A newer version of this project is available. See below for other available versions.
Jacob Kaplan's Concatenated Files: Uniform Crime Reporting Program Data: Law Enforcement Officers Killed and Assaulted (LEOKA) 1960-2018
Principal Investigator(s): View help for Principal Investigator(s) Jacob Kaplan, University of Pennsylvania
Version: View help for Version V7
| Name | File Type | Size | Last Modified |
|---|---|---|---|
|
|
application/zip | 170.5 MB | 02/18/2020 08:49:PM |
|
|
application/zip | 267.7 MB | 02/18/2020 08:37:PM |
|
|
application/zip | 100.2 MB | 02/18/2020 08:32:PM |
|
|
application/zip | 266 MB | 02/19/2020 03:55:AM |
|
|
application/zip | 25.3 MB | 02/18/2020 08:53:PM |
|
|
application/zip | 36.6 MB | 02/18/2020 08:50:PM |
|
|
application/zip | 22.4 MB | 02/18/2020 08:50:PM |
|
|
application/zip | 36.8 MB | 02/18/2020 08:21:PM |
Project Citation:
Kaplan, Jacob. Jacob Kaplan’s Concatenated Files: Uniform Crime Reporting Program Data: Law Enforcement Officers Killed and Assaulted (LEOKA) 1960-2018. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2020-02-19. https://doi.org/10.3886/E102180V7
Project Description
Summary:
View help for Summary
Version 7 release notes:
All the data was acquired from the FBI as text/DAT files and read into R using the package asciiSetupReader. The FBI also provided a PDF file explaining how to create the setup file to read the data. Both the FBI's PDF and the setup file I made are included in the zip files.
About 7% of all agencies in the data report more officers or civilians than population. As such, I removed the officers/civilians per 1,000 population variables. You should exercise caution if deciding to generate and use these variables yourself.
Several agency had impossible large (>15) officer deaths in a single month. For those months I changed the value to NA. See the R code for a complete list.
For the R code used to clean this data, see here. https://github.com/jacobkap/crime_data.
The UCR Handbook (https://ucr.fbi.gov/additional-ucr-publications/ucr_handbook.pdf/view) describes the LEOKA data as follows:
"The UCR Program collects data from all contributing agencies ... on officer line-of-duty deaths and assaults. Reporting agencies must submit data on ... their own duly sworn officers feloniously or accidentally killed or assaulted in the line of duty. The purpose of this data collection is to identify situations in which officers are killed or assaulted, describe the incidents statistically, and publish the data to aid agencies in developing policies to improve officer safety.
"... agencies must record assaults on sworn officers. Reporting agencies must count all assaults that resulted in serious injury or assaults in which a weapon was used that could have caused serious injury or death. They must include other assaults not causing injury if the assault involved more than mere verbal abuse or minor resistance to an arrest. In other words, agencies must include in this section all assaults on officers, whether or not the officers sustained injuries."
For any questions about this data please email me at jacob@crimedatatool.com. If you use this data, please cite it.
Version 7 release notes:
- Add data from 2018
Version 6 release notes:
- Adds data in the following formats: SPSS and Excel.
- Changes project name to avoid confusing this data for the ones done by NACJD.
Version 5 release notes:
- Adds data for 1960-1974 and 2017. Note: many columns (including number of female officers) will always have a value of 0 for years prior to 1971.
- Removes support for .csv and .sav files.
- Adds a number_of_months_reported variable for each agency-year. A month is considered reported if the month_indicator column for that month has a value of "normal update" or "reported, not data."
- The formatting of the monthly data has changed from wide to long.
This means that each agency-month has a single row. The old data had
each agency being a single row with each month-category (e.g.
jan_officers_killed_by_felony) being a column. Now there will just be a single column
for each category (e.g. officers_killed_by_felony) and the month can be identified in the
month column. This also results in most column names changing.
- As such, be careful when aggregating the monthly data since some variables are the same every month (e.g. number of officers employed is measured annually) so aggregating will be 12 times as high as the real value for those variables.
- Adds a date column. This date column is always set to the first of the month. It is NOT the date that a crime occurred or was reported. It is only there to make it easier to create time-series graphs that require a date input.
- All the data in this version was acquired from the FBI as text/DAT files and read into R using the package asciiSetupReader.
The FBI also provided a PDF file explaining how to create the setup
file to read the data. Both the FBI's PDF and the setup file I made are
included in the zip files. Data is the same as from NACJD but using all FBI files makes cleaning easier as all column names are already identical.
Version 4 release notes:
- Add data for 2016.
- Order rows by year (descending) and ORI.
Version 3 release notes:
- Fix bug where Philadelphia Police Department had incorrect FIPS county code.
The LEOKA data sets contain highly detailed data about the number of officers/civilians employed by an agency and how many officers were killed or assaulted.
All the data was acquired from the FBI as text/DAT files and read into R using the package asciiSetupReader. The FBI also provided a PDF file explaining how to create the setup file to read the data. Both the FBI's PDF and the setup file I made are included in the zip files.
About 7% of all agencies in the data report more officers or civilians than population. As such, I removed the officers/civilians per 1,000 population variables. You should exercise caution if deciding to generate and use these variables yourself.
Several agency had impossible large (>15) officer deaths in a single month. For those months I changed the value to NA. See the R code for a complete list.
For the R code used to clean this data, see here. https://github.com/jacobkap/crime_data.
The UCR Handbook (https://ucr.fbi.gov/additional-ucr-publications/ucr_handbook.pdf/view) describes the LEOKA data as follows:
"The UCR Program collects data from all contributing agencies ... on officer line-of-duty deaths and assaults. Reporting agencies must submit data on ... their own duly sworn officers feloniously or accidentally killed or assaulted in the line of duty. The purpose of this data collection is to identify situations in which officers are killed or assaulted, describe the incidents statistically, and publish the data to aid agencies in developing policies to improve officer safety.
"... agencies must record assaults on sworn officers. Reporting agencies must count all assaults that resulted in serious injury or assaults in which a weapon was used that could have caused serious injury or death. They must include other assaults not causing injury if the assault involved more than mere verbal abuse or minor resistance to an arrest. In other words, agencies must include in this section all assaults on officers, whether or not the officers sustained injuries."
Scope of Project
Subject Terms:
View help for Subject Terms
leoka;
police safety;
police;
ucr;
Uniform Crime Reports;
officers killed;
assault on police;
law enforcement officers killed and assaulted
Geographic Coverage:
View help for Geographic Coverage
United States
Time Period(s):
View help for Time Period(s)
1960 – 2018
Universe:
View help for Universe
Law enforcement agencies in the United States.
Data Type(s):
View help for Data Type(s)
administrative records data
Methodology
Data Source:
View help for Data Source
United States Department of Justice. Federal Bureau of Investigation
Unit(s) of Observation:
View help for Unit(s) of Observation
Police agency
Geographic Unit:
View help for Geographic Unit
Police agency jurisdiction
Related Publications
Published Versions
Report a Problem
Found a serious problem with the data, such as disclosure risk or copyrighted content? Let us know.
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.