Police Records Management System Market Outlook

The global police records management system market size was valued at approximately USD 2.5 billion in 2023 and is projected to reach around USD 5.3 billion by 2032, growing at a compound annual growth rate (CAGR) of 8.8% from 2024 to 2032. This dynamic growth is primarily driven by advancements in digital technology, increased focus on public safety, and the growing demand for efficient management of police records. The significant rise in criminal activities globally has necessitated the adoption of sophisticated records management systems by law enforcement agencies to streamline operations and improve response times. Furthermore, the integration of advanced technologies such as artificial intelligence and big data analytics into these systems is expected to further propel the market growth over the forecast period.

The increasing focus on public safety and security is one of the primary growth factors fueling the expansion of the police records management system market. With the rise in crime rates and the complexity of modern crimes, law enforcement agencies are compelled to adopt more effective and efficient systems for managing and analyzing records. These systems enable better coordination and faster decision-making, which are crucial in combating crime and ensuring public safety. Governments across the world are investing heavily in modernizing their police infrastructure, which includes the deployment of robust records management systems. This investment is expected to continue, driven by the need for more sophisticated solutions that can handle the growing volume and complexity of data involved in law enforcement operations.

Technological advancements play a critical role in the growth of the police records management system market. The introduction of technologies such as cloud computing, artificial intelligence, machine learning, and big data analytics into records management systems has revolutionized the way police records are processed, stored, and retrieved. These technologies enable real-time data analysis, predictive analytics, and enhanced data security, thereby improving the overall efficiency and effectiveness of law enforcement agencies. In addition, the shift towards cloud-based solutions offers scalability, flexibility, and cost-effectiveness, which are appealing to both small and large law enforcement agencies. The continuous innovation in this space is expected to drive further adoption and expansion of police records management systems globally.

Another significant driver for the market is the increasing collaboration and information sharing between law enforcement agencies across different regions and countries. The globalization of crime has necessitated a unified approach to law enforcement, with agencies working together to share critical information and insights. Police records management systems facilitate this cooperation by offering centralized platforms for data sharing and collaboration. As agencies continue to recognize the importance of inter-agency cooperation, the demand for robust and interoperable records management systems is expected to rise, contributing to the market's growth.

Policing Technologies have become an integral part of modern law enforcement strategies, significantly influencing the development and implementation of police records management systems. These technologies encompass a wide range of tools and solutions designed to enhance the capabilities of law enforcement agencies. From body-worn cameras and automated license plate readers to sophisticated data analytics platforms, policing technologies provide invaluable support in crime prevention, investigation, and community engagement. The integration of these technologies into records management systems allows for more comprehensive data collection and analysis, enabling agencies to make informed decisions and improve operational efficiency. As the demand for advanced policing technologies continues to grow, their role in shaping the future of police records management systems is expected to expand, offering new opportunities for innovation and collaboration in the field.

Regionally, North America holds a prominent position in the police records management system market, owing to the early adoption of advanced technologies and significant investments in law enforcement infrastructure. The presence of leading market players and the federal government's proactive approach towards public safety and security further bolster the market in this region. Europe f

A list of all closed allegations made against uniformed members of the New York Police Department since the year 2000. A single complaint may include multiple allegations between multiple victims / alleged victims and multiple officers. A single allegation is between one complainant and one officer. The term "Victim / Alleged Victim" refers to the person claiming harm by at least one or more allegation(s) of police misconduct. The dataset is part of a database of all public police misconduct records the Civilian Complaint Review Board (CCRB) maintains on complaints against New York Police Department uniformed members of service received in CCRB's jurisdiction since the year 2000, when CCRB's database was first built. This data is published as four tables: Civilian Complaint Review Board: Police Officers Civilian Complaint Review Board: Complaints Against Police Officers Civilian Complaint Review Board: Allegations Against Police Officers Civilian Complaint Review Board: Penalties A single complaint can include multiple allegations, and those allegations may include multiple subject officers and multiple complainants. Public records exclude complaints and allegations that were closed as Mediated, Mediation Attempted, Administrative Closure, Conciliated (for some complaints prior to the year 2000), or closed as Other Possible Misconduct Noted. This database is inclusive of prior datasets held on Open Data (previously maintained as "Civilian Complaint Review Board (CCRB) - Complaints Received," "Civilian Complaint Review Board (CCRB) - Complaints Closed," and "Civilian Complaint Review Board (CCRB) - Allegations Closed") but includes information and records made public by the June 2020 repeal of New York Civil Rights law 50-a, which precipitated a full revision of what CCRB data could be considered public.

