34 datasets found
  1. c

    Law Enforcement Facilities

    • s.cnmilf.com
    • data.oregon.gov
    • +3more
    Updated Jan 31, 2025
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    State of Oregon (2025). Law Enforcement Facilities [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/law-enforcement-facilities
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    Dataset updated
    Jan 31, 2025
    Dataset provided by
    State of Oregon
    Description

    Law Enforcement Locations Any _location where sworn officers of a law enforcement agency are regularly based or stationed. Law Enforcement agencies "are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Although TGS's intention is to only include locations associated with agencies that meet the above definition, TGS has discovered a few locations that are associated with agencies that are not publicly funded. TGS deleted these locations as we became aware of them, but some may still exist in this dataset. Personal homes, administrative offices, and temporary locations are intended to be excluded from this dataset; however, some personal homes of constables are included due to the fact that many constables work out of their homes. TGS has made a concerted effort to include all local police; county sheriffs; state police and/or highway patrol; Bureau of Indian Affairs; Bureau of Land Management; Bureau of Reclamation; U.S. Park Police; Bureau of Alcohol, Tobacco, Firearms, and Explosives; U.S. Marshals Service; U.S. Fish and Wildlife Service; National Park Service; U.S. Immigration and Customs Enforcement; and U.S. Customs and Border Protection. This dataset is comprised completely of license free data. FBI entities are intended to be excluded from this dataset, but a few may be included. The Law Enforcement dataset and the Correctional Institutions dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. With the merge of the Law Enforcement and the Correctional Institutions datasets, the NAICS Codes & Descriptions were assigned based on the facility's main function which was determined by the entity's name, facility type, web research, and state supplied data. In instances where the entity's primary function is both law enforcement and corrections, the NAICS Codes and Descriptions are assigned based on the dataset in which the record is located (i.e., a facility that serves as both a Sheriff's Office and as a jail is designated as [NAICSDESCR]="SHERIFFS' OFFICES (EXCEPT COURT FUNCTIONS ONLY)" in the Law Enforcement layer and as [NAICSDESCR]="JAILS (EXCEPT PRIVATE OPERATION OF)" in the Correctional Institutions layer). Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard fields that TGS populated. Double spaces were replaced by single spaces in these same fields. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been

  2. c

    HSIP Law Enforcement Locations in New Mexico

    • s.cnmilf.com
    • gstore.unm.edu
    • +1more
    Updated Dec 2, 2020
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    (Point of Contact) (2020). HSIP Law Enforcement Locations in New Mexico [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/hsip-law-enforcement-locations-in-new-mexico
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    Dataset updated
    Dec 2, 2020
    Dataset provided by
    (Point of Contact)
    Area covered
    New Mexico
    Description

    Law Enforcement Locations Any _location where sworn officers of a law enforcement agency are regularly based or stationed. Law Enforcement agencies "are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Although TGS's intention is to only include locations associated with agencies that meet the above definition, TGS has discovered a few locations that are associated with agencies that are not publicly funded. TGS deleted these locations as we became aware of them, but some may still exist in this dataset. Personal homes, administrative offices, and temporary locations are intended to be excluded from this dataset; however, some personal homes are included due to the fact that the New Mexico Mounted Police work out of their homes. TGS has made a concerted effort to include all local police; county sheriffs; state police and/or highway patrol; Bureau of Indian Affairs; Bureau of Land Management; Bureau of Reclamation; U.S. Park Police; Bureau of Alcohol, Tobacco, Firearms, and Explosives; U.S. Marshals Service; U.S. Fish and Wildlife Service; National Park Service; U.S. Immigration and Customs Enforcement; and U.S. Customs and Border Protection. This dataset is comprised completely of license free data. FBI entities are intended to be excluded from this dataset, but a few may be included. The Law Enforcement dataset and the Correctional Institutions dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. With the merge of the Law Enforcement and the Correctional Institutions datasets, the NAICS Codes & Descriptions were assigned based on the facility's main function which was determined by the entity's name, facility type, web research, and state supplied data. In instances where the entity's primary function is both law enforcement and corrections, the NAICS Codes and Descriptions are assigned based on the dataset in which the record is located (i.e., a facility that serves as both a Sheriff's Office and as a jail is designated as [NAICSDESCR]="SHERIFFS' OFFICES (EXCEPT COURT FUNCTIONS ONLY)" in the Law Enforcement layer and as [NAICSDESCR]="JAILS (EXCEPT PRIVATE OPERATION OF)" in the Correctional Institutions layer). Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard fields that TGS populated. Double spaces were replaced by single spaces in these same fields. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based on the values in this field, the oldest record dates from 08/14/2006 and the newest record dates from 10/23/2009

