cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25574/csc2.stk.acisfj1405276m612215_001
title: Chandra X-ray Observatory Stack acisfJ1405276m612215_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj1417206p265118_001
title: Chandra X-ray Observatory Stack acisfJ1417206p265118_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj1406501p341121_001
title: Chandra X-ray Observatory Stack acisfJ1406501p341121_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj1411556p341514_001
title: Chandra X-ray Observatory Stack acisfJ1411556p341514_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj1417307p073331_001
title: Chandra X-ray Observatory Stack acisfJ1417307p073331_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.15468/dl.hy2enf
title: Occurrence Download

description: A dataset containing 49325 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is one of (Canada, Mexico, United States of America)",
 "EventDate is greater than or equal to 2025-01-09",
 "EventDate is less than or equal to 2025-02-08",
 {
 "not" : {
 "Issue" : [
 "is one of (Basis of record invalid, Coordinate reprojection failed, Coordinate reprojection suspicious, Coordinate precision invalid, Coordinate uncertainty meters invalid, Country mismatch, Country invalid, Geodetic datum invalid, Presumed swapped coordinate, Presumed negated longitude, Presumed negated latitude, Country coordinate mismatch)"
 ]
 }
 }
 ]
}

 The dataset includes 49325 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010761-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25574/csc2.stk.acisfj1258490m014432_001
title: Chandra X-ray Observatory Stack acisfJ1258490m014432_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj1412388m652046_001
title: Chandra X-ray Observatory Stack acisfJ1412388m652046_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj1407358p442858_001
title: Chandra X-ray Observatory Stack acisfJ1407358p442858_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj1348531p270400_001
title: Chandra X-ray Observatory Stack acisfJ1348531p270400_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj1354412p161439_001
title: Chandra X-ray Observatory Stack acisfJ1354412p161439_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj1359228p513743_001
title: Chandra X-ray Observatory Stack acisfJ1359228p513743_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj1259407p312125_001
title: Chandra X-ray Observatory Stack acisfJ1259407p312125_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.25574/csc2.stk.acisfj1302257m325847_001
title: Chandra X-ray Observatory Stack acisfJ1302257m325847_001

description: CSC uses combined (i.e. overlapping) Chandra observations for detecting X-ray sources. This allows the catalog to include significantly fainter sources than CSC 1.1. The set of overlapping observations that have been combined in this way is known as a "stack".
DOI: 10.15468/dl.25wqfp
title: Occurrence Download

description: A dataset containing 33396061 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is Colombia"
 ]
}

 The dataset includes 33396061 records from 4624 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010757-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15187989
title: datos3.csv

description: prueba comunidad 3
DOI: 10.5281/zenodo.15187990
title: datos3.csv

description: prueba comunidad 3
DOI: 10.13144/lil-1268
title: Enquête Loyers et charges - 2002

description: L'objectif de l'enquête « Loyers et charges » est de mesurer l'évolution des loyers à qualité constante, et de l'intégrer à l'indice des prix à la consommation. De ce fait, cette enquête recueille plusieurs types d'informations : caractéristiques du bâtiment dans lequel se situe le logement (présence d'un ascenseur, etc.) ; caractéristiques du logement (surface, nombre de pièces, confort sanitaire, etc.) ; modalités de location et de paiement du loyer (type de bail, périodicité de révision, etc.) ; aides financières perçues (type et montant) ; loyer principal ; charges locatives (nature et montants) ; loyers des annexes ; composition du ménage occupant le logement (date d'arrivée dans le logement, sexe et date de naissance des occupants, etc.).
DOI: 10.13144/lil-1269
title: Enquête Loyers et charges - 2003

