Law-enforcement reported offense and clearance data made available through the FBI Crime Data Explorer, with coverage varying by agency and year.

Federal Bureau of Investigation, Department of Justice - Extraction of crime related data from the FBI's Uniform Crime Reporting (UCR) Program

For a comprehensive guide to this data and other UCR data, please see my book at ucrbook.comVersion 16 release notes:Adds .parquet file formatVersion 15 release notes:Adds 2023 and 2024 dataVersion 14 release notes:Reupload data to fix issue with Stata file not opening.Version 13 release notes:Adds 2022 dataVersion 12 release notes:Adds 2021 data.Version 11 release notes:Adds 2020 data. Please note that the FBI has retired UCR data ending in 2020 data so this will be the last SHR data they release. Changes .rda file to .rds.Version 10 release notes:Changes release notes description, does not change data.Version 9 release notes:Adds 2019 data.Version 8 release notes:Adds 2018 data.Changes source of data for years 1985-2018 to be directly from the FBI. 2018 data was received via email from the FBI, 2016-2017 is from the FBI who mailed me a DVD, and 1985-2015 data is from the FBI's Crime Data Explorer site (https://crime-data-explorer.fr.cloud.gov/downloads-and-docs).Adds .csv version of the data.Makes minor changes to value labels for consistency and to fix grammar. Version 7 release notes:Changes project name to avoid confusing this data for the ones done by NACJD.Version 6 release notes:Adds 2017 data.Version 5 release notes:Adds 2016 data.Standardizes the "group" column which categorizes cities and counties by population.Arrange rows in descending order by year and ascending order by ORI. Version 4 release notes: Fix bug where Philadelphia Police Department had incorrect FIPS county code. Version 3 Release Notes:Merges data with LEAIC data to add FIPS codes, census codes, agency type variables, and ORI9 variable.Change column names for relationship variables from offender_n_relation_to_victim_1 to victim_1_relation_to_offender_n to better indicate that all relationship are victim 1's relationship to each offender. Reorder columns.This is a single file containing all data from the Supplementary Homicide Reports from 1976 to 2018. The Supplementary Homicide Report provides detailed information about the victim, offender, and circumstances of the murder. Details include victim and offender age, sex, race, ethnicity (Hispanic/not Hispanic), the weapon used, circumstances of the incident, and the number of both offenders and victims. Years 1976-1984 were downloaded from NACJD, while more recent years are from the FBI. All files came as ASCII+SPSS Setup files and were cleaned using R. The "cleaning" just means that column names were standardized (different years have slightly different spellings for many columns). Standardization of column names is necessary to stack multiple years together. Categorical variables (e.g. state) were also standardized (i.e. fix spelling errors, have terminology be the same across years). The following is the summary of the Supplementary Homicide Report copied from ICPSR's 2015 page for the data.The Uniform Crime Reporting Program Data: Supplementary Homicide Reports (SHR) provide detailed information on criminal homicides reported to the police. These homicides consist of murders; non-negligent killings also called non-negligent manslaughter; and justifiable homicides. UCR Program contributors compile and submit their crime data by one of two means: either directly to the FBI or through their State UCR Programs. State UCR Programs frequently impose mandatory reporting requirements which have been effective in increasing both the number of reporting agencies as well as the number and accuracy of each participating agency's reports. Each agency may be identified by its numeric state code, alpha-numeric agency ("ORI") code, jurisdiction population, and population group. In addition, each homicide incident is identified by month of occurrence and situation type, allowing flexibility in creating aggregations and subsets.

