23 datasets found
  1. Crime Incidents in the Last 30 Days

    • catalog.data.gov
    • opendata.dc.gov
    • +4more
    Updated Mar 25, 2025
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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
    Mar 25, 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.

  2. a

    DC Crime Cards

    • hub.arcgis.com
    • catalog.data.gov
    Updated Mar 9, 2018
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    City of Washington, DC (2018). DC Crime Cards [Dataset]. https://hub.arcgis.com/datasets/3d553e9f7ba941918537d51f26d746e7
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    Dataset updated
    Mar 9, 2018
    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

    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.

  3. Crime Incidents in 2022

    • catalog.data.gov
    • opendata.dc.gov
    • +4more
    Updated Feb 11, 2025
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    Metropolitan Police Department (2025). Crime Incidents in 2022 [Dataset]. https://catalog.data.gov/dataset/crime-incidents-in-2022
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    Dataset updated
    Feb 11, 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 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. d

    Crime Incidents in 2025

    • opendata.dc.gov
    • catalog.data.gov
    • +4more
    Updated Jan 6, 2025
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    City of Washington, DC (2025). Crime Incidents in 2025 [Dataset]. https://opendata.dc.gov/datasets/74d924ddc3374e3b977e6f002478cb9b
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    Dataset updated
    Jan 6, 2025
    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.

  5. d

    Data from: Crime Incident Data for Selected HOPE VI Sites in Milwaukee,...

    • catalog.data.gov
    • gimi9.com
    • +1more
    Updated Mar 12, 2025
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    National Institute of Justice (2025). Crime Incident Data for Selected HOPE VI Sites in Milwaukee, Wisconsin, 2002-2010, and Washington, DC, 2000-2009 [Dataset]. https://catalog.data.gov/dataset/crime-incident-data-for-selected-hope-vi-sites-in-milwaukee-wisconsin-2002-2010-and-w-2000-5041b
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    National Institute of Justice
    Area covered
    Wisconsin, Milwaukee, Washington
    Description

    The purpose of this project was to conduct an evaluation of the impact on crime of the closing, renovation, and subsequent reopening of selected public housing developments under the United States Department of Housing and Urban Development's (HUD) Housing Opportunities for People Everywhere (HOPE VI) initiative. The study examined crime displacement and potential diffusion of benefits in and around five public housing developments that, since 2000, had been redeveloped using funds from HUD's HOPE VI initiative and other sources. In Milwaukee, Wisconsin, three sites were selected for inclusion in the study. However, due to substantial overlap between the various target sites and displacement zones, the research team ultimately decided to aggregate the three sites into a single target area. A comparison area was then chosen based on recommendations from the Housing Authority of the City of Milwaukee (HACM). In Washington, DC, two HOPE VI sites were selected for inclusion in the study. Based on recommendations from the District of Columbia Housing Authority (DCHA), the research team selected a comparison site for each of the two target areas. Displacement areas were then drawn as concentric rings ("buffers") around the target areas in both Milwaukee, Wisconsin and Washington, DC. Address-level incident data were collected for the city of Milwaukee from the Milwaukee Police Department for the period January 2002 through February 2010. Incident data included all "Group A" offenses as classified under National Incident Based Reporting System (NIBRS). The research team classified the offenses into personal and property offenses. The offenses were aggregated into monthly counts, yielding 98 months of data (Part 1: Milwaukee, Wisconsin Data). Address-level data were also collected for Washington, DC from the Metropolitan Police Department for the time period January 2000 through September 2009. Incident data included all Part I offenses as classified under the Uniform Crime Report (UCR) system. The data were classified by researchers into personal and property offenses and aggregated by month, yielding 117 months of data (Part 2: Washington, DC Data). Part 1 contains 15 variables, while Part 2 contains a total of 27 variables. Both datasets include variables on the number of personal offenses reported per month, the number of property offenses reported per month, and the total number of incidents reported per month for each target site, buffer zone area (1000 feet or 2000 feet), and comparison site. Month and year indicators are also included in each dataset.

  6. 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.

