cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1381249.10fu
title: SH1381249.10FU

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/sh1381250.10fu
title: SH1381250.10FU

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/sh1381252.10fu
title: SH1381252.10FU

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/sh1381253.10fu
title: SH1381253.10FU

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: 10.5281/zenodo.18229499
title: Data and appendices. Chile-Portugal pilot study on social determinants of the digital divide in initial teacher training. DSBD-HD-FID scale

description: The file contains the coded data and appendices derived from the pilot study (2023) that validates the Digital Hospitality Scale (DSBD-BD-FID), which allows for the analysis of the social determinants of the digital divide among students in initial teacher training.
DOI: 10.5281/zenodo.18229500
title: Data and appendices. Chile-Portugal pilot study on social determinants of the digital divide in initial teacher training. DSBD-HD-FID scale

description: The file contains the coded data and appendices derived from the pilot study (2023) that validates the Digital Hospitality Scale (DSBD-BD-FID), which allows for the analysis of the social determinants of the digital divide among students in initial teacher training.
DOI: 10.17632/nktfr26hrb
title: Communites of Pratice for enhancing soil health_Dataset_2025

description: Collection of descriptions of Communites of Pratice (stakeholder groups with the aim of learning together) focused on soil health in Europe, collected and filmed through the project PREPSOIL (HORIZON-MISS-2021-SOIL-01-01, Project number 101070045)
DOI: 10.17632/nktfr26hrb.1
title: Communites of Pratice for enhancing soil health_Dataset_2025

description: Collection of descriptions of Communites of Pratice (stakeholder groups with the aim of learning together) focused on soil health in Europe, collected and filmed through the project PREPSOIL (HORIZON-MISS-2021-SOIL-01-01, Project number 101070045)
DOI: 10.15468/dl.w2278q
title: Occurrence Download

description: A dataset containing 50 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is India",
 "TaxonKey is Isachne kunthiana"
 ]
}

 The dataset includes 50 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017636-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/8pcmr7szpz
title: Residual water bodies of permafrost peatlands (Western Siberia)

description: Concentrations of major and trace solutes averaged among all sampled drained lakes
DOI: 10.17632/8pcmr7szpz.1
title: Residual water bodies of permafrost peatlands (Western Siberia)

description: Concentrations of major and trace solutes averaged among all sampled drained lakes
DOI: 10.15468/dl.vj4td2
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cerebratulus theta",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017637-251025141854904/datasets/export for details.
DOI: 10.17632/8vf7z6v5sb
title: Personal Protective Equipment Detection Dataset (5-Class) for Construction Safety Monitoring

description: Personal Protective Equipment (PPE) Detection Dataset (5-Class) for Construction Safety Monitoring is an object-detection dataset curated to help developers build real-time systems that verify whether construction workers are wearing essential safety gear. Images were selected to stress practical deployment: diverse viewpoints (elevated cameras, close-ups), common occlusions (hands in pockets, partially hidden hard hats), and environmental variability (shadow, glare, dust). These characteristics encourage generalization and robustness in downstream models—a known gap when training only on clean, staged photos.
DOI: 10.17632/8vf7z6v5sb.1
title: Personal Protective Equipment Detection Dataset (5-Class) for Construction Safety Monitoring

description: Personal Protective Equipment (PPE) Detection Dataset (5-Class) for Construction Safety Monitoring is an object-detection dataset curated to help developers build real-time systems that verify whether construction workers are wearing essential safety gear. Images were selected to stress practical deployment: diverse viewpoints (elevated cameras, close-ups), common occlusions (hands in pockets, partially hidden hard hats), and environmental variability (shadow, glare, dust). These characteristics encourage generalization and robustness in downstream models—a known gap when training only on clean, staged photos.
DOI: 10.17632/tm8nv4m72g
title: Relative variation in β-glucan components in the oat grain (Avena sativa) during development and between varieties.

description: Supplementary data to accompany paper
DOI: 10.17632/tm8nv4m72g.1
title: Relative variation in β-glucan components in the oat grain (Avena sativa) during development and between varieties.

description: Supplementary data to accompany paper
DOI: 10.17632/6rd6pbd4rb.4
title: PENTEX II

description: MSCA project PENTEX
DOI: 10.17632/zpv2kjcyh7
title: Reflectance intensity dataset of roast coffee beans measured with AS7265X sensor

description: This dataset contains reflectance intensity measurements of roasted coffee beans collected using the AS7265X multispectral sensor module. The sensor provides 18 discrete spectral bands across the visible to near-infrared region (410-940 nm), capturing spectral responses that correspond to color development and chemical characteristics of roast coffee. The dataset includes samples representing various roasting levels quantified by Agtron value, allowing for detailed analysis of the relationship between roasting degree (Agtron) and multispectral reflectance characteristics.

Each sample entry consists of label (type and origin of Indonesian coffee), Agtron value reference, and the intensity values obtained from the AS7265X sensor for all available wavelength channels. The reflectance intensity values are original sensor outputs, which can be used directly or further calibrated depending on the analytical objectives.

This dataset is suitable for applications in coffee quality assessment, machine learning–based prediction of roast degree, spectral feature analysis, and development of real-time roasting monitoring systems. It provides a foundation for exploring non-destructive sensing techniques to classify and quantify coffee roasting characteristics.

