cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1399614.10fu
title: SH1399614.10FU

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/sh1399620.10fu
title: SH1399620.10FU

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/sh1399624.10fu
title: SH1399624.10FU

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/sh1399633.10fu
title: SH1399633.10FU

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/sh1399634.10fu
title: SH1399634.10FU

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/sh1399639.10fu
title: SH1399639.10FU

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/sh1399640.10fu
title: SH1399640.10FU

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.w3886y
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Psilocybe ningshanensis (Hymenogastraceae, Agaricales), a new species from China"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004905-240202131308920/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xawkyy
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034890-180508205500799/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yym24v
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025113-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8ezbsh
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034936-180508205500799/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bvixse
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025120-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ibbd1d
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034910-180508205500799/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h9tpih
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025123-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wlsrao
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034925-180508205500799/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m5w86g
title: Occurrence Download

description: A dataset containing 1542408043 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1542408043 records from 27542 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0226814-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17012278
title: A Longitudinal Dataset for Machine Learning-Based Student Retention Analysis in Bangladeshi STEM Higher Education

description: Educational data mining in Bangladesh has been limited by the absence of localized, longitudinal datasets suitable for machine learning-based retention analysis. This dataset provides anonymized academic records of 3,762 Computer Science and Engineering (CSE) students from Leading University, Sylhet, Bangladesh, spanning 16 years from Spring 2010 to Spring 2025.

The dataset includes 11 attributes covering student demographics, semester-wise academic performance (CGPA, credits completed), admission cohort, and an engineered retention status label (Graduate/Eligible, In Progress, Dropout) derived through cohort-based classification rules. Baseline machine learning benchmarks are provided using six standard classifiers with 5-fold cross-validation, achieving a predictive accuracy of 77.7% and an AUC of 0.82 for dropout prediction. Statistical analysis also confirms a significant rise in female student enrollment and academic performance over the 16-year period (p < 0.001).

This resource addresses a critical gap in localized longitudinal datasets for educational data mining in developing-country STEM contexts. It is intended to support researchers and policymakers in developing Early Warning Systems (EWS), predictive retention models, and data-driven strategies to strengthen higher education in Bangladesh.

This dataset accompanies the paper "A Longitudinal Dataset for Machine Learning-Based Student Retention Analysis in Bangladeshi STEM Higher Education," accepted at the 2026 IEEE 2nd International Conference on Quantum Photonics, Artificial Intelligence, and Networking (QPAIN), 16–18 April 2026, Chittagong, Bangladesh.
DOI: 10.5281/zenodo.17012279
title: A Longitudinal Dataset for Machine Learning-Based Student Retention Analysis in Bangladeshi STEM Higher Education

description: Educational data mining in Bangladesh has been limited by the absence of localized, longitudinal datasets suitable for machine learning-based retention analysis. This dataset provides anonymized academic records of 3,762 Computer Science and Engineering (CSE) students from Leading University, Sylhet, Bangladesh, spanning 16 years from Spring 2010 to Spring 2025.

The dataset includes 11 attributes covering student demographics, semester-wise academic performance (CGPA, credits completed), admission cohort, and an engineered retention status label (Graduate/Eligible, In Progress, Dropout) derived through cohort-based classification rules. Baseline machine learning benchmarks are provided using six standard classifiers with 5-fold cross-validation, achieving a predictive accuracy of 77.7% and an AUC of 0.82 for dropout prediction. Statistical analysis also confirms a significant rise in female student enrollment and academic performance over the 16-year period (p < 0.001).

This resource addresses a critical gap in localized longitudinal datasets for educational data mining in developing-country STEM contexts. It is intended to support researchers and policymakers in developing Early Warning Systems (EWS), predictive retention models, and data-driven strategies to strengthen higher education in Bangladesh.