  7. a

    Data from: Juvenile Arrests

    • hub.arcgis.com
    • opendata.dc.gov
    • +2more
    Updated Mar 9, 2018
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    City of Washington, DC (2018). Juvenile Arrests [Dataset]. https://hub.arcgis.com/maps/DCGIS::juvenile-arrests
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    Dataset updated
    Mar 9, 2018
    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

    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.

  8. O

    Crime_Incidents_2015

    • celebratingcities.data.socrata.com
    Updated Feb 12, 2016
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    (2016). Crime_Incidents_2015 [Dataset]. https://celebratingcities.data.socrata.com/DC/Crime_Incidents_2015/j6b8-wjwi
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    csv, application/rdfxml, application/rssxml, tsv, xml, application/geo+json, kml, kmzAvailable download formats
    Dataset updated
    Feb 12, 2016
    Description

    DC Index Crime incident locations for 2015. 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). Please visit http://crimemap.dc.gov for more information.

  9. 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/f516e0dd7b614b088ad781b0c4002331
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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.

  10. Felony Crime Incidents in 2016

    • catalog.data.gov
    • datasets.ai
    • +4more
    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.

  11. d

    DC COVID-19 Metropolitan Police Department

    • catalog.data.gov
    • datasets.ai
    • +2more
    Updated Feb 5, 2025
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    GIS Data Coordinator, D.C. Office of the Chief Technology Officer , GIS Data Coordinator (2025). DC COVID-19 Metropolitan Police Department [Dataset]. https://catalog.data.gov/dataset/dc-covid-19-metropolitan-police-department
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    Dataset updated
    Feb 5, 2025
    Dataset provided by
    GIS Data Coordinator, D.C. Office of the Chief Technology Officer , GIS Data Coordinator
    Area covered
    Washington
    Description

    On March 2, 2022 DC Health announced the District’s new COVID-19 Community Level key metrics and reporting. COVID-19 cases are now reported on a weekly basis. District of Columbia Metropolitan Police Department testing for the number of positive tests, quarantined, returned to work and lives lost. Due to rapidly changing nature of COVID-19, data for March 2020 is limited.General Guidelines for Interpreting Disease Surveillance DataDuring a disease outbreak, the health department will collect, process, and analyze large amounts of information to understand and respond to the health impacts of the disease and its transmission in the community. The sources of disease surveillance information include contact tracing, medical record review, and laboratory information, and are considered protected health information. When interpreting the results of these analyses, it is important to keep in mind that the disease surveillance system may not capture the full picture of the outbreak, and that previously reported data may change over time as it undergoes data quality review or as additional information is added. These analyses, especially within populations with small samples, may be subject to large amounts of variation from day to day. Despite these limitations, data from disease surveillance is a valuable source of information to understand how to stop the spread of COVID19.

  12. 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

  13. d

    Crime Incidents in 2011

    • opendata.dc.gov
    • catalog.data.gov
    • +1more
    Updated Jan 1, 2011
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    City of Washington, DC (2011). Crime Incidents in 2011 [Dataset]. https://opendata.dc.gov/datasets/9d5485ffae914c5f97047a7dd86e115b
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    Dataset updated
    Jan 1, 2011
    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.

  14. Data from: National Crime Surveys: Reverse Record Check Studies: Washington,...

    • catalog.data.gov
    • icpsr.umich.edu
    • +2more
    Updated Nov 28, 2023
    + more versions
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    Bureau of Justice Statistics (2023). National Crime Surveys: Reverse Record Check Studies: Washington, DC, San Jose, and Baltimore, 1970-1971 [Dataset]. https://catalog.data.gov/dataset/national-crime-surveys-reverse-record-check-studies-washington-dc-san-jose-and-baltim-1970
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    Dataset updated
    Nov 28, 2023
    Dataset provided by
    Bureau of Justice Statisticshttp://bjs.ojp.gov/
    Area covered
    San Jose, Washington
    Description

    These surveys were part of a series of pretests conducted during the early 1970s to reveal problems associated with doing a nationwide study on victimization. They were done to determine the most effective reference period to use when questioning respondents in order to gain the fullest and most reliable information, to measure the degree to which respondents move incidents occurring outside the reference period into that period when questioned, and to explore the possibility of identifying incidents by a few broad general questions as opposed to a series of more specific probing questions.

