cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1408231.10fu
title: SH1408231.10FU

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/sh1408235.10fu
title: SH1408235.10FU

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/sh1408237.10fu
title: SH1408237.10FU

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/sh1408239.10fu
title: SH1408239.10FU

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/sh1408243.10fu
title: SH1408243.10FU

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/sh1408244.10fu
title: SH1408244.10FU

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/sh1408248.10fu
title: SH1408248.10FU

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/sh1408249.10fu
title: SH1408249.10FU

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/sh1408251.10fu
title: SH1408251.10FU

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.jbxnvi
title: Occurrence Download

description: A dataset containing 7326574 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Suliformes"
 ]
}

 The dataset includes 7326574 records from 839 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015484-171219132708484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jnkf9t
title: Occurrence Download

description: A dataset containing 521415 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sphenisciformes"
 ]
}

 The dataset includes 521415 records from 226 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015303-171219132708484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.lst0lp
title: Occurrence Download

description: A dataset containing 1895221 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Procellariiformes"
 ]
}

 The dataset includes 1895221 records from 423 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015305-171219132708484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.c5owow
title: Occurrence Download

description: A dataset containing 159 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Achimenes patens Benth."
 ]
}

 The dataset includes 159 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007409-180730143533302/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.22638229
title: The effect of emodin on neuroblastoma SH-SY5Y cells

description: The effect of emodin on neuroblastoma SH-SY5Y cells.
DOI: 10.6084/m9.figshare.22638229.v4
title: The effect of emodin on neuroblastoma SH-SY5Y cells

description: The effect of emodin on neuroblastoma SH-SY5Y cells.
DOI: 10.6084/m9.figshare.22638229.v3
title: The effect of emodin on neuroblastoma SH-SY5Y cells

description: The effect of emodin on neuroblastoma SH-SY5Y cells.
DOI: 10.15468/dl.6pskxa
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "Year is 1970",
 "Geometry POLYGON((-174.32144 50.94112,-129.44572 50.94112,-129.44572 73.00755,-174.32144 73.00755,-174.32144 50.94112))",
 "TaxonKey is Polix coloradella (Walsingham, 1888)",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011910-190320150433242/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57745/9xfl4b
title: Data Martin et al 2025.tab

description: Preventing effect of plant extracts and omega-3 on age-related cognitive decline in male mice
DOI: 10.57745/sdf46g
title: Data Martin et al 2025 RNAseq.tab

description: :unav
DOI: 10.57745/lgolln
title: Data Martin et al 2025.tab

description: :unav
DOI: 10.57745/iaekvl
title: Effet d’une combinaison d’extraits végétaux et d’oméga-3 sur les processus biologiques impliqués dans le déclin cognitif lié à l’âge

description: Jeu de données PSPC Silver Brain Food : étude pré clinique sur modèle de souris âgées : données de comportements, de marqueurs biologiques dans le cerveau et de compositon de microbiote intestinale
DOI: 10.15468/dl.azmthk
title: Occurrence Download

description: A dataset containing 167 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "Country is South Africa",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Tilapia sparrmanii",
 "Year 2022-2026"
 ]
}

 The dataset includes 167 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000178-260225131425191/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.11583/dtu.31250992
title: Data for: 'Effects of Crosslinker Role Reversal on the Properties of Hydrosilylation-Cured Silicone Elastomers'

description: Dataset for research article. The study investigates the role of microstructure and functionality of crosslinkers in governing network formation and mechanics in hydrosilylation-cured silicone elastomers. The dataset includes: NMR, DSC, TGA, Tensile testing, rheology, and swelling data.
DOI: 10.11583/dtu.31250992.v1
title: Data for: 'Effects of Crosslinker Role Reversal on the Properties of Hydrosilylation-Cured Silicone Elastomers'

description: Dataset for research article. The study investigates the role of microstructure and functionality of crosslinkers in governing network formation and mechanics in hydrosilylation-cured silicone elastomers. The dataset includes: NMR, DSC, TGA, Tensile testing, rheology, and swelling data.
DOI: 10.15468/dl.88str6
title: Occurrence Download

description: A dataset containing 70715934 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "MediaType is Image"
 ]
}

 The dataset includes 70715934 records from 1553 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000118-260225131425191/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4u6u2w
title: Occurrence Download

description: A dataset containing 10703 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lutra lutra",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 2000",
 "Year is less than or equal to 2025",
 "Geometry POLYGON((\n\n 5.87 47.27,\n\n 15.03 47.27,\n\n 15.03 55.06,\n\n 5.87 55.06,\n\n 5.87 47.27\n\n ))"
 ]
}

