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 If any information presented in this web site is known to be outdated, please contact the Chicago Police Department at srwbmstr@chicagopolice.org, or mail to Sex Registration Unit, 3510 S Michigan Ave, Chicago, IL 60653.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).

Traditionally, criminal research on a national scale has relied primarily on the FBI's Uniform Crime Reports (UCR), a tool with several weaknesses: (1) it contains no unique personal identifiers, precluding analysis of re-offense rates, (2) it lacks detail about individual crimes and their outcomes (e.g., number of charges, plea bargains, dispositions, fines, jail sentences), (3) reporting to the UCR is highly variable, so the aggregate statistics cannot be read as a comprehensive picture of crime. An alternative approach to crime record analysis can be pursued by the study of individual court records, housed in hundreds of counties across the United States. However, each jurisdiction employs local laws and sparse, idiosyncratic information management systems, making it prohibitively difficult to compare detailed crime records across time and place.To overcome all these limitations, we have developed the NeuLaw Criminal Record Database (CRD), a rich and growing collection of tens of millions of crime records. The CRD provides an unprecedented level of detail about individual offenders, their crimes, and their interactions with the criminal justice system; additionally, it translates court records into a common framework for cross-jurisdiction comparison. In particular, the database includes anonymized identifiers to enable large-scale exploration of criminal re-offense (recidivism). The CRD is growing monthly; as of this writing it contains 22.5 million records from 1977 to 2014 from Harris County in Texas, New York City, Miami-Dade County in Florida, and the state of New Mexico. The database can enable or enhance many types of research—for example, identification of high-risk offenders, measurement of changes in policing strategies, and quantification of legislative efficacy—thus giving policy makers the best data upon which to base law enforcement decisions.

The purpose of the study was to quantify the effect of the embrace of DNA technology on offender behavior. In particular, researchers examined whether an offender's knowledge that their DNA profile was entered into a database deterred them from offending in the future and if probative effects resulted from DNA sampling. The researchers coded information using criminal history records and data from Florida's DNA database, both of which are maintained by the Florida Department of Law Enforcement (FDLE), and also utilized court docket information acquired through the Florida Department of Corrections (FDOC) to create a dataset of 156,702 cases involving offenders released from the FDOC in the state of Florida between January 1996 and December 2004. The data contain a total of 50 variables. Major categories of variables include demographic variables regarding the offender, descriptive variables relating to the initial crime committed by the offender, and time-specific variables regarding cases of recidivism.

The Educator Sexual Misconduct Database identifies a sample of criminal cases related to educator sexual misconduct (regardless of the specific criminal statute the defendant was ultimately charged under). The sample of cases all involve a defendant who was connected to the victim through their roles as an educator or school staff member, and who are alleged to have had physical sexual contact with a minor. This database provides a sample of criminal cases specific to educator sexual misconduct even if the defendant's custodial relationship to the minor is not specifically referenced in any of the criminal charges. The sample was identified through news media coverage of criminal proceedings based on a content analysis of newspaper archives and court records available in the LexisNexis news. Cases include convictions ranging from improper relationship between educator and student, to contributing to the delinquency of a minor.

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).

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. Product counterfeiting is the fraudulent reproduction of trademark, copyright, or other intellectual property related to tangible products without the authorization of the producer and motivated by the desire for profit. This study create a Product Counterfeiting Database (PCD) by assessing multiple units of analysis associated with counterfeiting crimes from 2000-2015: (1) scheme; (2) offender (individual); (3) offender (business); (4) victim (consumer); and (5) victim (trademark owner). Unique identification numbers link records for each unit of analysis in a relational database. The collection contains 5 Stata files and 1 Excel spreadsheet file. Scheme-Data.dta (n=196, 35 variables) Offender-Individual-Data.dta (n=551, 16 variables) Offender-Business-Data.dta (n=310, 5 variables) Victim-Consumer-Data.dta (n=54, 8 variables) Victim-Trademark-Owner-Data.dta (n=146, 5 variables) Relational-Data.xlsx (4 spreadsheet tabs)