  15. d

    Crime Incidents in 2016

    • opendata.dc.gov
    • catalog.data.gov
    • +3more
    Updated Jan 1, 2016
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    City of Washington, DC (2016). Crime Incidents in 2016 [Dataset]. https://opendata.dc.gov/datasets/crime-incidents-in-2016/api
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    Dataset updated
    Jan 1, 2016
    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.

  16. 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

  17. Federal Justice Statistics Program: Defendants in Federal Criminal Cases --...

    • icpsr.umich.edu
    • catalog.data.gov
    Updated Mar 8, 2011
    + more versions
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    United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics (2011). Federal Justice Statistics Program: Defendants in Federal Criminal Cases -- Terminated, 2005 [United States] [Dataset]. http://doi.org/10.3886/ICPSR24195.v2
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    Dataset updated
    Mar 8, 2011
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/24195/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/24195/terms

    Area covered
    United States
    Description

    The data contain records of defendants in federal criminal cases terminated in United States District Court during fiscal year 2005. The data were constructed from the Executive Office for United States Attorneys (EOUSA) Central System file. According to the EOUSA, the United States attorneys conduct approximately 95 percent of the prosecutions handled by the Department of Justice. The Central System data contain variables from the original EOUSA files as well as additional analysis variables, or "SAF" variables, that denote subsets of the data. These SAF variables are related to statistics reported in the Compendium of Federal Justice Statistics. Variables containing identifying information (e.g., name, Social Security Number) were replaced with blanks, and the day portions of date fields were also sanitized in order to protect the identities of individuals. These data are part of a series designed by the Urban Institute (Washington, DC) and the Bureau of Justice Statistics. Data and documentation were prepared by the Urban Institute.

  18. d

    Crime Incidents in 2013

    • opendata.dc.gov
    • catalog.data.gov
    • +2more
    Updated Jan 1, 2013
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    City of Washington, DC (2013). Crime Incidents in 2013 [Dataset]. https://opendata.dc.gov/datasets/DCGIS::crime-incidents-in-2013/about
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    Dataset updated
    Jan 1, 2013
    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.

  19. d

    Stop Data 2019 to 2022

    • catalog.data.gov
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • +1more
    Updated Feb 5, 2025
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    City of Washington, DC (2025). Stop Data 2019 to 2022 [Dataset]. https://catalog.data.gov/dataset/stop-data-2019-to-2022
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    Dataset updated
    Feb 5, 2025
    Dataset provided by
    City of Washington, DC
    Description

