cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0201268.10fu
title: SH0201268.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0201269.10fu
title: SH0201269.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0201270.10fu
title: SH0201270.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0201271.10fu
title: SH0201271.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.fjn2hz
title: Occurrence Download

description: A dataset containing 2779 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Blautia Liu et al., 2008"
 ]
}

 The dataset includes 2779 records from 309 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019955-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25345/c5dz03d9v
title: MassIVE MSV000098335 - A novel factor integrating transcription and repression of surface antigen genes in African trypanosomes
title: Mass spectrometry data and proteomic results relating to the manuscript: A novel factor integrating transcription and repression of surface antigen genes in African trypanosomes
DOI: 10.15468/dl.q9peeh
title: Occurrence Download

description: A dataset containing 6460 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "TaxonKey is Palaemon elegans Rathke, 1837",
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 6460 records from 153 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017015-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mjvba3
title: Occurrence Download

description: A dataset containing 151 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is Asia",
 "Country is Sri Lanka",
 "TaxonKey is Synoicus chinensis (Linnaeus, 1766)",
 "Year 2000-2025"
 ]
}

 The dataset includes 151 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002326-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g5pn5j
title: Occurrence Download

description: A dataset containing 144 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is Asia",
 "Country is Sri Lanka",
 "TaxonKey is Perdicula asiatica (Latham, 1790)",
 "Year 2000-2025"
 ]
}

 The dataset includes 144 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002327-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2j3wf4
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Bacidia gigantensis Lendemer, McCune & McMullin"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002328-250214102907787/datasets/export for details.
DOI: 10.15468/dl.qadwwp
title: Occurrence Download

description: A dataset containing 800515 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Material sample, Material citation, Specimen, Living Specimen, Occurrence evidence)",
 "Geometry POLYGON((67.67476 41.79183,66.24216 40.29261,67.44154 37.49405,71.23958 34.12912,74.67114 31.16399,77.63628 28.86518,83.2667 26.06662,88.16417 24.66735,94.49424 24.1676,99.09186 25.93336,101.49062 28.53202,100.39119 31.49715,98.29228 31.76368,94.16108 31.16399,86.93148 30.46435,83.30002 32.16347,79.56861 35.56172,76.83669 40.0594,71.73932 42.125,67.67476 41.79183))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 800515 records from 399 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002325-250214102907787/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e115006
title: National Neighborhood Data Archive (NaNDA): Crimes by County, United States, 2002-2014

description: This dataset contains county-level totals for the years 2002-2014 for eight types of crime: murder, rape, robbery, aggravated assault, burglary, larceny, motor vehicle theft, and arson. These crimes are classed as Part I criminal offenses by the United States Federal Bureau of Investigations (FBI) in their Uniform Crime Reporting (UCR) program. Each record in the dataset represents the total of each type of criminal offense reported in (or, in the case of missing data, attributed to) the county in a given year.
description: All counties in the United States, excluding US island territories. Smallest Geographic Unit: county
DOI: 10.3886/icpsr23780.v1
title: Uniform Crime Reporting Program Data [United States]: County-Level Detailed Arrest and Offense Data, 2006
title: Version 1