The purpose of the study was to expand understanding of the long-term consequences of juvenile delinquency by describing the prevalence and frequency of two adult outcomes -- arrest and the perpetration of abuse and neglect -- within a gender-diverse sample of known offenders. The researchers also sought to better inform the development and provision of services targeted to delinquent youth in residential care by exploring whether characteristics assessed at intake into care predict adult offending risk. The research team tracked a large sample of delinquent boys and girls released from juvenile correctional facilities/programs in New York State in the early 1990s and used state administrative databases to document their involvement with criminal justice and child protective services in young adulthood. Sample youth were initially drawn from a research database originally created to examine short-term criminal recidivism rates and associated risk factors among known juvenile delinquents (Frederick, 1999). As part of that study, a comprehensive list of adjudicated delinquents discharged from the custody of the New York State (NYS) Division of Youth between January 1, 1991, and December 31, 1994, was generated. The research team selected a stratified, random subsample of 999 youths with case reviews and tracked them forward through time from age 16 to age 28. The Administrative/Case File Review Data (Part 1) contain information on the experiences prior to being admitted into state custody of 999 youths. Specifically, Part 1 includes early risk factors taken from items coded during the initial recidivism study conducted by Frederick (1999). Part 1 also includes information on a youth's childhood experiences with child welfare services collected by the research team as part of this study. Information on a youth's prior receipt of child welfare services was obtained by extracting records from the NYS Child Care Review Service system (CCRS). The Child Protective Services Reports Data (Part 2) contain information on the sampled subjects' involvement with Child Protective Services (CPS) as young adults (ages 16-28). CPS data were collected by conducting person-based searches of CONNECTIONS, the NYS Statewide Automated Child Welfare Information System. For Part 2, adult perpetration of child maltreatment outcome data were collected on a total of 1,543 child protective services (CPS) reports. The Criminal History Data (Part 3) contain information on the sampled subjects' early adult involvement (ages 16-28) with the NYS adult criminal justice system. The research team documented adult crime and perpetration of child abuse and neglect via searches of two independent state administrative databases: (1) the NYS Offender-Based Transaction Statistics Computerized Criminal History (OBTS/CCH) database, which records all New York state-based arrests of individuals age 16 or older from point of arrest through disposition and sentencing; (2) the Department of Correctional Services (DOCS) database, which tracks all New York State prison admissions and discharges. For Part 3, data were collected on a total of 6,627 adult arrest events. Part 1 contains 30 variables detailing information on the study participants, including demographic variables and variables related to offense history, individual functioning, child maltreatment, receipt of child welfare services, and family environment. Part 2 includes 22 variables derived from child protective services (CPS) reports linked to a study participant, including variables relating to the participant's perpetration of child maltreatment, type of alleged maltreatment, investigation outcome, and outcome variables reflecting participants' involvement in various types of maltreatment allegations. Finally, Part 3 of the study contains 147 variables derived from specific adult arrest events associated with the participants, including arrest-specific variables, case outcome variables, and criminal history variables.

The data contain records of sentenced offenders committed to the custody of the Bureau of Prisons (BOP) during fiscal year 2007. The data include commitments of United States District Court, violators of conditions of release (e.g., parole, probation, or supervised release violators), offenders convicted in other courts (e.g., military or District of Columbia courts), and persons admitted to prison as material witnesses or for purposes of treatment, examination, or transfer to another authority. These data include variables that describe the offender, such as age, race, citizenship, as well as variables that describe the sentences and expected prison terms. The data file contains original variables from the Bureau of Prisons' SENTRY database, as well as "SAF" variables that denote subsets of the data. These SAF variables are related to statistics reported in the Compendium of Federal Justice Statistics, Tables 7.9-7.16. Variables containing identifying information (e.g., name, Social Security Number) were replaced with blanks, and the day portions of date fields were also sanitized in order to protect the identities of individuals. These data are part of a series designed by the Urban Institute (Washington, DC) and the Bureau of Justice Statistics. Data and documentation were prepared by the Urban Institute.

The central system for storing information relating to deaths in prison custody in England and Wales.

The SSA National Instant Criminal Background Check Database (PNICS) captures information on clients that have been identified as legally incompetent or disabled adults, diagnosed with certain mental disabilities, receiving Title II/XVI payments due to certain mental impairments, and have been paid benefits through a representative payee. The information is shared with the FBI. It is added to the FBI database to identify these individuals that are prohibited from purchasing , owning or transferring firearms and ammunition.

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 data contain records of arrests and bookings for federal offenses in the United States during fiscal year 2018. The data were constructed from the United States Marshals Service (USMS) Prisoner Tracking System database. Records include arrests made by federal law enforcement agencies (including the USMS), state and local agencies, and self-surrenders. Offenders arrested for federal offenses are transferred to the custody of the USMS for processing, transportation, and detention. The Prisoner Tracking System contains data on all offenders within the custody of the USMS. The data file contains variables from the original USMS files as well as additional analysis variables. Variables containing identifying information (e.g., name, Social Security number) were either removed, coarsened, or blanked in order to protect the identities of individuals. These data are part of a series designed by Abt and the Bureau of Justice Statistics. Data and documentation were prepared by Abt.

Datasets include Civil and Criminal Mapping of Case Types, Mapping for Stages (Civil and Criminal) and Percentage of Data from E-courts on DAKSH’s Database.