Sadly, the trend of fatal police shootings in the United States seems to only be increasing, with a total 1,173 civilians having been shot, 248 of whom were Black, as of December 2024. In 2023, there were 1,164 fatal police shootings. Additionally, the rate of fatal police shootings among Black Americans was much higher than that for any other ethnicity, standing at 6.1 fatal shootings per million of the population per year between 2015 and 2024. Police brutality in the U.S. In recent years, particularly since the fatal shooting of Michael Brown in Ferguson, Missouri in 2014, police brutality has become a hot button issue in the United States. The number of homicides committed by police in the United States is often compared to those in countries such as England, where the number is significantly lower. Black Lives Matter The Black Lives Matter Movement, formed in 2013, has been a vocal part of the movement against police brutality in the U.S. by organizing “die-ins”, marches, and demonstrations in response to the killings of black men and women by police. While Black Lives Matter has become a controversial movement within the U.S., it has brought more attention to the number and frequency of police shootings of civilians.

The primary table for all public data on complaints, including dates, locations and the outcomes of closed complaints received since the year 2000. The dataset is part of a database of all public police misconduct records the Civilian Complaint Review Board (CCRB) maintains on complaints against New York Police Department uniformed members of service received in CCRB's jurisdiction since the year 2000, when CCRB's database was first built. This data is published as four tables: Civilian Complaint Review Board: Police Officers Civilian Complaint Review Board: Complaints Against Police Officers Civilian Complaint Review Board: Allegations Against Police Officers Civilian Complaint Review Board: Penalties A single complaint can include multiple allegations, and those allegations may include multiple subject officers and multiple complainants. Public records exclude complaints and allegations that were closed as Mediated, Mediation Attempted, Administrative Closure, Conciliated (for some complaints prior to the year 2000), or closed as Other Possible Misconduct Noted. This database is inclusive of prior datasets held on Open Data (previously maintained as "Civilian Complaint Review Board (CCRB) - Complaints Received," "Civilian Complaint Review Board (CCRB) - Complaints Closed," and "Civilian Complaint Review Board (CCRB) - Allegations Closed") but includes information and records made public by the June 2020 repeal of New York Civil Rights law 50-a, which precipitated a full revision of what CCRB data could be considered public.

Updated daily postings on Montgomery County’s open data website, dataMontgomery, provide the public with direct access to crime statistic databases - including raw data and search functions – of reported County crime. The data presented is derived from reported crimes classified according to the National Incident-Based Reporting System (NIBRS) of the Criminal Justice Information Services (CJIS) Division Uniform Crime Reporting (UCR) Program and documented by approved police incident reports. The data is compiled by “EJustice”, a respected law enforcement records-management system used by the Montgomery County Police Department and many other law enforcement agencies. To protect victims’ privacy, no names or other personal information are released. All data is refreshed on a quarterly basis to reflect any changes in status due to on-going police investigation.

dataMontgomery allows the public to query the Montgomery County Police Department's database of founded crime. The information contained herein includes all founded crimes reported after July 1st 2016 and entered to-date utilizing Uniform Crime Reporting (UCR) rules. Please note that under UCR rules multiple offenses may appear as part of a single founded reported incident, and each offense may have multiple victims. Please note that these crime reports are based on preliminary information supplied to the Police Department by the reporting parties. Therefore, the crime data available on this web page may reflect:

-Information not yet verified by further investigation -Information that may include attempted and reported crime -Preliminary crime classifications that may be changed at a later date based upon further investigation -Information that may include mechanical or human error -Arrest information [Note: all arrested persons are presumed innocent until proven guilty in a court of law.]

