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Valuating Law Enforcement Data in the 21st Century: An Adaptive Mixed Methods Approach, 10 U.S. states, 2017-2019 (ICPSR 37469)

Released/updated on: 2026-07-16
Geographic coverage: North Carolina, Indiana, United States, Massachusetts, Colorado, Louisiana, Minnesota, Kansas, New York (state), Washington, South Carolina
Time period: 2017-01-01--2019-12-31

The Valuating Law Enforcement Data in the 21st Century study was conducted in four phases. Phase I included a literature scan and expert interviews. Phase II was an exploratory effort at understanding the dimensions and characteristics of valuation efforts focused on policing data. Phase III focused on developing a cost-benefit analysis (CBA) framework for body-worn cameras (BWCs). Finally, Phase IV turned the BWC CBA tool into a web-based calculator for law enforcement agencies to assess the likely impact of BWCs on their agency.

This collection includes qualitative notes from focus group discussions at site visits conducted in Phase II and Phase III of the study. Personnel from 13 law enforcement agencies across 10 U.S. states participated in the focus groups. Efforts were made to diversify among municipal police and sheriffs, the variety of agency sizes and populations served, and geography. In general, site visits were designed to include a variety of personnel, including from executive staff, information technology, patrol, investigations, and crime analysis.

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Applying Data Science to Justice Systems: The North Carolina Statewide Warrant Repository (NCAWARE), 2014-2019 (ICPSR 37462)

Released/updated on: 2022-12-13
Geographic coverage: North Carolina, Greensboro, United States
Time period: 2014-01-01--2019-12-31
This study uses the data from the unified, statewide warrant repository NCAWARE (NC Arrest Warrant Repository) to evaluate a proposed system for processing and serving arrest warrants. The NCAWARE system is maintained by the North Carolina Administrative Office of the Courts (NCAOC). The study takes place within the Greensboro, NC police department where two of the four police districts utilized the system. This study is the result of the unorganized system for processing and serving warrants and the significant backlog of cases with outstanding warrants that exists across the country. One of the purposes of this study was to create a systematic approach for law enforcement agencies to prioritize the execution of warrants.
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'Near Repeat' Theory into a Geospatial Policing Strategy: A Randomized Experiment Testing a Theoretically-Informed Strategy for Preventing Residential Burglary, Baltimore County, Maryland and Redlands, California, 2014-2015 (ICPSR 37108)

Released/updated on: 2019-05-30
Geographic coverage: Baltimore County, United States, California, Maryland, Redlands
Time period: 2014-01-01--2015-12-31

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 except 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) if further information is needed.

This data collection represents an experimental micro-level geospatial crime prevention strategy that attempted to interrupt the near repeat (NR) pattern in residential burglary by creating a NR space-time high risk zone around residential burglaries as they occurred and then using uniformed volunteers to notify residents of their increased risk and provide burglary prevention tips. The research used a randomized controlled trial to test whether high risk zones that received the notification had fewer subsequent burglaries than those that did not. In addition, two surveys were administered to gauge the impact of the program, one of residents of the treatment areas and one of treatment providers.

The collection contains 6 Stata datasets:

  1. BCo_FinalData_20180118_Archiving.dta(n = 484, 8 variables)
  2. Red_FinalData_20180117_Archiving.dta (n = 268, 8 variables)
  3. BCo_FinalDatasetOtherCrime_ForArchiving_v2.dta(n = 484, 8 variables)
  4. Redlands_FinalDataSecondary_ForArchiving_v2.dta (n = 266, 8 variables)
  5. ResidentSurvey_AllResponses_V1.4_ArchiveCleaned.dta (n = 457, 42 variables)
  6. VolunteerSurvey_V1.2_ArchiveCleaned.dta (n = 38, 16 variables)
The collection also includes 5 sets of geographic information system (GIS) data:
  1. BaltimoreCounty_Bnd.zip
  2. BC_NR_HRZs.zip
  3. BurglaryAreaMinus800_NoApts.zip
  4. Redlands_CityBnd.zip
  5. RedlandsNR_HRZs.shp.zip
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