description: This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and counts of arrests for Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).
description: Datasets: DS0: Study-Level Files DS1: Arrests, All Ages DS2: Arrests, Adult DS3: Arrests, Juveniles DS4: Crimes Reported DS5: Allocated Statewide Data for Arrests, All Ages DS6: Allocated Statewide Data for Arrests, Adults DS7: Allocated Statewide Data for Arrests, Juveniles DS8: Allocated Statewide Data for Crimes Reported
description: County law enforcement agencies in the United States. Smallest Geographic Unit: county
description: self-enumerated questionnaireTwo major changes to the Uniform Crime Reports (UCR) county-level files were implemented beginning with the 1994 data. A new imputation algorithm to adjust for incomplete reporting by individual law enforcement jurisdictions was adopted. Within each county, data from agencies reporting 3 to 11 months of information were weighted to yield 12-month equivalents. Data for agencies reporting less than three months of data were replaced with data estimated by rates calculated from agencies reporting 12 months of data located in the agency's geographic stratum within its state. Secondly, a new Coverage Indicator was created to provide users with a diagnostic measure of aggregated data quality in a particular county. Data from agencies reporting only statewide figures were allocated to the counties in the state in proportion to each county's share of the state population.In the arrest files (Parts 1-3 and 5-7), data were estimated for agencies reporting zero months based on the procedures mentioned above. However, due to the structure of the data received from the FBI, estimations could not be produced for agencies reporting zero months in the crimes reported files (Parts 4 and 8). Offense data for agencies reporting one or two months are estimated using the above procedures. Users are encouraged to refer to the codebook for more information.No arrest data were provided for Florida. Limited arrest data were available for Illinois and Kentucky. Limited offense data were available for Alaska, Illinois, Mississippi, Montana, North Dakota, and South Dakota.UCR program staff at the Federal Bureau of Investigation (FBI) were consulted in developing the new adjustment procedures. However, these UCR county-level files are not official FBI UCR releases and are being provided for research purposes only. Users with questions regarding these UCR county-level data files can contact the National Archive of Criminal Justice Data at ICPSR.
DOI: 10.3886/icpsr30763.v2
title: Uniform Crime Reporting Program Data: County-Level Detailed Arrest and Offense Data, United States, 2009
title: Version 2

description: This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and counts of arrests for Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).
description: Datasets: DS0: Study-Level Files DS1: Arrests, All Ages DS2: Arrests, Adult DS3: Arrests, Juveniles DS4: Crimes Reported DS5: Allocated Statewide Data for Arrests, All Ages DS6: Allocated Statewide Data for Arrests, Adults DS7: Allocated Statewide Data for Arrests, Juveniles DS8: Allocated Statewide Data for Crimes Reported
description: County law enforcement agencies in the United States. Smallest Geographic Unit: county
description: self-enumerated questionnaireTwo major changes to the Uniform Crime Reports (UCR) county-level files were implemented beginning with the 1994 data. A new imputation algorithm to adjust for incomplete reporting by individual law enforcement jurisdictions was adopted. Within each county, data from agencies reporting 3 to 11 months of information were weighted to yield 12-month equivalents. Data for agencies reporting less than three months of data were replaced with data estimated by rates calculated from agencies reporting 12 months of data located in the agency's geographic stratum within its state. Secondly, a new Coverage Indicator was created to provide users with a diagnostic measure of aggregated data quality in a particular county. Data from agencies reporting only statewide figures were allocated to the counties in the state in proportion to each county's share of the state population.In the arrest files (Parts 1-3 and 5-7), data were estimated for agencies reporting zero months based on the procedures mentioned above. However, due to the structure of the data received from the Federal Bureau of Investigation (FBI), estimations could not be produced for agencies reporting zero months in the crimes reported files (Parts 4 and 8). Offense data for agencies reporting one or two months are estimated using the above procedures. Users are encouraged to refer to the codebook for more information.No arrest data were provided for Florida. Limited arrest data were available for Illinois. Limited offense data were available for Alaska, Illinois, Mississippi, Montana, North Dakota, and South Dakota.UCR program staff at the Federal Bureau of Investigation (FBI) were consulted in developing the new adjustment procedures. However, these UCR county-level files are not official FBI UCR releases and are being provided for research purposes only. Users with questions regarding these UCR county-level data files can contact the National Archive of Criminal Justice Data at ICPSR.
DOI: 10.3886/icpsr33523.v2
title: Uniform Crime Reporting Program Data: County-Level Detailed Arrest and Offense Data, 2010
title: Version 2

description: This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and counts of arrests for Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).
description: Datasets: 
 
