cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1260278.10fu
title: SH1260278.10FU

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/sh1260283.10fu
title: SH1260283.10FU

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/sh1260284.10fu
title: SH1260284.10FU

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/sh1260298.10fu
title: SH1260298.10FU

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/sh1260300.10fu
title: SH1260300.10FU

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/sh1260302.10fu
title: SH1260302.10FU

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/sh1260303.10fu
title: SH1260303.10FU

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.tvjada
title: Occurrence Download

description: A dataset containing 267401353 species occurrences available in GBIF matching the query:
{
 "MediaType" : [
 "is Image"
 ]
}

 The dataset includes 267401353 records from 2263 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003572-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9t3b87
title: Occurrence Download

description: A dataset containing 2788 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Eleocharis dulcis (Burm.f.) Trin. ex Hensch.)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2788 records from 108 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089897-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vc3wry
title: Occurrence Download

description: A dataset containing 439 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Eleocharis minuta Boeckeler)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 439 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089899-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2esxgp
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "TaxonKey is Ichthyomys hydrobates (Winge, 1891)"
 ]
}

 The dataset includes 12 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089901-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.984bmn
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Thailand",
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Pegasus volitans Linnaeus, 1758",
 "Year 2000-2024"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089902-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vc9fyt
title: Occurrence Download

description: A dataset containing 865 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Eleocharis atropurpurea (Retz.) J.Presl & C.Presl)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 865 records from 133 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089900-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e82zu9
title: Occurrence Download

description: A dataset containing 38 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Thailand",
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Pelargopsis amauroptera (J.T.Pearson, 1841)",
 "Year 2000-2024"
 ]
}

 The dataset includes 38 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089903-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nq3baq
title: Occurrence Download

description: A dataset containing 94 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Thailand",
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Pelecanus philippensis Gmelin, 1789",
 "Year 2000-2024"
 ]
}

 The dataset includes 94 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089904-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j72rm3
title: Occurrence Download

description: A dataset containing 136 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Eleocharis schaffneri Boeckeler)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 136 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089905-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s83kr5
title: Occurrence Download

description: A dataset containing 569937 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Cistus ladanifer L.)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 569937 records from 137 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089890-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bbhwgj
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Thailand",
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Pellorneum malaccense (Hartlaub, 1844)",
 "Year 2000-2024"
 ]
}

 The dataset includes 16 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089906-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hzqx7e
title: Occurrence Download

description: A dataset containing 9554654 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is Peru"
 ]
}

 The dataset includes 9554654 records from 2542 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0089898-240506114902167/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.28093580
title: Chromosome-level genome assembly of the estuarine <i>Corbicula flumnalis</i> from the Yangtze River estuary in China

description: The chromosome-level genome assembly and annotation of the estuarine <i>Corbicula flumnalis</i> from the Yangtze River estuary in China
DOI: 10.7910/dvn/vecvsm
title: Replication Data for: Optical coherence tomography analysis at initial diagnosis in patients with retinitis pigmentosa and associated cystoid macular edema

description: This data set includes optical coherence tomography (OCT) findings in 130 eyes of 130 patients with retinitis pigmentosa (RP) at initial diagnosis, including 42 with cystoid macular edema (CME) and 88 without, between September 2016 and March 2024.
DOI: 10.7910/dvn/si4er3
title: Pancreatic Cancer Biomedical Knowledge Graph

description: This dataset comprises approximately 1 million high-confidence biomedical triples focused on pancreatic cancer, constructed from a curated set of 23 relevant biomedical entities (KRAS, TP53, gemcitabine) and 11 common relation types ( mutated_in, treats, interacts_with). Each triple is embedded in a synthetic, natural language sentence mimicking scientific phrasing and is paired with a simulated attention score ranging from 0.75 to 1.00, reflecting transformer-based model confidence. Heuristic boosting was applied to biologically plausible combinations, resulting in an average attention score near 0.88. This structured resource is ideal for training, validating, or benchmarking biomedical NLP models and knowledge extraction systems within the context of pancreatic cancer.
DOI: 10.15468/dl.zb9qz2
title: Occurrence Download

description: A dataset containing 14724 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Lithocarpus Blume"
 ]
}

 The dataset includes 14724 records from 51 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015121-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qx72jq
title: Occurrence Download

description: A dataset containing 126 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Collichthys lucidus (Richardson, 1844)"
 ]
}

 The dataset includes 126 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015122-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.5919482
title: ChinaHighPMC: Big Data Seamless 1 km Ground-level PM2.5 Chemical Composition Dataset for China