This dataset contains all the final charging documents for defendants charged before the International Criminal Court, International Criminal Tribunal for the Former Yugoslavia, International Criminal Tribunal for Rwanda, and the Special Court for Sierra Leone. The dataset is contained in a MAXQDA2020 file and a REFI file. Each final charge has been coded with the name of the relevant defendant(s); the category of alleged offence (war crimes, crimes against humanity, or genocide-related); whether the charge is an alternative charge or not; and a descriptive summary of the crime. The final charging documents are grouped according to the court in which the defendant was charged. Each charging document has been assigned variables for the court, as well as the year, month, quarter of the year, and 'consecutive quarter' (to allow for mapping of charges over time).

This dataset details the global extent and variance of legislative responses to wildlife crimes. The dataset compiles wildlife, forestry, fishery, and environmental legislation (and in some cases Penal and Criminal Codes) and documents wildlife related offences and their corresponding penalties. Source legislation is hyperlinked in the text and offences are grouped into three categories; 1. wild animals, 2 wild animals (marine), and 3. wild plants. Details of the offence outlined in legislation are given, these are also consolidated to allow for greater comparison in the Wildlife Crime Penalties dashboard. Details on penalties are grouped by; 1. Fines, 2. Other financial penalties, 3. Imprisonment, 4. Restorative penalties, and 5. Additional penalties.This data was compiled as part of a study investigating the potential for Restorative Justice as a mechanism to address wildlife crimes. The findings of this legislative review have been published in the Global Journal of Animal Law and are also available online through the Wildlife Crime Penalties dashboard. Our hope is that the availability of this information will help to inform more effective management and intervention measures, including the wider adoption of restorative justice approaches to wildlife crime. We intend for this database and dashboard to be a living document and encourage the global community to contribute to updating the database.

Drug consumption database with original values of attributes. DescriptionDB.pdf contains detailed description of database.

This file contains description of the drug consumption database.

The data contain records of sentenced offenders released from the custody of the Bureau of Prisons (BOP) during fiscal year 2008. The data include commitments of United States District Court, violators of conditions of release (e.g., parole, probation, or supervised release violators), offenders convicted in other courts (e.g., military or District of Columbia courts), and persons admitted to prison as material witnesses or for purposes of treatment, examination, or transfer to another authority. Records of offenders who exit federal prison temporarily, such as for transit to another location, to serve a weekend sentence, or for health care, are not included in the exiting cohort. These data include variables that describe the offender, such as age, race, citizenship, as well as variables that describe the sentences and expected prison terms. The data file contains original variables from the Bureau of Prisons' SENTRY database, as well as "SAF" variables that denote subsets of the data. These SAF variables are related to statistics reported in the Compendium of Federal Justice Statistics, Tables 7.9-7.16. Variables containing identifying information (e.g., name, Social Security Number) were replaced with blanks, and the day portions of date fields were also sanitized in order to protect the identities of individuals. These data are part of a series designed by the Urban Institute (Washington, DC) and the Bureau of Justice Statistics. Data and documentation were prepared by the Urban Institute.

When CPSC is involved in a civil or criminal investigations into violations of the Consumer Products Safety Act the Commission publishes final determinations and those penalties are recorded in the Civil and Criminal Penalties Database. You can search this database for records by civil or criminal penalties as well as by company, product, and fiscal year.

For this study, convenience store robbery victims and offenders in five states (Georgia, Massachusetts, Maryland, Michigan, and South Carolina) were interviewed. Robbery victims were identified by canvassing convenience stores in high-crime areas, while a sample of unrelated offenders was obtained from state prison rolls. The aims of the survey were to address questions of injury, to examine store characteristics that might influence the rate of robbery and injury, to compare how both victims and offenders perceived the robbery event (including their assessment of what could be done to prevent convenience store robberies in the future), and to identify ways in which the number of convenience store robberies might be reduced. Variables unique to Part 1, the Victim Data file, provide information on how the victim was injured, whether hospitalization was required for the injury, if the victim used any type of self-protection, and whether the victim had been trained to handle a robbery. Part 2, the Offender Data file, presents variables describing offenders' history of prior convenience store robberies, whether there had been an accomplice, motive for robbing the store, and whether various factors mattered in choosing the store to rob (e.g., cashier location, exit locations, lighting conditions, parking lot size, the number of clerks working, weather conditions, the time of day, and the number of customers in the store). Found in both files are variables detailing whether a victim injury occurred, use of a weapon, how each participant behaved, perceptions of why the store was targeted, what could have been done to prevent the robbery, and ratings by the researchers on the completeness, honesty, and cooperativeness of each participant during the interview. Demographic variables found in both the victim and offender files include age, gender, race, and ethnicity.