In 2021, the San Diego Police Department began reporting to the FBI’s National Incident-Based Reporting System (NIBRS) for statistics. NIBRS collects data on all crimes reported to law enforcement agencies, not just the highest charges within those crimes. Crime categories in NIBRS include crimes against Persons (i.e., assault, homicide, etc.), Property (i.e., burglary, theft, robbery, etc.), and Society (i.e., alcohol and drug offenses, weapon offenses, gambling, etc.). These new categories are a shift from the older FBI reporting style (UCR Summary) of simply reporting violent and property crime counts. For the most part, SDPD’s crime reporting will follow the NIBRS categories now. Historical data will still be posted to the Annual Crime Reports website. This dataset comprises of Crime Offense Data extracted from the San Diego Police Department’s Records Management System and includes information such as the date/time of the reported offense, offense category, underlying code sections, and the hundred block address where the incident occurred. This data is dynamic as records are updated daily and may change or be deleted as police investigations proceed. Records range from January 2020 – Present. The SDPD Neighborhood Crime Summary Dashboard visualizes this dataset. For more information on NIBRS reporting guidelines please refer to the FBI’s 2021.1 National Incident-Based Reporting System User Manual. For national NIBRS data, you can visit the FBI’s Crime Data Explorer.

For a comprehensive guide to this data and other UCR data, please see my book at ucrbook.comVersion 12 release notes:Adds 2021 data.Version 11 release notes:Adds 2020 data. Please note that the FBI has retired UCR data ending in 2020 data so this will be the last SHR data they release. Changes .rda file to .rds.Version 10 release notes:Changes release notes description, does not change data.Version 9 release notes:Adds 2019 data.Version 8 release notes:Adds 2018 data.Changes source of data for years 1985-2018 to be directly from the FBI. 2018 data was received via email from the FBI, 2016-2017 is from the FBI who mailed me a DVD, and 1985-2015 data is from the FBI's Crime Data Explorer site (https://crime-data-explorer.fr.cloud.gov/downloads-and-docs).Adds .csv version of the data.Makes minor changes to value labels for consistency and to fix grammar. Version 7 release notes:Changes project name to avoid confusing this data for the ones done by NACJD.Version 6 release notes:Adds 2017 data.Version 5 release notes:Adds 2016 data.Standardizes the "group" column which categorizes cities and counties by population.Arrange rows in descending order by year and ascending order by ORI. Version 4 release notes: Fix bug where Philadelphia Police Department had incorrect FIPS county code. Version 3 Release Notes:Merges data with LEAIC data to add FIPS codes, census codes, agency type variables, and ORI9 variable.Change column names for relationship variables from offender_n_relation_to_victim_1 to victim_1_relation_to_offender_n to better indicate that all relationship are victim 1's relationship to each offender. Reorder columns.This is a single file containing all data from the Supplementary Homicide Reports from 1976 to 2018. The Supplementary Homicide Report provides detailed information about the victim, offender, and circumstances of the murder. Details include victim and offender age, sex, race, ethnicity (Hispanic/not Hispanic), the weapon used, circumstances of the incident, and the number of both offenders and victims. Years 1976-1984 were downloaded from NACJD, while more recent years are from the FBI. All files came as ASCII+SPSS Setup files and were cleaned using R. The "cleaning" just means that column names were standardized (different years have slightly different spellings for many columns). Standardization of column names is necessary to stack multiple years together. Categorical variables (e.g. state) were also standardized (i.e. fix spelling errors, have terminology be the same across years). The following is the summary of the Supplementary Homicide Report copied from ICPSR's 2015 page for the data.The Uniform Crime Reporting Program Data: Supplementary Homicide Reports (SHR) provide detailed information on criminal homicides reported to the police. These homicides consist of murders; non-negligent killings also called non-negligent manslaughter; and justifiable homicides. UCR Program contributors compile and submit their crime data by one of two means: either directly to the FBI or through their State UCR Programs. State UCR Programs frequently impose mandatory reporting requirements which have been effective in increasing both the number of reporting agencies as well as the number and accuracy of each participating agency's reports. Each agency may be identified by its numeric state code, alpha-numeric agency ("ORI") code, jurisdiction population, and population group. In addition, each homicide incident is identified by month of occurrence and situation type, allowing flexibility in creating aggregations and subsets.

The property crime rate indicator includes both the total number of property crime incidents per year in Champaign County, and the number of property crime incidents per 100,000 people per year in Champaign County. “Property crimes” are those counted in the following categories in the Illinois State Police’s annual Crime in Illinois report: Burglary, Theft (Larceny), Motor Vehicle Theft, and Arson. Like violent crime, property crime is also a major indicator of community safety.

