Uniform Crime Reporting Program Data: Offenses Known and Clearances by Arrest, 1960-2016
Principal Investigator(s): View help for Principal Investigator(s) Jacob Kaplan, University of Pennsylvania. Department of Criminology
Version: View help for Version V3
Name | File Type | Size | Last Modified |
---|---|---|---|
UCR_offenses_known_monthly_1960_2016_csv.zip | application/zip | 224.1 MB | 03/02/2018 10:39:AM |
UCR_offenses_known_monthly_1960_2016_dta.zip | application/zip | 327.8 MB | 03/02/2018 11:17:AM |
UCR_offenses_known_monthly_1960_2016_rda.zip | application/zip | 301.1 MB | 03/02/2018 10:28:AM |
UCR_offenses_known_monthly_1960_2016_sav.zip | application/zip | 333.8 MB | 03/02/2018 10:21:AM |
UCR_offenses_known_yearly_1960_2016_csv.zip | application/zip | 53.1 MB | 03/02/2018 11:09:AM |
UCR_offenses_known_yearly_1960_2016_dta.zip | application/zip | 72.6 MB | 03/02/2018 11:04:AM |
UCR_offenses_known_yearly_1960_2016_rda.zip | application/zip | 61.6 MB | 03/02/2018 11:04:AM |
UCR_offenses_known_yearly_1960_2016_sas.zip | application/zip | 74.3 MB | 03/02/2018 11:02:AM |
UCR_offenses_known_yearly_1960_2016_sav.zip | application/zip | 72.6 MB | 03/02/2018 11:07:AM |
Project Citation:
Kaplan, Jacob. Uniform Crime Reporting Program Data: Offenses Known and Clearances by Arrest, 1960-2016. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2018-03-02. https://doi.org/10.3886/E100707V3
Project Description
Summary:
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This version (V3) fixes a bug in Version 2 where 1993 data did not properly deal with missing values, leading to enormous counts of crime being reported.
This is a collection of Offenses Known and Clearances By Arrest data from 1960 to 2016. The monthly zip files contain one data file per year(57 total, 1960-2016) as well as a codebook for each year. These files have been read into R using the ASCII and setup files from ICPSR (or from the FBI for 2016 data) using the package asciiSetupReader. The end of the zip folder's name says what data type (R, SPSS, SAS, Microsoft Excel CSV, feather, Stata) the data is in. Due to file size limits on open ICPSR, not all file types were included for all the data.
The files are lightly cleaned. What this means specifically is that column names and value labels are standardized. In the original data column names were different between years (e.g. the December burglaries cleared column is "DEC_TOT_CLR_BRGLRY_TOT" in 1975 and "DEC_TOT_CLR_BURG_TOTAL" in 1977). The data here have standardized columns so you can compare between years and combine years together. The same thing is done for values inside of columns. For example, the state column gave state names in some years, abbreviations in others. For the code uses to clean and read the data, please see my GitHub file here. https://github.com/jacobkap/crime_data/blob/master/R_code/offenses_known.R
The zip files labeled "yearly" contain yearly data rather than monthly. These also contain far fewer descriptive columns about the agencies in an attempt to decrease file size. Each zip folder contains two files: a data file in whatever format you choose and a codebook. The data file is aggregated yearly and has already combined every year 1960-2016. For the code I used to do this, see here https://github.com/jacobkap/crime_data/blob/master/R_code/yearly_offenses_known.R.
If you find any mistakes in the data or have any suggestions, please email me at jkkaplan6@gmail.com
As a description of what UCR Offenses Known and Clearances By Arrest data contains, the following is copied from ICPSR's 2015 page for the data.
The Uniform Crime Reporting Program Data: Offenses Known and Clearances By Arrest dataset is a compilation of offenses reported to law enforcement agencies in the United States. Due to the vast number of categories of crime committed in the United States, the FBI has limited the type of crimes included in this compilation to those crimes which people are most likely to report to police and those crimes which occur frequently enough to be analyzed across time. Crimes included are criminal homicide, forcible rape, robbery, aggravated assault, burglary, larceny-theft, and motor vehicle theft. Much information about these crimes is provided in this dataset. The number of times an offense has been reported, the number of reported offenses that have been cleared by arrests, and the number of cleared offenses which involved offenders under the age of 18 are the major items of information collected.
This is a collection of Offenses Known and Clearances By Arrest data from 1960 to 2016. The monthly zip files contain one data file per year(57 total, 1960-2016) as well as a codebook for each year. These files have been read into R using the ASCII and setup files from ICPSR (or from the FBI for 2016 data) using the package asciiSetupReader. The end of the zip folder's name says what data type (R, SPSS, SAS, Microsoft Excel CSV, feather, Stata) the data is in. Due to file size limits on open ICPSR, not all file types were included for all the data.
The files are lightly cleaned. What this means specifically is that column names and value labels are standardized. In the original data column names were different between years (e.g. the December burglaries cleared column is "DEC_TOT_CLR_BRGLRY_TOT" in 1975 and "DEC_TOT_CLR_BURG_TOTAL" in 1977). The data here have standardized columns so you can compare between years and combine years together. The same thing is done for values inside of columns. For example, the state column gave state names in some years, abbreviations in others. For the code uses to clean and read the data, please see my GitHub file here. https://github.com/jacobkap/crime_data/blob/master/R_code/offenses_known.R
The zip files labeled "yearly" contain yearly data rather than monthly. These also contain far fewer descriptive columns about the agencies in an attempt to decrease file size. Each zip folder contains two files: a data file in whatever format you choose and a codebook. The data file is aggregated yearly and has already combined every year 1960-2016. For the code I used to do this, see here https://github.com/jacobkap/crime_data/blob/master/R_code/yearly_offenses_known.R.
If you find any mistakes in the data or have any suggestions, please email me at jkkaplan6@gmail.com
As a description of what UCR Offenses Known and Clearances By Arrest data contains, the following is copied from ICPSR's 2015 page for the data.
The Uniform Crime Reporting Program Data: Offenses Known and Clearances By Arrest dataset is a compilation of offenses reported to law enforcement agencies in the United States. Due to the vast number of categories of crime committed in the United States, the FBI has limited the type of crimes included in this compilation to those crimes which people are most likely to report to police and those crimes which occur frequently enough to be analyzed across time. Crimes included are criminal homicide, forcible rape, robbery, aggravated assault, burglary, larceny-theft, and motor vehicle theft. Much information about these crimes is provided in this dataset. The number of times an offense has been reported, the number of reported offenses that have been cleared by arrests, and the number of cleared offenses which involved offenders under the age of 18 are the major items of information collected.
Scope of Project
Subject Terms:
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crime;
UCR;
murder;
police;
Uniform Crime Reports;
FBI
Geographic Coverage:
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United States
Time Period(s):
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1960 – 2016
Universe:
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Crimes committed, declared unfounded, and cleared in police agencies in the United States during 1960-2016.
Data Type(s):
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administrative records data;
aggregate data
Methodology
Data Source:
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United States Department of Justice. Federal Bureau of Investigation
Unit(s) of Observation:
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Monthly or yearly crime in a police agency
Geographic Unit:
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Police agency
Related Publications
This study is un-published. See below for other available versions.
Published Versions
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This material is distributed exactly as it arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigator(s) if further information is desired.