cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1384122.10fu
title: SH1384122.10FU

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/sh1384123.10fu
title: SH1384123.10FU

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/sh1384124.10fu
title: SH1384124.10FU

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/sh1384125.10fu
title: SH1384125.10FU

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/sh1384126.10fu
title: SH1384126.10FU

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/sh1384127.10fu
title: SH1384127.10FU

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.kqmmsd
title: Occurrence Download

description: A dataset containing 4406 species occurrences available in GBIF matching the query:
{
 "and" : [
 "VerbatimScientificName is Trachyphonus erythrocephalus",
 "BasisOfRecord is one of (Machine Observation, Human Observation)",
 "Year 2011-2021",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Specimen, Material citation, Material sample)"
 ]
 }
 }
 ]
}

 The dataset includes 4406 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0087506-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m5z8de
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Pseudocalotes saravacensis Inger & Stuebing, 1994)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027178-230224095556074/datasets/export for details.
DOI: 10.15468/dl.r8ss2b
title: Occurrence Download

description: A dataset containing 1218 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Human Observation, Material sample, Living Specimen, Occurrence evidence)",
 "Country is Australia",
 "TaxonKey is Chiloglottis gunnii Lindl.",
 "Year 1970-2003"
 ]
}

 The dataset includes 1218 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013005-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kupm6k
title: Occurrence Download

description: A dataset containing 766444 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Poa trivialis L."
 ]
}

 The dataset includes 766444 records from 2273 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0088662-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18710/rxenfc/3kpehg
title: Egenevaluering_for_og_etter.pdf
DOI: 10.18710/rxenfc
title: Maker centered learning - cultivating creativity in tomorrows schools

description: The primary objective of this project was to analyse creative maker-centered learning and pedagogical practices for systematically educating creativity in primary and secondary schools, and to develop scientific knowledge on accessible educational practices that cultivated learners’ creativity and innovation capabilities to help bridge the ingenuity gap in future education. The secondary objectives were to: (1) enhance knowledge of how creativity was deliberately educated in school makerspaces and how maker-centered learning supported the development of creative capabilities and digital competences; (2) develop knowledge of how maker-centered learning could be applied in pedagogical practices to systematically educate creativity and innovation in basic education; and (3) generate knowledge on how teachers could effectively facilitate and scaffold students’ innovation processes in maker-centered projects.

The project results demonstrated how design and creativity could be systematically integrated into regular educational practices. Maker-centered learning proved applicable across educational levels and generated actionable pedagogical models that contributed to the advancement of STEAM education and the professional development of teachers in STEAM subjects.
DOI: 10.15468/dl.jdspye
title: Occurrence Download

description: A dataset containing 99 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Ceblepyris pectoralis (Jardine & Selby, 1828))",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 99 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0298012-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qp5ksz
title: Occurrence Download

description: A dataset containing 25214 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Allium scorodoprasum L.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 25214 records from 254 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0070901-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9c5gjv
title: Occurrence Download

description: A dataset containing 2363756679 species occurrences available in GBIF matching the query:
{ }

 The dataset includes 2363756679 records from 59878 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056339-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12564395
title: Dataset: SPS Commerce, Inc. (SPSC) 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.12564396
title: Dataset: SPS Commerce, Inc. (SPSC) 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.12564399
title: Dataset: Sprout Social, Inc. (SPT) 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.12564400
title: Dataset: Sprout Social, Inc. (SPT) 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.12564401
title: Dataset: SpartanNash Company (SPTN) 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.12564402
title: Dataset: SpartanNash Company (SPTN) 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.12564405
title: Dataset: Sportsman's Warehouse Holdings, Inc. (SPWH) 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.12564406
title: Dataset: Sportsman's Warehouse Holdings, Inc. (SPWH) 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.12564409
title: Dataset: SunPower Corporation (SPWR) 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.12564410
title: Dataset: SunPower Corporation (SPWR) 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.12564411
title: Dataset: Presidio Property Trust, Inc. (SQFT) 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.12564412
title: Dataset: Presidio Property Trust, Inc. (SQFT) 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.12564415
title: Dataset: Presidio Property Trust, Inc. (SQFTP) 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.12564416
title: Dataset: Presidio Property Trust, Inc. (SQFTP) 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.11181164
title: Memristive circuits based on multilayer hexagonal boron nitride for millimetre wave radiofrequency applications - Source data

description: Source data for the paper "Memristive circuits based on multilayer hexagonal boron nitride for radiofrequency and millimetre wave applications"

Find online at:

https://doi.org/10.1038/s41928-024-01192-2
DOI: 10.5281/zenodo.12564417
title: Dataset: Presidio Property Trust, Inc. (SQFTW) 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.12564418
title: Dataset: Presidio Property Trust, Inc. (SQFTW) 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.12564419
title: Dataset: Royce Quant Small-Cap Quality Value ETF (SQLV) 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.12564420
title: Dataset: Royce Quant Small-Cap Quality Value ETF (SQLV) 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.12562315
title: Predicting critical transitions with surrogate data-based machine learning: Project

description: This project accompanies the Github repository https://github.com/ZhiqinMa/surrogate_data_based_machine_learning. It contains the model time series data that are used to train the machine learning algorithms, as well as all the process and result files. Please extract all .rar files to G:/surrogate_data_based_machine_learning_v4.0.0 folder to run this project.
DOI: 10.5281/zenodo.12562316
title: Predicting critical transitions with surrogate data-based machine learning: Project

description: This project accompanies the Github repository https://github.com/ZhiqinMa/surrogate_data_based_machine_learning. It contains the model time series data that are used to train the machine learning algorithms, as well as all the process and result files. Please extract all .rar files to G:/surrogate_data_based_machine_learning_v4.0.0 folder to run this project.
DOI: 10.5281/zenodo.12564423
title: Dataset: ProShares UltraPro Short QQQ (SQQQ) 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.12564424
title: Dataset: ProShares UltraPro Short QQQ (SQQQ) 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.12564425
title: Dataset: Sportradar Group AG (SRAD) 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.12564426
title: Dataset: Sportradar Group AG (SRAD) 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.12564429
title: Dataset: SR Bancorp, Inc. (SRBK) 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.12564430
title: Dataset: SR Bancorp, Inc. (SRBK) 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.