Throughout its history, the conversion to NIBRS—as well as its ongoing maintenance—can incur considerable cost. See Table 1 for cost estimates from 2002 (FBI, 2002):

For many law enforcement agencies and their jurisdictions, it is becoming more common to develop an online data portal that contains crime data alongside other jurisdiction-related information. Often these crime datasets include NIBRS data but without all the rich data fields reported to the FBI. For example, Little Rock, Arkansas has been NIBRS-compliant and reporting for over a decade but provides only the traditional UCR Part I crime categories through their data portal. In contrast, Dallas, Texas has a data portal containing their “police incidents” data that include the general crime characteristics with NIBRS crime category codes alongside specific fields indicating whether the crime was a hate incident, the type of weapon used, and whether it was gang- or drug-related. Although this is clearly not all the fields within NIBRS, many cities include NIBRS data online that include the more easily accessible fields.

The Federal Bureau of Investigation (FBI) developed a Crime Data Explorer (CDE) data portal to create easy access and transparency in law enforcement data. The CDE has crime data back to 1985 with a combination of Summary Reporting System and NIBRS in more recent years. The benefit of using the CDE consists of the built-in data visualization tools. The CDE provides yearly crime trends at the national, state, or law enforcement agency level. The user can select out crime types (e.g., violent, property, or specific offenses), and the CDE has integrated many of the detailed variables that NIBRS provides above and beyond other data collections. For example, age, sex, race, ethnicity, location, victim–offender relationship, weapon involvement, and if the offense is linked to another offense are each an option for data visualization. Within each visualization, the user can download specific summary data to use offline. Lastly, through the Documents & Downloads menu, the CDE allows users to download larger datasets and reports.

Window: Recovered Property: This segment expands on the Property Segment by focusing on the recovery of property connected to up to 10 Group A offenses.

Administrative: These variables provide a summary of the data, including total offenses, victims, offenders, and arrestees (found in their respective segments). Important to this segment are the reported incident date and hour of occurrence.

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NIBRSparticipation by State

As a data reporting system, NIBRS had garnered considerable attention concerning its creation, adoption, and future. Over the years, publications concerning NIBRS as a data collection effort have resulted in the publication of overviews and cautionary statements (Addington, 2008, 2019; Akiyama & Nolan, 1999; Bibel, 2015; Jarvis, 2015; Roberts, 2009) as well as critiques of its data accuracy and reliability (Chilton & Jarvis, 1999; Cross et al., 2022; Pattavina et al., 2017). More recent articles and studies focus on the transition away from the older UCR data collection to NIBRS and what this means for law enforcement agencies and research communities (Drawve et al., 2021; Lantz, 2022; Parker, 2022; Strom & Smith, 2017). The use of NIBRS data in both policy decision-making and research will continue to grow as adoption accelerates and accessibility increases.

NIBRScrime types

Filters: Enables users to filter by a variety of data elements, including year, geography, crime, victim, and relationship. Multiple filters can be selected and will affect all visualizations within the topic page. As filters are selected or removed, a filtered summary will be displayed below each chart, identifying which filters are currently being applied to the chart.

Offender: Offender data are reported when information is provided to the law enforcement agency, which can be more limited as compared with the victim segment described above. This segment includes variables focused on the demographics of the offender (e.g., age, sex, and race). For the Offender Segment, the maximum number of offenders is set to 99.

Arrestee: When an arrest is made for a crime incident, the arrest date is reported. In addition, variables include the type of arrest, the presence of weapons, arrestee demographics, and the resident status.

Analytics on Demand: Provides users with the ability to create a customizable dataset that can be exported. Users can define the unit of analysis as incidents or individual victims, filter elements they wish to include or exclude, and further define up to two columns and two rows of data.

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NIBRSvs UCR

Like other nationwide crime data collection efforts from official justice agencies, reporting of NIBRS data is voluntary. Although all 50 state administering agencies are certified to collect and report NIBRS data to the FBI, not all law enforcement agencies within each state participate in this collection and reporting. While many states have complete (or near-complete) participation from their law enforcement agencies, some states do not currently participate at all or have only a few agencies reporting (e.g., Florida, California, Pennsylvania, and New York). As of June 2022, NIBRS reporting law enforcement agencies covered about 66% of the population of the United States and represented 61% of law enforcement agencies.