This dataset accompanies the paper "A Longitudinal Dataset for Machine Learning-Based Student Retention Analysis in Bangladeshi STEM Higher Education," accepted at the 2026 IEEE 2nd International Conference on Quantum Photonics, Artificial Intelligence, and Networking (QPAIN), 16–18 April 2026, Chittagong, Bangladesh.
DOI: 10.15468/dl.r3sucf
title: Occurrence Download

description: A dataset containing 716 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Blechnum occidentale",
 "Country is Colombia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 716 records from 65 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004621-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e246221
title: Department of Nursing Sciences, University of Maiduguri, Maiduguri, Borno State.2026/2027 Admission Form/Application Form Is Out Call the Registrar (09024168245)09024168245(09024168245) For More Details On How To Apply And Register Online.

description: Department of Nursing Sciences, University of Maiduguri, Maiduguri, Borno State.2026/2027 Admission Form/Application Form Is Out Call the Registrar (09024168245)09024168245(09024168245) For More Details On How To Apply And Register Online. The Management Of The School Hereby Inform The general Public On The Sales Of The General Nursing Admission Form Into The School Of Nursing, And Also The Sales Of Two (2) Years Post Basic Nursing Program. Contact The Educational Board Admin On (09024168245) For More Details On How To Purchase The Form And Register Online. REQUIREMENT FOR THE THREE YEARS GENERAL NURSING PROGRAMMES1. GENERAL NURSING PROGRAMME Admission Requirements Candidates For Admission Into The General Nursing Program Of The Nursing And Midwifery Council Of Nigeria Must Posses The …
DOI: 10.15468/dl.r5bc6k
title: Occurrence Download

description: A dataset listing the 1 species recorded in GBIF matching the query:
{
 "TaxonKey" : [
 "is Plantae"
 ]
}

 The dataset's 1 records were derived from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004601-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7t9bm4
title: Occurrence Download

description: A dataset containing 38161 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Barnea",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 38161 records from 218 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004622-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qznqa8
title: Occurrence Download

description: A dataset containing 586307 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Insect Species Occurrence Data from Multiple Projects Worldwide with Focus on Bees and Wasps in North America"
 ]
}

 The dataset includes 586307 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004604-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tjxdun
title: Occurrence Download

description: A dataset containing 29 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-113.81297 53.29425,-113.14144 53.29425,-113.14144 53.77038,-113.81297 53.77038,-113.81297 53.29425))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Anaxyrus hemiophrys"
 ]
}

 The dataset includes 29 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004623-260221153910048/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.31395576
title: Mitochondrial genome for IMR-90 cell line

description: Mitochondrial genome for the IMR-90 cell line
DOI: 10.6084/m9.figshare.31395576.v1
title: Mitochondrial genome for IMR-90 cell line

description: Mitochondrial genome for the IMR-90 cell line
DOI: 10.15468/dl.spz9s3
title: Occurrence Download

description: A dataset containing 351 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "StateProvince is Tamaulipas",
 "TaxonKey is Senna"
 ]
}

 The dataset includes 351 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004625-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e246222
title: College of Nursing Sciences, UMTH, Maiduguri, Borno State.2026/2027 Admission Form/Application Form Is Out Call the Registrar (09024168245)09024168245(09024168245) For More Details On How To Apply And Register Online.

description: College of Nursing Sciences, UMTH, Maiduguri, Borno State.2026/2027 Admission Form/Application Form Is Out Call the Registrar (09024168245)09024168245(09024168245) For More Details On How To Apply And Register Online. The Management Of The School Hereby Inform The general Public On The Sales Of The General Nursing Admission Form Into The School Of Nursing, And Also The Sales Of Two (2) Years Post Basic Nursing Program. Contact The Educational Board Admin On (09024168245) For More Details On How To Purchase The Form And Register Online. REQUIREMENT FOR THE THREE YEARS GENERAL NURSING PROGRAMMES1. GENERAL NURSING PROGRAMME Admission Requirements Candidates For Admission Into The General Nursing Program Of The Nursing And Midwifery Council Of Nigeria Must Posses The …
DOI: 10.48580/dgwql
title: Lista Vermelha da Flora Vascular de Portugal Continental
DOI: 10.48580/dgwqm
title: Typification of two names in the genera Euonymus L. and Glyptopetalum Thwaites and the correct taxonomic position of Hippocratea angulata Griff. (Celastraceae)
DOI: 10.48580/dgwqn
title: A new synonym of Neottia alternifolia (King & Pantl.) Szlach. (Orchidaceae) and lectotypification of its basionym
DOI: 10.48580/dgwqp
title: Three new species of Gnomoniopsis and Ternstroemiomyces (Diaporthales, Sordariomycetes) from China
DOI: 10.15468/dl.2zsbq8
title: Occurrence Download

description: A dataset containing 1330 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Boa constrictor",
 "Country is Colombia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1330 records from 158 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004624-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sdrm36
title: Occurrence Download

description: A dataset containing 7494 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ligidium",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 7494 records from 105 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004626-260221153910048/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.