cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/icpsr37694
title: Firearm Injury Surveillance Study, 1993-2016
title: Archival Version

description: These data were collected using the National Electronic Injury Surveillance System (NEISS), the primary data system of the United States Consumer Product Safety Commission (CPSC). CPSC began operating NEISS in 1972 to monitor product-related injuries treated in United States hospital emergency departments (EDs). In June 1992, the National Center for Injury Prevention and Control (NCIPC), within the Centers for Disease Control and Prevention, established an interagency agreement with CPSC to begin collecting data on nonfatal firearm-related injuries in order to monitor the incidents and the characteristics of persons with nonfatal firearm-related injuries treated in United States hospital EDs over time. This dataset represents all nonfatal firearm-related injuries (i.e., injuries associated with powder-charged guns) and all nonfatal BB and pellet gun-related injuries reported through NEISS from 1993 through 2016. The cases consist of initial ED visits for treatment of the injuries. Cases were reported even if the patients subsequently died. Secondary visits and transfers from other hospitals were excluded. Information is available on injury diagnosis, firearm type, use of drugs or alcohol, criminal incident, and locale of the incident. Demographic information includes age, sex, and race of the injured person.
description: A weight variable (WT_C) is present in the data.
description: The sample design of NEISS is a stratified, probability sample of all United States hospitals that had at least six beds and provided 24-hour emergency services. There were four hospital-sized strata (defined as very large, large, medium, and small, based on the number of annual ED visits) and one children's hospital stratum. From 1993 through 1996, there were 91 NEISS hospital EDs in the sample. In 1997, the sampling frame was updated so that in 1997 through 1999 the sample included 101 NEISS hospital EDs. In 2000-2001, one NEISS hospital dropped out of the system, so there were 100 NEISS hospital EDs in the sample. In 2002, another hospital dropped out of the system, so there were 99 NEISS hospital EDs in the sampling frame. In 1997, CPSC collected firearm-related cases using the "old" and "new" NEISS hospital samples for a nine-month period. This dataset includes data from the "new" sample. The overlapping "old" sample is not included. Comparisons of weighted estimates based on the "old" and "new" samples indicated a difference of about 1 percent in the overall national estimate using these samples. The characteristics of firearm-related cases from these two overlapping samples were also very similar.
description: Datasets: DS1: Firearm Injury Surveillance Study, 1993-2016
description: United States hospitals providing emergency services.
description: computer-assisted self interview (CASI); self-enumerated questionnaire
DOI: 10.3886/icpsr34705
title: Probationer Compliance With Conditions of Supervision, Virginia, 1994-1997
title: Archival Version

description: The impact of probation on the criminal activities of offenders and the relationship between these activities and technical violations were studied using both self-report and official data regarding 126 offenders on probation in Northern Virginia. Results revealed that probation reduced the self-reported criminal activities of the offenders. Younger males self-reported more criminal activities than did other groups. Offenders were more likely to be involved in criminal activity during the months when they were in school, using illegal drugs, or drinking alcohol heavily. Probation was more effective in reducing the criminal activities of older offenders than of younger offenders. Individuals with mental health counseling as a condition of probation self-reported fewer criminal activities than others. Self-reported criminal activities were also less likely to occur in months when probationers had personal contact with their probation officer or were assigned to the day reporting center.
description: The purpose of this study was to identify factors in probation compliances and violations.
description: Variables in the data files provided information on gender, race, age, offense, district, supervision level, risk, need, probation conditions, probation contacts, noncompliance with probation conditions, criminal activity during community supervision, and other factors.
description: Response Rates: 84.9 percent of offenders who were interviewed shortly after they began probation gave a follow-up interview.
description: One hundred twenty-six offenders were interviewed shortly after they began probation; 107 of them were interviewed approximately 6-8 months after the first interview.
description: Datasets: DS1: Probationer Compliance With Conditions of Supervision, Virginia, 1994-1997
description: Probationers in Virginia. Smallest Geographic Unit: District
description: record abstracts; self-enumerated questionnaireThese data, which are only available to users who have an approved restricted data access request, are a Fast Track Release and distributed as they were received from the data depositor. The files have been zipped for release.
DOI: 10.3886/icpsr38552
title: Monitoring of Federal Criminal Sentences, [United States], 2020-2021
title: Archival Version

