98 datasets found
  1. u

    HSIP Law Enforcement Locations in New Mexico

    • gstore.unm.edu
    • s.cnmilf.com
    • +1more
    Updated Feb 4, 2010
    + more versions
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    (2010). HSIP Law Enforcement Locations in New Mexico [Dataset]. http://gstore.unm.edu/apps/rgis/datasets/faeb3a73-8c0d-40f2-9d69-6075aa1e108e/metadata/ISO-19115:2003.html
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    Dataset updated
    Feb 4, 2010
    Time period covered
    Aug 14, 2006
    Area covered
    New Mexico, West Bound -108.84618475534 East Bound -103.049692021254 North Bound 36.9348613580651 South Bound 31.7845116518986
    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

  2. d

    Law Enforcement Facilities

    • catalog.data.gov
    • data.oregon.gov
    • +3more
    Updated Jan 31, 2025
    + more versions
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    State of Oregon (2025). Law Enforcement Facilities [Dataset]. 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

  3. Census of Federal Law Enforcement Officers (CFLEO), [United States], Fiscal...

    • catalog.data.gov
    • s.cnmilf.com
    • +1more
    Updated Mar 12, 2025
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    Bureau of Justice Statistics (2025). Census of Federal Law Enforcement Officers (CFLEO), [United States], Fiscal Year 2016 [Dataset]. https://catalog.data.gov/dataset/census-of-federal-law-enforcement-officers-cfleo-united-states-fiscal-year-2016-3b8ef
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    Bureau of Justice Statisticshttp://bjs.ojp.gov/
    Area covered
    United States
    Description

    In 2016, there were approximately 132,000 full-time federal law enforcement officers who were authorized to make arrests and carry firearms in the United States and its territories. This data collection comes from the Census of Federal Law Enforcement Officers (CFLEO) and describes the agencies, functions, sex, and race of these officers. The data cover federal officers with arrest and firearm authority in both supervisory and non-supervisory roles employed as of September 30, 2016. The Bureau of Justice Statistics (BJS) administered the CFLEO to 86 federal agencies employing officers with arrest and firearm authority. The data do not include officers stationed in foreign countries and also exclude officers in the U.S. Armed Forces.

  4. T

    Utah Law Enforcement

    • opendata.utah.gov
    • opendata.gis.utah.gov
    • +3more
    application/rdfxml +5
    Updated Mar 20, 2020
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    (2020). Utah Law Enforcement [Dataset]. https://opendata.utah.gov/dataset/Utah-Law-Enforcement/az9m-juif
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    tsv, json, csv, xml, application/rssxml, application/rdfxmlAvailable 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

  5. d

    Law Enforcement Locations.

    • datadiscoverystudio.org
    • data.wu.ac.at
    Updated Dec 8, 2014
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    (2014). Law Enforcement Locations. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/fa287428d04d4219aa88a9304bac46cd/html
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    Dataset updated
    Dec 8, 2014
    Description

    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; abstract: 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

  6. a

    New Hampshire Law Enforcement

    • new-hampshire-geodata-portal-1-nhgranit.hub.arcgis.com
    • nh-granit-nhgranit.hub.arcgis.com
    Updated Dec 30, 2009
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    New Hampshire GRANIT GIS Clearinghouse (2009). New Hampshire Law Enforcement [Dataset]. https://new-hampshire-geodata-portal-1-nhgranit.hub.arcgis.com/datasets/NHGRANIT::new-hampshire-law-enforcement/about
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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

  7. Reported Threats and Assaults on Police Officers

    • data.cincinnati-oh.gov
    application/rdfxml +5
    Updated Nov 27, 2024
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    Cincinnati Police Department (2024). Reported Threats and Assaults on Police Officers [Dataset]. https://data.cincinnati-oh.gov/Safety/Reported-Threats-and-Assaults-on-Police-Officers/a8ms-rdf2
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    csv, application/rdfxml, tsv, json, application/rssxml, xmlAvailable download formats
    Dataset updated
    Nov 27, 2024
    Dataset authored and provided by
    Cincinnati Police Departmenthttp://www.cincinnati-oh.gov/police/
    Description

    Data Description: This data represents reported threats or assaults on officers. Assaults on officers may be defined as the assault of duly sworn city, university and college, county, state, tribal, and federal law enforcement officers. Incidents that are identified as an assault on an officer can include but are not limited to crimes such as aggravated assault, robbery, theft, vandalism, targeted assault (knowingly harming and officer), and recklessly harming an officer.

