (RMS).Unknown or blank values in the Targeted Group field may be present prior to 2016 data. As of January 2022, an offense with multiple bias categories would be reflected as such.Data is updated on the 15th of every month.

  11. w

    Crime Mapper: Elliston (DC) Local Government Area

    • data.wu.ac.at
    • data.gov.au
    html
    Updated Oct 27, 2016
    + more versions
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    South Australian Governments (2016). Crime Mapper: Elliston (DC) Local Government Area [Dataset]. https://data.wu.ac.at/schema/data_gov_au/NzcyY2E2NmItMjM2Zi00MjA1LWI3ZDItMGMzMWIxYTM5NGY5
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    html(76550.0)Available download formats
    Dataset updated
    Oct 27, 2016
    Dataset provided by
    South Australian Governments
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Description

    Crime Mapper is an online application that provides the geographic distribution of recorded crime across South Australia. Two units of measurement are reported: 1. Number of offences - provides a count of all offences listed on all incident reports recorded by South Australia Police . 2. Rate per 1,000 estimated resident population - provides the number of offences as a rate per 1,000 population residing in each given location. Offences are categorised as follows: • Offences against the person (homicide; major assault; other); • Sexual offences (rape; indecent assault; unlawful sexual intercourse; other); • Robbery and extortion offences (armed robbery; unarmed robbery; extortion); • Offences against property (serious criminal trespass/break and enter; fraud and misappropriation; receiving/illegal possession of stolen goods; larceny/illegal use of a motor vehicle; other larceny; larceny from shops; larceny from a motor vehicle; arson/explosives; property damage and environmental offences); • Offences against good order; • Drug offences (possess/use drugs; sell/trade drugs; produce/manufacture drugs; possess implement for drug use; other); • Driving offences (driving under the influence of alcohol/drugs; dangerous driving; driving licence offences; traffic offences; motor vehicle registration offences; other); or • Other offences. When using Crime Mapper it is important to understand that the statistics it contains may not provide an accurate measure of the true prevalence or incidence of crime in a community. Crime Mapper statistics represent only those offences reported to police or which come to the attention of police. They can, therefore, be influenced by a number of factors, including victim reporting rates, the identification or detection of offences by police (in the case of ‘victimless’ crimes) and police interpretation and decision as to whether a crime has occurred. In addition, Crime Mapper does not include offences that are dealt with by way of expiation (e.g., speeding, littering, etc.). Please also see explanatory notes: http://www.ocsar.sa.gov.au/about2.html

  12. w

    Crime Mapper: Wakefield (DC) Local Government Area

    • data.wu.ac.at
    • data.gov.au
    html
    Updated Oct 27, 2016
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    South Australian Governments (2016). Crime Mapper: Wakefield (DC) Local Government Area [Dataset]. https://data.wu.ac.at/schema/data_gov_au/Yjc0OGUyMjMtYzQxYy00ZmQ5LWExMDItNGFhMGJmNjE2YTEx
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    html(77868.0)Available download formats
    Dataset updated
    Oct 27, 2016
    Dataset provided by
    South Australian Governments
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Description

    Crime Mapper is an online application that provides the geographic distribution of recorded crime across South Australia. Two units of measurement are reported: 1. Number of offences - provides a count of all offences listed on all incident reports recorded by South Australia Police . 2. Rate per 1,000 estimated resident population - provides the number of offences as a rate per 1,000 population residing in each given location. Offences are categorised as follows: • Offences against the person (homicide; major assault; other); • Sexual offences (rape; indecent assault; unlawful sexual intercourse; other); • Robbery and extortion offences (armed robbery; unarmed robbery; extortion); • Offences against property (serious criminal trespass/break and enter; fraud and misappropriation; receiving/illegal possession of stolen goods; larceny/illegal use of a motor vehicle; other larceny; larceny from shops; larceny from a motor vehicle; arson/explosives; property damage and environmental offences); • Offences against good order; • Drug offences (possess/use drugs; sell/trade drugs; produce/manufacture drugs; possess implement for drug use; other); • Driving offences (driving under the influence of alcohol/drugs; dangerous driving; driving licence offences; traffic offences; motor vehicle registration offences; other); or • Other offences. When using Crime Mapper it is important to understand that the statistics it contains may not provide an accurate measure of the true prevalence or incidence of crime in a community. Crime Mapper statistics represent only those offences reported to police or which come to the attention of police. They can, therefore, be influenced by a number of factors, including victim reporting rates, the identification or detection of offences by police (in the case of ‘victimless’ crimes) and police interpretation and decision as to whether a crime has occurred. In addition, Crime Mapper does not include offences that are dealt with by way of expiation (e.g., speeding, littering, etc.). Please also see explanatory notes: http://www.ocsar.sa.gov.au/about2.html