Update Frequency: Daily

This dataset contains Crime and Safety data from the Cary Police Department.

This data is extracted by the Town of Cary's Police Department's RMS application. The police incidents will provide data on the Part I crimes of arson, motor vehicle thefts, larcenies, burglaries, aggravated assaults, robberies and homicides. Sexual assaults and crimes involving juveniles will not appear to help protect the identities of victims.

This dataset includes criminal offenses in the Town of Cary for the previous 10 calendar years plus the current year. The data is based on the National Incident Based Reporting System (NIBRS) which includes all victims of person crimes and all crimes within an incident. The data is dynamic, which allows for additions, deletions and/or modifications at any time, resulting in more accurate information in the database. Due to continuous data entry, the number of records in subsequent extractions are subject to change. Crime data is updated daily however, incidents may be up to three days old before they first appear.

About Crime Data

The Cary Police Department strives to make crime data as accurate as possible, but there is no avoiding the introduction of errors into this process, which relies on data furnished by many people and that cannot always be verified. Data on this site are updated daily, adding new incidents and updating existing data with information gathered through the investigative process.

This dynamic nature of crime data means that content provided here today will probably differ from content provided a week from now. Additional, content provided on this site may differ somewhat from crime statistics published elsewhere by other media outlets, even though they draw from the same database.

Withheld Data

In accordance with legal restrictions against identifying sexual assault and child abuse victims and juvenile perpetrators, victims, and witnesses of certain crimes, this site includes the following precautionary measures: (a) Addresses of sexual assaults are not included. (b) Child abuse cases, and other crimes which by their nature involve juveniles, or which the reports indicate involve juveniles as victims, suspects, or witnesses, are not reported at all.

Certain crimes that are under current investigation may be omitted from the results in avoid comprising the investigative process.

Incidents five days old or newer may not be included until the internal audit process has been completed.

This data is updated daily.

Global Police Records Management System comes with the extensive industry analysis of development components, patterns, flows and sizes. The report also calculates present and past market values to forecast potential market management through the forecast period between 2024 - 2032. The report may be the best of what is a geographic area which expands the competitive landscape and industry perspective of the market.

Description: Pursuant to the Sex Offender and Child Murderer Community Notification Law, 730 ILCS 152/101,et seq., the Chicago Police Department maintains a list of sex offenders residing in the City of Chicago who are required to register under the Sex Offender Registration Act, 730 ILCS 150/2, et seq. To protect the privacy of the individuals, addresses are shown at the block level only and specific locations are not identified. The data are extracted from the CLEAR (Citizen Law Enforcement Analysis and Reporting) system developed by the Department. Although every effort is made to keep this list accurate and current, the city cannot guarantee the accuracy of this information. Offenders may have moved and failed to notify the Chicago Police Department as required by law. If any information presented in this web site is known to be outdated, please contact the Chicago Police Department at srwbmstr@chicagopolice.org, or mail to Sex Registration Unit, 3510 S Michigan Ave, Chicago, IL 60653. Disclaimer: This registry is based upon the legislature's decision to facilitate access to publicly available information about persons convicted of specific sexual offenses. The Chicago Police Department has not considered or assessed the specific risk of re-offense with regard to any individual prior to his or her inclusion within this registry, and has made no determination that any individual included within the registry is currently dangerous. Individuals included within this registry are included solely by virtue of their conviction record and Illinois law. The main purpose of providing this data on the internet is to make the information more available and accessible, not to warn about any specific individual.

Anyone who uses information contained in the Sex Offender Database to commit a criminal act against another person is subject to criminal prosecution. Data Owner: Chicago Police Department. Frequency: Data is updated daily. Related Applications: CLEARMAP (http://j.mp/lLluSa).