    Data Creation: This data is recorded using the City's Record Management System (RMS) that stores agency-wide data about law enforcement operations.

    Data Created By: The source of this data is the Cincinnati Police Department.

    Refresh Frequency: This information will not be updated while the Cincinnati Police Department undergoes transfer to a new data management system.

    CincyInsights: The City of Cincinnati maintains an interactive dashboard portal, CincyInsights in addition to our Open Data in an effort to increase access and usage of city data. This data set has an associated dashboard available here: https://insights.cincinnati-oh.gov/stories/s/mrju-z9ui

    Data Dictionary: A data dictionary providing definitions of columns and attributes is available as an attachment to this dataset.

    Processing: The City of Cincinnati is committed to providing the most granular and accurate data possible. In that pursuit the Office of Performance and Data Analytics facilitates standard processing to most raw data prior to publication. Processing includes but is not limited: address verification, geocoding, decoding attributes, and addition of administrative areas (i.e. Census, neighborhoods, police districts, etc.).

    Data Usage: For directions on downloading and using open data please visit our How-to Guide: https://data.cincinnati-oh.gov/dataset/Open-Data-How-To-Guide/gdr9-g3ad

    Disclaimer: In compliance with privacy laws, all Public Safety datasets are anonymized and appropriately redacted prior to publication on the City of Cincinnati’s Open Data Portal. This means that for all public safety datasets: (1) the last two digits of all addresses have been replaced with “XX,” and in cases where there is a single digit street address, the entire address number is replaced with "X"; and (2) Latitude and Longitude have been randomly skewed to represent values within the same block area (but not the exact location) of the incident.

    DISCLAIMER: In compliance with privacy laws, all Public Safety datasets are anonymized and appropriately redacted prior to publication on the City of Cincinnati’s Open Data Portal. This means that for all public safety datasets: (1) the last two digits of all addresses have been replaced with “XX,” and in cases where there is a single digit street address, the entire address number is replaced with "X"; and (2) Latitude and Longitude have been randomly skewed to represent values within the same block area (but not the exact location) of the incident.

  8. T

    PDI (Police Data Initiative) Assaults on Officers

    • data.cincinnati-oh.gov
    application/rdfxml +5
    Updated Aug 2, 2025
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    City of Cincinnati (2025). PDI (Police Data Initiative) Assaults on Officers [Dataset]. https://data.cincinnati-oh.gov/Safety/PDI-Police-Data-Initiative-Assaults-on-Officers/bmmy-avxm
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    csv, tsv, xml, application/rdfxml, json, application/rssxmlAvailable download formats
    Dataset updated
    Aug 2, 2025
    Dataset authored and provided by
    City of Cincinnati
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    This information will not be updated while the Cincinnati Police Department undergoes transfer to a new data management system.

    Data Description: This data represents documented assaults on officers. Assaults on Officers may be defined as the assault of duly sworn city, university and college, county, state, tribal, and federal law enforcement officers. Incidents that are identified as an assault on an officer can include but are not limited to crimes such as aggravated assault, robbery, theft, vandalism, targeted assault (knowingly harming and officer), and recklessly harming an officer.

    Data Creation: This data is recorded using the City's Record Management System (RMS) that stores agency-wide data about law enforcement operations.

    Data Created By: The source of this data is the Cincinnati Police Department.

    Refresh Frequency: This information will not be updated while the Cincinnati Police Department undergoes transfer to a new data management system.