  13. w

    Crime Mapper: Yankalilla (DC) Local Government Area

    • data.wu.ac.at
    • data.gov.au
    html
    Updated Oct 27, 2016
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    South Australian Governments (2016). Crime Mapper: Yankalilla (DC) Local Government Area [Dataset]. https://data.wu.ac.at/odso/data_gov_au/NDdmNjk1ZDUtYmEyNC00OTQ2LWE0YTQtNmZkY2M1ODk1ZGM3
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    html(77782.0)Available download formats
    Dataset updated
    Oct 27, 2016
    Dataset provided by
    South Australian Governments
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Description

    Crime Mapper is an online application that provides the geographic distribution of recorded crime across South Australia. Two units of measurement are reported: 1. Number of offences - provides a count of all offences listed on all incident reports recorded by South Australia Police . 2. Rate per 1,000 estimated resident population - provides the number of offences as a rate per 1,000 population residing in each given location. Offences are categorised as follows: • Offences against the person (homicide; major assault; other); • Sexual offences (rape; indecent assault; unlawful sexual intercourse; other); • Robbery and extortion offences (armed robbery; unarmed robbery; extortion); • Offences against property (serious criminal trespass/break and enter; fraud and misappropriation; receiving/illegal possession of stolen goods; larceny/illegal use of a motor vehicle; other larceny; larceny from shops; larceny from a motor vehicle; arson/explosives; property damage and environmental offences); • Offences against good order; • Drug offences (possess/use drugs; sell/trade drugs; produce/manufacture drugs; possess implement for drug use; other); • Driving offences (driving under the influence of alcohol/drugs; dangerous driving; driving licence offences; traffic offences; motor vehicle registration offences; other); or • Other offences. When using Crime Mapper it is important to understand that the statistics it contains may not provide an accurate measure of the true prevalence or incidence of crime in a community. Crime Mapper statistics represent only those offences reported to police or which come to the attention of police. They can, therefore, be influenced by a number of factors, including victim reporting rates, the identification or detection of offences by police (in the case of ‘victimless’ crimes) and police interpretation and decision as to whether a crime has occurred. In addition, Crime Mapper does not include offences that are dealt with by way of expiation (e.g., speeding, littering, etc.). Please also see explanatory notes: http://www.ocsar.sa.gov.au/about2.html

  14. w

    Crime Mapper: Alexandrina (DC) Local Government Area

    • data.wu.ac.at
    • data.gov.au
    html
    Updated Jul 14, 2016
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    Attorney-General's Dept (2016). Crime Mapper: Alexandrina (DC) Local Government Area [Dataset]. https://data.wu.ac.at/schema/data_sa_gov_au/YzUyOGQ1ZDEtNDc4NC00NjgwLWIxMGItZDYxMTk2ZDRlOTNi
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    html(78146.0)Available download formats
    Dataset updated
    Jul 14, 2016
    Dataset provided by
    Attorney-General's Dept
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Crime Mapper is an online application that provides the geographic distribution of recorded crime across South Australia. Two units of measurement are reported: 1. Number of offences - provides a count of all offences listed on all incident reports recorded by South Australia Police . 2. Rate per 1,000 estimated resident population - provides the number of offences as a rate per 1,000 population residing in each given location. Offences are categorised as follows: • Offences against the person (homicide; major assault; other); • Sexual offences (rape; indecent assault; unlawful sexual intercourse; other); • Robbery and extortion offences (armed robbery; unarmed robbery; extortion); • Offences against property (serious criminal trespass/break and enter; fraud and misappropriation; receiving/illegal possession of stolen goods; larceny/illegal use of a motor vehicle; other larceny; larceny from shops; larceny from a motor vehicle; arson/explosives; property damage and environmental offences); • Offences against good order; • Drug offences (possess/use drugs; sell/trade drugs; produce/manufacture drugs; possess implement for drug use; other); • Driving offences (driving under the influence of alcohol/drugs; dangerous driving; driving licence offences; traffic offences; motor vehicle registration offences; other); or • Other offences. When using Crime Mapper it is important to understand that the statistics it contains may not provide an accurate measure of the true prevalence or incidence of crime in a community. Crime Mapper statistics represent only those offences reported to police or which come to the attention of police. They can, therefore, be influenced by a number of factors, including victim reporting rates, the identification or detection of offences by police (in the case of ‘victimless’ crimes) and police interpretation and decision as to whether a crime has occurred. In addition, Crime Mapper does not include offences that are dealt with by way of expiation (e.g., speeding, littering, etc.). Please also see explanatory notes: http://www.ocsar.sa.gov.au/about2.html

