cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.iifd0q
title: Occurrence Download

description: A dataset containing 31883 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Trema Lour."
 ]
}

 The dataset includes 31883 records from 489 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009171-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13144/lil-0186
title: Trajectoires des demandeurs d'emploi et marché local du travail - 1996-1998

description: Cette enquête s'inscrit dans la perspective de l'enquête "suivi des chômeurs" réalisée par l'Insee en 1986-1988. L'enquête porte sur une population d'entrants en chômage au cours du deuxième trimestre 1995 dans huit zones d'emploi réparties dans trois régions (Ile-de-France : Cergy-Pontoise, Mantes-la-Jolie et Poissy-les-Mureaux ; Nord-Pas-de-Calais : Roubaix-Tourcoing et Lens ; Provence-Alpes-Côte-d'Azur : Aix-en-Provence, Etang de Berre et Marseille-Aubagne). Dans chaque zone d'emploi un échantillon de 1000 à 1500 individus, représentatif du flux des " nouveaux entrants en chômage " a été constitué. Une première interrogation a été effectuée au premier trimestre 1996, sur la base d'un questionnaire, par un enquêteur au domicile. Les répondants ont ensuite été suivis selon la technique des panels, et réinterrogés à deux reprises (trois dans les zones du nord), à une année d'intervalle environ, cette fois par téléphone, selon un questionnaire plus court que le questionnaire initial. Un premier calendrier permet de reconstituer le passé professionnel des individus interrogés depuis la fin de la scolarité initiale. Cette reconstruction est synthétique jusqu'en 1992 et exhaustive entre 1992 et le deuxième trimestre 1995 (période de l'entrée au chômage de l'ensemble de la cohorte). Cependant, les situations décrites en détail dans le premier questionnaire ne portent que sur un nombre réduit d'événements considérés par hypothèse comme significatifs pour résumer le passé professionnel. Un deuxième calendrier reproposé à chaque interrogation permet de reconstituer mensuellement les situations rencontrées par chaque individu (emploi, chômage, études, formation, inactivité) depuis l'entrée en chômage en 1995. Chaque situation repérée est ensuite décrite en détail par le biais d'une batterie de questions. D'autres questions portent sur l'environnement social et familial des interviewés, les revenus, la recherche d'emploi...
DOI: 10.13144/lil-0188
title: Revenus fiscaux localisés des ménages - 2000

description: Les chiffres "Revenus fiscaux des ménages" ont été établis à partir des fichiers exhaustifs des déclarations de revenus des personnes physiques et de la taxe d'habitation fournis à l'Insee par la Direction Générale des Impôts. L'INSEE procède au rapprochement de ces fichiers afin d'estimer le revenu fiscal à des niveaux géographiques finement localisés, tout en préservant la confidentialité des données. Les données sont exprimées suivant trois niveaux d'observation : ménage, personne et unité de consommation. Elles se présentent sous la forme d'indicateurs de distribution et d'indicateurs de structure qui permettent deux types d'analyses : une analyse de la distribution des revenus et une analyse de la structure des revenus. L'unité utilisée pour toutes les données monétaires est l'euro.
DOI: 10.13144/lil-0189
title: Revenus fiscaux localisés des ménages - 2001

description: Les chiffres "Revenus fiscaux des ménages" ont été établis à partir des fichiers exhaustifs des déclarations de revenus des personnes physiques et de la taxe d'habitation fournis à l'Insee par la Direction Générale des Impôts. L'INSEE procède au rapprochement de ces fichiers afin d'estimer le revenu fiscal à des niveaux géographiques finement localisés, tout en préservant la confidentialité des données. Les données sont exprimées suivant trois niveaux d'observation : ménage, personne et unité de consommation. Elles se présentent sous la forme d'indicateurs de distribution et d'indicateurs de structure qui permettent deux types d'analyses : une analyse de la distribution des revenus et une analyse de la structure des revenus. L'unité utilisée pour toutes les données monétaires est l'euro.
DOI: 10.15468/dl.aa6us9
title: Occurrence Download

description: A dataset containing 15064 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Belone belone (Linnaeus, 1760)",
 "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 15064 records from 89 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004286-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13144/lil-0193
title: Impôt sur le revenu dans les communes de France métropolitaine - 1998

description: Présentation du nombre de foyers fiscaux et du revenu net moyen des foyers fiscaux de France métropolitaine au niveau communal. Les données datées d'une année n correspondent à la taxation des revenus de l'année n, à la date du 31 décembre n+1. Les contribuables ayant leur domicile fiscal en France métropolitaine au niveau communal sont : - les personnes qui ont leur foyer ou leur lieu de séjour principal dans une commune française, - celles qui exercent en France le centre de leurs intérêts économiques, - les agents de l'Etat qui exercent leurs fonctions dans un pays étranger où ils ne sont pas soumis à un impôt personnel sur leurs revenus.
DOI: 10.15468/dl.5dghpd
title: Occurrence Download

description: A dataset containing 2534 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Utricularia ×neglecta Lehm."
 ]
}

 The dataset includes 2534 records from 109 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004287-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4dn4kk
title: Occurrence Download

description: A dataset containing 359 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Occurrence evidence)",
 "Continent is North America",
 "TaxonKey is Erythranthe dentata"
 ]
}

 The dataset includes 359 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041025-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17258940
title: Open Science Access Advantage for the Platform HAL.archives-ouvertes.fr

description: This dataset contains the value of the Open Science Access Advantage indicator calculated for all the ressources accessed on the French Open Science platform HAL.archives-ouvertes.fr, between September 2023 et August 2024.