    CincyInsights: The City of Cincinnati maintains an interactive dashboard portal, CincyInsights in addition to our Open Data in an effort to increase access and usage of city data. This data set has an associated dashboard available here: https://insights.cincinnati-oh.gov/stories/s/mrju-z9ui

    Data Dictionary: A data dictionary providing definitions of columns and attributes is available as an attachment to this dataset.

    Processing: The City of Cincinnati is committed to providing the most granular and accurate data possible. In that pursuit the Office of Performance and Data Analytics facilitates standard processing to most raw data prior to publication. Processing includes but is not limited: address verification, geocoding, decoding attributes, and addition of administrative areas (i.e. Census, neighborhoods, police districts, etc.).

    Data Usage: For directions on downloading and using open data please visit our How-to Guide: https://data.cincinnati-oh.gov/dataset/Open-Data-How-To-Guide/gdr9-g3ad

    Disclaimer: In compliance with privacy laws, all Public Safety datasets are anonymized and appropriately redacted prior to publication on the City of Cincinnati’s Open Data Portal. This means that for all public safety datasets: (1) the last two digits of all addresses have been replaced with “XX,” and in cases where there is a single digit street address, the entire address number is replaced with "X"; and (2) Latitude and Longitude have been randomly skewed to represent values within the same block area (but not the exact location) of the incident.

    DISCLAIMER: In compliance with privacy laws, all Public Safety datasets are anonymized and appropriately redacted prior to publication on the City of Cincinnati’s Open Data Portal. This means that for all public safety datasets: (1) the last two digits of all addresses have been replaced with “XX,” and in cases where there is a single digit street address, the entire address number is replaced with "X"; and (2) Latitude and Longitude have been randomly skewed to represent values within the same block area (but not the exact location) of the incident.

  9. Data from: Federal Criminal Case Processing Statistics (FCCPS)

    • catalog.data.gov
    Updated Mar 12, 2025
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    Bureau of Justice Statistics (2025). Federal Criminal Case Processing Statistics (FCCPS) [Dataset]. https://catalog.data.gov/dataset/federal-criminal-case-processing-statistics
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    Bureau of Justice Statisticshttp://bjs.ojp.gov/
    Description

    The Federal Criminal Case Processing Statistics (FCCPS) data tool is an interface that can be used to analyze federal case processing data. Users can generate various statistics in the areas of federal law enforcement, prosecution/courts, and incarceration from 1998. Users can also look up data based on title and section of the U.S. Criminal Code from 1994. This data tool includes offenders held for violating federal laws. It excludes commitments from the D.C. Superior Court.

  10. o

    Federal Justice Statistics Program: Arrests and Bookings for Federal...

    • explore.openaire.eu
    • icpsr.umich.edu
    • +1more
    Updated Feb 9, 2009
    + more versions
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    United States Department Of Justice. Office Of Justice Programs. Bureau Of Justice Statistics (2009). Federal Justice Statistics Program: Arrests and Bookings for Federal Offenses, 2007 [United States] [Dataset]. http://doi.org/10.3886/icpsr24231.v2
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    Dataset updated
    Feb 9, 2009
    Authors
    United States Department Of Justice. Office Of Justice Programs. Bureau Of Justice Statistics
    Area covered
    United States
    Description

    The data contain records of arrests and bookings for federal offenses in the United States during fiscal year 2007. The data were constructed from the United States Marshals Service (USMS) Prisoner Tracking System database. Records include arrests made by federal law enforcement agencies (including the USMS), state and local agencies, and self-surrenders. Offenders arrested for federal offenses are transferred to the custody of the USMS for processing, transportation, and detention. The Prisoner Tracking System contains data on all offenders within the custody of the USMS. The data file contains variables from the original USMS 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, Tables 1.1-1.3. 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. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created variable labels and/or value labels.. Federal offenders in the custody of the United States Marshals Service during fiscal year 2007. Federal Justice Statistics Program Data Series Datasets: DS1: Dataset