  3. Directory of Law Enforcement Agencies, 1996: [United States]

    • icpsr.umich.edu
    • catalog.data.gov
    • +1more
    ascii, sas, spss
    Updated Sep 11, 1998
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    United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics (1998). Directory of Law Enforcement Agencies, 1996: [United States] [Dataset]. http://doi.org/10.3886/ICPSR02260.v1
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    ascii, spss, sasAvailable download formats
    Dataset updated
    Sep 11, 1998
    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/2260/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/2260/terms

    Time period covered
    1996
    Area covered
    United States
    Description

    To ensure an accurate sampling frame for its Law Enforcement Management and Administrative Statistics (LEMAS) survey, the Bureau of Justice Statistics periodically sponsors a census of the nation's state and local law enforcement agencies. This census, known as the Directory Survey, gathers data on 49 primary state law enforcement agencies and all sheriffs' departments, local police departments, and special police agencies (state or local) that are publicly funded and employ at least one sworn officer with general arrest powers. The 1996 Directory Survey collected data on the number of sworn and nonsworn personnel employed by each agency, including both full-time and part-time employees. Within the full-time sworn category, data were collected from all agencies on the number who were uniformed officers with regularly assigned duties that included responding to calls for service. For agencies with at least 10 full-time sworn officers, the number whose primary duties were related to investigations, court operations, or jail operations was also obtained. This data collection, compiled in June 1996, represents the third such census, with the first occurring in 1986 (DIRECTORY OF LAW ENFORCEMENT AGENCIES, 1986: [UNITED STATES] [ICPSR 8696]) and the second in 1992 (DIRECTORY OF LAW ENFORCEMENT AGENCIES, 1992: [UNITED STATES] [ICPSR 2266]). Variables include personnel totals, type of government, type of agency, and whether the agency had the legal authority to hold a person beyond arraignment for 48 or more hours.

  4. Data from: Police Departments, Arrests and Crime in the United States,...

    • catalog.data.gov
    • icpsr.umich.edu
    Updated Mar 12, 2025
    + more versions
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    Bureau of Justice Statistics (2025). Police Departments, Arrests and Crime in the United States, 1860-1920 [Dataset]. https://catalog.data.gov/dataset/police-departments-arrests-and-crime-in-the-united-states-1860-1920-476a7
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    Bureau of Justice Statisticshttp://bjs.ojp.gov/
    Area covered
    United States
    Description

    These data on 19th- and early 20th-century police department and arrest behavior were collected between 1975 and 1978 for a study of police and crime in the United States. Raw and aggregated time-series data are presented in Parts 1 and 3 on 23 American cities for most years during the period 1860-1920. The data were drawn from annual reports of police departments found in the Library of Congress or in newspapers and legislative reports located elsewhere. Variables in Part 1, for which the city is the unit of analysis, include arrests for drunkenness, conditional offenses and homicides, persons dismissed or held, police personnel, and population. Part 3 aggregates the data by year and reports some of these variables on a per capita basis, using a linear interpolation from the last decennial census to estimate population. Part 2 contains data for 267 United States cities for the period 1880-1890 and was generated from the 1880 federal census volume, REPORT ON THE DEFECTIVE, DEPENDENT, AND DELINQUENT CLASSES, published in 1888, and from the 1890 federal census volume, SOCIAL STATISTICS OF CITIES. Information includes police personnel and expenditures, arrests, persons held overnight, trains entering town, and population.

  5. Census of State and Local Law Enforcement Agencies (CSLLEA), 2000: [United...

    • catalog.data.gov
    • icpsr.umich.edu
    Updated Mar 12, 2025
    + more versions
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    Bureau of Justice Statistics (2025). Census of State and Local Law Enforcement Agencies (CSLLEA), 2000: [United States] [Dataset]. https://catalog.data.gov/dataset/census-of-state-and-local-law-enforcement-agencies-csllea-2000-united-states
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    Bureau of Justice Statisticshttp://bjs.ojp.gov/
    Area covered
    United States
    Description

    To ensure an accurate sampling frame for its Law Enforcement Management and Administrative Statistics (LEMAS) survey, the Bureau of Justice Statistics periodically sponsors a census of the nation's state and local law enforcement agencies. This census, known as the Directory Survey, includes all state and local law enforcement agencies that are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers. As in previous years, the 2000 Directory Survey collected data on the number of sworn and nonsworn personnel employed by each agency, including both full-time and part-time employees. The pay period that included June 30, 2000, was the reference date for all personnel data. A 97.4 percent response rate was obtained from the 17,784 state and local law enforcement agencies operating in the United States. This data collection contains June 2000 data from the fourth Directory Survey. Previous directory censuses were conducted in 1986 (DIRECTORY OF LAW ENFORCEMENT AGENCIES, 1986: [UNITED STATES] [ICPSR 8696]), 1992 (DIRECTORY OF LAW ENFORCEMENT AGENCIES, 1992: [UNITED STATES] [ICPSR 2266]), and 1996 (DIRECTORY OF LAW ENFORCEMENT AGENCIES, 1996: [UNITED STATES] [ICPSR 2260]). Variables include personnel totals, type of government, type of agency, and whether the agency had the legal authority to hold a person beyond arraignment for 48 or more hours.

