The Tempe Police Department prides itself in its continued efforts to reduce harm within the community and is providing this dataset on hate crime incidents that occur in Tempe.The Tempe Police Department documents the type of bias that motivated a hate crime according to those categories established by the FBI. These include crimes motivated by biases based on race and ethnicity, religion, sexual orientation, disability, gender and gender identity.The Bias Type categories provided in the data come from the Bias Motivation Categories as defined in the Federal Bureau of Investigation (FBI) National Incident-Based Reporting System (NIBRS) manual, version 2020.1 dated 4/15/2021. The FBI NIBRS manual can be found at https://www.fbi.gov/file-repository/ucr/ucr-2019-1-nibrs-user-manua-093020.pdf with the Bias Motivation Categories found on pages 78-79.Although data is updated monthly, there is a delay by one month to allow for data validation and submission.Information about Tempe Police Department's collection and reporting process for possible hate crimes is included in https://storymaps.arcgis.com/stories/a963e97ca3494bfc8cd66d593eebabaf.Additional InformationSource: Data are from the Law Enforcement Records Management System (RMS)Contact: Angelique BeltranContact E-Mail: angelique_beltran@tempe.govData Source Type: TabularPreparation Method: Data from the Law Enforcement Records Management System (RMS) are entered by the Tempe Police Department into a GIS mapping system, which automatically publishes to open data.Publish Frequency: MonthlyPublish Method: New data entries are automatically published to open data. Data Dictionary

Crime data assembled by census block group for the MSA from the Applied Geographic Solutions' (AGS) 1999 and 2005 'CrimeRisk' databases distributed by the Tetrad Computer Applications Inc. CrimeRisk is the result of an extensive analysis of FBI crime statistics. Based on detailed modeling of the relationships between crime and demographics, CrimeRisk provides an accurate view of the relative risk of specific crime types at the block group level. Data from 1990 - 1996,1999, and 2004-2005 were used to compute the attributes, please refer to the 'Supplemental Information' section of the metadata for more details. Attributes are available for two categories of crimes, personal crimes and property crimes, along with total and personal crime indices. Attributes for personal crimes include murder, rape, robbery, and assault. Attributes for property crimes include burglary, larceny, and mother vehicle theft. 12 block groups have no attribute information. CrimeRisk is a block group and higher level geographic database consisting of a series of standardized indexes for a range of serious crimes against both persons and property. It is derived from an extensive analysis of several years of crime reports from the vast majority of law enforcement jurisdictions nationwide. The crimes included in the database are the "Part I" crimes and include murder, rape, robbery, assault, burglary, theft, and motor vehicle theft. These categories are the primary reporting categories used by the FBI in its Uniform Crime Report (UCR), with the exception of Arson, for which data is very inconsistently reported at the jurisdictional level. Part II crimes are not reported in the detail databases and are generally available only for selected areas or at high levels of geography. In accordance with the reporting procedures using in the UCR reports, aggregate indexes have been prepared for personal and property crimes separately, as well as a total index. While this provides a useful measure of the relative "overall" crime rate in an area, it must be recognized that these are unweighted indexes, in that a murder is weighted no more heavily than a purse snatching in the computation. For this reason, caution is advised when using any of the aggregate index values. The block group boundaries used in the dataset come from TeleAtlas's (formerly GDT) Dynamap data, and are consistent with all other block group boundaries in the BES geodatabase.

   This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase.


   The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive.


   The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders.


   Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.


   This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase.


   The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive.


   The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders.


   Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

The Regional Crime Analysis GIS (RCAGIS) is an Environmental Systems Research Institute (ESRI) MapObjects-based system that was developed by the United States Department of Justice Criminal Division Geographic Information Systems (GIS) Staff, in conjunction with the Baltimore County Police Department and the Regional Crime Analysis System (RCAS) group, to facilitate the analysis of crime on a regional basis. The RCAGIS system was designed specifically to assist in the analysis of crime incident data across jurisdictional boundaries. Features of the system include: (1) three modes, each designed for a specific level of analysis (simple queries, crime analysis, or reports), (2) wizard-driven (guided) incident database queries, (3) graphical tools for the creation, saving, and printing of map layout files, (4) an interface with CrimeStat spatial statistics software developed by Ned Levine and Associates for advanced analysis tools such as hot spot surfaces and ellipses, (5) tools for graphically viewing and analyzing historical crime trends in specific areas, and (6) linkage tools for drawing connections between vehicle theft and recovery locations, incident locations and suspects' homes, and between attributes in any two loaded shapefiles. RCAGIS also supports digital imagery, such as orthophotos and other raster data sources, and geographic source data in multiple projections. RCAGIS can be configured to support multiple incident database backends and varying database schemas using a field mapping utility.