 The dataset includes 10703 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000179-260225131425191/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9jj42c
title: Occurrence Download

description: A dataset containing 140 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Kobresia humilis",
 "Year is less than or equal to 2000",
 "Year is greater than or equal to 1970",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 140 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000180-260225131425191/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.euhfqt
title: Occurrence Download

description: A dataset containing 1416 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "Country is South Africa",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Rhinocerotidae",
 "Year 2020-2026"
 ]
}

 The dataset includes 1416 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000181-260225131425191/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.przahr
title: Occurrence Download

description: A dataset containing 409 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhinolophus borneensis"
 ]
}

 The dataset includes 409 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000182-260225131425191/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.htravg
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Bucerotiformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((-130 80,-120 80,-120 90,-130 90,-130 80))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018787-251009101135966/datasets/export for details.
DOI: 10.5281/zenodo.17349175
title: Solar parks in the Netherlands

description: The Solar Parks of the Netherlands is a geospatial vector dataset that provides information on the location and extent of all existing land-based solar parks in the Netherlands. The dataset is further enriched with information on underlying landscape factors, including soil type, distance to built-up areas, and the openness of the surrounding land.

The dataset was first created in 2020 and has been updated annually at the end of June. It exclusively includes solar parks constructed on land, excluding those installed on rooftops or water bodies. Additionally, it only covers areas primarily dedicated to solar energy production (i.e., the paneled area), excluding associated buildings and boundary lands.

For each solar park, the dataset provides the following attributes:

    Location – specified in latitude and longitude coordinates.

    Area (hectares) – total surface area covered by the solar park (ha).

    Soil type – dominant soil type within the solar park.

    Municipality – name of the municipality where the solar park is situated.

    Landscape openness – a measure of the visible surface area (ha).

    Distance to built-up areas – measured in kilometers.

 

The dataset was generated using an automated detection approach based on Sentinel-2 satellite imagery. A machine-learning model employing the random forest algorithm was trained and validated using auxiliary land use datasets, including LGN, BRT TOP10NL, and OpenStreetMap. The detected solar park areas were initially represented as a raster layer and subsequently converted into a vector format.

The precision of boundary delineation varies across the dataset. Approximately half of the solar parks, particularly those constructed in earlier years, have a higher level of precision as a result of additional manual boundary refinement. The additional attributes for each solar park were derived either directly from its geometry or through spatial overlays with ancillary datasets.

The production of this dataset is part of the EcoCertified Solar Parks project.
DOI: 10.5281/zenodo.17349176
title: Solar parks in the Netherlands

description: The Solar Parks of the Netherlands is a geospatial vector dataset that provides information on the location and extent of all existing land-based solar parks in the Netherlands. The dataset is further enriched with information on underlying landscape factors, including soil type, distance to built-up areas, and the openness of the surrounding land.

The dataset was first created in 2020 and has been updated annually at the end of June. It exclusively includes solar parks constructed on land, excluding those installed on rooftops or water bodies. Additionally, it only covers areas primarily dedicated to solar energy production (i.e., the paneled area), excluding associated buildings and boundary lands.

For each solar park, the dataset provides the following attributes:

    Location – specified in latitude and longitude coordinates.

    Area (hectares) – total surface area covered by the solar park (ha).

    Soil type – dominant soil type within the solar park.

    Municipality – name of the municipality where the solar park is situated.

    Landscape openness – a measure of the visible surface area (ha).

    Distance to built-up areas – measured in kilometers.

 

The dataset was generated using an automated detection approach based on Sentinel-2 satellite imagery. A machine-learning model employing the random forest algorithm was trained and validated using auxiliary land use datasets, including LGN, BRT TOP10NL, and OpenStreetMap. The detected solar park areas were initially represented as a raster layer and subsequently converted into a vector format.

The precision of boundary delineation varies across the dataset. Approximately half of the solar parks, particularly those constructed in earlier years, have a higher level of precision as a result of additional manual boundary refinement. The additional attributes for each solar park were derived either directly from its geometry or through spatial overlays with ancillary datasets.

The production of this dataset is part of the EcoCertified Solar Parks project.
DOI: 10.7910/dvn/tys852
title: Creative Tourist Segmentation in Thailand’s National Parks_Data_Questionnaire_2025

description: The dataset accompanies the study titled “Creative Tourist Segmentation in Thailand’s National Parks: A Social Media Framework for Recreation Planning and Management.” It comprises anonymized survey responses collected from 1,133 participants between January and November 2024. A DOI has been assigned to facilitate citation and future reuse in recreation planning research.