The Law Enforcement Agency Reported Crime Analysis Tool (LEARCAT) dashboard, developed by the BJS, provides access to NIBRS data on crimes reported by participating law enforcement agencies. LEARCAT contains NIBRS data from 2016 to 2021 at both the incident and victimization levels, and contextual information from other federal data sources (e.g., Census Bureau) is also accessible. Using LEARCAT, users can examine data at multiple levels of geography, including the state, country, and agency levels. Moreover, LEARCAT enables users to produce customized datasets for analysis and to access various statistical analyses for crime analysis.

NIBRSdata

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Inter-University Consortium for Political and Social Research (ICPSR) continues to grow in its ever-expanding data archives, and criminal justice–related datasets are a mainstay of their efforts. Since NIBRS is open access, users do not need to be affiliated with a partner institution. ICPSR houses the NIBRS data as provided by the National Archives of Criminal Justice Data (NACJD) (see next section). Uniquely available through open ICPSR is a concatenated NIBRS dataset from 1991 to 2021 constructed by Dr. Jacob Kaplan. The concatenated longitudinal dataset provides ease of access to many users.

Rates on Demand: Enables users to customize data exports and examine crime and victimization rates. However, only states that are considered “full reporter states” are included. To be considered a full reporter state, a state must have at least 90% of the state population covered by NIBRS participating law enforcement agencies.

By 2015, a letter of support from the International Association of Chiefs of Police, Major Cities Chiefs Association, National Sheriffs’ Association, and the Major County Sheriffs’ Association supported the move toward NIBRS across the nation. This support was largely articulated as a move toward modernizing crime reporting (FBI, 2015). Additionally, as quoted in the FBI’s letter to State UCR Program Managers from the Criminal Justice Information Services (CJIS) recommendation (in 2015),

Victim: Victim data are collected on those involved in the incidents with a maximum number of 999 victims in any one incident. Variables within this segment focus on, for example, the type of victim, their demographics (i.e., age, sex, race, and ethnicity), resident status, level of injury, circumstances related to an aggravated assault/homicide, and victim–offender relationship.

Topic: At the incident level, LEARCAT allows users to visualize data according to the offense(s) in the incident as well as information on the type(s) of victims in the incident. For each incident, NIBRS collects information, such as whether the incident was cleared and (if so) whether it was cleared by arrest, on up to 10 offenses. At the victimization level, users can create a custom view representing the total number of times that a person or organization was the victim of a crime. For crimes against persons, each victim in the incident generates a separate victim segment, which contains specific information regarding the offense(s) committed against the victim, victim demographic characteristics, and the relationship of the victim to the offender(s).

Interactive Map: A map of the United States is displayed in the topic view, which provides an overview of the NIBRS reporting status of each state for the selected year.

NIBRStraining

Property: Variables within this segment relate to, for example, the type of property, its value, the date it was recovered (if applicable), and the number of stolen motor vehicles. The property segment also includes the types of drug and narcotics involved in the crime as well as its estimated quantity.

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Additionally, in more recent years, the FBI has produced a series of yearly NIBRS web pages. Within each year of NIBRS, users can interact with a map of participating agencies across the United States. The user can zoom in, click on an agency, and see the general offense data for that year for any specific participating agency. See Figure 2 below as an example of the 2021 NIBRS data submitted by Fayetteville, Arkansas. These web pages function as quick access points to identify participating agencies in addition to summaries of crime.

When the UCR SRS was retired, 16,543 out of 18,630 law enforcement agencies reported either NIBRS or the older record management data. As seen in Figure 1, when NIBRS became the primary crime data reporting system in 2021, the number of agencies reporting data was only 11,794, or just less than double the number of agencies reporting a decade ago but still far short of the number involved in the prior UCR SRS. To overcome the limitation of still missing agencies, crime estimates are generated upon completion of data collection (see Berzofsky et al., 2022). The process for generating crime estimates from NIBRS data was jointly developed by the BJS and the FBI and involves statistical methods designed to account for missing data by estimating the population value for all potential contributors. This means that if an agency does not submit data (e.g., missing data element[s], missing months of reporting, or does not participate at all), the NIBRS estimation procedures approximate what the expected value would be for that missing data.