The Public Safety Records Management System (RMS) market is experiencing robust growth, driven by the increasing need for efficient and secure management of ever-growing volumes of criminal justice data. Agencies are under pressure to improve response times, enhance inter-agency collaboration, and comply with stringent data privacy regulations. This is fueling the demand for sophisticated RMS solutions that offer advanced features such as data analytics, predictive policing capabilities, and seamless integration with other critical systems. The market is witnessing a shift towards cloud-based deployments, offering scalability, cost-effectiveness, and improved accessibility. Furthermore, the incorporation of artificial intelligence (AI) and machine learning (ML) is transforming RMS, enabling improved investigative capabilities, enhanced crime pattern analysis, and better resource allocation. Key players like IBM, Accenture, and Axon are actively innovating and expanding their product portfolios to meet this growing demand. The market is segmented by deployment type (cloud, on-premise), functionality (case management, evidence management, records management), and end-user (police departments, courts, correctional facilities). While high initial investment costs and complexities associated with system integration can pose challenges, the long-term benefits of improved efficiency and enhanced public safety outweigh these hurdles. The market's projected Compound Annual Growth Rate (CAGR) suggests a steady expansion over the forecast period (2025-2033). We estimate the market size to be approximately $5 billion in 2025, based on industry reports and considering the growth trajectory of similar technology markets. This figure is expected to increase significantly by 2033, driven by continued technological advancements, increased adoption by smaller agencies, and ongoing investments in public safety infrastructure. Regional variations will likely exist, with North America and Europe maintaining a dominant market share due to high technology adoption rates and strong government support. However, emerging markets in Asia-Pacific and Latin America are anticipated to show promising growth in the coming years, fueled by rising urbanization and increasing crime rates. Competition in the market is intense, with both established players and emerging technology providers vying for market share through product innovation, strategic partnerships, and acquisitions.

Learn more about Market Research Intellect's Police Records Management System Market Report, valued at USD 1.2 billion in 2024, and set to grow to USD 2.5 billion by 2033 with a CAGR of 9.3% (2026-2033).

The global Police Records Management System (RMS) Software market is experiencing robust growth, driven by increasing demand for efficient crime management and improved public safety. The market, currently estimated at $119 million in 2025, is projected to exhibit a significant Compound Annual Growth Rate (CAGR) – let's assume a conservative 8% based on the adoption of advanced technologies in law enforcement and the ongoing need for digital transformation within justice agencies. This growth is fueled by several key factors. Firstly, the increasing volume of criminal data necessitates advanced software solutions capable of managing, analyzing, and retrieving information quickly and accurately. Secondly, the growing emphasis on evidence-based policing and improved inter-agency collaboration necessitates integrated RMS solutions that facilitate seamless data sharing. Thirdly, the ongoing adoption of cloud-based RMS systems offers scalability, cost-effectiveness, and enhanced accessibility for law enforcement agencies of all sizes. The market segmentation reveals a strong preference for cloud-based solutions over on-premises systems, driven by factors such as reduced infrastructure costs and improved data security. Justice agencies, law enforcement agencies, and national security agencies constitute the major end-user segments, each contributing significantly to market expansion. Geographic analysis suggests that North America and Europe currently hold a significant share of the market, though regions like Asia Pacific are expected to witness rapid growth in the coming years due to increasing investment in public safety infrastructure and technological advancements. Competitive dynamics are characterized by a mix of established players and emerging technology providers, continuously innovating to offer advanced features such as predictive policing capabilities, facial recognition integration, and improved mobile accessibility. Growth challenges include concerns over data security and privacy, the need for substantial upfront investment in system implementation and training, and the complexity of integrating RMS with existing legacy systems. However, ongoing technological advancements are addressing these concerns, with enhanced security features and streamlined integration processes becoming increasingly prevalent. The market is likely to see further consolidation through mergers and acquisitions, as larger players seek to expand their market share and service offerings. This dynamic market landscape will present both opportunities and challenges for existing and new entrants, necessitating strategic investments in R&D and a deep understanding of evolving customer needs. Future growth will be driven by the continued adoption of AI-powered analytics, improved data visualization tools, and the integration of various data sources to offer comprehensive situational awareness for law enforcement agencies.