  11. Federal Law Enforcement Agency Deaths in Custody Reporting Program (FDCRP),...

    • icpsr.umich.edu
    Updated Apr 26, 2023
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    United States. Bureau of Justice Statistics (2023). Federal Law Enforcement Agency Deaths in Custody Reporting Program (FDCRP), [United States], 2020 [Dataset]. http://doi.org/10.3886/ICPSR38581.v1
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    Dataset updated
    Apr 26, 2023
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    United States. Bureau of Justice Statistics
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/38581/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/38581/terms

    Time period covered
    2020
    Area covered
    United States
    Description

    The Death in Custody Reporting Act of 2013 (DICRA) requires the head of each federal law enforcement agency to submit to the U.S. attorney general, information about the death of any person who is detained, under arrest, or in the process of being arrested by a federal law enforcement officer (or by a state or local law enforcement officer while participating in a federal law enforcement operation, task force, or other capacity) being transported to, incarcerated at, or detained at any facility (including immigration or juvenile facilities) pursuant to a contract with a federal law enforcement agency, state or local government facility used by a federal law enforcement agency, or federal correctional or pre-trial detention facility located within the United States (Death in Custody Reporting Act of 2013, P.L. 113-242). The Bureau of Justice Statistics (BJS) created the Federal Deaths in Custody Reporting Program (FDCRP) to collect the data required of federal law enforcement agencies. Federal law enforcement agencies are surveyed on an annual basis about deaths that fall under the scope of DICRA. This data collection includes the 2020 Arrest-Related Death Incident Report (CJ-13A) data and the 2020 Detention/Incarceration Incident Report (CJ-13B) data.

  12. Sworn Law Enforcement Officer Locations

    • gis-calema.opendata.arcgis.com
    • hub.arcgis.com
    Updated May 23, 2019
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    CA Governor's Office of Emergency Services (2019). Sworn Law Enforcement Officer Locations [Dataset]. https://gis-calema.opendata.arcgis.com/items/b56ab9b746d64d1085ab481be58a0614
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    Dataset updated
    May 23, 2019
    Dataset provided by
    California Governor's Office of Emergency Services
    Authors
    CA Governor's Office of Emergency Services
    Area covered
    Description

    Feature layer showing the locations of Sworn Law Enforcement Officer Locations in California.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. This also applies to mounted police in New Mexico. 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 in the United States and its territories. This dataset is comprised completely of license free data. At the request of NGA, FBI entities are intended to be excluded from this dataset, but a few may be included. The HSIP Freedom Law Enforcement dataset and the HSIP Freedom Correctional Institutions dataset were merged into one working file. TGS processed as one file and then separated for delivery purposes. Please see the process description for the breakdown of how the records were merged. With the merge of the Law Enforcement and the Correctional Institutions datasets, the HSIP Themes and 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 HSIP fields that TGS populated. Double spaces were replaced by single spaces in these same fields. At the request of NGA, text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. At the request of NGA, 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 12/07/2004 and the newest record dates from 09/10/2009.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.

  13. California Crime and Law Enforcement

    • kaggle.com
    Updated Dec 8, 2016
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    Federal Bureau of Investigation (2016). California Crime and Law Enforcement [Dataset]. https://www.kaggle.com/fbi-us/california-crime/metadata
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 8, 2016
    Dataset provided by
    Kaggle
    Authors
    Federal Bureau of Investigation
    Area covered
    California
    Description

    Context

    The Uniform Crime Reporting (UCR) Program has been the starting place for law enforcement executives, students of criminal justice, researchers, members of the media, and the public at large seeking information on crime in the nation. The program was conceived in 1929 by the International Association of Chiefs of Police to meet the need for reliable uniform crime statistics for the nation. In 1930, the FBI was tasked with collecting, publishing, and archiving those statistics.

    Today, four annual publications, Crime in the United States, National Incident-Based Reporting System, Law Enforcement Officers Killed and Assaulted, and Hate Crime Statistics are produced from data received from over 18,000 city, university/college, county, state, tribal, and federal law enforcement agencies voluntarily participating in the program. The crime data are submitted either through a state UCR Program or directly to the FBI’s UCR Program.