description: This collection contains information on federal criminal cases sentenced under the Sentencing Guidelines and Policy Statements of the Sentencing Reform Act of 1984. The data files include all cases received by the United States Sentencing Commission that had sentencing dates between October 1, 2020, and September 30, 2021, and were assessed as constitutional. Constitutionality compares each case's sentencing date, circuit, district, and judge to provide uniformity in reporting the cases. In 1999, the United States Sentencing Commission added more variables from its databases to this collection, so the data are now provided in two files. Several variables iterate to include multiple occurrences of the same event. Part 1, Main Data, includes all noniterating variables plus the highest occurrences of each iterating variable. Part 2, Supplementary Data, includes the remaining iterations.
description: Datasets: DS0: Study-Level Files DS1: Main Data DS2: Supplemental Data
description: All cases received by the United States Sentencing Commission that had sentencing dates between October 1, 2020, and September 30, 2021, and were assessed as constitutional. Smallest Geographic Unit: federal court district
description: Starting with the 1999 data, ICPSR archives MONITORING OF FEDERAL CRIMINAL SENTENCES under a new study number for each year of data. Data for the years 1993-1998 are archived in MONITORING OF FEDERAL CRIMINAL SENTENCES, 1987-1998 (ICPSR 9317).The data producer is the United States Sentencing Commission, Washington, DC.
DOI: 10.3886/icpsr38482.v1
title: A Comprehensive Assessment of Deadly Mass Shootings, 1980-2018, United States
title: Version 1

description: As deadly mass shootings constitute a pressing concern for Americans, the database was created to assess features and trends in all deadly mass shootings in America between 1980 and 2018. In these data, mass shootings encompass all incidents with four or more gunshot fatalities, not including the shooter, within 24 hours. Open source media reports as well as official police and court records were used to code and verify details of mass shooting incidents. The data include information on public deadly mass shooting incidents, as well as all the other deadly mass shootings that occurred over this period (e.g., those that happened in private spaces among family members, and those that occurred in public spaces but were part of another criminal event). In all, the database contains information on 719 incidents that occurred in both public and private spaces between 1980 and 2018.
description: The purpose of this study is to compile a comprehensive database to assess features and trends in all deadly mass shootings in America between 1980 and 2018. In these data, mass shootings encompass all incidents with four or more gunshot fatalities, not including the shooter, within 24 hours.
description: Data was collected from consulting 21 existing databases and reports on homicides, gun violence, and mass shootings. Two additional sources were located for each incident found through these databases. Systematic internet searches were conducted to review journalistic sources. Lastly, a review of official records was conducted, using the Florida State University Law Library, law enforcement agencies, court records, legal databases, shooters' criminal histories, and civil court proceedings.
description: Variable groups include date of shooting, location of shooting, public or private nature of shooting, nature of the crime, shooter demographics, victim counts, victim demographics, number and type of firearms used, shooters' legal and medical history, and news coverage of each incident.
description: Datasets: DS1: A Comprehensive Assessment of Deadly Mass Shootings, 1980-2018, United States
description: Deadly mass shooting events with four or more gunshot fatalities, not including the shooter, within 24 hours. Smallest Geographic Unit: City
description: record abstracts; web scraping
DOI: 10.15468/dl.y2h7ps
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "PublishingOrg is one of (0870a77b-587c-4369-a8ed-bc3d347b8e1c, b8323864-602a-4a7d-9127-bb903054e97d, c8d737e0-2ff8-42e8-b8fc-6b805d26fc5f, ccc2e3ec-98ba-4e74-878d-7dcf0f57baba, 64ee55c9-570a-42af-b7da-3f13c6b4e5a9, 764dc23f-4a2f-4d81-93cb-3cf16077d191, 1928bdf0-f5d2-11dc-8c12-b8a03c50a862, d3978a37-635a-4ae3-bb85-7b4d41bc0b88, 04fd2e13-6881-4e5c-9dd1-8fdd9ab993c1)",
 "TaxonKey is Basidiomycota"
 ]
}