Global Police Records Management System is segmented by Application (Law Enforcement, Government, Criminal Justice, Security, Compliance), Type (Digital, Cloud-based, Automated, Integrated, Customizable) and Geography(North America, LATAM, West Europe, Central & Eastern Europe, Northern Europe, Southern Europe, East Asia, Southeast Asia, South Asia, Central Asia, Oceania, MEA)

description: Please read and understand the following information. Understanding the following conditions will allow you to get the most out of the data provided. ??? Due to the methodological differences in data collection, different data sources may produce different results. ??? Our on-line database is continuously being updated. The data provided here represents a particular point in time. Searches may be accomplished using several geographic boundaries: Police area commands or districts, zip codes and census tracts. Additionally, a known case number may be entered. Updates to the police report database occur daily. Information is available from today???s date back 18 months. Due to several factors (once-a-day updates, offense reclassification, reported versus occurred dates, etc.) comparisons should not be made between numbers generated with this database to any other official police reports. Data provided represents only calls for police service where a report was written. Totals in the database may vary considerably from official totals following investigation and final categorization. Therefore, the data should not be used for comparisons with Uniform Crime Report statistics. The Austin Police Department does not assume any liability for any decision made or action taken or not taken by the recipient in reliance upon any information or data provided.; abstract: Please read and understand the following information. Understanding the following conditions will allow you to get the most out of the data provided. ??? Due to the methodological differences in data collection, different data sources may produce different results. ??? Our on-line database is continuously being updated. The data provided here represents a particular point in time. Searches may be accomplished using several geographic boundaries: Police area commands or districts, zip codes and census tracts. Additionally, a known case number may be entered. Updates to the police report database occur daily. Information is available from today???s date back 18 months. Due to several factors (once-a-day updates, offense reclassification, reported versus occurred dates, etc.) comparisons should not be made between numbers generated with this database to any other official police reports. Data provided represents only calls for police service where a report was written. Totals in the database may vary considerably from official totals following investigation and final categorization. Therefore, the data should not be used for comparisons with Uniform Crime Report statistics. The Austin Police Department does not assume any liability for any decision made or action taken or not taken by the recipient in reliance upon any information or data provided.

description: Law Enforcement Locations in Kansas Any location where sworn officers of a law enforcement agency are regularly based or stationed. Law enforcement agencies "are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Although TGS's intention is to only include locations associated with agencies that meet the above definition, TGS has discovered a few locations that are associated with agencies that are not publicly funded. TGS is deleting these locations as we become aware of them, but some probably still exist in this dataset. Personal homes, administrative offices and temporary locations are intended to be excluded from this dataset, but a few may be included. Personal homes of constables may exist due to fact that many constables work out of their home. FBI entites are intended to be excluded from this dataset, but a few may be included. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] attribute. Based upon this attribute, the oldest record dates from 2006/06/27 and the newest record dates from 2008/03/06; abstract: Law Enforcement Locations in Kansas Any location where sworn officers of a law enforcement agency are regularly based or stationed. Law enforcement agencies "are publicly funded and employ at least one full-time or part-time sworn officer with general arrest powers". This is the definition used by the US Department of Justice - Bureau of Justice Statistics (DOJ-BJS) for their Law Enforcement Management and Administrative Statistics (LEMAS) survey. Although LEMAS only includes non Federal Agencies, this dataset includes locations for federal, state, local, and special jurisdiction law enforcement agencies. Law enforcement agencies include, but are not limited to, municipal police, county sheriffs, state police, school police, park police, railroad police, federal law enforcement agencies, departments within non law enforcement federal agencies charged with law enforcement (e.g., US Postal Inspectors), and cross jurisdictional authorities (e.g., Port Authority Police). In general, the requirements and training for becoming a sworn law enforcement officer are set by each state. Law Enforcement agencies themselves are not chartered or licensed by their state. County, city, and other government authorities within each state are usually empowered by their state law to setup or disband Law Enforcement agencies. Generally, sworn Law Enforcement officers must report which agency they are employed by to the state. Although TGS's intention is to only include locations associated with agencies that meet the above definition, TGS has discovered a few locations that are associated with agencies that are not publicly funded. TGS is deleting these locations as we become aware of them, but some probably still exist in this dataset. Personal homes, administrative offices and temporary locations are intended to be excluded from this dataset, but a few may be included. Personal homes of constables may exist due to fact that many constables work out of their home. FBI entites are intended to be excluded from this dataset, but a few may be included. Text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. All diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is indicated by the [CONTDATE] attribute. Based upon this attribute, the oldest record dates from 2006/06/27 and the newest record dates from 2008/03/06