Rash et al. (2022) provide, as an example of the value of NIBRS for agencies, a case study in Arlington, Texas, where the police department changed how they addressed larceny-thefts. Arlington transitioned to NIBRS in 2017, at the same time the agency was changing their broader records management system. Because of issues associated with the older system’s aggregation and hierarchy limitations, the Arlington Police Department had limited options for implementing crime prevention efforts. With the new NIBRS data, different types of larceny-thefts were separated out for specific times of day to identify “hot” time points for the forms of larceny-theft. Because of the new data provided by NIBRS, police resources could be more efficiently allocated to best reduce crime. Similarly, Scott et al. (2022) demonstrate the benefits of NIBRS arrest and exceptional clearance fields compared with the older data system by using a cross-jurisdiction comparison. The authors compare exceptional clearance and arrest clearance rates for sexual assault incidents, highlighting the separation of fields that can provide a clearance benchmark to establish progress over time.

Given that small- to medium-sized agencies constitute the bulk of law enforcement organizations throughout the United States, the cost associated with NIBRS adds up quickly. As Strom and Smith (2017) described, participation in the early years of NIBRS came largely from small- to medium-sized agencies, creating a bias in the population covered given that such agencies represent only about 29% of the population. Thus, without assistance from the FBI and the BJS, many agencies would not be able to transition to NIBRS.

Window: Arrestee: This segment expands the Arrestee Segment with a clearance flag and up to 10 Group A offenses tied to the incident.

The main source of crime data in the United States is the National Incident-Based Reporting System, frequently referred to as NIBRS. NIBRS records crime incidents and is collected by each specific NIBRS-certified law enforcement agency, which then reports those incidents to their corresponding state agency. State agencies then send data on crime incidents to the Federal Bureau of Investigation (FBI). NIBRS became the primary source of crime data collection and reporting in 2021 as a replacement for the Uniform Crime Reporting program Summary Reporting System, which was retired.

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LEARCAT has many features to navigate these sections, such as a dynamic incident and victimization counts, a menu of filters, a toggle to view results as counts, percentages, rates, or as an interactive map of the United States to select specific geographic areas. A brief discussion of these components appears below.

Recent years have seen a push across the United States to better capture hate crime occurrence. NIBRS contains a bias motivation variable that allows users to examine crime motivated by different types of bias. The UCR Program defines a bias crime as a committed criminal offense that is motivated in whole or in part by the offender’s bias(es) against a race, religion, disability, sexual orientation, ethnicity, gender, or gender identity. While the indication of bias is extremely rare within NIBRS (e.g., in the 2020 extract file, only about 0.1% had a known bias; see National Archives of Criminal Justice Data, 2020), researchers have used this part of NIBRS in broader exploration of hate crime occurrence (Haas et al., 2011; Lantz & Kim, 2019; Strom, 2001; Zhang et al., 2021). Among the incident reports that agencies submitted to NIBRS in 2021 were 7,262 bias crime incidents involving 8,673 offenses.

Dynamic Incident and Victimization Count: Provides a customized view that changes as the user selects or removes filters of specific geographic locations. For example, if a specific state is selected, the dynamic incident and victimization counts will update to show counters only for the selected geographic location.

In 2012, the BJS partnered with the FBI to implement the National Crime Statistics Exchange (NCS-X) with the purpose of expanding law enforcement agency participation in NIBRS reporting. When NCS-X was developed, only about 25% of the total nationwide law enforcement agencies were participating in NIBRS and reporting to the FBI. One goal of NCS-X was to assist and fund local law enforcement agencies to transition to NIBRS. For instance, a smaller and less-resourced law enforcement agency might not have the budget for a new records management system or the hardware necessary to collect and report NIBRS data.