  6. Census of State and Local Law Enforcement Agencies (CSLLEA), 2018

    • icpsr.umich.edu
    ascii, delimited +5
    Updated May 30, 2023
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    United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics (2023). Census of State and Local Law Enforcement Agencies (CSLLEA), 2018 [Dataset]. http://doi.org/10.3886/ICPSR38771.v1
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    delimited, spss, ascii, qualitative data, r, sas, stataAvailable download formats
    Dataset updated
    May 30, 2023
    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/38771/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/38771/terms

    Time period covered
    2018
    Area covered
    United States
    Description

    The BJS Census of State and Local Law Enforcement Agencies (CSLLEA) is conducted every 4 years to provide a complete enumeration of agencies and their employees. Employment data are reported by agencies for sworn and nonsworn (civilian) personnel and, within these categories, by full-time or part-time status. The pay period that included June 30, 2018, was the reference date for personnel data. Agencies also complete a checklist of functions they regularly perform, or have primary responsibility for, within the following areas: patrol and response, criminal investigation, traffic and vehicle-related functions, detention-related functions, court-related functions, forensic services, special public safety functions (e.g., animal control), task force participation, and specialized functions (e.g., search and rescue). The CSLLEA provides national data on the number of state and local law enforcement agencies and employees for local police departments, sheriffs' offices, state law enforcement agencies, and special jurisdiction agencies. It also serves as the sampling frame for BJS surveys of law enforcement agencies.

  7. a

    New Hampshire Law Enforcement

    • nh-granit-nhgranit.hub.arcgis.com
    • nhgeodata.unh.edu
    • +2more
    Updated Dec 30, 2009
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    New Hampshire GRANIT GIS Clearinghouse (2009). New Hampshire Law Enforcement [Dataset]. https://nh-granit-nhgranit.hub.arcgis.com/items/d65797d2c7384722a1fcbc1fc0a6bdd6
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    Dataset updated
    Dec 30, 2009
    Dataset authored and provided by
    New Hampshire GRANIT GIS Clearinghouse
    Area covered
    Description

    Law Enforcement Locations Any location where sworn officers of a law enforcement agency are regularly based or stationed. Law Enforcement agencies "are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Although TGS's intention is to only include locations associated with agencies that meet the above definition, TGS has discovered a few locations that are associated with agencies that are not publicly funded. TGS deleted these locations as we became aware of them, but some may still exist in this dataset. Personal homes, administrative offices, and temporary locations are intended to be excluded from this dataset; however, some personal homes of constables are included due to the fact that many constables work out of their homes. TGS has made a concerted effort to include all local police; county sheriffs; state police and/or highway patrol; Bureau of Indian Affairs; Bureau of Land Management; Bureau of Reclamation; U.S. Park Police; Bureau of Alcohol, Tobacco, Firearms, and Explosives; U.S. Marshals Service; U.S. Fish and Wildlife Service; National Park Service; U.S. Immigration and Customs Enforcement; and U.S. Customs and Border Protection. This dataset is comprised completely of license free data. FBI entities are intended to be excluded from this dataset, but a few may be included. The Law Enforcement dataset and the Correctional Institutions dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. With the merge of the Law Enforcement and the Correctional Institutions datasets, the NAICS Codes & Descriptions were assigned based on the facility's main function which was determined by the entity's name, facility type, web research, and state supplied data. In instances where the entity's primary function is both law enforcement and corrections, the NAICS Codes and Descriptions are assigned based on the dataset in which the record is located (i.e., a facility that serves as both a Sheriff's Office and as a jail is designated as [NAICSDESCR]="SHERIFFS' OFFICES (EXCEPT COURT FUNCTIONS ONLY)" in the Law Enforcement layer and as [NAICSDESCR]="JAILS (EXCEPT PRIVATE OPERATION OF)" in the Correctional Institutions layer). Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard fields that TGS populated. Double spaces were replaced by single spaces in these same fields. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based on the values in this field, the oldest record dates from 04/26/2006 and the newest record dates from 10/19/2009

  8. w

    Law Enforcement Locations

    • data.wu.ac.at
    • datadiscoverystudio.org
    Updated Dec 8, 2014
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    Kansas Data Access and Support Center (2014). Law Enforcement Locations [Dataset]. https://data.wu.ac.at/schema/data_gov/MjQwZDU2MjYtNzJlOC00NzBjLTg0NTctNmUyNWM3ODk5ZDE2
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    Dataset updated
    Dec 8, 2014
    Dataset provided by
    Kansas Data Access and Support Center
    Area covered
    4e1981910e1840ee949f9713d0c3bef63e315c10
    Description

