The data are provided are the Maryland Statistical Analysis Center (MSAC), within the Governor's Office of Crime Control and Prevention (GOCCP). MSAC, in turn, receives these data from the Maryland State Police's annual Uniform Crime Reports.

Historical crime rates per 100,000 people, 1975 - present. In June 2017 we changed the update frequency of this dataset from annual to as-needed because sometimes there is a lag that is often 6 months after the annual date before the new data is available.

In 2023, the District of Columbia had the highest reported violent crime rate in the United States, with 1,150.9 violent crimes per 100,000 of the population. Maine had the lowest reported violent crime rate, with 102.5 offenses per 100,000 of the population. Life in the District The District of Columbia has seen a fluctuating population over the past few decades. Its population decreased throughout the 1990s, when its crime rate was at its peak, but has been steadily recovering since then. While unemployment in the District has also been falling, it still has had a high poverty rate in recent years. The gentrification of certain areas within Washington, D.C. over the past few years has made the contrast between rich and poor even greater and is also pushing crime out into the Maryland and Virginia suburbs around the District. Law enforcement in the U.S. Crime in the U.S. is trending downwards compared to years past, despite Americans feeling that crime is a problem in their country. In addition, the number of full-time law enforcement officers in the U.S. has increased recently, who, in keeping with the lower rate of crime, have also made fewer arrests than in years past.

This dataset shows the total number of violent crimes by county and statewide, for CY2006 versus CY2013. Data are provided by the Maryland Statistical Analysis Center (MSAC) within the Governor's Office of Crime Control and Prevention (GOCCP).

The District of Columbia had the highest robbery rate in the United States in 2023, with 614.2 robberies per 100,000 inhabitants. The lowest robbery rate in the country was found in Idaho, with 9.5 robberies per 100,000 inhabitants. Crime in the District of Columbia The violent crime rate in the District of Columbia was found to be the highest in the United States, with there being a few reasons for this: Firstly, the population of the District of Columbia is quite low (causing a higher rate of crime), and secondly, issues such as the crack epidemic of the 1990s exacerbated the prevalence of crime in the District. As rising rents and gentrification force more people out of the District, crime is moving into neighboring Maryland and Virginia suburbs, as poorer residents seek more affordable living conditions. Crime in the United States Overall, violent crime in the United States and the District of Columbia today is far below the violent crime rate of the 1990s. While some may feel that crime is on the rise, due in part to media sensationalism in fact, the opposite is true, and the United States is becoming safer over time.

Note: This filtered view of opioid crime incidents does not reflect overdoses.

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.]

Street addresses are temporarily unavailable. The Police Response Area (PRA) is the most precise geographic field currently available. For a map of PRA boundaries, please refer to: https://mcpd-md.maps.arcgis.com/apps/webappviewer/index.html?id=12fca77d915742faa1faf14b5f5334a1.

Update Frequency: Daily

The ArcGIS Pro Dashboard for the City of Bowie's Crime Trend Map is a cutting-edge tool that provides real-time insights into the crime trends in the city. With data from the last 30, 180, and 365 days, this dashboard compares the current crime trends to the same time frame from the previous year, giving a clear picture of the direction the city's crime is headed. The IT Department of the City of Bowie, with data sourced from the City of Bowie Police Department, created this dashboard to provide residents and officials with a comprehensive view of crime in the city. The dashboard features interactive charts, graphs, and maps that make it easy to explore the data and understand the trends. The information on this dashboard can be used to inform decision-making and crime prevention strategies, helping to keep the community safe.

This study examines the relationship between socio-economic factors and crime distribution using a dataset that includes variables such as unemployment rates, literacy rates, per capita income, and population density. The analysis explores how these factors influence crime rates across different regions, comparing urban and rural areas to identify variations in crime patterns due to economic and social disparities. Additionally, the study investigates cultural and psychological influences on criminal activities. The findings offer valuable insights for policymakers to develop more effective crime prevention strategies.This dataset supports the manuscript ‘Crime and Socio-Economic Inequalities: Leveraging Deep Learning and Generative AI for Comprehensive Analysis.’ It includes:- CrimeEconomicsData.csv: Original dataset with 114 observations across 10 socio-economic variables (Per Capita Income, Population Density, Unemployment, Literacy Rate, Happiness Index, Crime Rate).- supplementary_data.zip: Contains: - table_ii_metrics.csv: Performance metrics (Accuracy, Precision, Recall, F1-Score, ROC-AUC) for machine learning and deep learning models in Table II. - figure_2_confusion_matrices.csv: Confusion matrix data for each model, supporting Figure 2’s visualizations. - README.txt: Description of the files and their purpose.Preprocessed datasets are not included, as preprocessing steps (e.g., mean imputation, standardization, PCA) are detailed in the manuscript and can be replicated using CrimeEconomicsData.csv.

Financial overview and grant giving statistics of Maryland Crime Victims Resourcefoundation Inc

Filtered view of County crime data to show driving under the influence for liquor and drugs.

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.

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

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 2013 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.]

Street addresses are temporarily unavailable. The Police Response Area (PRA) is the most precise geographic field currently available. For a map of PRA boundaries, please refer to: https://mcpd-md.maps.arcgis.com/apps/webappviewer/index.html?id=12fca77d915742faa1faf14b5f5334a1.

Update Frequency: Daily

Crime Data dataset current as of 2011. MTA Police ARC GIS CompStat Map.

Victim legal services generally, and victims rights enforcement legal services specifically, are still relatively new victim assistance fields compared with other forms of crime victim services. Therefore, the field of victim legal services has so far lacked a conceptual framework that articulates the ultimate goals of these services, and how the provision of these services is intended to promote those goals. This formative evaluation, which is a collaboration between the Justice Research and Statistics Association (JRSA) and the National Crime Victim Law Institute (NCVLI) and funded by the National Institute of Justice, seeks to address this gap by first creating a conceptual model and theory of change, and then testing it in practice.

Assets:data tables each for city of Indianapolis (IN) and Baltimore (MD) in MS Excel and MS Word, ditto shapefiles in ESRI format; all files ZIPPEDContext – abstract of report published in a blog at the serial Geospatial World:This case study called into question police conduct and policy injustice discovered in two American big cities. My path to learn about Indianapolis (IN) and Baltimore (MD) policing patterns and crime events was due to availability of open data focused on use-of-force (UOF). My specific goal was to conduct geospatial data analytics aimed at these two cities using location and other key variables. Two spreadsheets captured small data that laid acceptable statistical groundwork for iterations of exploratory spatial data analysis (ESDA). Bivariate scatterplots revealed possible police misconduct. Parallel coordinate plotting – an innovative multivariate tool – was then used to display co-occurrences of plotted UOF and racial variables associated with key police districts in Indianapolis and Baltimore. A final summary visualization sought to cartographically and dramatically compare force and race variables by way of comparative plots, graphs, and maps. I closed with three action items pertaining to a “social-justice” framework for future data-visualization, to the heightening of standards for law enforcement reform, and for a need to make a hypothetical “citizen’s arrest” of police misconduct.