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

Important Note: This item is in mature support as of June 2023 and will be retired in December 2025.This map shows the total crime index in the U.S. in 2022 in a multi-scale map (by state, county, ZIP Code, tract, and block group). The layer uses 2020 Census boundaries.The pop-up is configured to include the following information for each geography level:Total crime indexPersonal and Property crime indices Sub-categories of personal and property crime indicesPermitted use of this data is covered in the DATA section of the EsriMaster Agreement (E204CW) and these supplemental terms.

Serious violent crimes consist of Part 1 offenses as defined by the U.S. Department of Justice’s Uniform Reporting Statistics. These include murders, nonnegligent homicides, rapes (legacy and revised), robberies, and aggravated assaults. LAPD data were used for City of Los Angeles, LASD data were used for unincorporated areas and cities that contract with LASD for law enforcement services, and CA Attorney General data were used for all other cities with local police departments. This indicator is based on location of residence. Single-year data are only available for Los Angeles County overall, Service Planning Areas, Supervisorial Districts, City of Los Angeles overall, and City of Los Angeles Council Districts.Neighborhood violence and crime can have a harmful impact on all members of a community. Living in communities with high rates of violence and crime not only exposes residents to a greater personal risk of injury or death, but it can also render individuals more susceptible to many adverse health outcomes. People who are regularly exposed to violence and crime are more likely to suffer from chronic stress, depression, anxiety, and other mental health conditions. They are also less likely to be able to use their parks and neighborhoods for recreation and physical activity.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

This dataset reflects reported incidents of crime (with the exception of murders where data exists for each victim) that occurred in the City of Chicago from 2001 to present, minus the most recent seven days. Data is extracted from the Chicago Police Department's CLEAR (Citizen Law Enforcement Analysis and Reporting) system. In order to protect the privacy of crime victims, addresses are shown at the block level only and specific locations are not identified. Should you have questions about this dataset, you may contact the Research & Development Division of the Chicago Police Department at 312.745.6071 or RandD@chicagopolice.org. Disclaimer: These crimes may be based upon preliminary information supplied to the Police Department by the reporting parties that have not been verified. The preliminary crime classifications may be changed at a later date based upon additional investigation and there is always the possibility of mechanical or human error. Therefore, the Chicago Police Department does not guarantee (either expressed or implied) the accuracy, completeness, timeliness, or correct sequencing of the information and the information should not be used for comparison purposes over time. The Chicago Police Department will not be responsible for any error or omission, or for the use of, or the results obtained from the use of this information. All data visualizations on maps should be considered approximate and attempts to derive specific addresses are strictly prohibited. The Chicago Police Department is not responsible for the content of any off-site pages that are referenced by or that reference this web page other than an official City of Chicago or Chicago Police Department web page. The user specifically acknowledges that the Chicago Police Department is not responsible for any defamatory, offensive, misleading, or illegal conduct of other users, links, or third parties and that the risk of injury from the foregoing rests entirely with the user. The unauthorized use of the words "Chicago Police Department," "Chicago Police," or any colorable imitation of these words or the unauthorized use of the Chicago Police Department logo is unlawful. This web page does not, in any way, authorize such use. Data is updated daily Tuesday through Sunday. The dataset contains more than 65,000 records/rows of data and cannot be viewed in full in Microsoft Excel. Therefore, when downloading the file, select CSV from the Export menu. Open the file in an ASCII text editor, such as Wordpad, to view and search. To access a list of Chicago Police Department - Illinois Uniform Crime Reporting (IUCR) codes, go to http://data.cityofchicago.org/Public-Safety/Chicago-Police-Department-Illinois-Uniform-Crime-R/c7ck-438e

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

***Starting on March 7th, 2024, the Los Angeles Police Department (LAPD) will adopt a new Records Management System for reporting crimes and arrests. This new system is being implemented to comply with the FBI's mandate to collect NIBRS-only data (NIBRS — FBI - https://www.fbi.gov/how-we-can-help-you/more-fbi-services-and-information/ucr/nibrs). During this transition, users will temporarily see only incidents reported in the retiring system. However, the LAPD is actively working on generating new NIBRS datasets to ensure a smoother and more efficient reporting system. ***

******Update 1/18/2024 - LAPD is facing issues with posting the Crime data, but we are taking immediate action to resolve the problem. We understand the importance of providing reliable and up-to-date information and are committed to delivering it.

As we work through the issues, we have temporarily reduced our updates from weekly to bi-weekly to ensure that we provide accurate information. Our team is actively working to identify and resolve these issues promptly.