Key Features:
Multispectral reflectance data from 18 wavelength channels in arbitrary unit (a.u.).
Multiple roast degrees of Arabica and Robusta coffee beans.
Original sensor output values for flexible processing and modeling.
Enables development of predictive and classification models for roast degree.
DOI: 10.17632/zpv2kjcyh7.1
title: Reflectance intensity dataset of roast coffee beans measured with AS7265X sensor

description: This dataset contains reflectance intensity measurements of roasted coffee beans collected using the AS7265X multispectral sensor module. The sensor provides 18 discrete spectral bands across the visible to near-infrared region (410-940 nm), capturing spectral responses that correspond to color development and chemical characteristics of roast coffee. The dataset includes samples representing various roasting levels quantified by Agtron value, allowing for detailed analysis of the relationship between roasting degree (Agtron) and multispectral reflectance characteristics.

Each sample entry consists of label (type and origin of Indonesian coffee), Agtron value reference, and the intensity values obtained from the AS7265X sensor for all available wavelength channels. The reflectance intensity values are original sensor outputs, which can be used directly or further calibrated depending on the analytical objectives.

This dataset is suitable for applications in coffee quality assessment, machine learning–based prediction of roast degree, spectral feature analysis, and development of real-time roasting monitoring systems. It provides a foundation for exploring non-destructive sensing techniques to classify and quantify coffee roasting characteristics.

Key Features:
Multispectral reflectance data from 18 wavelength channels in arbitrary unit (a.u.).
Multiple roast degrees of Arabica and Robusta coffee beans.
Original sensor output values for flexible processing and modeling.
Enables development of predictive and classification models for roast degree.
DOI: 10.15468/dl.88mmn3
title: Occurrence Download

description: A dataset containing 1234869 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Fagus sylvatica",
 "BasisOfRecord is one of (Human Observation)"
 ]
}

 The dataset includes 1234869 records from 1922 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017603-251025141854904/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.28473323
title: A dataset for "Seed density and priority effects outweigh limiting similarity and diversity in contributing biotic resistance to invasion"

description: This is the dataset for "Seed density and priority effects outweigh limiting similarity and diversity in contributing biotic resistance to invasion"
DOI: 10.6084/m9.figshare.28473323.v1
title: A dataset for "Seed density and priority effects outweigh limiting similarity and diversity in contributing biotic resistance to invasion"

description: This is the dataset for "Seed density and priority effects outweigh limiting similarity and diversity in contributing biotic resistance to invasion"
DOI: 10.5281/zenodo.12555233
title: Dataset: Conn's, Inc. (CONN) Stock Performance

description: This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
DOI: 10.5281/zenodo.12555234
title: Dataset: Conn's, Inc. (CONN) Stock Performance

description: This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
DOI: 10.5281/zenodo.12555235
title: Dataset: The Cooper Companies, Inc. (COO) Stock Performance

description: This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
DOI: 10.5281/zenodo.12555236
title: Dataset: The Cooper Companies, Inc. (COO) Stock Performance

description: This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
DOI: 10.5281/zenodo.12555237
title: Dataset: Mr. Cooper Group Inc. (COOP) Stock Performance

description: This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
DOI: 10.5281/zenodo.12555238
title: Dataset: Mr. Cooper Group Inc. (COOP) Stock Performance

description: This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
DOI: 10.5281/zenodo.12555240
title: Dataset: Australian Oilseeds Holdings Limited (COOT) Stock Performance

description: This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
DOI: 10.5281/zenodo.12555241
title: Dataset: Australian Oilseeds Holdings Limited (COOT) Stock Performance

description: This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
DOI: 10.5281/zenodo.12555244
title: Dataset: Australian Oilseeds Holdings Limited (COOTW) Stock Performance

description: This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
DOI: 10.5281/zenodo.12555245
title: Dataset: Australian Oilseeds Holdings Limited (COOTW) Stock Performance

description: This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
DOI: 10.5281/zenodo.12555246
title: Dataset: Sprott Junior Copper Miners ETF (COPJ) Stock Performance

description: This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
DOI: 10.5281/zenodo.12555247
title: Dataset: Sprott Junior Copper Miners ETF (COPJ) Stock Performance

description: This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
DOI: 10.5281/zenodo.12555248
title: Dataset: Sprott Copper Miners ETF (COPP) Stock Performance

description: This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
DOI: 10.5281/zenodo.12555249
title: Dataset: Sprott Copper Miners ETF (COPP) Stock Performance

description: This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
DOI: 10.15468/dl.84rkq6
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sciaena spinifera Forsskål, 1775"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000869-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f5jjmg
title: Occurrence Download

description: A dataset containing 454 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Urobatis jamaicensis (Cuvier, 1816)"
 ]
}

 The dataset includes 454 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000864-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ddpzhy
title: Occurrence Download

description: A dataset containing 3297 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "TaxonKey is Phlogophilus hemileucurus Gould, 1860"
 ]
}

 The dataset includes 3297 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000866-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.98sqcq
title: Occurrence Download

description: A dataset containing 820 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "TaxonKey is Harpia harpyja (Linnaeus, 1758)"
 ]
}

 The dataset includes 820 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000867-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12555250
title: Dataset: Corcept Therapeutics Incorporated (CORT) Stock Performance

description: This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
DOI: 10.5281/zenodo.12555251
title: Dataset: Corcept Therapeutics Incorporated (CORT) Stock Performance

description: This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
DOI: 10.5281/zenodo.12555254
title: Dataset: Core Scientific, Inc. (CORZ) Stock Performance

description: This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
DOI: 10.5281/zenodo.12555255
title: Dataset: Core Scientific, Inc. (CORZ) Stock Performance

description: This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.