    Law Enforcement Locations in Kansas Any location where sworn officers of a law enforcement agency are regularly based or stationed. Law enforcement agencies "are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Although TGS's intention is to only include locations associated with agencies that meet the above definition, TGS has discovered a few locations that are associated with agencies that are not publicly funded. TGS is deleting these locations as we become aware of them, but some probably still exist in this dataset. Personal homes, administrative offices and temporary locations are intended to be excluded from this dataset, but a few may be included. Personal homes of constables may exist due to fact that many constables work out of their home. FBI entites are intended to be excluded from this dataset, but a few may be included. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] attribute. Based upon this attribute, the oldest record dates from 2006/06/27 and the newest record dates from 2008/03/06

  9. Stanford Open Policing Project - Ohio

    • kaggle.com
    zip
    Updated Jul 24, 2017
    + more versions
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    Stanford Open Policing Project (2017). Stanford Open Policing Project - Ohio [Dataset]. https://www.kaggle.com/datasets/stanford-open-policing/stanford-open-policing-project-ohio
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    zip(185573983 bytes)Available download formats
    Dataset updated
    Jul 24, 2017
    Dataset authored and provided by
    Stanford Open Policing Project
    Area covered
    Ohio
    Description

    Context:

    On a typical day in the United States, police officers make more than 50,000 traffic stops. The Stanford Open Policing Project team is gathering, analyzing, and releasing records from millions of traffic stops by law enforcement agencies across the country. Their goal is to help researchers, journalists, and policymakers investigate and improve interactions between police and the public.

    If you'd like to see data regarding other states, please go to https://www.kaggle.com/stanford-open-policing.

    Content:

    This dataset includes over 1 gb of stop data from Ohio. Please see the data readme for the full details of the available fields.

    Acknowledgements:

    This dataset was kindly made available by the Stanford Open Policing Project. If you use it for a research publication, please cite their working paper: E. Pierson, C. Simoiu, J. Overgoor, S. Corbett-Davies, V. Ramachandran, C. Phillips, S. Goel. (2017) “A large-scale analysis of racial disparities in police stops across the United States”.

    Inspiration:

    • How predictable are the stop rates? Are there times and places that reliably generate stops?
    • Concerns have been raised about jurisdictions using civil forfeiture as a funding mechanism rather than to properly fight drug trafficking. Can you identify any jurisdictions that may be exhibiting this behavior?
  10. Data from: Study of Sworn Nonfederal Law Enforcement Officers Arrested in...

    • catalog.data.gov
    • icpsr.umich.edu
    Updated Mar 12, 2025
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    National Institute of Justice (2025). Study of Sworn Nonfederal Law Enforcement Officers Arrested in the United States, 2005-2011 [Dataset]. https://catalog.data.gov/dataset/study-of-sworn-nonfederal-law-enforcement-officers-arrested-in-the-united-states-2005-2011-65a5b
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    National Institute of Justicehttp://nij.ojp.gov/
    Area covered
    United States
    Description

    These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed expect for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) is further information is needed. This collection is composed of archived news articles and court records reporting (n=6,724) on the arrest(s) of law enforcement officers in the United States from 2005-2011. Police crimes are those crimes committed by sworn law enforcement officers given the general powers of arrest at the time the offense was committed. These crimes can occur while the officer is on or off duty and include offenses committed by state, county, municipal, tribal, or special law enforcement agencies.Three distinct but related research questions are addressed in this collection:What is the incidence and prevalence of police officers arrested across the United States? How do law enforcement agencies discipline officers who are arrested?To what degree do police crime arrests correlate with other forms of police misconduct?

  11. d

    Use of Force department data

    • data.world
    csv, zip
    Updated Mar 8, 2024
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    NJ Advance Data Team (2024). Use of Force department data [Dataset]. https://data.world/njdotcom/use-of-force-department-data
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    csv, zipAvailable download formats
    Dataset updated
    Mar 8, 2024
    Authors
    NJ Advance Data Team
    Description

    This is five years of police use of force data for all 468 New Jersey municipal police departments and the New Jersey State Police compiled by NJ Advance Media for The Force Report.

    When police punch, pepper spray or use other force against someone in New Jersey, they are required to fill out a form detailing what happened. NJ Advance Media filed 506 public records requests and received 72,607 forms covering 2012 through 2016. For more data collection details, see our Methodology here. Data cleaning details can be found here.

    We then cleaned, analyzed and compiled the data by department to get a better look at what departments were using the most force, what type of force they were using, and who they were using it on. The result, our searchable database, can be found at NJ.com/force. But we wanted to make department-level results — our aggregate data — available in another way to the broader public.