    This dataset focuses on the crime rates and law enforcement employment data in the state of California.

    Content

    Crime and law enforcement employment rates are separated into individual files, focusing on offenses by enforcement agency, college/university campus, county, and city. Categories of crimes reported include violent crime, murder and nonnegligent manslaughter, rape, robbery, aggravated assault, property crime, burglary, larceny-theft, motor vehicle damage, and arson. In the case of rape, data is collected for both revised and legacy definitions. In some cases, a small number of enforcement agencies switched definition collection sometime within the same year.

    Acknowledgements

    This dataset originates from the FBI UCR project, and the complete dataset for all 2015 crime reports can be found here.

    Inspiration

    • What are the most common types of crimes in California? Are there certain crimes that are more common in a particular place category, such as a college/university campus, compared to the rest of the state?
    • How does the number of law enforcement officers compare to the crime rates of a particular area? Is the ratio similar throughout the state, or do certain campuses, counties, or cities have a differing rate?
    • How does the legacy vs. refined definition of rape differ, and how do the rape counts compare? If you pulled the same data from FBI datasets for previous years, can you see a difference in rape rates over time?
  14. a

    Police Station

    • mountain-view-fpd-cwpp-mvfpd.hub.arcgis.com
    Updated Dec 12, 2023
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    elisabeth_mvfpd (2023). Police Station [Dataset]. https://mountain-view-fpd-cwpp-mvfpd.hub.arcgis.com/datasets/e20c9aefd4a1435e9f60918ec85a6dd2
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    Dataset updated
    Dec 12, 2023
    Dataset authored and provided by
    elisabeth_mvfpd
    Area covered
    Description

    The local law enforcement locations feature class/ shapefile contains point location and tabular information pertaining to a wide range of law enforcement entities in the United States. 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 Census of State and Local Law Enforcement Agencies (CSLLEA). Unlike the previous version of this dataset, published in 2009, federal level law enforcement agencies are excluded from this effort. Data fusion techniques are utilized to synchronize overlapping yet disparate source data. The primary sources for this effort are the DOJ-BJS CSLLEA from 2008 and the previously mentioned 2009 feature class from Homeland Security Infrastructure Foundation-Level Data (HIFLD). This feature class contains data for agencies across all 50 U.S. states, Washington D.C. and Puerto Rico.

  15. UCI Communities and Crime Unnormalized Data Set

    • kaggle.com
    Updated Feb 21, 2018
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    Kavitha (2018). UCI Communities and Crime Unnormalized Data Set [Dataset]. https://www.kaggle.com/kkanda/communities%20and%20crime%20unnormalized%20data%20set/notebooks
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 21, 2018
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Kavitha
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Description

    Context

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

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

    Content

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

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

    Acknowledgements

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

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

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

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

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

    Inspiration

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

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

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

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

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

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

    4. Does ethnicity play a role in crime rate?

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

  16. Federal Employee Viewpoint Survey (FEVS)

    • catalog.data.gov
    Updated Jan 26, 2024
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    U.S. Office of Personnel Management (2024). Federal Employee Viewpoint Survey (FEVS) [Dataset]. https://catalog.data.gov/dataset/federal-employee-viewpoint-survey-fevs-2ddfc
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    Dataset updated
    Jan 26, 2024
    Dataset provided by
    United States Office of Personnel Managementhttps://opm.gov/
    Description

    The Federal Employee Viewpoint Survey is climate survey and results allow decision makers to assess how employees jointly experience the policies, practices, and procedures of their organizations. The survey allows government employees to share their opinions about what matters most to them, and gives them the opportunity to let their leadership know how they feel about their job, their supervisor, and their agency. Topics assessed in the FEVS focus on organizational practices within leadership scope to act upon. The ultimate goal of the FEVS program is to provide leadership with information that can be leveraged for improving and achieving effective Federal workplaces.Largescale government-wide survey administered by OPM's Employee Services. Each agency has an internal POC leading efforts supporting administration of the survey. Captures agency employee perceptions on work environment; supervisors; managers; executives; Diversity, Equity, Inclusion, and Accessibility; Engagement; job and pay satisfaction; rewards and recognition; as well as demographics of survey takers. ~2300 OPM employees receive this survey / year.