 The dataset includes 11 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022860-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s8dtf6
title: Occurrence Download

description: A dataset containing 421 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Expedición ornitológica en los municipios de Florencia y Morelia, (Caquetá) - BIO Alas, cantos y colores"
 ]
}

 The dataset includes 421 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022861-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14836524
title: National Checklists: Burundi Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.13317348
title: National Checklists: Burundi Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.15468/dl.2fjd4x
title: Occurrence Download

description: A dataset containing 7900 records in GBIF matching the query:
 SELECT "year", GBIF_EEARGCode( 1000, decimalLatitude, decimalLongitude, COALESCE(coordinateUncertaintyInMeters, 1000) ) AS eeaCellCode, classKey, class, familyKey, family, COUNT(*) AS occurrences, MIN(COALESCE(coordinateUncertaintyInMeters, 1000)) AS minCoordinateUncertaintyInMeters, MIN(GBIF_TemporalUncertainty(eventDate)) AS minTemporalUncertainty, IF(ISNULL(classKey), NULL, SUM(COUNT(*)) OVER (PARTITION BY classKey)) AS classCount FROM occurrence WHERE occurrenceStatus = 'PRESENT' AND familyKey = 5666 AND continent = 'EUROPE' AND "year" &gt;= 1900 AND hasCoordinate = TRUE AND familyKey IS NOT NULL AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE') AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE') AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID') AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH') AND ( LOWER(identificationVerificationStatus) NOT IN ( 'unverified', 'unvalidated', 'not validated', 'under validation', 'not able to validate', 'control could not be conclusive due to insufficient knowledge', 'uncertain', 'unconfirmed', 'unconfirmed - not reviewed', 'validation requested' ) OR identificationVerificationStatus IS NULL ) GROUP BY "year", eeaCellCode, classKey, class, familyKey, family ORDER BY "year" DESC, eeaCellCode ASC, familyKey ASC; 

 The dataset's 7900 records were derived from 160 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022833-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14837357
title: National Checklists: Indonesia Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.13316579
title: National Checklists: Indonesia Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.13316477
title: National Checklists: Fiji Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.14836836
title: National Checklists: Fiji Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.13317594
title: National Checklists: Pakistan Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.14837919
title: National Checklists: Pakistan Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.13317549
title: National Checklists: Monaco Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.14837575
title: National Checklists: Monaco Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.15468/dl.8h95v8
title: Occurrence Download

description: A dataset containing 1713 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Pantherophis alleghaniensis (Holbrook, 1836)"
 ]
}

 The dataset includes 1713 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022862-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13317225
title: National Checklists: Kosovo Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.13317226
title: National Checklists 2019: Kosovo Species List

description: Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See https://github.com/diatomsRcool/checklists for details.
A list of species from Kosovo collected using effechecka and geonames polygons
DOI: 10.5281/zenodo.14844969
title: National Checklists: Kosovo Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.13316670
title: National Checklists: Kenya Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.13316671
title: National Checklists 2019: Kenya Species List

description: Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See https://github.com/diatomsRcool/checklists for details.
A list of species from Kenya collected using effechecka and geonames polygons
DOI: 10.5281/zenodo.14837494
title: National Checklists: Kenya Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.13317383
title: National Checklists: Eritrea Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.13317384
title: National Checklists 2019: Eritrea Species List

