cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0215568.10fu
title: SH0215568.10FU

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/sh0215569.10fu
title: SH0215569.10FU

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/sh0215570.10fu
title: SH0215570.10FU

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/sh0215571.10fu
title: SH0215571.10FU

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/sh0215572.10fu
title: SH0215572.10FU

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/sh0215573.10fu
title: SH0215573.10FU

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/sh0215574.10fu
title: SH0215574.10FU

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/sh0215575.10fu
title: SH0215575.10FU

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.qg7pk7
title: Occurrence Download

description: A dataset containing 19452 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Geometry POLYGON((111.357 21.461,115.422 21.461,115.422 24.392,111.357 24.392,111.357 21.461))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Centropus sinensis"
 ]
}

 The dataset includes 19452 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072660-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w93bx8
title: Occurrence Download

description: A dataset containing 386854720 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-118.42215 80,-118.5412 75,-118.15028 70,-110.56395 65,-102.69947 60,-97.14579 55,-93.42354 50,-91.1403 45,-89.68094 40,-88.8258 35,-87.35671 30,-85.88762 25,-83.12602 20,-76.60577 15,-70.18239 10,-65.76942 5,-62.36635 0,-61.58992 -5,-61.84945 -10,-63.00314 -15,-64.99583 -20,-66.82394 -25,-68.65205 -30,-70.22892 -35,-70.22562 -40,-70.12173 -45,-69.91715 -50,-69.61161 -55,-67.80687 -60,-62.86825 -60,-56.18175 -55,-51.29446 -50,-46.93061 -45,-43.01955 -40,-39.50844 -35,-36.35665 -30,-33.53228 -25,-31.00988 -20,-28.76893 -15,-27.92603 -10,-28.30317 -5,-29.77421 0,-32.5836 5,-38.50833 10,-46.23331 15,-53.95828 20,-61.68326 25,-65.23646 30,-64.71612 35,-56.67663 40,-49.99074 45,-49.29708 50,-50.6119 55,-53.91159 60,-58.84733 65,-64.1735 70,-70.60214 75,-78.664 80,-88.54241 84.56382,-118.42215 80))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Passeriformes",
 "Year 2015-2024"
 ]
}

 The dataset includes 386854720 records from 247 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072648-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q2jk3q
title: Occurrence Download

description: A dataset containing 82383 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Genista anglica"
 ]
}

 The dataset includes 82383 records from 701 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072655-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18144445
title: Data and figures for reconstruction and multi-scale transfer learning of complex fracture networks

description: The cvPINN-TL-DFN framework introduces a transfer learning approach that bridges lab experiments and field-scale models. It leverages a multi-fidelity loss to adapt features from lab-trained cvPINNs to subsurface discrete fracture networks (DFNs) at the kilometer scale, ensuring consistency in toughness regimes and the preservation of critical fracture connectivity for geothermal applications.
DOI: 10.5281/zenodo.18144446
title: Data and figures for reconstruction and multi-scale transfer learning of complex fracture networks

description: The cvPINN-TL-DFN framework introduces a transfer learning approach that bridges lab experiments and field-scale models. It leverages a multi-fidelity loss to adapt features from lab-trained cvPINNs to subsurface discrete fracture networks (DFNs) at the kilometer scale, ensuring consistency in toughness regimes and the preservation of critical fracture connectivity for geothermal applications.
DOI: 10.15468/dl.ah8mb5
title: Occurrence Download

description: A dataset listing the 2739 species recorded in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Occurrence evidence, Fossil, Specimen, Material sample, Human Observation, Machine Observation, Observation)",
 "Continent is Asia",
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "IucnRedListCategory is one of (NT, LC, CR, EN, VU)",
 "OccurrenceStatus is Present",
 "TaxonKey is Chordata",
 "Year 1991-2020"
 ]
}

 The dataset's 2739 records were derived from 102 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072657-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tzsyq4
title: Occurrence Download

description: A dataset containing 2513 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Hyparrhenia rufa)",
 "Year is greater than or equal to 2000",
 "Year is less than or equal to 2025",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2513 records from 214 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072666-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8jw66h
title: Occurrence Download

description: A dataset containing 1990 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Gleditsia aquatica"
 ]
}

 The dataset includes 1990 records from 142 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072667-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yct38w
title: Occurrence Download

description: A dataset containing 179 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Naemorhedus"
 ]
}