The property crime data spans the same time period as the violent crime data: 1996 to 2021. The total number of offenses and rate per 100,000 population are both substantially lower as of 2021 than at the beginning of the study period in 1996. 2021 actually saw the lowest number of offenses and the lowest rate per 100,000 population in the study period. There are significantly more property crime offenses in Champaign County than violent crime incidents.

This data is sourced from the Illinois State Police’s annually released Crime in Illinois: Annual Uniform Crime Report, available on the Uniform Crime Report Index Offense Explorer.

Sources: Illinois State Police. (2021). Crime in Illinois: Annual Uniform Crime Report 2021. Illinois State Police. (2020). Crime in Illinois: Annual Uniform Crime Report 2020. Illinois State Police. (2019). Crime in Illinois: Annual Uniform Crime Report 2019. Illinois State Police. (2018). Crime in Illinois: Annual Uniform Crime Report 2018. Illinois State Police. (2017). Crime in Illinois: Annual Uniform Crime Report 2017. Illinois State Police. (2018). Crime in Illinois: Annual Uniform Crime Report 2018. Illinois State Police. (2017). Crime in Illinois: Annual Uniform Crime Report 2017. Illinois State Police. (2016). Crime in Illinois: Annual Uniform Crime Report 2016. Illinois State Police. (2015). Crime in Illinois: Annual Uniform Crime Report 2015. Illinois State Police. (2014). Crime in Illinois: Annual Uniform Crime Report 2014.; Illinois State Police. (2012). Crime in Illinois: Annual Uniform Crime Report 2012.; Illinois State Police. (2011). Crime in Illinois: Annual Uniform Crime Report 2010-2011.; Illinois State Police. (2009). Crime in Illinois: Annual Uniform Crime Report 2009.; Illinois State Police. (2007). Crime in Illinois: Annual Uniform Crime Report 2007.; Illinois State Police. (2005). Crime in Illinois: Annual Uniform Crime Report 2005.; Illinois State Police. (2003). Crime in Illinois: Annual Uniform Crime Report 2003.; Illinois State Police. (2001). Crime in Illinois: Annual Uniform Crime Report 2001.; Illinois State Police. (1999). Crime in Illinois: Annual Uniform Crime Report 1999.; Illinois State Police. (1997). Crime in Illinois: Annual Uniform Crime Report 1997.

This data set is up-to-date as of 2017, but is no longer actively maintained by the City of South Bend.Updated crime data for South Bend can be found on the following website: https://crime-data-explorer.fr.cloud.gov/explorer/agency/IN0710200/crimeThis data set contains historic annual totals for the FBI's Uniform Crime Reporting Program. Includes violent and property crime data for South Bend from 1992 through 2017. *Note that the agency reporting definition of rape changed in 2013, so figures before and after the change may not be comparable.