We apologize for any inconvenience this may cause and appreciate your understanding. Rest assured, we are doing everything we can to fix the problem and get back to providing weekly updates as soon as possible. ******

This dataset reflects incidents of crime in the City of Los Angeles dating back to 2020. This data is transcribed from original crime reports that are typed on paper and therefore there may be some inaccuracies within the data. Some location fields with missing data are noted as (0°, 0°). Address fields are only provided to the nearest hundred block in order to maintain privacy. This data is as accurate as the data in the database. Please note questions or concerns in the comments.

Description Crime incidents starting with those reported in 2016. The data provided is the latest available information and is updated regularly as statistics change. For access to comprehensive reports, kindly submit a public record request here.Note: Crimes that occurred before 2016 are included if the date reported was in 2016 or later.

Disclaimer: The City strives to provide the highest-quality information on this platform. The content on this website is provided as a public service, on an ‘as is’ basis. The City makes no warranty, representation, or guarantee of any type as to the content, accuracy, timeliness, completeness, or fitness for any particular purpose or use of any public data provided on this portal; nor shall any such warranty be implied, including, without limitation, the implied warranties of merchantability and fitness for a particular purpose. The City assumes no liability by making data available to the public or other departments.This dataset is featured in the following app(s): Cleveland Division of Police Crime DashboardCrime Incidents MapData GlossarySee the Attributes section below for details about each column in this dataset.Update Frequency Daily around 8 AM EST

Contacts

 City of Cleveland, Division of Police

Field Descriptions Crime Dashboard Document - https://www.minneapolismn.gov/government/government-data/datasource/crime-dashboard/crime-dashboard-document/

The data set is refreshed on a daily basis by 9:30 AM. The website will reflect the last time the data set was updated and the total count of rows. The grid on the “Data” tab will display the up to date data. However, in certain situations there is a delay in the refresh of the downloadable data file. Sometimes the downloadable file does not reflect the updates to the data in the portal. After a delay (duration has been variable; up to 30 minutes), the file will be updated on the server and then downloads will include the updated data.

The Detroit Police Department provided property and violent crime location data for 2016. Data Driven Detroit aggregated the data up to a block level. Data was obtained for the health and Safety section of Little Caesar's Arena District Needs Assessment.Click here for metadata (descriptions of the fields).

This dataset includes all valid felony, misdemeanor, and violation crimes reported to the New York City Police Department (NYPD) for all complete quarters so far this year (2017). For additional details, please see the attached data dictionary in the ‘About’ section.

CrimeStat III is a spatial statistics program for the analysis of crime incident locations, developed by Ned Levine and Associates under the direction of Ned Levine, PhD, that was funded by grants from the National Institute of Justice (grants 1997-IJ-CX-0040, 1999-IJ-CX-0044, 2002-IJ-CX-0007, and 2005-IJ-CX-K037). The program is Windows-based and interfaces with most desktop GIS programs. The purpose is to provide supplemental statistical tools to aid law enforcement agencies and criminal justice researchers in their crime mapping efforts. CrimeStat is being used by many police departments around the country as well as by criminal justice and other researchers. The program inputs incident locations (e.g., robbery locations) in 'dbf', 'shp', ASCII or ODBC-compliant formats using either spherical or projected coordinates. It calculates various spatial statistics and writes graphical objects to ArcGIS, MapInfo, Surfer for Windows, and other GIS packages. CrimeStat is organized into five sections: Data Setup Primary file - this is a file of incident or point locations with X and Y coordinates. The coordinate system can be either spherical (lat/lon) or projected. Intensity and weight values are allowed. Each incident can have an associated time value. Secondary file - this is an associated file of incident or point locations with X and Y coordinates. The coordinate system has to be the same as the primary file. Intensity and weight values are allowed. The secondary file is used for comparison with the primary file in the risk-adjusted nearest neighbor clustering routine and the duel kernel interpolation. Reference file - this is a grid file that overlays the study area. Normally, it is a regular grid though irregular ones can be imported. CrimeStat can generate the grid if given the X and Y coordinates for the lower-left and upper-right corners. Measurement parameters - This page identifies the type of distance measurement (direct, indirect or network) to be used and specifies parameters for the area of the study region and the length of the street network. CrimeStat III has the ability to utilize a network for linking points. Each segment can be weighted by travel time, travel speed, travel cost or simple distance. This allows the interaction between points to be estimated more realistically. Spatial Description Spatial distribution - statistics for describing the spatial distribution of incidents, such as the mean center, center of minimum distance, standard deviational ellipse, the convex hull, or directional mean. Spatial autocorrelation - statistics for describing the amount of spatial autocorrelation between zones, including general spatial autocorrelation indices - Moran's I , Geary's C, and the Getis-Ord General G, and correlograms that calculate spatial autocorrelation for different distance separations - the Moran, Geary, Getis-Ord correlograms. Several of these routines can simulate confidence intervals with a Monte Carlo simulation. Distance analysis I - statistics for describing properties of distances between incidents including nearest neighbor analysis, linear nearest neighbor analysis, and Ripley's K statistic. There is also a routine that assigns the primary points to the secondary points, either on the basis of nearest neighbor or point-in-polygon, and then sums the results by the secondary point values. Distance analysis II - calculates matrices representing the distance between points for the primary file, for the distance between the primary and secondary points, and for the distance between either the primary or secondary file and the grid. 'Hot spot' analysis I - routines for conducting 'hot spot' analysis including the mode, the fuzzy mode, hierarchical nearest neighbor clustering, and risk-adjusted nearest neighbor hierarchical clustering. The hierarchical nearest neighbor hot spots can be output as ellipses or convex hulls. 'Hot spot' analysis II - more routines for conducting hot spot analysis including the Spatial and Temporal Analysis of Crime (STAC), K-means clustering, Anselin's local Moran, and the Getis-Ord local G statistics. The STAC and K-means hot spots can be output as ellipses or convex hulls. All of these routines can simulate confidence intervals with a Monte Carlo simulation. Spatial Modeling Interpolation I - a single-variable kernel density estimation routine for producin