  15. w

    Crime Mapper: Renmark Paringa (DC) Local Government Area

    • data.wu.ac.at
    • data.gov.au
    html
    Updated Oct 27, 2016
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    South Australian Governments (2016). Crime Mapper: Renmark Paringa (DC) Local Government Area [Dataset]. https://data.wu.ac.at/odso/data_gov_au/Y2E4NmI2NGUtMzY1MS00NWJmLTk4YWQtMDFhM2MxYTlhNTVm
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    html(78018.0)Available download formats
    Dataset updated
    Oct 27, 2016
    Dataset provided by
    South Australian Governments
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Description

    Crime Mapper is an online application that provides the geographic distribution of recorded crime across South Australia. Two units of measurement are reported: 1. Number of offences - provides a count of all offences listed on all incident reports recorded by South Australia Police . 2. Rate per 1,000 estimated resident population - provides the number of offences as a rate per 1,000 population residing in each given location. Offences are categorised as follows: • Offences against the person (homicide; major assault; other); • Sexual offences (rape; indecent assault; unlawful sexual intercourse; other); • Robbery and extortion offences (armed robbery; unarmed robbery; extortion); • Offences against property (serious criminal trespass/break and enter; fraud and misappropriation; receiving/illegal possession of stolen goods; larceny/illegal use of a motor vehicle; other larceny; larceny from shops; larceny from a motor vehicle; arson/explosives; property damage and environmental offences); • Offences against good order; • Drug offences (possess/use drugs; sell/trade drugs; produce/manufacture drugs; possess implement for drug use; other); • Driving offences (driving under the influence of alcohol/drugs; dangerous driving; driving licence offences; traffic offences; motor vehicle registration offences; other); or • Other offences. When using Crime Mapper it is important to understand that the statistics it contains may not provide an accurate measure of the true prevalence or incidence of crime in a community. Crime Mapper statistics represent only those offences reported to police or which come to the attention of police. They can, therefore, be influenced by a number of factors, including victim reporting rates, the identification or detection of offences by police (in the case of ‘victimless’ crimes) and police interpretation and decision as to whether a crime has occurred. In addition, Crime Mapper does not include offences that are dealt with by way of expiation (e.g., speeding, littering, etc.). Please also see explanatory notes: http://www.ocsar.sa.gov.au/about2.html

  16. Data from: Juvenile Arrests

    • catalog.data.gov
    • opendata.dc.gov
    • +1more
    Updated May 7, 2025
    + more versions
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    Metropolitan Police Department (2025). Juvenile Arrests [Dataset]. https://catalog.data.gov/dataset/juvenile-arrests-434b1
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    Dataset updated
    May 7, 2025
    Dataset provided by
    Metropolitan Police Department of the District of Columbiahttps://mpdc.dc.gov/
    Description

    This juvenile arrest report contains all arrests made by MPD and other law enforcement agencies of individuals 17 and under, excluding any arrests that have been expunged. Only the top charge (most serious charge) is reported for each arrest.The "Home PSA" of all arrests for which a valid District of Columbia address was given are provided. For all cases where the home address was outside the District of Columbia, the home address field was manually reviewed and marked as "OUT OF STATE". "UNKNOWN" is provided for cases where no address was reported.The "Crime/Arrest PSA" field contains the PSA associated with the original crime where the arrest record could be matched against the original crime report. For cases where the DC Moultrie Courthouse was indicated as the crime address (e.g., for Juvenile Custody Order, Failure to Appear, Fugitive from Justice, and Booking Order), "COURT" was listed as the crime PSA instead of PSA 102. For cases for which the Juvenile Processing Center (JPC) was indicated as the crime address, or for cases where other processing locations were listed as the crime address (e.g., District station or MPD Headquarters), "DISTRICT/JPC" was listed as the crime PSA . For arrest cases without proper crime incident address, it was assumed that the arrest was made at the site of the crime, and the PSA associated with the arrest location was provided.

