cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0176723.10fu
title: SH0176723.10FU

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/sh0176724.10fu
title: SH0176724.10FU

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/sh0176725.10fu
title: SH0176725.10FU

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/sh0176726.10fu
title: SH0176726.10FU

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/sh0176727.10fu
title: SH0176727.10FU

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/sh0176728.10fu
title: SH0176728.10FU

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/sh0176729.10fu
title: SH0176729.10FU

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.4wrgzq
title: Occurrence Download

description: A dataset containing 224 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Megaleledone setebos (G.C.Robson, 1932)"
 ]
}

 The dataset includes 224 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056356-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ms26dz
title: Occurrence Download

description: A dataset containing 36919 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Insecta)",
 "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((15 -22.5,22.5 -22.5,22.5 -15,15 -15,15 -22.5))"
 ]
}

 The dataset includes 36919 records from 84 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041229-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15151/esrf-es-2227958953
title: Stability of S-bearing minerals in the Earth's lower mantle

description: Sulfur is one of the five most abundant elements on Earth and it has played an important role in many geodynamic processes throughout the Earth's history, from core formation to modern subduction systems. While the behavior of sulfur in upper mantle processes is relatively well-studied due to direct access to natural samples, its behavior in the lower mantle remains unclear. We started investigating the reactions occuring between relevant oxidised phases, such as siderite (FeCO3) and hematite (Fe2O3), and CS2, as a source of sulfur and carbon. We will extend the characterization to Fe3O4 and FeO to investigate different redox conditions (spanning from the Fe3+ in Fe2O3 to Fe2+ in FeO passing through the mixed states of Fe3O4) and Al-bridgmanite in representation of different mantle geodynamic settings. This research aims to develop a deeper understanding of sulfur's behavior in complex Fe-S-C-O systems in the lower mantle and to provide insights on the deep sulfur cycle.
DOI: 10.15151/esrf-es-2227978465
title: X-ray tomography of glass modifications induced by fs-laser writing

description: The aim of this experiment is to collect high-resolution 3D information on the distribution of electron density of subwavelength photonic structures using near-field ptychography to convert into refractive index. We will study samples fabricated using fs-laser direct writing, a technique to induce permanent changes in the molecular structure of the transparent materials that is widely used in integrated photonics. Obtaining such high-resolution information on the induced material modifications yields fundamental understanding of the writing process and the limits of its reproducibility, which directly aids the design and fabrication of integrated photonic circuits and reproducible scattering materials. Furthermore, these low-contrast samples offer an opportunity to explore the limitations of metrology at ID16A.
DOI: 10.15468/dl.cw8d45
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.28_1",
 "TaxonKey is Deyeuxia tianschanica"
 ]
}

 The dataset includes 7 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041230-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cpp52t
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Consolida orientalis",
 "Country is Poland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 16 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014438-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.97szar
title: Occurrence Download

description: A dataset containing 135 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Consolida orientalis",
 "Country is Russian Federation",
 "HasCoordinate is true"
 ]
}

 The dataset includes 135 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014440-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kes5z2
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Consolida orientalis",
 "Country is Portugal",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014439-250920141307145/datasets/export for details.
DOI: 10.15468/dl.aa64dx
title: Occurrence Download

description: A dataset containing 796135 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Australia",
 "HasCoordinate is true",
 "Year is 1978"
 ]
}

 The dataset includes 796135 records from 335 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014361-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6j92wk
title: Occurrence Download

description: A dataset containing 270373 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Platanus hispanica",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 270373 records from 575 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014383-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17193770
title: Annual Mean NDVI for Mexico Derived from MODIS/061/MYD13Q1.
title: NDVI anual promedio en México (MODIS MYD13Q1, Colección 6.1).

description: Annual mean NDVI rasters for Mexico covering the period 2003–present. The data were derived from the MODIS/061/MYD13Q1 product and processed to generate annual composites. The files are provided in GeoTIFF raster format with a spatial resolution of 250 m per pixel.
DOI: 10.5281/zenodo.17193771
title: Annual Mean NDVI for Mexico Derived from MODIS/061/MYD13Q1.
title: NDVI anual promedio en México (MODIS MYD13Q1, Colección 6.1).

description: Annual mean NDVI rasters for Mexico covering the period 2003–present. The data were derived from the MODIS/061/MYD13Q1 product and processed to generate annual composites. The files are provided in GeoTIFF raster format with a spatial resolution of 250 m per pixel.
DOI: 10.15468/dl.fptutq
title: Occurrence Download

description: A dataset containing 5350355 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry MULTIPOLYGON(((83.50235 23.56362,88.50236 23.56362,93.50236 23.56362,93.50236 18.56362,98.50236 18.56362,103.50236 18.56362,103.50236 13.56362,103.50236 8.56362,103.50236 3.56362,103.50236 -1.43638,108.50236 -1.43638,113.50236 -1.43638,113.50236 3.56362,118.50236 3.56362,118.50236 8.56362,123.50236 8.56362,123.50236 13.56362,123.50236 18.56362,128.50236 18.56362,128.50236 23.56362,133.50236 23.56362,133.50236 28.56362,133.50236 33.56362,128.50236 33.56362,128.50236 38.56362,133.50236 38.56362,133.50236 43.56362,138.50236 43.56362,138.50236 48.56362,138.50236 53.56362,133.50236 53.56362,128.50236 53.56362,128.50236 58.56362,123.50236 58.56362,118.50236 58.56362,118.50236 53.56362,113.50236 53.56362,113.50236 48.56362,108.50236 48.56362,108.50236 43.56362,103.50236 43.56362,98.50236 43.56362,98.50236 48.56362,93.50236 48.56362,93.50236 53.56362,88.50236 53.56362,83.50235 53.56362,83.50235 48.56362,78.50235 48.56362,78.50235 43.56362,73.50235 43.56362,68.50235 43.56362,68.50235 38.56362,68.50235 33.56362,73.50235 33.56362,73.50235 28.56362,78.50235 28.56362,78.50235 23.56362,83.50235 23.56362)))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "LastInterpreted is greater than or equal to 2025-09-23",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 5350355 records from 1678 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014395-250920141307145/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.07768
title: Chandra X-ray Observatory ObsId 07768

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.12503
title: Chandra X-ray Observatory ObsId 12503

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.16663
title: Chandra X-ray Observatory ObsId 16663

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.22356
title: Chandra X-ray Observatory ObsId 22356

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.02361
title: Chandra X-ray Observatory ObsId 02361

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.09600
title: Chandra X-ray Observatory ObsId 09600

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.07396
title: Chandra X-ray Observatory ObsId 07396

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.10571
title: Chandra X-ray Observatory ObsId 10571

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.19512
title: Chandra X-ray Observatory ObsId 19512

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.16441
title: Chandra X-ray Observatory ObsId 16441

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.08166
title: Chandra X-ray Observatory ObsId 08166

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.22307
title: Chandra X-ray Observatory ObsId 22307

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.03735
title: Chandra X-ray Observatory ObsId 03735

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.04827
title: Chandra X-ray Observatory ObsId 04827

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.16272
title: Chandra X-ray Observatory ObsId 16272

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.03737
title: Chandra X-ray Observatory ObsId 03737

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.13420
title: Chandra X-ray Observatory ObsId 13420

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.12920
title: Chandra X-ray Observatory ObsId 12920

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.14559
title: Chandra X-ray Observatory ObsId 14559

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.01568
title: Chandra X-ray Observatory ObsId 01568

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.09032
title: Chandra X-ray Observatory ObsId 09032

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".