 The dataset includes 179 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072668-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/f3ty-6n16
title: "SAREdgeNet-Derived 2022 Tibetan Plateau Lake Extent (Shapefile Format)"

description: "This dataset consists of 2022 Tibetan Plateau lake extent data generated by the SAREdgeNet lightweight deep learning algorithm, presented in Shapefile format (a commonly used geospatial vector format). It is specifically designed to provide high-quality foundational data for remote sensing water body monitoring, climate change research, and algorithm performance validation.The core data of this dataset is derived from 288 Sentinel-1 satellite SAR images, integrated with 30m-resolution STRM Digital Elevation Model (DEM) data. It covers the entire Tibetan Plateau, spanning approximately 460,000 km\u00b2\u2014a region where lake area accounts for over 50% of China\u2019s total lake area and serves as a sensitive zone for global climate change. The data has undergone standardized preprocessing, including radiometric calibration, speckle noise filtering, and accurate registration. Additionally, it integrates SAR scattering features, topographic features, and geometric characteristics of lakes, effectively avoiding misclassification of dunes, shadows, and other non-water features as lakes, thus ensuring the accuracy of lake boundaries.The dataset includes the complete extents of various lakes on the Tibetan Plateau, ranging from small lakes to large ones such as Qinghai Lake. The annotation benchmark is based on manually refined NDVI-based water body data, with an overall extraction accuracy exceeding 96%. As vector data in Shapefile format, it can be directly used in mainstream GIS software (e.g., ArcGIS, QGIS) to support multiple operations such as lake area statistics, boundary analysis, and spatiotemporal change comparison, without the need for additional format conversion.This dataset provides reliable support for both researchers (for lake extraction model training and algorithm generalization validation) and relevant authorities (for water resource surveys and ecological protection assessments). Currently, the dataset is available upon request by contacting the corresponding author (email: yminruan@163.com). The source code of the supporting SAREdgeNet algorithm has been open-sourced (https:\/\/github.com\/Abolewaer\/SAREdgeNet), facilitating users to reproduce results or conduct secondary development."
DOI: 10.15468/dl.t8w78e
title: Occurrence Download

description: A dataset containing 201 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Imperata brasiliensis)",
 "Year is greater than or equal to 2000",
 "Year is less than or equal to 2025",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 201 records from 79 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072669-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rmb4ty
title: Occurrence Download

description: A dataset containing 31505 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Imperata cylindrica)",
 "Year is greater than or equal to 2000",
 "Year is less than or equal to 2025",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 31505 records from 315 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072670-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k6ahx8
title: Occurrence Download

description: A dataset containing 2962 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Gorilla I.Geoffroy Saint-Hilaire, 1852"
 ]
}

 The dataset includes 2962 records from 96 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003093-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4f4t4z
title: Occurrence Download

description: A dataset containing 7047 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Herpestes auropunctatus (Hodgson, 1836))",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 7047 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003094-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wsjz9c
title: Occurrence Download

description: A dataset containing 916 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Callosciurus erythraeus (Pallas, 1779)",
 "Country is Japan",
 "Year is greater than or equal to 1500"
 ]
}

 The dataset includes 916 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003096-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ce463h
title: Occurrence Download

description: A dataset containing 1694254 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cuculus canorus Linnaeus, 1758",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1950"
 ]
}

 The dataset includes 1694254 records from 3775 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003084-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/cc115rvt
title: CCDC 958856: Experimental Crystal Structure Determination

description: Related Article: G. K. Surya Prakash, Zhe Zhang, Fang Wang, Martin Rahm, Chuanfa Ni, Marc Iuliucci, Ralf Haiges, George A. Olah|2014|Chem.-Eur.J.|20|831|doi:10.1002/chem.201303509
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc115pvr
title: CCDC 958794: Experimental Crystal Structure Determination

description: Related Article: Wuji Sun, Yangye Jiang, Hong Yan and Xiuqing Song|2015|Aust.J.Chem.|68|273|doi:10.1071/CH14113
description: Related Article: Shijie Wang, Xiuqing Song, Runzhi Sun, Hong Yan, Yeming Wang|2023|Tetrahedron|131|133212|doi:10.1016/j.tet.2022.133212
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc115sqq
title: CCDC 958883: Experimental Crystal Structure Determination

description: Related Article: Bo Han, Xin Xie, Wei Huang, Xiang Li, Lei Yang, Cheng Peng|2014|Adv.Synth.Catal.|356|3676|doi:10.1002/adsc.201400622
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc115sww
title: CCDC 958888: Experimental Crystal Structure Determination

description: Related Article: Michael Monday Onakpa, Ming Zhao, Tanja Gödecke, Wei-Lun Chen, Chun-Tao Che, Bernard D. Santarsiero, Steven M. Swanson, Isaac Uzoma Asuzu|2014|Chem.Biodiversity|11|1914|doi:10.1002/cbdv.201400151
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.