description: L'objectif de l'enquête « Loyers et charges » est de mesurer l'évolution des loyers à qualité constante, et de l'intégrer à l'indice des prix à la consommation. De ce fait, cette enquête recueille plusieurs types d'informations : caractéristiques du bâtiment dans lequel se situe le logement (présence d'un ascenseur, etc.) ; caractéristiques du logement (surface, nombre de pièces, confort sanitaire, etc.) ; modalités de location et de paiement du loyer (type de bail, périodicité de révision, etc.) ; aides financières perçues (type et montant) ; loyer principal ; charges locatives (nature et montants) ; loyers des annexes ; composition du ménage occupant le logement (date d'arrivée dans le logement, sexe et date de naissance des occupants, etc.).
DOI: 10.13144/lil-1271
title: Enquête Loyers et charges - 2005

description: L'objectif de l'enquête « Loyers et charges » est de mesurer l'évolution des loyers à qualité constante, et de l'intégrer à l'indice des prix à la consommation. De ce fait, cette enquête recueille plusieurs types d'informations : caractéristiques du bâtiment dans lequel se situe le logement (présence d'un ascenseur, etc.) ; caractéristiques du logement (surface, nombre de pièces, confort sanitaire, etc.) ; modalités de location et de paiement du loyer (type de bail, périodicité de révision, etc.) ; aides financières perçues (type et montant) ; loyer principal ; charges locatives (nature et montants) ; loyers des annexes ; composition du ménage occupant le logement (date d'arrivée dans le logement, sexe et date de naissance des occupants, etc.).
DOI: 10.15468/dl.crvfn2
title: Occurrence Download

description: A dataset containing 149 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dipturus oxyrinchus (Linnaeus, 1758)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen, Material sample)"
 ]
 }
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 149 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004354-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13144/lil-1272
title: Enquête Loyers et charges - 2006

description: L'objectif de l'enquête « Loyers et charges » est de mesurer l'évolution des loyers à qualité constante, et de l'intégrer à l'indice des prix à la consommation. De ce fait, cette enquête recueille plusieurs types d'informations : caractéristiques du bâtiment dans lequel se situe le logement (présence d'un ascenseur, etc.) ; caractéristiques du logement (surface, nombre de pièces, confort sanitaire, etc.) ; modalités de location et de paiement du loyer (type de bail, périodicité de révision, etc.) ; aides financières perçues (type et montant) ; loyer principal ; charges locatives (nature et montants) ; loyers des annexes ; composition du ménage occupant le logement (date d'arrivée dans le logement, sexe et date de naissance des occupants, etc.).
DOI: 10.15156/bio/sh0177159.10fu
title: SH0177159.10FU

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/sh0177160.10fu
title: SH0177160.10FU

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/sh0177161.10fu
title: SH0177161.10FU

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.wwjaj4
title: Occurrence Download

description: A dataset containing 417 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Inventaires Aéro Biodiversité - DOL - Aéroport de Deauville-Inventaires Aéro Biodiversité - DOL - Observations opportunistes"
 ]
}

 The dataset includes 417 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001591-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0177162.10fu
title: SH0177162.10FU

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/sh0177163.10fu
title: SH0177163.10FU

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: 10.7910/dvn/s0klpg
title: Community Resilience Estimates (CRE)

description: The Community Resilience Estimates (CRE) tracks the social vulnerability of every single neighborhood in the U.S. to the impact of local disasters. It measures the capacity of individuals and households to absorb, endure, and recover from the health, social, and economic impacts of a disaster such as a hurricane or pandemic. Small area resilience estimates are used to identify communities where resources and information may effectively mitigate the impact of disasters. These estimates can help facilitate disaster preparedness and aid stakeholders and public health officials model differential impacts to develop plans to reduce a disaster’s potential effects.
description: <b>Intended Use</b>Local planners, policy makers, public health officials, and community stakeholders can use the estimates as one tool to help assess the potential resiliency of communities and plan mitigation and recovery strategies.<br>
DOI: 10.15156/bio/sh0177164.10fu
title: SH0177164.10FU

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/sh0177165.10fu
title: SH0177165.10FU

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/sh0177166.10fu
title: SH0177166.10FU

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/sh0177167.10fu
title: SH0177167.10FU

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/sh0177168.10fu
title: SH0177168.10FU

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.