For any questions about this data please email me at jacob@crimedatatool.com. If you use this data, please cite it.Version 8 release notes:Adds 2018 data.Changes source of data for years 1985-2018 to be directly from the FBI. 2018 data was received via email from the FBI, 2016-2017 is from the FBI who mailed me a DVD, and 1985-2015 data is from the FBI's Crime Data Explorer site (https://crime-data-explorer.fr.cloud.gov/downloads-and-docs).Adds .csv version of the data.Makes minor changes to value labels for consistency and to fix grammar. Version 7 release notes:Changes project name to avoid confusing this data for the ones done by NACJD.Version 6 release notes:Adds 2017 data.Version 5 release notes:Adds 2016 data.Standardizes the "group" column which categorizes cities and counties by population.Arrange rows in descending order by year and ascending order by ORI. Version 4 release notes: Fix bug where Philadelphia Police Department had incorrect FIPS county code. Version 3 Release Notes:Merges data with LEAIC data to add FIPS codes, census codes, agency type variables, and ORI9 variable.Change column names for relationship variables from offender_n_relation_to_victim_1 to victim_1_relation_to_offender_n to better indicate that all relationship are victim 1's relationship to each offender. Reorder columns.This is a single file containing all data from the Supplementary Homicide Reports from 1976 to 2018. The Supplementary Homicide Report provides detailed information about the victim, offender, and circumstances of the murder. Details include victim and offender age, sex, race, ethnicity (Hispanic/not Hispanic), the weapon used, circumstances of the incident, and the number of both offenders and victims. Years 1976-1984 were downloaded from NACJD, while more recent years are from the FBI. All files came as ASCII+SPSS Setup files and were cleaned using R. The "cleaning" just means that column names were standardized (different years have slightly different spellings for many columns). Standardization of column names is necessary to stack multiple years together. Categorical variables (e.g. state) were also standardized (i.e. fix spelling errors, have terminology be the same across years). The following is the summary of the Supplementary Homicide Report copied from ICPSR's 2015 page for the data.The Uniform Crime Reporting Program Data: Supplementary Homicide Reports (SHR) provide detailed information on criminal homicides reported to the police. These homicides consist of murders; non-negligent killings also called non-negligent manslaughter; and justifiable homicides. UCR Program contributors compile and submit their crime data by one of two means: either directly to the FBI or through their State UCR Programs. State UCR Programs frequently impose mandatory reporting requirements which have been effective in increasing both the number of reporting agencies as well as the number and accuracy of each participating agency's reports. Each agency may be identified by its numeric state code, alpha-numeric agency ("ORI") code, jurisdiction population, and population group. In addition, each homicide incident is identified by month of occurrence and situation type, allowing flexibility in creating aggregations and subsets.

The violent crime rate indicator includes both the total number of violent crime incidents per year in Champaign County, and the number of violent crime incidents per 100,000 people per year in Champaign County. “Violent crimes” are those counted in the following categories in the Illinois State Police’s annual Crime in Illinois report: Criminal Homicide, Criminal Sexual Assault (Rape), Robbery, Aggravated Assault, and Aggravated Battery. The incidence of violent crime is an integral part of understanding the safety of a given community.

Both the total number of offenses in Champaign County and the rate per 100,000 population were significantly lower in 2021 than at the start of the measured time period, 1996. The most recent rise in both of these figures was in 2019-2020, before falling again in 2021. The year with the lowest number of total offenses and the rate per 100,000 population in the study period was 2015; both measures are slightly higher since then.

This data is sourced from the Illinois State Police’s annually released Crime in Illinois: Annual Uniform Crime Report, available on the Uniform Crime Report Index Offense Explorer.

Sources: Illinois State Police. (2021). Crime in Illinois: Annual Uniform Crime Report 2021. Illinois State Police. (2020). Crime in Illinois: Annual Uniform Crime Report 2020. Illinois State Police. (2019). Crime in Illinois: Annual Uniform Crime Report 2019. Illinois State Police. (2018). Crime in Illinois: Annual Uniform Crime Report 2018. Illinois State Police. (2017). Crime in Illinois: Annual Uniform Crime Report 2017.Illinois State Police. (2016). Crime in Illinois: Annual Uniform Crime Report 2016. Illinois State Police. (2015). Crime in Illinois: Annual Uniform Crime Report 2015. Illinois State Police. (2014). Crime in Illinois: Annual Uniform Crime Report 2014.; Illinois State Police. (2012). Crime in Illinois: Annual Uniform Crime Report 2012.; Illinois State Police. (2011). Crime in Illinois: Annual Uniform Crime Report 2010-2011.; Illinois State Police. (2009). Crime in Illinois: Annual Uniform Crime Report 2009.; Illinois State Police. (2007). Crime in Illinois: Annual Uniform Crime Report 2007.; Illinois State Police. (2005). Crime in Illinois: Annual Uniform Crime Report 2005.; Illinois State Police. (2003). Crime in Illinois: Annual Uniform Crime Report 2003.; Illinois State Police. (2001). Crime in Illinois: Annual Uniform Crime Report 2001.; Illinois State Police. (1999). Crime in Illinois: Annual Uniform Crime Report 1999.; Illinois State Police. (1997). Crime in Illinois: Annual Uniform Crime Report 1997.

Offenses in Colorado for 2016 through 2022 by Agency from the FBI's Crime Data Explorer.