    In July 2019, the Metropolitan Police Department (MPD) implemented new data collection methods that enabled officers to collect more comprehensive information about each police stop in an aggregated manner. More specifically, these changes have allowed for more detailed data collection on stops, protective pat down (PPDs), searches, and arrests. (For a complete list of terms, see the glossary on page 2.) These changes support data collection requirements in the Neighborhood Engagement Achieves Results Amendment Act of 2016 (NEAR Act).The accompanying data cover all MPD stops including vehicle, pedestrian, bicycle, and harbor stops for the period from July 22, 2019 to December 31, 2022. A stop may involve a ticket (actual or warning), investigatory stop, protective pat down, search, or arrest.If the final outcome of a stop results in an actual or warning ticket, the ticket serves as the official documentation for the stop. The information provided in the ticket include the subject’s name, race, gender, reason for the stop, and duration. All stops resulting in additional law enforcement actions (e.g., pat down, search, or arrest) are documented in MPD’s Record Management System (RMS). This dataset includes records pulled from both the ticket (District of Columbia Department of Motor Vehicles [DMV]) and RMS sources. Data variables not applicable to a particular stop are indicated as “NULL.” For example, if the stop type (“stop_type” field) is a “ticket stop,” then the fields: “stop_reason_nonticket” and “stop_reason_harbor” will be “NULL.” Each row in the data represents an individual stop of a single person, and that row reveals any and all recorded outcomes of that stop (including information about any actual or warning tickets issued, searches conducted, arrests made, etc.). A single traffic stop may generate multiple tickets, including actual, warning, and/or voided tickets. Additionally, an individual who is stopped and receives a traffic ticket may also be stopped for investigatory purposes, patted down, searched, and/or arrested. If any of these situations occur, the “stop_type” field would be labeled “Ticket and Non-Ticket Stop.” If an individual is searched, MPD differentiates between person and property searches. The “stop_location_block” field represents the block-level location of the stop and/or a street name. The age of the person being stopped is calculated based on the time between the person’s date ofbirth and the date of the stop.There are certain locations that have a high prevalence of non-ticket stops. These can be attributed to some centralized processing locations. Additionally, there is a time lag for data on some ticket stops as roughly 20 percent of tickets are handwritten. In these instances, the handwritten traffic tickets are delivered by MPD to the DMV, and then entered into data systems by DMV contractors. On August 1, 2021, MPD transitioned to a new version of its current records management system, Mark43 RMS.Due to this transition, the data collection and structures for the period between August 1, 2021 – December 31, 2021 were changed. The list below provides explanatory notes to consider when using this dataset.New fields for data collection resulted in an increase of outliers in stop duration (affecting 0.98% of stops). In order to mitigate the disruption of outliers on any analysis, these values have been set to null as consistent with past practices.Due to changes to the data structure that occurred after August 1, 2021, six attributes pertaining to reasons for searches of property and person are only available for the first seven months of 2021. These attributes are: Individual’s Actions, Information Obtained from Law Enforcement Sources, Information Obtained from Witnesses or Informants, Characteristics of an Armed Individual, Nature of the Alleged Crime, Prior Knowledge. These data structure changes have been updated to include these attributes going forward (as of April 23, 2022).Out of the four attributes for types of property search, warrant property search is only available for the first seven months of 2021. Data structure changes were made to include this type of property search in future datasets.The following chart shows how certain property search fields were aligned prior to and after August 1, 2021. A glossary is also provided following the chart. As of August 2, 2022, these fields have reverted to the original alignment.https://mpdc.dc.gov/sites/default/files/dc/sites/mpdc/publication/attachments/Explanatory%20Notes%202021%20Data.pdfIn October 2022 several fields were added to the dataset to provide additional clarity differentiating NOIs issued to bicycles (including Personal Mobility Devices, aka stand-on scooters), pedestrians, and vehicles as well as stops related specifically to MPD’s Harbor Patrol Unit and stops of an investigative nature where a police report was written. Please refer to the Data Dictionary for field definitions.In March 2023 an indicator was added to the data which reflects stops related to traffic enforcement and/or traffic violations. This indicator will be 1 if a stop originated as a traffic stop (including both stops where only a ticket was issued as well as stops that ultimately resulted in police action such as a search or arrest), involved an arrest for a traffic violation, and/or if the reason for the stop was Response to Crash, Observed Moving Violation, Observed Equipment Violation, or Traffic Violation.Between November 2021 and February 2022 several fields pertaining to items seized during searches of a person were not available for officers to use, leading to the data showing that no objects were seized pursuant to person searches during this time period. Finally, MPD is conducting on-going data audits on all data for thorough and complete information. For more information regarding police stops, please see: https://mpdc.dc.gov/stopdataFigures are subject to change due to delayed reporting, on-going data quality audits, and data improvement processes.

  20. Felony Arrest Charges in 2016

    • catalog.data.gov
    • opendata.dc.gov
    • +1more
    Updated Feb 5, 2025
    + more versions
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    Metropolitan Police Department (2025). Felony Arrest Charges in 2016 [Dataset]. https://catalog.data.gov/dataset/felony-arrest-charges-in-2016-93a53
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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 arrests made by the Metropolitan Police Department (MPD) in 2016. Visit mpdc.dc.gov/page/data-and-statistics for more information.

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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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Crime Incidents in the Last 30 Days

Explore at:
Dataset updated
Mar 25, 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.

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