  17. 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

  18. c

    HSIP Correctional Institutions in New Mexico

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

    Jails and Prisons (Correctional Institutions). The Jails and Prisons sub-layer is part of the Emergency Law Enforcement Sector and the Critical Infrastructure Category. A Jail or Prison consists of any facility or _location where individuals are regularly and lawfully detained against their will. This includes Federal and State prisons, local jails, and juvenile detention facilities, as well as law enforcement temporary holding facilities. Work camps, including camps operated seasonally, are included if they otherwise meet the definition. A Federal Prison is a facility operated by the Federal Bureau of Prisons for the incarceration of individuals. A State Prison is a facility operated by a state, commonwealth, or territory of the US for the incarceration of individuals for a term usually longer than 1 year. A Juvenile Detention Facility is a facility for the incarceration of those who have not yet reached the age of majority (usually 18 years). A Local Jail is a locally administered facility that holds inmates beyond arraignment (usually 72 hours) and is staffed by municipal or county employees. A temporary holding facility, sometimes referred to as a "police lock up" or "drunk tank", is a facility used to detain people prior to arraignment. Locations that are administrative offices only are excluded from the dataset. This definition of Jails is consistent with that used by the Department of Justice (DOJ) in their "National Jail Census", with the exception of "temporary holding facilities", which the DOJ excludes. Locations which function primarily as law enforcement offices are included in this dataset if they have holding cells. If the facility is enclosed with a fence, wall, or structure with a gate around the buildings only, the locations were depicted as "on entity" at the center of the facility. If the facility's buildings are not enclosed, the locations were depicted as "on entity" on the main building or "block face" on the correct street segment. Personal homes, administrative offices, and temporary locations are intended to be excluded from this dataset. TGS has made a concerted effort to include all correctional institutions. This dataset includes non license restricted data from the following federal agencies: Bureau of Indian Affairs; Bureau of Reclamation; U.S. Park Police; Federal Bureau of Prisons; 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. 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, 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 12/27/2004 and the newest record dates from 09/08/2009

  19. Consumer Sentinel Network Data Book CY 2019

    • datasets.ai
    • s.cnmilf.com
    • +1more
    33, 58
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    Federal Trade Commission, Consumer Sentinel Network Data Book CY 2019 [Dataset]. https://datasets.ai/datasets/consumer-sentinel-network-data-book-cy-2019
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    33, 58Available download formats
    Dataset authored and provided by
    Federal Trade Commissionhttp://www.ftc.gov/
    Description

    The FTC produces the Consumer Sentinel Network Data Book annually using a data set of fraud, identity theft, and other reports from consumers received by the Consumer Sentinel Network. These include reports made directly by consumers to the FTC, as well as reports received by federal, state, local, and international law enforcement agencies and other non-governmental organizations. This data set includes national statistics, as well as a state-by-state listing of top report categories in each state and a listing of metropolitan areas that generated the most complaints per capita, for calendar year 2019. (Zip archive, CSV files)

  20. Data from: Study of Sworn Nonfederal Law Enforcement Officers Arrested in...

    • catalog.data.gov
    • icpsr.umich.edu
    • +1more
    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?

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(2010). HSIP Law Enforcement Locations in New Mexico [Dataset]. http://gstore.unm.edu/apps/rgis/datasets/faeb3a73-8c0d-40f2-9d69-6075aa1e108e/metadata/ISO-19115:2003.html

HSIP Law Enforcement Locations in New Mexico

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Dataset updated
Feb 4, 2010
Time period covered
Aug 14, 2006
Area covered
New Mexico, West Bound -108.84618475534 East Bound -103.049692021254 North Bound 36.9348613580651 South Bound 31.7845116518986
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

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