 DS0: Study-Level Files 
 DS1: Arrests, All Ages 
 DS2: Arrests, Adult 
 DS3: Arrests, Juveniles 
 DS4: Crimes Reported 
 DS5: Allocated Statewide Data for Arrests, All Ages 
 DS6: Allocated Statewide Data for Arrests, Adults 
 DS7: Allocated Statewide Data for Arrests, Juveniles 
 DS8: Allocated Statewide Data for Crimes Reported
description: Uniform Crime Reporting Program Data Series
description: self-enumerated questionnaire 
Two major changes to the Uniform Crime Reports (UCR) county-level files were implemented beginning with the 1994 data. A new imputation algorithm to adjust for incomplete reporting by individual law enforcement jurisdictions was adopted. Within each county, data from agencies reporting 3 to 11 months of information were weighted to yield 12-month equivalents. Data for agencies reporting less than three months of data were replaced with data estimated by rates calculated from agencies reporting 12 months of data located in the agency's geographic stratum within its state. Secondly, a new Coverage Indicator was created to provide users with a diagnostic measure of aggregated data quality in a particular county. Data from agencies reporting only statewide figures were allocated to the counties in the state in proportion to each county's share of the state population.
In the arrest files (Parts 1-3 and 5-7), data were estimated for agencies reporting zero months based on the procedures mentioned above. However, due to the structure of the data received from the Federal Bureau of Investigation (FBI), estimations could not be produced for agencies reporting zero months in the crimes reported files (Parts 4 and 8). Offense data for agencies reporting one or two months are estimated using the above procedures. Users are encouraged to refer to the codebook for more information.
No arrest data were provided for Florida. Limited arrest data were available for Illinois. Limited offense data were available for Alaska, Kentucky, Mississippi, Montana, and South Dakota.
UCR program staff at the Federal Bureau of Investigation (FBI) were consulted in developing the new adjustment procedures. However, these UCR county-level files are not official FBI UCR releases and are being provided for research purposes only. Users with questions regarding these UCR county-level data files can contact the National Archive of Criminal Justice Data at ICPSR.
description: County law enforcement agencies in the United States. Smallest Geographic Unit: county
DOI: 10.3886/icpsr34582.v2
title: Uniform Crime Reporting Program Data: County-Level Detailed Arrest and Offense Data, United States, 2011
title: Version 2

description: This data collection contains county-level counts of arrests and offenses for Part I offenses (murder, rape, robbery, aggravated assault, burglary, larceny, auto theft, and arson) and counts of arrests for Part II offenses (forgery, fraud, embezzlement, vandalism, weapons violations, sex offenses, drug and alcohol abuse violations, gambling, vagrancy, curfew violations, and runaways).
description: Datasets: DS0: Study-Level Files DS1: Arrests, All Ages DS2: Arrests, Adult DS3: Arrests, Juveniles DS4: Crimes Reported DS5: Allocated Statewide Data for Arrests, All Ages DS6: Allocated Statewide Data for Arrests, Adults DS7: Allocated Statewide Data for Arrests, Juveniles DS8: Allocated Statewide Data for Crimes Reported
description: County law enforcement agencies in the United States. Smallest Geographic Unit: county
description: self-enumerated questionnaireTwo major changes to the Uniform Crime Reports (UCR) county-level files were implemented beginning with the 1994 data. A new imputation algorithm to adjust for incomplete reporting by individual law enforcement jurisdictions was adopted. Within each county, data from agencies reporting 3 to 11 months of information were weighted to yield 12-month equivalents. Data for agencies reporting less than three months of data were replaced with data estimated by rates calculated from agencies reporting 12 months of data located in the agency's geographic stratum within its state. Secondly, a new Coverage Indicator was created to provide users with a diagnostic measure of aggregated data quality in a particular county. Data from agencies reporting only statewide figures were allocated to the counties in the state in proportion to each county's share of the state population.In the arrest files (Parts 1-3 and 5-7), data were estimated for agencies reporting zero months based on the procedures mentioned above. However, due to the structure of the data received from the Federal Bureau of Investigation (FBI), estimations could not be produced for agencies reporting zero months in the crimes reported files (Parts 4 and 8). Offense data for agencies reporting one or two months are estimated using the above procedures. Users are encouraged to refer to the codebook for more information.No arrest data were provided for Alabama, Florida, or Illinois. Limited crimes reported data were available for Alaska.UCR program staff at the Federal Bureau of Investigation (FBI) were consulted in developing the new adjustment procedures. However, these UCR county-level files are not official FBI UCR releases and are being provided for research purposes only. Users with questions regarding these UCR county-level data files can contact the National Archive of Criminal Justice Data at ICPSR.