    Below you'll find two files:

    • UOF_BY_DEPARTMENTS.csv, with every department's summary data, including the State Police. (This is important to note because the State Police patrols multiple towns and may not be comparable to other departments.)
    • UOF_STATEWIDE.csv, a statewide summary of the same data.

    For more details on individual columns, see the data dictionary for UOF_BY_DEPARTMENTS. We have also created sample SQL queries to make it easy for users to quickly find their town or county.

    It's important to note that these forms were self-reported by police officers, sometimes filled out by hand, so even our data cleaning can't totally prevent inaccuracies from cropping up. We've also included comparisons to population data (from the Census) and arrest data (from the FBI Uniform Crime Report), to try to help give context to what you're seeing.

    What about the form-level data?

    We have included individual incidents on each department page, but we are not publishing the form-level data freely to the public. Not only is that data extremely dirty and difficult to analyze — at least, it took us six months — but it contains private information about subjects of force, including minors and people with mental health issues. However, we are planning to make a version of that file available upon request in the future.

    Data analysis FAQ

    What are rows? What are incidents?
    Every time any police officer uses force against a subject, they must fill out a form detailing what happened and what force they used. But sometimes multiple police officers used force against the same subject in the same incident. "Rows" are individual forms officers filled out, "incidents" are unique incidents based on the incident number and date.

    What are the odds ratios, and how did you calculate them?
    We wanted a simple way of showing readers the disparity between black and white subjects in a particular town. So we used an odds ratio, a statistical method often used in research to compare the odds of one thing happening to another. For population, the calculation was (Number of black subjects/Total black population of area)/(Number of white subjects/Total white population of area). For arrests, the calculation was (Number of black subjects/Total number of black arrests in area)/(Number of white subjects/Total number of white arrests in area). In addition, when we compared anything to arrests, we took out all incidents where the subject was an EDP (emotionally disturbed person).

    What are the NYC/LA/Chicago warning systems?
    Those three departments each look at use of force to flag officers if they show concerning patterns, as way to select those that could merit more training or other action by the department. We compared our data to those three systems to see how many officers would trigger the early warning systems for each. Here are the three systems: - In New York City, officers are flagged for review if they use higher levels of force — including a baton, Taser or firearm, but not pepper spray — or if anyone was injured or hospitalized. We calculated this number by identifying every officer who met one or more of the criteria. - In Los Angeles, officers are compared with one another based on 14 variables, including use of force. If an officer ranks significantly higher than peers for any of the variables — technically, 3 standards of deviation from the norm — supervisors are automatically notified. We calculated this number conservatively by using only use of force as a variable over the course of a calendar year. - In Chicago, officers are flagged for review if force results in an injury or hospitalization, or if the officer uses any level of force above punches or kicks. We calculated this number by identifying every officer who met one or more of the criteria.

    What are the different levels of force?
    Each officer was required to include in the form what type of force they used against a subject. We cleaned and standardized the data to major categories, although officers could write-in a different type of force if they wanted to. Here are the major categories: - Compliance hold: A compliance hold is a painful maneuver using pressure points to gain control over a suspect. It is the lowest level of force and the most commonly used. But it is often used in conjunction with other types of force. - Takedown: This technique is used to bring a suspect to the ground and eventually onto their stomach to cuff them. It can be a leg sweep or a tackle. - Hands/fist: Open hands or closed fist strikes/punches. - Leg strikes: Leg strikes are any kick or knee used on a subject. - Baton: Officers are trained to use a baton when punches or kicks are unsuccessful. - Pepper spray: Police pepper spray, a mist derived from the resin of cayenne pepper, is considered “mechanical force” under state guidelines. - Deadly force: The firing of an officer's service weapon, regardless of whether a subject was hit. “Warning shots” are prohibited, and officers are instructed not to shoot just to maim or subdue a suspect.

  12. T

    Utah Law Enforcement

    • opendata.utah.gov
    • opendata.gis.utah.gov
    • +2more
    csv, xlsx, xml
    Updated Mar 20, 2020
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    (2020). Utah Law Enforcement [Dataset]. https://opendata.utah.gov/dataset/Utah-Law-Enforcement/az9m-juif
    Explore at:
    csv, xml, xlsxAvailable download formats
    Dataset updated
    Mar 20, 2020
    Area covered
    Utah
    Description

    Law Enforcement Locations in Utah Any location where sworn officers of a law enforcement agency are regularly based or stationed. Law enforcement agencies "are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Although TGS's intention is to only include locations associated with agencies that meet the above definition, TGS has discovered a few locations that are associated with agencies that are not publicly funded. TGS is deleting these locations as we become aware of them, but some probably still exist in this dataset. Personal homes, administrative offices and temporary locations are intended to be excluded from this dataset, but a few may be included. Personal homes of constables may exist due to fact that many constables work out of their home. FBI entites are intended to be excluded from this dataset, but a few may be included. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] attribute. Based upon this attribute, the oldest record dates from 2006/06/27 and the newest record dates from 2013/05/20