Batch Header 3 of 3: The three Batch Header segments identify the law enforcement agency submitting NIBRS data, also known as the ORI. Variables within the Batch Header include incident number, city name, state abbreviation, and population covered.

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Group B Arrest Report: As the segment name implies, Group B NIBRS offenses are reported only when there is an arrest. Similar to the Arrestee Segment (9), similar field are collected in the Group B Arrest Report; the only difference is the type of offense for which there was an arrest.

As more law enforcement agencies transition to NIBRS and as the data become more representative of the United States, researchers will be able to significantly advance research on crime and criminal justice responses to it. To date, a single year of NIBRS data consists of millions of crime offenses that, when paired across years, can quickly include enough cases to explore even relatively rare types of crime. Several advances in crime research have benefited from the adoption and expansion of NIBRS data:

Gun violence remains a major concern among the public and policymakers. Given the level of detail provided by the different NIBRS segments, research on gun-related crimes in the United States has increasingly leveraged NIBRS data. For example, there are fields that capture multiple weapon types (including firearms) that can be used to describe the victims of gun violence, the location of gun-involved criminal events, and the circumstances that produce gun-related events (Burgason et al., 2014; Dierenfeldt et al., 2017; Haas et al., 2007; Parker, 2022).

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With additional value within NIBRS data, law enforcement agencies could collaborate with researchers, who are often trained in more complex statistical analyses, to better understand local crime occurrence. For example, agencies collect incident addresses and then standardize that location for NIBRS reporting (rather than include the original address). Some scholarship has shown that researchers can collaborate with law enforcement agencies to obtain NIBRS fields attached to a specific incident address. For example, Drawve et al. (2021) use data from the Arkansas Crime Information Center that, as part of a statewide NIBRS effort to include incident addresses, can geolocate offenses to increasingly smaller geographic units. As more law enforcement agencies transition to NIBRS, researcher–practitioner partnerships will provide increasingly rich analyses of crime in the same manner (see Bibel, 2015).

Although NIBRS is a more recent data collection effort, NIBRS began in 1989 with implementation in South Carolina (Federal Bureau of Investigation [FBI], 2018b). Much of this advancement in crime data reporting links back to the Blueprint for the Future of the Uniform Crime Reporting Program published in 1985 by the Uniform Crime Reports (UCR) Study Task Force composed of members from the Bureau of Justice Statistics (BJS) and the FBI (Poggio et al., 1985). Two main recommendations were advanced from this report, both of which are seen in current NIBRS data collections:

NIBRS data are available to analyze and download through several different portals. Outlined below are general repositories through which users examine and download NIBRS data.

The NIBRS reflects the culmination of decades of work to improve crime records management across the United States. Replacing the older UCR system, these data provide considerably greater detail about the type of crimes committed in our communities as well as the persons involved and the circumstances of the offenses for each incident. These data have grown increasingly more accessible, and portals and archives contain NIBRS data in a multitude of different formats and host different visualization and analysis features. Though the adoption of NIBRS has yet to reach every law enforcement agency—and continues to require considerable analytic skill to extract its full value—these data hold considerable potential for law enforcement agencies themselves as well as the academic research on crime and justice system processes that inform policy and practice.

In addition to the primary tools noted above, other databases have been digitized for accessibility as a means to supplement NIBRS. For example, the National Crime Victimization Survey (NCVS) is a separate data collection effort on crime victimization in the United States. The NCVS is worth noting here given that NIBRS consists only of crimes known to or move (i.e., reported or detected to after law enforcement agencies) law enforcement agencies, which can produce an undercount of crime. The data and results from the NCVS have been made available through National Crime Victimization Survey Data Dashboard (N-DASH), allowing users to employ tools and create quick or custom graphics. Data on personal and property victimization are available to select from within N-DASH. Like LEARCAT, N-DASH is part of the BJS and can provide users with a more complete picture of crime occurrence in the United States and can be used along with or in contrast to NIBRS to understand crime occurrence and victimization more deeply across the country.