description: ChinaHighPMC is one of the series of long-term, full-coverage, high-resolution, and high-quality datasets of ground-level air pollutants for China (i.e., ChinaHighAirPollutants, CHAP). It is generated from the big data (e.g., ground-based measurements, satellite remote sensing products, atmospheric reanalysis, and model simulations) using artificial intelligence by considering the spatiotemporal heterogeneity of air pollution. This is the big data-derived seamless (spatial coverage = 100%) daily, monthly, and yearly 1 km (i.e., D1K, M1K, and Y1K) dataset of ground-level PM<sub>2.5</sub> chemical composition (including SO<sub>4</sub><sup>2-</sup>, NO<sub>3</sub><sup>-</sup>, NH<sub>4</sub><sup>+</sup>, Cl<sup>-</sup>, BC, and OM) in China since 2000. This dataset yields a high quality with average cross-validation coefficients (CV-R<sup>2</sup>) of 0.74, 0.75, 0.71, 0.66, and 0.66, and root-mean-square errors (RMSEs) of 6.0, 6.6, 4.3, and 2.3 µg m<sup>-3</sup> for SO<sub>4</sub><sup>2-</sup>, NO<sub>3</sub><sup>-</sup>, NH<sub>4</sub><sup>+</sup>, and Cl<sup>-</sup>, respectively, on a daily basis. All the data will be made public online once our paper is accepted, and if you want to use the ChinaHighPMC dataset for related scientific research, please contact us (Email: weijing_rs@163.com; weijing@umd.edu). <strong>More CHAP datasets of different air pollutants can be found at: https://weijing-rs.github.io/product.html</strong>
description: Note that this dataset is continuously updated and if you need more data, please contact me (Email: weijing_rs@163.com; weijing@umd.edu).
DOI: 10.5281/zenodo.7971311
title: ChinaHighPMC: Big Data Seamless 1 km Ground-level PM2.5 Chemical Composition Dataset for China

description: ChinaHighPMC is one of the series of long-term, full-coverage, high-resolution, and high-quality datasets of ground-level air pollutants for China (i.e., ChinaHighAirPollutants, CHAP). It is generated from the big data (e.g., ground-based measurements, satellite remote sensing products, atmospheric reanalysis, and model simulations) using artificial intelligence by considering the spatiotemporal heterogeneity of air pollution. 
This is the big data-derived seamless (spatial coverage = 100%) monthly and yearly 1 km (i.e., M1K and Y1K) dataset of ground-level PM2.5 inorganic chemical composition (i.e., SO42-, NO3-, NH4+, and Cl-) in Eastern China from 2013 to 2020. This dataset yields a high quality with average cross-validation coefficients (CV-R2) of 0.74, 0.75, 0.71, and 0.66, and root-mean-square errors (RMSEs) of 6.0, 6.6, 4.3, and 2.3 µg m-3 for SO42-, NO3-, NH4+, and Cl-, respectively, on a daily basis.
Note that this dataset is closed since a new version is published at 10.5281/zenodo.10011898.
description: Note that this dataset is continuously updated and if you need more data (daily or long-period data), please contact me (Email: weijing_rs@163.com; weijing@umd.edu or chenxi@nieh.chinacdc.cn) due to space limits.
DOI: 10.1594/pangaea.975976
title: Biomarkers of sediment core PS115/2_2

description: Sediment Core PS115/2-2 was recovered from the Amundsen Basin in 3600 m water depth at the eastern flank of the Gakkel Ridge during Polarstern Expedition PS115/2 in 2018 (Stein, 2019). The well-dated core is used to reconstruct in detail the interrelationship between ice-sheet dynamics and organic carbon burial in the central Eurasian Basin during the last 430 kyr, and to correlate marine and terrestrial records of the Eurasian Ice Sheet (EIS) history. Using organic-geochemical bulk parameters (i.e., TOC, C/N ratios, Rock Eval) and biomarkers, we have identified prominent well-defined sections with strongly elevated concentration of ancient (petrogenic) predominantly terrestrial OC, coinciding with glacial time intervals of extended ice sheets and the subsequent terminations/deglacials. Based on the presence of specific biomarkers indicative for increased preservation of labile algae-type OC under anoxic sedimentary conditions, we demonstrate that even during strong glacial intervals there must have been at least occasionally open-water (polynya-type) conditions along the Eurasian continental margin in front of the ice sheet with marine and sea-ice algae productivity (cf., Fahl & Stein, 2012; Naafs et al., 2024). For details and methods, we also refer to Stein et al. (this paper).
DOI: 10.1594/pangaea.975989
title: Rock eval analysis of sediment core PS115/2_2

description: Sediment Core PS115/2-2 was recovered from the Amundsen Basin in 3600 m water depth at the eastern flank of the Gakkel Ridge during Polarstern Expedition PS115/2 in 2018 (Stein, 2019). The well-dated core is used to reconstruct in detail the interrelationship between ice-sheet dynamics and organic carbon burial in the central Eurasian Basin during the last 430 kyr, and to correlate marine and terrestrial records of the Eurasian Ice Sheet (EIS) history. Using organic-geochemical bulk parameters (i.e., TOC, C/N ratios, Rock Eval) and biomarkers, we have identified prominent well-defined sections with strongly elevated concentration of ancient (petrogenic) predominantly terrestrial OC, coinciding with glacial time intervals of extended ice sheets and the subsequent terminations/deglacials. Rock-Eval pyrolysis was performed on bulk ground sediment samples using a Rock-Eval 6 analyzer (cf., Lafarque et al., 1998) to determine (1) the amount of hydrocarbons (HC) present (S1 peak) and generated by pyrolytic degradation of the OC during heating up to 650°C (S2 peak), (2) the amount of carbon dioxide (CO2) generated from the decomposing OC during heating up to 390 °C (S3 peak), and (3) the temperature of maximum pyrolysis yield (Tmax value in °C). The HC and CO2 yields were normalized to OC and expressed as hydrogen index (HI) in mgHC/gOC and oxygen index (OI) in mgCO2/gOC, respectively, and may give information about the composition of the organic matter. Tmax values may give further information about the composition as well as the maturity of the organic matter. For details and methods, we refer to Stein et al. (this paper).