  17. w

    Crime Mapper: Robe (DC) Local Government Area

    • data.wu.ac.at
    • data.gov.au
    html
    Updated Oct 27, 2016
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    South Australian Governments (2016). Crime Mapper: Robe (DC) Local Government Area [Dataset]. https://data.wu.ac.at/schema/data_gov_au/YTUyMWJiZjUtZTY1Yi00Yjg2LTgwNDctZmMyNDI0YzE4Zjg4
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    html(76858.0)Available download formats
    Dataset updated
    Oct 27, 2016
    Dataset provided by
    South Australian Governments
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Description

    Crime Mapper is an online application that provides the geographic distribution of recorded crime across South Australia. Two units of measurement are reported: 1. Number of offences - provides a count of all offences listed on all incident reports recorded by South Australia Police . 2. Rate per 1,000 estimated resident population - provides the number of offences as a rate per 1,000 population residing in each given location. Offences are categorised as follows: • Offences against the person (homicide; major assault; other); • Sexual offences (rape; indecent assault; unlawful sexual intercourse; other); • Robbery and extortion offences (armed robbery; unarmed robbery; extortion); • Offences against property (serious criminal trespass/break and enter; fraud and misappropriation; receiving/illegal possession of stolen goods; larceny/illegal use of a motor vehicle; other larceny; larceny from shops; larceny from a motor vehicle; arson/explosives; property damage and environmental offences); • Offences against good order; • Drug offences (possess/use drugs; sell/trade drugs; produce/manufacture drugs; possess implement for drug use; other); • Driving offences (driving under the influence of alcohol/drugs; dangerous driving; driving licence offences; traffic offences; motor vehicle registration offences; other); or • Other offences. When using Crime Mapper it is important to understand that the statistics it contains may not provide an accurate measure of the true prevalence or incidence of crime in a community. Crime Mapper statistics represent only those offences reported to police or which come to the attention of police. They can, therefore, be influenced by a number of factors, including victim reporting rates, the identification or detection of offences by police (in the case of ‘victimless’ crimes) and police interpretation and decision as to whether a crime has occurred. In addition, Crime Mapper does not include offences that are dealt with by way of expiation (e.g., speeding, littering, etc.). Please also see explanatory notes: http://www.ocsar.sa.gov.au/about2.html

  18. w

    Crime Mapper: Kingston (DC) Local Government Area

    • data.wu.ac.at
    • data.gov.au
    html
    Updated Oct 27, 2016
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    South Australian Governments (2016). Crime Mapper: Kingston (DC) Local Government Area [Dataset]. https://data.wu.ac.at/odso/data_gov_au/ZjdkMDNmY2MtNzJlMS00ZTJkLWEzYjAtMGViZGU5MjAxNzQx
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    html(77162.0)Available download formats
    Dataset updated
    Oct 27, 2016
    Dataset provided by
    South Australian Governments
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Description

    Crime Mapper is an online application that provides the geographic distribution of recorded crime across South Australia. Two units of measurement are reported: 1. Number of offences - provides a count of all offences listed on all incident reports recorded by South Australia Police . 2. Rate per 1,000 estimated resident population - provides the number of offences as a rate per 1,000 population residing in each given location. Offences are categorised as follows: • Offences against the person (homicide; major assault; other); • Sexual offences (rape; indecent assault; unlawful sexual intercourse; other); • Robbery and extortion offences (armed robbery; unarmed robbery; extortion); • Offences against property (serious criminal trespass/break and enter; fraud and misappropriation; receiving/illegal possession of stolen goods; larceny/illegal use of a motor vehicle; other larceny; larceny from shops; larceny from a motor vehicle; arson/explosives; property damage and environmental offences); • Offences against good order; • Drug offences (possess/use drugs; sell/trade drugs; produce/manufacture drugs; possess implement for drug use; other); • Driving offences (driving under the influence of alcohol/drugs; dangerous driving; driving licence offences; traffic offences; motor vehicle registration offences; other); or • Other offences. When using Crime Mapper it is important to understand that the statistics it contains may not provide an accurate measure of the true prevalence or incidence of crime in a community. Crime Mapper statistics represent only those offences reported to police or which come to the attention of police. They can, therefore, be influenced by a number of factors, including victim reporting rates, the identification or detection of offences by police (in the case of ‘victimless’ crimes) and police interpretation and decision as to whether a crime has occurred. In addition, Crime Mapper does not include offences that are dealt with by way of expiation (e.g., speeding, littering, etc.). Please also see explanatory notes: http://www.ocsar.sa.gov.au/about2.html