The structure of the NIBRS data allows users to merge the data with other sources. For instance, the agency name, ORI, city, county, and state fields could all be used individually or in combination with one another to merge with a host of other data. These merged data are limited to agencies and/or locales that are present in both datasets; however, by merging additional data, the potential analysis provides greater depth and allows additional research questions to be answered. As just a few examples, research has merged NIBRS with (a) Law Enforcement Management and Administrative Statistics (Roberts & Roberts, 2016; Tillyer, 2018; Walefield, 2016), (b) Supplementary Homicide Reports (Addington, 2004; Fegadel & Heide, 2018), (c) the NCVS (Chilton & Jarvis, 1999; Ross et al., 2021), and (d) the American Community Survey (Claus et al., 2018; Drawve et al., 2021; Poole et al., 2018).

The nature of NIBRS data collections requires capturing a multitude of fields that law enforcement agencies can use to benefit their own organizations. However, the growing complexity of NIBRS data necessitates some analytical skills or a crime analysis unit to take on this endeavor. Unfortunately, such units or skilled positions are often limited to medium or large agencies. Others have highlighted the value of pracademics (Braga, 2016; Huey & Mitchell, 2016), who can connect research with practice to assist law enforcement agencies with their increasingly complex data needs. This could include both analysis and evaluation.

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The FBI letter was distributed in 2018 and further outlined the need to secure resources and to plan accordingly to assist with the transition from the soon-defunct UCR to NIBRS. The FBI provided an overview of the benefits of NIBRS participation (FBI, 2017), such as,

IsNIBRS reportingmandatory

Given the nature of the NIBRS data consisting of multiple segments, yearly extract files have been constructed to provide a more user-friendly version of these data. Extract files are limited to three offenses, victims, offenders, and arrestees. So the data are smaller in terms of file size but can still be merged into one file.

From 2015 through 2021, the FBI and the BJS invested more than $120 million to assist state and local law enforcement agencies in their data collection efforts as well as over $20 million to support training and technical assistance to law enforcement agencies. As noted above, NIBRS data reporting is voluntary for law enforcement agencies, so this type of assistance to agencies supports the adoption, transition, and reporting of NIBRS data to boost participation more broadly.

NIBRSManual

As another major advantage, NIBRS provides much greater detail about crimes that are committed, the characteristics of offenders and victims, and the general circumstances of the crime. This level of detail is accomplished in NIBRS by using 13 different segments that can be adjoined to each other using common incident identifiers. A brief overview of each segment is provided in the following section, along with a few example variables for each segment. While the 13 different segments in NIBRS can make it challenging to join the data into a single data file, unique linking variables are common throughout each segment to allow files to be merged (e.g., originating agency identifier [ORI] and incident number).

The FBI UCR Program will transition to a NIBRS-only data collection by January 1, 2021, and will evaluate the probability of achieving that goal on an annual basis. Federal, state, local, and tribal agencies unable to meet the five year transition and who have committed to transitioning to NIBRS will collaborate with the FBI CJIS to develop a transition plan and timeline for conversion.

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Other research has used the victim, offender, and arrestee segments of NIBRS to analyze racial disparities in victimization, arrest, and crime clearance. As one example, across the United States, some research has examined changes in marijuana enforcement amidst uneven legalization efforts that may produce racial disparities in law enforcement response (Doonan et al., 2020; Firth et al., 2019; Meize et al., 2022).

A major benefit of NIBRS over its predecessors is the expansion of offenses reported as compared with older reporting systems. Within NIBRS, offenses are divided into two categories: Group A and Group B offenses. There are 28 Group A offense categories, comprising a total of 71 Group A offenses. Additionally, there are 10 Group B offense categories. As with the older SRS, NIBRS Group B offenses are reported only for those incidents that involve an arrest. An overview of all offenses reported to NIBRS is provided in the “Group A Offenses” and “Group B Offenses” for more information. By including a wide variety of offense types, NIBRS encompasses a much broader inclusion of crime than older systems that either excluded or combined offenses.

NIBRSdata download

NIBRS data can be downloaded through the NACJD, which has created a resource page just for NIBRS and how to better understand the data. Within NACJD, there are yearly files containing full datasets and the reduced extract files (limited to three offenses). The benefit of going through NACJD is that when the NIBRS data are cited in publications, the publication is linked to the NIBRS data being used in the study. This allows practitioners and researchers to read about how the data are being used in research.