description: Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See https://github.com/diatomsRcool/checklists for details.
A list of species from Eritrea collected using effechecka and geonames polygons
DOI: 10.5281/zenodo.14836814
title: National Checklists: Eritrea Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.14837499
title: National Checklists: Kyrgyzstan Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.13317493
title: National Checklists: Kyrgyzstan Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.14839987
title: unimpeded: walcdm bao.sdss_dr16+planck_2018_plik_nolens

description: cosmological model:walcdm, dataset:bao.sdss_dr16+planck_2018_plik_nolens
DOI: 10.5281/zenodo.14839988
title: unimpeded: walcdm bao.sdss_dr16+planck_2018_plik_nolens

description: cosmological model:walcdm, dataset:bao.sdss_dr16+planck_2018_plik_nolens
DOI: 10.5281/zenodo.13316589
title: National Checklists: Iraq Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.13316590
title: National Checklists 2019: Iraq Species List

description: Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See https://github.com/diatomsRcool/checklists for details.
A list of species from Iraq collected using effechecka and geonames polygons
DOI: 10.5281/zenodo.14837441
title: National Checklists: Iraq Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.14837749
title: National Checklists: Namibia Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.13316744
title: National Checklists: Namibia Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.14836582
title: National Checklists: Bhutan Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.13317326
title: National Checklists: Bhutan Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.14836737
title: National Checklists: Cuba Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.13316519
title: National Checklists: Cuba Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.13316776
title: National Checklists: Palau Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.14837968
title: National Checklists: Palau Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.13316736
title: National Checklists: Montenegro Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.14837580
title: National Checklists: Montenegro Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.13316445
title: National Checklists: Bolivia Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.13316446
title: National Checklists 2019: Bolivia Species List

description: Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See https://github.com/diatomsRcool/checklists for details.
A list of species from Bolivia collected using effechecka and geonames polygons
DOI: 10.5281/zenodo.14836568
title: National Checklists: Bolivia Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.13316368
title: National Checklists: Afghanistan Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.13316369
title: National Checklists 2019: Afghanistan Species List

description: Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See https://github.com/diatomsRcool/checklists for details.
A list of species from Afghanistan collected using effechecka and geonames polygons
DOI: 10.5281/zenodo.14836390
title: National Checklists: Afghanistan Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.14846026
title: 4DHydro_Results_Tetis_Smap_Po_0p0667deg_daily_SC11_20220402_20221231

description: Modeling results with TETIS software, for Po River with a spatial resolution of 0.0667 degrees, and temporal resolution daily. Experiment SC11. Earth observation Smap.

Includes results for the following variables:



Discharge flux in m-3 s-1

Volumetric soil moisture content in percentage

Total water storage content in kg m-2

Total evapotranspiration flux in kg m-2 s-1

Snow water equivalent in kg m-2


Additional, a .csv file with discharge values at certain points, for each day in cubic meters per second.
DOI: 10.5281/zenodo.14846027
title: 4DHydro_Results_Tetis_Smap_Po_0p0667deg_daily_SC11_20220402_20221231

description: Modeling results with TETIS software, for Po River with a spatial resolution of 0.0667 degrees, and temporal resolution daily. Experiment SC11. Earth observation Smap.

Includes results for the following variables:



Discharge flux in m-3 s-1

Volumetric soil moisture content in percentage

Total water storage content in kg m-2

Total evapotranspiration flux in kg m-2 s-1

Snow water equivalent in kg m-2


Additional, a .csv file with discharge values at certain points, for each day in cubic meters per second.
DOI: 10.5281/zenodo.13317483
title: National Checklists: Kazakhstan Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk
DOI: 10.5281/zenodo.13317484
title: National Checklists 2019: Kazakhstan Species List

description: Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See https://github.com/diatomsRcool/checklists for details.
A list of species from Kazakhstan collected using effechecka and geonames polygons
DOI: 10.5281/zenodo.14837536
title: National Checklists: Kazakhstan Species List

description: Data from: GBIF.org (23 January 2025) GBIF Occurrence Download https://doi.org/10.15468/dl.vd2ajk