The data have been obtained through a partnership with the platform which provided us all the logs of its server for the period above. Though a parnership with IPinfo.io, we categorized these access geographically and by economic sector.

The Open Science Access Advantage compares the ratio of accesses directed to OS resources over the total number of views, to the ratio of open publications among the relevant resources. This indicator has been computed for the entire HAL platform, for a single discipline (considering all publications associated with it), a single country or sector (considering all the publications accessed from it), as well as for any combination of thereof.

The indicator is operationalized through a relatively straightforward metric comparing the ratio to which OS resources are accessed to the ratio of their availability. More precisely, the metric is calculated as follows



Where:





SO (stock open) is the number OS resources accessed in a given disciplinary, sectoral and geographical combination.




SC (stock closed) is the number of non-OS resources accessed in the same combination.




AO (access open) is the number of views collected by OS resources




AC (access closed) is the number of views collected by non-OS resources



Basically, the metrics compare the ratio of SO resources (the part of SO over the total of relevant resources) to the ratio of the accesses directed to SO resources (over the total of accesses). Since both the ratios vary between zero and one, their difference varies between one (when most of the available resources are closed and yet most of the accesses are directed to few open ones) and minus one and is minimal (when most of the available resources are open and yet most of the accesses are directed to the few close ones).

As both ratios can be expressed as percentages, the Open Access Advantage indicator can also be expressed as a percentage which is the larger the higher is the the probability of open resources to be consulted compared to closed ones.
DOI: 10.5281/zenodo.17258941
title: Open Science Access Advantage for the Platform HAL.archives-ouvertes.fr

description: This dataset contains the value of the Open Science Access Advantage indicator calculated for all the ressources accessed on the French Open Science platform HAL.archives-ouvertes.fr, between September 2023 et August 2024.

The data have been obtained through a partnership with the platform which provided us all the logs of its server for the period above. Though a parnership with IPinfo.io, we categorized these access geographically and by economic sector.

The Open Science Access Advantage compares the ratio of accesses directed to OS resources over the total number of views, to the ratio of open publications among the relevant resources. This indicator has been computed for the entire HAL platform, for a single discipline (considering all publications associated with it), a single country or sector (considering all the publications accessed from it), as well as for any combination of thereof.

The indicator is operationalized through a relatively straightforward metric comparing the ratio to which OS resources are accessed to the ratio of their availability. More precisely, the metric is calculated as follows



Where:





SO (stock open) is the number OS resources accessed in a given disciplinary, sectoral and geographical combination.




SC (stock closed) is the number of non-OS resources accessed in the same combination.




AO (access open) is the number of views collected by OS resources




AC (access closed) is the number of views collected by non-OS resources



Basically, the metrics compare the ratio of SO resources (the part of SO over the total of relevant resources) to the ratio of the accesses directed to SO resources (over the total of accesses). Since both the ratios vary between zero and one, their difference varies between one (when most of the available resources are closed and yet most of the accesses are directed to few open ones) and minus one and is minimal (when most of the available resources are open and yet most of the accesses are directed to the few close ones).

As both ratios can be expressed as percentages, the Open Access Advantage indicator can also be expressed as a percentage which is the larger the higher is the the probability of open resources to be consulted compared to closed ones.
DOI: 10.15156/bio/sh0174670.10fu
title: SH0174670.10FU

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/sh0174671.10fu
title: SH0174671.10FU

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/sh0174672.10fu
title: SH0174672.10FU

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/sh0174673.10fu
title: SH0174673.10FU

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/sh0174674.10fu
title: SH0174674.10FU

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.b3ggtv
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((75.201014 21.60601, 75.125478 21.600434, 75.05181899999999 21.583843, 74.981866 21.55665, 74.91735300000001 21.519529, 74.859876 21.473403, 74.81085299999999 21.419414, 74.771489 21.3589, 74.742744 21.293357, 74.725313 21.224405, 74.719612 21.153744, 74.725764 21.083117, 74.743601 21.01426, 74.77267000000001 20.948866, 74.812242 20.888539, 74.86133599999999 20.834758, 74.918741 20.78884, 74.983047 20.751907, 75.052677 20.724862, 75.125929 20.708367, 75.201014 20.702824, 75.276099 20.708367, 75.349351 20.724862, 75.418981 20.751907, 75.483287 20.78884, 75.54069200000001 20.834758, 75.589786 20.888539, 75.629358 20.948866, 75.658427 21.01426, 75.676264 21.083117, 75.682416 21.153744, 75.676715 21.224405, 75.659284 21.293357, 75.630539 21.3589, 75.59117500000001 21.419414, 75.542152 21.473403, 75.484675 21.519529, 75.420162 21.55665, 75.35020900000001 21.583843, 75.27655 21.600434, 75.201014 21.60601))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001519-260108223611665/datasets/export for details.
DOI: 10.15156/bio/sh0174675.10fu
title: SH0174675.10FU

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/sh0174676.10fu
title: SH0174676.10FU

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/sh0174677.10fu
title: SH0174677.10FU

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/sh0174678.10fu
title: SH0174678.10FU

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.