Law enforcement agencies participating in the NIBRS program position themselves to better track, analyze, and evaluate their own crime prevention and control efforts. Most of this value stems from linking offenses within any specific criminal incident as well as through the richness of the data generated across the NIBRS fields for location, time, and context of criminal offending and victimization. Additionally, transparency and data-driven approaches to crime control have grown early in the 21st century, and law enforcement agencies using NIBRS are better positioned to demonstrate where and when crime occurs, the different ways that offenses group together, and who is most impacted by crime. Therefore, the expectation is that NIBRS agencies will be better able to show progress in implementing and evaluating evidence-based crime control approaches.

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LEARCAT provides three primary areas to explore, visualize, and analyze NIBRS data: Topic, Analytics on Demand, and Rates on Demand. They are described briefly as follows:

Researchers have frequently used NIBRS incident data to examine issues associated with arrest and crime clearance, including how law enforcement agencies are resolving cases. With millions of incidents per year captured in NIBRS, using arrest or clearance or both has been a pillar of academic research with studies focusing on issues associated with clearance across crime type, demographic characteristics of victims/offenders, policies that impact arrest and clearance, and even theory testing the mechanisms that produce clearance disparities (e.g., Cross et al., 2022; D’Alessio & Stolzenberg, 2003; Drawve et al., 2014; Hirschel et al., 2007; Loeffler & Chalfin, 2017; Pattavina et al., 2007, 2017; Roberts & Roberts, 2016).

NIBRS data capture crime incidents known to law enforcement agencies. Within each crime incident, there is the possibility for multiple offenses to have been committed by the same person or group at the same time and place. This allows NIBRS data to link multiple offenses to one incident, overcoming the hierarchy issue found within the older Summary Reporting System (SRS). Like many other official crime data sources, NIBRS represents only crimes that are reported to or detected by law enforcement. This creates what is known as the dark figure of crime—or offenses that go unreported to law enforcement. While this is a limitation of NIBRS, the value of these data in linking multiple offenses and offenders is further complemented by at least two other advantages.

Window: Exceptionally Cleared: This segment includes the Administrative Segment fields along with the reporting of the type of exceptional clearance and date of clearance. There are five circumstances that could lead to an exceptional clearance:

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Offense: As implied by the name, the offense segment focuses on offense characteristics, including the offense attempted/completed, suspected drug or alcohol use, location type, bias motivation, and weapon use. Up to 10 offenses are listed as separate records in the offense segment.

Other research has leveraged the location type and value indicators within NIBRS to examine the severity of specific types of crime. For example, Steffensmeier et al. (2015) describe the prevalence of “white collar crime” by using both the NIBRS segments to identify the value stolen/embezzled as well as the type of location where the crime took place. In doing so, they move beyond what is possible with prior data that aggregate these kinds of offenses and miss the places where crime takes place.

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The United States relies on the National Incident-Based Reporting System (NIBRS) as the primary source of crime occurrence. In 2021, crime reporting in the United States transitioned from the Uniform Crime Reports (UCR) Program to NIBRS. In similar fashion, NIBRS data consist of crime known to law enforcement. Law enforcement agencies then report these data to the Federal Bureau of Investigation (FBI). Key to this reporting, and a relevant concern, is that, law enforcement agencies voluntarily report their crime data to the FBI. The transition from UCR to NIBRS data reporting has created monetary and technical hurdles for agencies to overcome to be certified in reporting their NIBRS data. NIBRS is a significant improvement from UCR reporting, benefiting not only law enforcement agencies but the public at large since these data are openly available. NIBRS provides much greater detail about crimes that are committed, the characteristics of offenders and victims, and the general circumstances of the crime. This level of detail is accomplished within NIBRS using 13 different segments that can be adjoined to each other using common incident identifiers. Given the rich data within NIBRS, practitioners and researchers have numerous opportunities to use these data to their advantage. Additionally, based on the structure of NIBRS, the data could be merged with other existing datasets, furthering the depth and understanding of crime occurrence.