    Last Update: March 6, 2014

  13. b

    US Crime Dataset

    • brightdata.com
    .json, .csv, .xlsx
    Updated May 21, 2024
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    Bright Data (2024). US Crime Dataset [Dataset]. https://brightdata.com/products/datasets/crime/us
    Explore at:
    .json, .csv, .xlsxAvailable download formats
    Dataset updated
    May 21, 2024
    Dataset authored and provided by
    Bright Data
    License

    https://brightdata.com/licensehttps://brightdata.com/license

    Area covered
    Worldwide, United States
    Description

    We will build you a custom US crime dataset based on your needs. Data points may include date, time, location, crime type, crime description, victim demographics, offender demographics, arrest records, charges filed, court outcomes, police department response time, incident outcome, weapon used, property stolen or damaged, crime location type, and other related data.

    Use our US crime datasets for a range of applications to enhance public safety and policy effectiveness. Analyzing these datasets can help organizations understand crime patterns and trends across different regions of the United States, enabling them to tailor their strategies and interventions accordingly. Depending on your needs, you may access the entire dataset or a customized subset.

    Popular use cases include: improving public safety measures, designing targeted crime prevention programs, resource allocation for law enforcement, and more.

  14. C

    Officer Use of Force (UOF)

    • phoenixopendata.com
    csv
    Updated Aug 1, 2025
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    Police (2025). Officer Use of Force (UOF) [Dataset]. https://www.phoenixopendata.com/dataset/ouof
    Explore at:
    csv(708614), csv(768951), csv(1241786), csv(1380101), csv(6139039)Available download formats
    Dataset updated
    Aug 1, 2025
    Dataset authored and provided by
    Police
    License

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

    Description

    This dataset contains Use of Force (UOF) incidents (formerly referred to as "Response to Resistance" incidents) from January 2018 forward, including demographic information for officers as well as individuals. All incidents included in the UOF dataset have gone through a review process and have been completed and finalized. Incidents still in process are not included in the dataset until marked complete. Data is updated on the 1st of each month, with a 3-month lag time due to the reporting and review process.

    View Operations Order 1.5

    Provide your feedback!

    Help us improve this site and complete the Open Data Customer Survey.

  15. A

    ‘Stanford Open Policing Project’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Sep 30, 2021
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2021). ‘Stanford Open Policing Project’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-stanford-open-policing-project-0379/607f2ae4/?iid=023-180&v=presentation
    Explore at:
    Dataset updated
    Sep 30, 2021
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘Stanford Open Policing Project’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/faressayah/stanford-open-policing-project on 29 August 2021.

    --- Dataset description provided by original source is as follows ---

    Context

    On a typical day in the United States, police officers make more than 50,000 traffic stops. Our team is gathering, analyzing, and releasing records from millions of traffic stops by law enforcement agencies across the country. Our goal is to help researchers, journalists, and policymakers investigate and improve interactions between police and the public.

    Content

    This dataset includes 9 Mb of stop data from Rhode Island, covering all of 2013 onwards. Please see the data readme for the full details of the available fields.

    Acknowledgements

    This dataset was kindly made available by the Stanford Open Policing Project. If you use it for a research publication, please cite their working paper: E. Pierson, C. Simoiu, J. Overgoor, S. Corbett-Davies, V. Ramachandran, C. Phillips, S. Goel. (2017) “A large-scale analysis of racial disparities in police stops across the United States”.

    Inspiration

    • Do men or women speed more often?
    • Does gender affect who gets searched during a stop?
    • During a search, how often is the driver frisked?
    • Which year had the least number of stops?
    • How does drug activity change by time of day?
    • Do most stops occur at night?

    Those all are question waiting for you to answer them, Good Luck😃

    --- Original source retains full ownership of the source dataset ---

  16. Data from: Police Corruption in Thirty Agencies in the United States, 1997

    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    • icpsr.umich.edu
    • +1more
    Updated Mar 12, 2025
    + more versions
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    National Institute of Justice (2025). Police Corruption in Thirty Agencies in the United States, 1997 [Dataset]. https://res1catalogd-o-tdatad-o-tgov.vcapture.xyz/dataset/police-corruption-in-thirty-agencies-in-the-united-states-1997-0b158
    Explore at:
    Dataset updated
    Mar 12, 2025
    Dataset provided by
    National Institute of Justicehttp://nij.ojp.gov/
    Area covered
    United States
    Description

