cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.b7zdv3
title: Occurrence Download

description: A dataset containing 599998 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Juniperus communis L."
 ]
}

 The dataset includes 599998 records from 1481 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043086-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0176599.10fu
title: SH0176599.10FU

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/sh0176600.10fu
title: SH0176600.10FU

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/sh0176601.10fu
title: SH0176601.10FU

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/sh0176602.10fu
title: SH0176602.10FU

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/sh0176603.10fu
title: SH0176603.10FU

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/sh0176604.10fu
title: SH0176604.10FU

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/sh0176605.10fu
title: SH0176605.10FU

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.qya5zn
title: Occurrence Download

description: A dataset containing 3642 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Spain",
 "Geometry POLYGON((0.4915 40.47988,3.22841 40.47988,3.22841 42.85797,0.4915 42.85797,0.4915 40.47988))",
 "OccurrenceStatus is Present",
 "TaxonKey is Quercus ilex",
 "Year 1985-2026"
 ]
}

 The dataset includes 3642 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001571-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0176606.10fu
title: SH0176606.10FU

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/sh0176607.10fu
title: SH0176607.10FU

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: 10.13144/lil-1033
title: Enquête Emploi dans les DOM - 2005

description: L'enquête Emploi dans les DOM permet d'améliorer la connaissance de l'emploi en prenant en compte les spécificités de la population active (emplois occasionnels et ponctuels, pluri-activité, mobilité), mais également de fournir des informations de base sur des domaines non couverts par les sources administratives (emploi des non salariés, emploi informel, formations des individus,...). L'enquête fait partie du dispositif communautaire européen (Eurostat) d'enquête sur les forces de travail. L'information concerne l'ensemble des personnes de 15 ans et plus, vivant dans les ménages ordinaires de Guadeloupe, Martinique, Guyane et de la Réunion. L’échantillon, renouvelé par tiers tous les ans, est composé d’environ 5 200 logements par DOM. Les ménages sont interrogés trois années de suite.Sont explicitement exclues les personnes des établissements hospitaliers, scolaires et hôteliers vivant en collectivité ainsi que les membres des communautés religieuses. Les principaux items de l'enquête sont relatifs aux caractéristiques socio-démographiques des personnes (sexe, nationalité, état matrimonial, date de naissance, département ou pays de naissance), les liens entre les personnes du ménage, la catégorie et le type de logement, l'occupation principale à la date de l'enquête, l'activité professionnelle (principale et marginale), le statut professionnel, le niveau de qualification, la fonction exercée, la nature et le secteur d'activité de l'établissement, l'ancienneté, le type d'activité, la nature du contrat de travail, la durée effective du travail, les horaires de travail, le salaire mensuel, le chômage, la recherche d'emploi, l'inactivité, la mobilité professionnelle, la formation (date de fin d'étude, diplôme le plus élevé, niveau de formation), la mobilité sociale (situation professionnelle du père à la fin des études de l'enquêté). Le questionnaire de l'enquête Emploi dans les DOM a été bâti à partir du questionnaire de l'enquête rénovée métropolitaine et complété par des questions sur la mobilité et le travail occasionnel et informel qui occupe une place non négligeable dans les DOM.La réglementation européenne prévoit que les enquêtes forces de travail soient complétées, chaque année, par un module thématique variable (dit module ad hoc), de l’ordre de 10 à 20 questions supplémentaires, concernant seulement la vague sortante de l’enquête. En 2005, le titre de ce module est : "Conciliation vie professionnelle / vie familiale".
DOI: 10.13144/lil-1034
title: Enquête Emploi dans les DOM - 2006

description: L'enquête Emploi dans les DOM permet d'améliorer la connaissance de l'emploi en prenant en compte les spécificités de la population active (emplois occasionnels et ponctuels, pluri-activité, mobilité), mais également de fournir des informations de base sur des domaines non couverts par les sources administratives (emploi des non salariés, emploi informel, formations des individus,...). L'enquête fait partie du dispositif communautaire européen (Eurostat) d'enquête sur les forces de travail. L'information concerne l'ensemble des personnes de 15 ans et plus, vivant dans les ménages ordinaires de Guadeloupe, Martinique, Guyane et de la Réunion. L’échantillon, renouvelé par tiers tous les ans, est composé d’environ 5 200 logements par DOM. Les ménages sont interrogés trois années de suite.Sont explicitement exclues les personnes des établissements hospitaliers, scolaires et hôteliers vivant en collectivité ainsi que les membres des communautés religieuses. Les principaux items de l'enquête sont relatifs aux caractéristiques socio-démographiques des personnes (sexe, nationalité, état matrimonial, date de naissance, département ou pays de naissance), les liens entre les personnes du ménage, la catégorie et le type de logement, l'occupation principale à la date de l'enquête, l'activité professionnelle (principale et marginale), le statut professionnel, le niveau de qualification, la fonction exercée, la nature et le secteur d'activité de l'établissement, l'ancienneté, le type d'activité, la nature du contrat de travail, la durée effective du travail, les horaires de travail, le salaire mensuel, le chômage, la recherche d'emploi, l'inactivité, la mobilité professionnelle, la formation (date de fin d'étude, diplôme le plus élevé, niveau de formation), la mobilité sociale (situation professionnelle du père à la fin des études de l'enquêté). Le questionnaire de l'enquête Emploi dans les DOM a été bâti à partir du questionnaire de l'enquête rénovée métropolitaine et complété par des questions sur la mobilité et le travail occasionnel et informel qui occupe une place non négligeable dans les DOM.La réglementation européenne prévoit que les enquêtes forces de travail soient complétées, chaque année, par un module thématique variable (dit module ad hoc), de l'ordre de 10 à 20 questions supplémentaires, concernant seulement la vague sortante de l'enquête. En 2006, le titre de ce module est : "Passage à la retraite".
DOI: 10.15468/dl.yvnj5z
title: Occurrence Download

description: A dataset containing 30978 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is The cnidarians collection (IK) of the Muséum national d'Histoire naturelle (MNHN - Paris)"
 ]
}

 The dataset includes 30978 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015017-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25574/csc2.obs.09977
title: Chandra X-ray Observatory ObsId 09977

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.obs.10263
title: Chandra X-ray Observatory ObsId 10263

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.obs.23242
title: Chandra X-ray Observatory ObsId 23242

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.obs.12944
title: Chandra X-ray Observatory ObsId 12944

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.obs.07051
title: Chandra X-ray Observatory ObsId 07051

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.obs.08686
title: Chandra X-ray Observatory ObsId 08686

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.obs.18643
title: Chandra X-ray Observatory ObsId 18643

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.obs.08750
title: Chandra X-ray Observatory ObsId 08750

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.obs.09992
title: Chandra X-ray Observatory ObsId 09992

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.obs.19726
title: Chandra X-ray Observatory ObsId 19726

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.obs.24966
title: Chandra X-ray Observatory ObsId 24966

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.obs.08704
title: Chandra X-ray Observatory ObsId 08704

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.obs.10020
title: Chandra X-ray Observatory ObsId 10020

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.obs.20075
title: Chandra X-ray Observatory ObsId 20075

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.obs.18647
title: Chandra X-ray Observatory ObsId 18647

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.obs.18653
title: Chandra X-ray Observatory ObsId 18653

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.obs.21154
title: Chandra X-ray Observatory ObsId 21154

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.obs.02289
title: Chandra X-ray Observatory ObsId 02289

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.obs.06260
title: Chandra X-ray Observatory ObsId 06260

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.obs.08687
title: Chandra X-ray Observatory ObsId 08687

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.obs.12453
title: Chandra X-ray Observatory ObsId 12453

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".