This project used national databases to describe the incidence and distribution of fatal and nonfatal police shootings and to develop an empirically based typology of legal intervention homicides. To accomplish this, the study team evaluated the comprehensiveness of the National Violent Death Reporting System (NVDRS) for fatal police shootings along with various open-source databases. The study team also explained the variation across states in fatal police shootings using a validated national database (Washington Post "Fatal Force Database") and is currently examining the variation in fatal police shooting across urban vs. rural areas.

This report describes the purpose for developing the National Law Enforcement Accountability Database (NLEAD), a centralized repository of official records documenting instances of law enforcement officer misconduct as well as commendations and awards to help inform hiring, job assignment, and promotion decisions. It also provides statistics on the NLEAD’s records, the federal law enforcement officers included, and its usage. This is the first annual report, and it covers NLEAD records for events occurring in calendar years 2018 to 2023 and usage of the NLEAD from January 1, 2024 to August 31, 2024.Downloaded from BJS website on 2025-02-25.

Crime report data is provided for Louisville Metro Police Divisions only; crime data does not include smaller class cities.The data provided in this dataset is preliminary in nature and may have not been investigated by a detective at the time of download. The data is therefore subject to change after a complete investigation. This data represents only calls for police service where a police incident report was taken. Due to the variations in local laws and ordinances involving crimes across the nation, whether another agency utilizes Uniform Crime Report (UCR) or National Incident Based Reporting System (NIBRS) guidelines, and the results learned after an official investigation, comparisons should not be made between the statistics generated with this dataset to any other official police reports. Totals in the database may vary considerably from official totals following the investigation and final categorization of a crime. Therefore, the data should not be used for comparisons with Uniform Crime Report or other summary statistics.Data is broken out by year into separate CSV files. Note the file grouping by year is based on the crime's Date Reported (not the Date Occurred).Older cases found in the 2003 data are indicative of cold case research. Older cases are entered into the Police database system and tracked but dates and times of the original case are maintained.Data may also be viewed off-site in map form for just the last 6 months on Crimemapping.comData Dictionary:INCIDENT_NUMBER - the number associated with either the incident or used as reference to store the items in our evidence roomsDATE_REPORTED - the date the incident was reported to LMPDDATE_OCCURED - the date the incident actually occurredUOR_DESC - Uniform Offense Reporting code for the criminal act committedCRIME_TYPE - the crime type categoryNIBRS_CODE - the code that follows the guidelines of the National Incident Based Reporting System. For more details visit https://ucr.fbi.gov/nibrs/2011/resources/nibrs-offense-codes/viewUCR_HIERARCHY - hierarchy that follows the guidelines of the FBI Uniform Crime Reporting. For more details visit https://ucr.fbi.gov/ATT_COMP - Status indicating whether the incident was an attempted crime or a completed crime.LMPD_DIVISION - the LMPD division in which the incident actually occurredLMPD_BEAT - the LMPD beat in which the incident actually occurredPREMISE_TYPE - the type of location in which the incident occurred (e.g. Restaurant)BLOCK_ADDRESS - the location the incident occurredCITY - the city associated to the incident block locationZIP_CODE - the zip code associated to the incident block locationID - Unique identifier for internal databaseContact:Crime Information CenterCrimeInfoCenterDL@louisvilleky.gov