    This study examined police officers' perceptions of and tolerance for corruption. In contrast to the popular viewpoint that police corruption is a result of moral defects in the individual police officer, this study investigated corruption from an organizational viewpoint. The approach examined the ways rules are communicated to officers, how rules are enforced by supervisors, including sanctions for violation of ethical guidelines, the unspoken code against reporting the misconduct of a fellow officer, and the influence of public expectations about police behavior. For the survey, a questionnaire describing 11 hypothetical scenarios of police misconduct was administered to 30 police agencies in the United States. Specifically, officers were asked to compare the violations in terms of seriousness and to assess the level of sanctions each violation of policies and procedures both should and would likely receive. For each instance of misconduct, officers were asked about the extent to which they supported agency discipline for it and their willingness to report it. Scenarios included issues such as off-duty private business, free meals, bribes for speeding, free gifts, stealing, drinking on duty, and use of excessive force. Additional information was collected about the officers' personal characteristics, such as length of time in the police force (in general and at their agency), the size of the agency, and the level of rank the officer held.

  17. Police Stations

    • chicago.gov
    • data.cityofchicago.org
    • +5more
    csv, xlsx, xml
    Updated Jun 10, 2016
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    Chicago Police Department (2016). Police Stations [Dataset]. https://www.chicago.gov/city/en/depts/cpd/dataset/police_stations.html
    Explore at:
    xml, xlsx, csvAvailable download formats
    Dataset updated
    Jun 10, 2016
    Dataset authored and provided by
    Chicago Police Departmenthttp://www.chicagopolice.org/
    Description

    Chicago Police district station locations and contact information.

  18. u

    Data from: Address Directory

    • gstore.unm.edu
    csv, geojson, gml +5
    Updated Feb 4, 2010
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    Earth Data Analysis Center (2010). Address Directory [Dataset]. http://gstore.unm.edu/apps/rgisarchive/datasets/faeb3a73-8c0d-40f2-9d69-6075aa1e108e/metadata/FGDC-STD-001-1998.html
    Explore at:
    geojson(5), json(5), xls(5), csv(5), shp(5), kml(5), zip(1), gml(5)Available download formats
    Dataset updated
    Feb 4, 2010
    Dataset provided by
    Earth Data Analysis Center
    Time period covered
    Aug 14, 2006
    Area covered
    Rio Arriba County (35039), West Bounding Coordinate -108.84618475534 East Bounding Coordinate -103.049692021254 North Bounding Coordinate 36.9348613580651 South Bounding Coordinate 31.7845116518986, New Mexico
    Description

    Law Enforcement Locations Any location where sworn officers of a law enforcement agency are regularly based or stationed. Law Enforcement agencies "are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Although TGS's intention is to only include locations associated with agencies that meet the above definition, TGS has discovered a few locations that are associated with agencies that are not publicly funded. TGS deleted these locations as we became aware of them, but some may still exist in this dataset. Personal homes, administrative offices, and temporary locations are intended to be excluded from this dataset; however, some personal homes are included due to the fact that the New Mexico Mounted Police work out of their homes. TGS has made a concerted effort to include all local police; county sheriffs; state police and/or highway patrol; Bureau of Indian Affairs; Bureau of Land Management; Bureau of Reclamation; U.S. Park Police; Bureau of Alcohol, Tobacco, Firearms, and Explosives; U.S. Marshals Service; U.S. Fish and Wildlife Service; National Park Service; U.S. Immigration and Customs Enforcement; and U.S. Customs and Border Protection. This dataset is comprised completely of license free data. FBI entities are intended to be excluded from this dataset, but a few may be included. The Law Enforcement dataset and the Correctional Institutions dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. With the merge of the Law Enforcement and the Correctional Institutions datasets, the NAICS Codes & Descriptions were assigned based on the facility's main function which was determined by the entity's name, facility type, web research, and state supplied data. In instances where the entity's primary function is both law enforcement and corrections, the NAICS Codes and Descriptions are assigned based on the dataset in which the record is located (i.e., a facility that serves as both a Sheriff's Office and as a jail is designated as [NAICSDESCR]="SHERIFFS' OFFICES (EXCEPT COURT FUNCTIONS ONLY)" in the Law Enforcement layer and as [NAICSDESCR]="JAILS (EXCEPT PRIVATE OPERATION OF)" in the Correctional Institutions layer). Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard fields that TGS populated. Double spaces were replaced by single spaces in these same fields. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based on the values in this field, the oldest record dates from 08/14/2006 and the newest record dates from 10/23/2009

  19. a

    TN Law Enforcement

    • opentn-myutk.opendata.arcgis.com
    Updated Sep 13, 2013
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    State of Tennessee STS GIS (2013). TN Law Enforcement [Dataset]. https://opentn-myutk.opendata.arcgis.com/datasets/tnmap::tn-law-enforcement/geoservice
    Explore at:
    Dataset updated
    Sep 13, 2013
    Dataset authored and provided by
    State of Tennessee STS GIS
    Area covered
    Description