This data shows approximate location of select offenses within unincorporated Pierce County, and the cities of Bonney Lake, Eatonville, Edgewood, Gig Harbor, Puyallup, South Prairie, and University Place. The data is for the previous 12 months and is updated monthly. Please see full metadata (https://matterhorn.piercecountywa.gov/GISmetadata/pdbsd_crime_data.html) for additional information. Any data download constitutes acceptance of the Terms of Use (https://matterhorn.piercecountywa.gov/Disclaimer/PierceCountyGISDataTermsofUse.pdf).

Use Crime Dashboard to view crime by geographies like CPD District, CPD Beat, Ward and Community Area. Visualize how those polygons overlap. Includes interactive graphs like time of day & day of week. Allows for filtering by date and crime types. Query results can be exported as a .csv file by using a button lower left on the Crime Incidents widget. Be aware popup blockers may prevent downloading.Crime data is updated daily but with a 7-day lag from yesterday to allow the data to stabilize before it’s released to the public. Exact house numbers are not shown, and the data is not offset off the street centerline.

Crimes & incidents within Sarpy County, NebraskaData current as of the last business day.

The City of Ferndale uses the service CrimeMapping.com to provide near-live mapping of local crimes, sorted by category. Our goal in providing this information is to reduce crime through a better-informed citizenry. Crime reports older than 180 days can be accessed in this data set. For near-live crime data, go to crimemapping.com. this is a subset of this historic data that has been geocoded to allow for easy analysis and mapping in a different data set. It contains all easily geocoded addresses. A complete CSV file covering all crime reports from 5/2011 to 5/2017 is also available.

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

As a first step in understanding law enforcement agencies' use and knowledge of crime mapping, the Crime Mapping Research Center (CMRC) of the National Institute of Justice conducted a nationwide survey to determine which agencies were using geographic information systems (GIS), how they were using them, and, among agencies that were not using GIS, the reasons for that choice. Data were gathered using a survey instrument developed by National Institute of Justice staff, reviewed by practitioners and researchers with crime mapping knowledge, and approved by the Office of Management and Budget. The survey was mailed in March 1997 to a sample of law enforcement agencies in the United States. Surveys were accepted until May 1, 1998. Questions asked of all respondents included type of agency, population of community, number of personnel, types of crimes for which the agency kept incident-based records, types of crime analyses conducted, and whether the agency performed computerized crime mapping. Those agencies that reported using computerized crime mapping were asked which staff conducted the mapping, types of training their staff received in mapping, types of software and computers used, whether the agency used a global positioning system, types of data geocoded and mapped, types of spatial analyses performed and how often, use of hot spot analyses, how mapping results were used, how maps were maintained, whether the department kept an archive of geocoded data, what external data sources were used, whether the agency collaborated with other departments, what types of Department of Justice training would benefit the agency, what problems the agency had encountered in implementing mapping, and which external sources had funded crime mapping at the agency. Departments that reported no use of computerized crime mapping were asked why that was the case, whether they used electronic crime data, what types of software they used, and what types of Department of Justice training would benefit their agencies.