  19. a

    Homicide Reduction Partnership Areas

    • private-demo-dcdev.opendata.arcgis.com
    • opendata.dc.gov
    • +2more
    Updated Feb 25, 2022
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    City of Washington, DC (2022). Homicide Reduction Partnership Areas [Dataset]. https://private-demo-dcdev.opendata.arcgis.com/maps/DCGIS::homicide-reduction-partnership-areas
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    Dataset updated
    Feb 25, 2022
    Dataset authored and provided by
    City of Washington, DC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    Homicide Reduction Partnership, a collaborative effort to reduce violent crime through strategic prevention and focused enforcement. With this new partnership, MPD will focus resources and intelligence-led policing strategies in collaboration with local and federal law enforcement and criminal justice partners, DC government agencies, and community partners.The Homicides Reduction Partnership (HRP) will focus on reducing violent crime within four Police Service Areas throughout the entire 2022 calendar year. These areas include PSAs 603, 604, 706 and 708, which accounted for 21% of all murders city-wide in 2021. The objective of the HRP is to use a “whole of government” approach to reduce violent crime, have a positive impact on the community’s perception of safety and security, and increase trust among residents in the police and DC government. By committing an entire year, the goal is to sustain success after the conclusion of the initiative.For more information visit https://dc.gov/release/mayor-bowser-announces-new-year-round-partnership-focused-violent-crime

  20. d

    Crime Mapper: The Coorong (DC) Local Government Area

    • data.gov.au
    • data.wu.ac.at
    html
    Updated Jul 13, 2016
    + more versions
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    Attorney-General's Department (2016). Crime Mapper: The Coorong (DC) Local Government Area [Dataset]. https://data.gov.au/dataset/ds-sa-9683f764-4033-474f-b742-9bbc4688dee1/details
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Jul 13, 2016
    Dataset provided by
    Attorney-General's Departmenthttp://www.ag.gov.au/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Coorong District Council
    Description

    Crime Mapper is an online application that provides the geographic distribution of recorded crime across South Australia. Two units of measurement are reported: 1. Number of offences - provides a …Show full descriptionCrime Mapper is an online application that provides the geographic distribution of recorded crime across South Australia. Two units of measurement are reported: 1. Number of offences - provides a count of all offences listed on all incident reports recorded by South Australia Police . 2. Rate per 1,000 estimated resident population - provides the number of offences as a rate per 1,000 population residing in each given location. Offences are categorised as follows: • Offences against the person (homicide; major assault; other); • Sexual offences (rape; indecent assault; unlawful sexual intercourse; other); • Robbery and extortion offences (armed robbery; unarmed robbery; extortion); • Offences against property (serious criminal trespass/break and enter; fraud and misappropriation; receiving/illegal possession of stolen goods; larceny/illegal use of a motor vehicle; other larceny; larceny from shops; larceny from a motor vehicle; arson/explosives; property damage and environmental offences); • Offences against good order; • Drug offences (possess/use drugs; sell/trade drugs; produce/manufacture drugs; possess implement for drug use; other); • Driving offences (driving under the influence of alcohol/drugs; dangerous driving; driving licence offences; traffic offences; motor vehicle registration offences; other); or • Other offences. When using Crime Mapper it is important to understand that the statistics it contains may not provide an accurate measure of the true prevalence or incidence of crime in a community. Crime Mapper statistics represent only those offences reported to police or which come to the attention of police. They can, therefore, be influenced by a number of factors, including victim reporting rates, the identification or detection of offences by police (in the case of ‘victimless’ crimes) and police interpretation and decision as to whether a crime has occurred. In addition, Crime Mapper does not include offences that are dealt with by way of expiation (e.g., speeding, littering, etc.). Please also see explanatory notes: http://www.ocsar.sa.gov.au/about2.html

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City of Washington, DC (2025). DC Crime Cards [Dataset]. https://catalog.data.gov/dataset/dc-crime-cards

DC Crime Cards

Explore at:
Dataset updated
Feb 5, 2025
Dataset provided by
City of Washington, DC
Area covered
Washington
Description

An interactive public crime mapping application providing DC residents and visitors easy-to-understand data visualizations of crime locations, types and trends across all eight wards. Crime Cards was created by the DC Metropolitan Police Department (MPD) and Office of the Chief Technology Officer (OCTO). Special thanks to the community members who participated in reviews with MPD Officers and IT staff, and those who joined us for the #SaferStrongerSmarterDC roundtable design review. All statistics presented in Crime Cards are based on preliminary DC Index crime data reported from 2009 to midnight of today’s date. They are compiled based on the date the offense was reported (Report Date) to MPD. The application displays two main crime categories: Violent Crime and Property Crime. Violent Crimes include homicide, sex abuse, assault with a dangerous weapon (ADW), and robbery. Violent crimes can be further searched by the weapon used. Property Crimes include burglary, motor vehicle theft, theft from vehicle, theft (other), and arson.CrimeCards collaboration between the Metropolitan Police Department (MPD), the Office of the Chief Technology Officer (OCTO), and community members who participated at the #SafterStrongerSmarterDC roundtable design review.

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