Version 9 release notes:Adds 2022 dataVersion 8 release notes:Fixes issue where 2021 Property Segment data was excluded. Thank you to Uriel Lomeli for telling me about this issue.Version 7 release notes:Adds 2021 data.Version 6 release notes:Adds batch header segments for all years. Version 5 release notes:Adds 2020 dataVersion 4 release notes:Fix bug where most years had arrestee and property were incorrectly window arrestee and window property segments.Changes R files from .rda to .rds.Version 3 release notes:Adds 2019 dataVersion 2 release notes:Changes release notes description, does not change data.These data are the FBI's National Incident-Based Reporting System (NIBRS) data for years 1991-2018. NIBRS data are incident-level data that have highly detailed information for each crime that is reported to the police agency. This data has 10 segments. Each segment has different data about the crime. AdministrativeBasic information about the crime incident - this is basically metadata about the other segments for this crime. This includes the date of the crime, the number of offense segments, the number of victim segments, the number of offender segments, the number of arrestee segments, if the crime was cleared exceptionally and (if it was) what date it was cleared. ArresteeArrestee-level information for those who are arrested. This includes demographics (age, sex, race, ethnicity), the date of the arrest (can be different than the date of the crime), what weapon (if any) was used, and the outcome of the case if the arrestee was a juvenile. Group B Arrest ReportsArrestee-level information for those who are arrested for Group B crimes. This includes the same variables as the arrestee segment. OffenderOffender-level information for each offender. Includes offender demographics (age, sex, race, ethnicity).OffenseDetailed information about each crime. Includes the weapon used (if any), the location of the crime, if the offender was intoxicated (including drugs and alcohol), and what their bias motivation (if any) was (if there is one, this would be considered a hate crime). PropertyInformation about property involved in the crime (i.e. drugs or stolen property). This includes the value of the property, what type of the property it was, when it was recovered. For drugs, this includes the drug and its quantity. VictimVictim-level information for each victim of a crime. Includes victim demographics (age, sex, race, ethnicity), injury, and relationship to the offender(s).Window ArresteeWindows segments have the same columns as their non-window counterparts and are incidents that occurred prior to the year of data or prior to when the agency started reporting to NIBRS.Window Exceptional ClearanceWindows segments have the same columns as their non-window counterparts and are incidents that occurred prior to the year of data or prior to when the agency started reporting to NIBRS.Window PropertyWindows segments have the same columns as their non-window counterparts and are incidents that occurred prior to the year of data or prior to when the agency started reporting to NIBRS.Due to the large file size, each year is its own file. All segment headers are available except for the batch headers. What I did here was read the data into R and save it as R and Stata files. No other changes to the data were made. The data was downloaded as NIBRS Master Files for each year from the FBI's Crime Data Explorer website - https://crime-data-explorer.fr.cloud.gov/downloads-and-docs.