    Agency: US Department of Homeland Security. Frequency of updates: irregular. Description: Any location where sworn officers of a law enforcement agency are regularly based or stationed. Law Enforcement agencies "are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Personal homes, administrative offices, and temporary locations are intended to be excluded from this dataset; however, some personal homes of constables are included due to the fact that many constables work out of their homes. TGS has made a concerted effort to include all local police; county sheriffs; state police and/or highway patrol; Bureau of Indian Affairs; Bureau of Land Management; Bureau of Reclamation; U.S. Park Police; Bureau of Alcohol, Tobacco, Firearms, and Explosives; U.S. Marshals Service; U.S. Fish and Wildlife Service; National Park Service; U.S. Immigration and Customs Enforcement; and U.S. Customs and Border Protection. This dataset is comprised completely of license free data. FBI entities are intended to be excluded from this dataset, but a few may be included. Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard fields that TGS populated. Double spaces were replaced by single spaces in these same fields. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] field. Based on the values in this field, the oldest record dates from 04/05/2006 and the newest record dates from 10/16/2009 Purpose Homeland Security Use Cases: Use cases describe how the data may be used and help to define and clarify requirements. 1. An assessment of whether or not the total police capability in a given area is adequate. 2. A list of resources to draw upon in surrounding areas when local resources have temporarily been overwhelmed by a disaster - route analysis can help to determine those entities who are able to respond the quickest. 3. A resource for emergency management planning purposes. 4. A resource for catastrophe response to aid in the retrieval of equipment by outside responders in order to deal with the disaster. 5. A resource for situational awareness planning and response for federal government events. Projection: WGS 1984.

  20. NYPD Shooting Incident Data (Year To Date)

    • data.cityofnewyork.us
    • datasets.ai
    • +4more
    Updated Jul 15, 2025
    + more versions
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    Police Department (NYPD) (2025). NYPD Shooting Incident Data (Year To Date) [Dataset]. https://data.cityofnewyork.us/Public-Safety/NYPD-Shooting-Incident-Data-Year-To-Date-/5ucz-vwe8
    Explore at:
    csv, tsv, application/rssxml, xml, application/rdfxml, application/geo+json, kmz, kmlAvailable download formats
    Dataset updated
    Jul 15, 2025
    Dataset provided by
    New York City Police Departmenthttps://nyc.gov/nypd
    Authors
    Police Department (NYPD)
    Description

    List of every shooting incident that occurred in NYC during the current calendar year.

    This is a breakdown of every shooting incident that occurred in NYC 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 shooting incident in NYC and includes information about the event, the location and time of occurrence. In addition, information related to suspect and victim 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.

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State of Oregon (2025). Law Enforcement Facilities [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/law-enforcement-facilities

Law Enforcement Facilities

Explore at:
Dataset updated
Jan 31, 2025
Dataset provided by
State of Oregon
Description

Law Enforcement Locations Any _location where sworn officers of a law enforcement agency are regularly based or stationed. Law Enforcement agencies "are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Although TGS's intention is to only include locations associated with agencies that meet the above definition, TGS has discovered a few locations that are associated with agencies that are not publicly funded. TGS deleted these locations as we became aware of them, but some may still exist in this dataset. Personal homes, administrative offices, and temporary locations are intended to be excluded from this dataset; however, some personal homes of constables are included due to the fact that many constables work out of their homes. TGS has made a concerted effort to include all local police; county sheriffs; state police and/or highway patrol; Bureau of Indian Affairs; Bureau of Land Management; Bureau of Reclamation; U.S. Park Police; Bureau of Alcohol, Tobacco, Firearms, and Explosives; U.S. Marshals Service; U.S. Fish and Wildlife Service; National Park Service; U.S. Immigration and Customs Enforcement; and U.S. Customs and Border Protection. This dataset is comprised completely of license free data. FBI entities are intended to be excluded from this dataset, but a few may be included. The Law Enforcement dataset and the Correctional Institutions dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. With the merge of the Law Enforcement and the Correctional Institutions datasets, the NAICS Codes & Descriptions were assigned based on the facility's main function which was determined by the entity's name, facility type, web research, and state supplied data. In instances where the entity's primary function is both law enforcement and corrections, the NAICS Codes and Descriptions are assigned based on the dataset in which the record is located (i.e., a facility that serves as both a Sheriff's Office and as a jail is designated as [NAICSDESCR]="SHERIFFS' OFFICES (EXCEPT COURT FUNCTIONS ONLY)" in the Law Enforcement layer and as [NAICSDESCR]="JAILS (EXCEPT PRIVATE OPERATION OF)" in the Correctional Institutions layer). Records with "-DOD" appended to the end of the [NAME] value are located on a military base, as defined by the Defense Installation Spatial Data Infrastructure (DISDI) military installations and military range boundaries. "#" and "*" characters were automatically removed from standard fields that TGS populated. Double spaces were replaced by single spaces in these same fields. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been

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