Crime report data is provided for Louisville Metro Police Divisions only; crime data does not include smaller class cities.The data provided in this dataset is preliminary in nature and may have not been investigated by a detective at the time of download. The data is therefore subject to change after a complete investigation. This data represents only calls for police service where a police incident report was taken. Due to the variations in local laws and ordinances involving crimes across the nation, whether another agency utilizes Uniform Crime Report (UCR) or National Incident Based Reporting System (NIBRS) guidelines, and the results learned after an official investigation, comparisons should not be made between the statistics generated with this dataset to any other official police reports. Totals in the database may vary considerably from official totals following the investigation and final categorization of a crime. Therefore, the data should not be used for comparisons with Uniform Crime Report or other summary statistics.Data is broken out by year into separate CSV files. Note the file grouping by year is based on the crime's Date Reported (not the Date Occurred).Older cases found in the 2003 data are indicative of cold case research. Older cases are entered into the Police database system and tracked but dates and times of the original case are maintained.Data may also be viewed off-site in map form for just the last 6 months on Crimemapping.comData Dictionary:INCIDENT_NUMBER - the number associated with either the incident or used as reference to store the items in our evidence roomsDATE_REPORTED - the date the incident was reported to LMPDDATE_OCCURED - the date the incident actually occurredUOR_DESC - Uniform Offense Reporting code for the criminal act committedCRIME_TYPE - the crime type categoryNIBRS_CODE - the code that follows the guidelines of the National Incident Based Reporting System. For more details visit https://ucr.fbi.gov/nibrs/2011/resources/nibrs-offense-codes/viewUCR_HIERARCHY - hierarchy that follows the guidelines of the FBI Uniform Crime Reporting. For more details visit https://ucr.fbi.gov/ATT_COMP - Status indicating whether the incident was an attempted crime or a completed crime.LMPD_DIVISION - the LMPD division in which the incident actually occurredLMPD_BEAT - the LMPD beat in which the incident actually occurredPREMISE_TYPE - the type of location in which the incident occurred (e.g. Restaurant)BLOCK_ADDRESS - the location the incident occurredCITY - the city associated to the incident block locationZIP_CODE - the zip code associated to the incident block locationID - Unique identifier for internal databaseContact:Crime Information CenterCrimeInfoCenterDL@louisvilleky.gov

Gain in-depth insights into Police Records Management System (RMS) Software Market Report from Market Research Intellect, valued at USD 1.2 billion in 2024, and projected to grow to USD 2.3 billion by 2033 with a CAGR of 8.3% from 2026 to 2033.

The data provided in this dataset is preliminary in nature and may have not been investigated by a detective at the time of download. The data is therefore subject to change after a complete investigation. This data represents only calls for police service where a police incident report was taken. Due to the variations in local laws and ordinances involving crimes across the nation, whether another agency utilizes Uniform Crime Report (UCR) or National Incident Based Reporting System (NIBRS) guidelines, and the results learned after an official investigation, comparisons should not be made between the statistics generated with this dataset to any other official police reports. Totals in the database may vary considerably from official totals following the investigation and final categorization of a crime. Therefore, the data should not be used for comparisons with Uniform Crime Report or other summary statistics.Data is broken out by year into separate CSV files. Note the file grouping by year is based on the crime's Date Reported (not the Date Occurred).Older cases found in the 2003 data are indicative of cold case research. Older cases are entered into the Police database system and tracked but dates and times of the original case are maintained.Data may also be viewed off-site in map form for just the last 6 months on communitycrimemap.comData Dictionary:

Field Name

Field Description

Incident Number

the number associated with either the incident or used as reference to store the items in our evidence rooms

Date Reported

the date the incident was reported to LMPD

Date Occurred

the date the incident actually occurred

Badge ID

Badge ID of responding Officer

Offense Classification

NIBRS Reporting category for the criminal act committed

Offense Code Name

NIBRS Reporting code for the criminal act committed

NIBRS_CODE

the code that follows the guidelines of the National Incident Based Reporting System. For more details visit https://ucr.fbi.gov/nibrs/2011/resources/nibrs-offense-codes/view

NIBRS Group

hierarchy that follows the guidelines of the FBI National Incident Based Reporting System

Was Offense Completed

Status indicating whether the incident was an attempted crime or a completed crime.

LMPD Division

the LMPD division in which the incident actually occurred

LMPD Beat

the LMPD beat in which the incident actually occurred

Location Category

the type of location in which the incident occurred (e.g. Restaurant)

Block Address

the location the incident occurred

City

the city associated to the incident block location

Zip Code

the zip code associated to the incident block location

Contact:LMPD Open Records lmpdopenrecords@louisvilleky.gov