Version 11 release notes:Adds 2023-2024 dataMakes some changes to offense description (e.g. change description of "fondling") and victim-offender relationship values to be consistent with FBI changes. This affects all years, not just 2023-2024.Adds .parquet file formats. Version 10 release notes:Updates 2021 Property Segment and Window Recovered Property Segment to fix issue in older version of FBI data where the drug type column incorrectly had the values of the quantity unit column, which then made every subsequent column incorrect. This led to strange behavior such as zero marijuana values and an incredibly high number of opium values because opium has the value of "G" and "GM" for gram is extremely common as a quantity unit. This was an error in the FBI Master File I downloaded shortly after the 2021 data was released and was fixed when I downloaded the current version of the file which has a date of 8/17/2023 in the zip file. Both files were downloaded from the FBI's Crime Data Explorer website. Thank you to Roland Neil for informing me about this issue. Version 9 release notes:Adds 2022 dataVersion 8 release notes:Fixes issue where 2021 Property Segment data was excluded. Thank you to Uriel Lomeli for telling me about this issue.Version 7 release notes:Adds 2021 data.Version 6 release notes:Adds batch header segments for all years. Version 5 release notes:Adds 2020 dataVersion 4 release notes:Fix bug where most years had arrestee and property were incorrectly window arrestee and window property segments.Changes R files from .rda to .rds.Version 3 release notes:Adds 2019 dataVersion 2 release notes:Changes release notes description, does not change data.These data are the FBI's National Incident-Based Reporting System (NIBRS) data for years 1991-2018. NIBRS data are incident-level data that have highly detailed information for each crime that is reported to the police agency. This data has 10 segments. Each segment has different data about the crime. AdministrativeBasic information about the crime incident - this is basically metadata about the other segments for this crime. This includes the date of the crime, the number of offense segments, the number of victim segments, the number of offender segments, the number of arrestee segments, if the crime was cleared exceptionally and (if it was) what date it was cleared. ArresteeArrestee-level information for those who are arrested. This includes demographics (age, sex, race, ethnicity), the date of the arrest (can be different than the date of the crime), what weapon (if any) was used, and the outcome of the case if the arrestee was a juvenile. Group B Arrest ReportsArrestee-level information for those who are arrested for Group B crimes. This includes the same variables as the arrestee segment. OffenderOffender-level information for each offender. Includes offender demographics (age, sex, race, ethnicity).OffenseDetailed information about each crime. Includes the weapon used (if any), the location of the crime, if the offender was intoxicated (including drugs and alcohol), and what their bias motivation (if any) was (if there is one, this would be considered a hate crime). PropertyInformation about property involved in the crime (i.e. drugs or stolen property). This includes the value of the property, what type of the property it was, when it was recovered. For drugs, this includes the drug and its quantity. VictimVictim-level information for each victim of a crime. Includes victim demographics (age, sex, race, ethnicity), injury, and relationship to the offender(s).Window ArresteeWindows segments have the same columns as their non-window counterparts and are incidents that occurred prior to the year of data or prior to when the agency started reporting to NIBRS.Window Exceptional ClearanceWindows segments have the same columns as their non-window counterparts and are incidents that occurred prior to the year of data or prior to when the agency started reporting to NIBRS.Window PropertyWindows segments have the same columns as their non-window counterparts and are incidents that occurred prior to the year of data or prior to when the agency started reporting to NIBRS.Due to the large file size, each year is its own file. All segment headers are available except for the batch headers. What I did here was read the data into R and save it as R and

The EU Lesbian, Gay, Bisexual and Transgender Survey (EU LGBT) was conducted by the European Union Agency for Fundamental Rights (FRA). It is the first ever EU-wide online survey to establish an overview concerning the lives of lesbian, gay, bisexual and trans people (18 years or older) and their experiences with regard to fundamental rights in the 28 EU Member States. Up until now, there has been very little comparable data collected across the EU about the everyday experiences of LGBT people with respect to discrimination, and lot of the available information is limited to occasional news reports and court judgements. As the first EU-wide survey of its kind, the results support the development of equal treatment policies for LGBT people in the European Union and set the agenda for years to come. Based on the survey results, national and European policy makers, as well as non-governmental organisations, are able to better target their advocacy strategies and activities to support LGBT communities to live and express themselves freely in a non-discriminatory environment. The survey was completely anonymous (no additional data on the participants and their sessions were logged in any way). The survey data collection operated by Gallup Europe, a professional survey and consultancy firm. In order to ensure that the survey delivers evidence needed for policy making, the EU LGBT Survey counted on the participation of a large and diverse group of lesbian, gay, bisexual and trans people from each country. Hence, it was vitally important for the success of the survey that FRA and Gallup worked together with civil society organisations to reach a wide audience and raise awareness concerning the survey, including participants emailing the survey, sharing it through social media or simply inviting LGBT friends to take part. More information (including, downloading the data and documentation) can be found on the FRA website. The survey data can also be explored online using the FRA's Data Explorer.

In 2023, online users in Finland displayed the highest tendency to change their internet browser settings to limit cookie functionalities. Approximately 66 percent of respondents in Finland reported having done so, while in the Netherlands, the share of respondents displaying the same online behavior was of approximately 55.6 percent. By comparison, users in Serbia, Bulgaria, and Romania were the least likely to change their browser settings to limit the cookies tracking functionalities.