cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.8h49ha
title: Occurrence Download

description: A dataset containing 97 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "Geometry POLYGON((-103.72377 18.15544,-102.88368 18.51141,-103.93735 20.31975,-104.49267 21.4019,-105.49822 25.78606,-108.7423 29.84675,-112.19752 25.6237,-108.35838 21.78456,-103.72377 18.15544))",
 "TaxonKey is Leopardus wiedii"
 ]
}

 The dataset includes 97 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001838-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e242793v1
title: An aggregated dataset of serially collected influenza A virus morbidity and titer measurements from virus-infected ferrets.

description: Data from influenza A virus (IAV) infected ferrets (Mustela putorius furo) provides invaluable information towards the study of novel and emerging viruses that pose a threat to human health. This gold standard animal model can recapitulate many clinical signs of infection present in IAV-infected humans, support virus replication of human and zoonotic strains without prior adaptation, and permit evaluation of virus transmissibility by multiple modes. While ferrets have been employed in risk assessment settings for &gt;20 years, results from this work are typically reported in discrete stand-alone publications, making aggregation of raw data from this work over time nearly impossible. Here, we describe a dataset of 746 ferrets inoculated with 129 unique IAV, conducted by a single research group (NCIRD/ID/IPB/Pathogenesis Laboratory Team) under a uniform experimental protocol. This collection of morbidity, mortality, and viral titer data represents the largest publicly available dataset to date of in vivo-generated IAV infection outcomes on a per-individual ferret level.

Published Data Descriptor for more information:
Kieran TJ, Sun X, Creager HM, Tumpey TM, Maine TR, Belser JA. 2024. An aggregated dataset of serial morbidity and titer measurements from influenza A virus-infected ferrets. Sci Data 11, 510. https://doi.org/10.1038/s41597-024-03256-6

Additional publications using and describing data:
Kieran TJ, Sun X, Maines TR, Beauchemin CAA, Belser JA. 2024. Exploring associations between viral titer measurements and disease outcomes in ferrets inoculated with 125 contemporary influenza A viruses. J Virol. 98:e01661-23. https://doi.org/10.1128/jvi.01661-23

Belser JA, Kieran TJ, Mitchell ZA, Sun X, Mayfield K, Tumpey TM, Spengler JR, Maines TR. 2024. Key considerations to improve the normalization, interpretation and reproducibility of morbidity data in mammalian models of viral disease. Dis Model Mech; 17 (3): dmm050511. https://doi.org/10.1242/dmm.050511

Kieran TJ, Sun X, Maines TR, Belser JA. 2024. Machine learning approaches for influenza A virus risk assessment identifies predictive correlates using ferret model in vivo data. Communications Biology 7, 927. https://doi.org/10.1038/s42003-024-06629-0

Additional publications supporting responsible use and interpretation of data by others:
Kieran TJ, Maine TR, Belser JA. 2025. Eleven quick tips to unlock the power of in vivo data science. PLoS Comput Biol, 21(4):e1012947. https://doi.org/10.1371/journal.pcbi.1012947

Kieran TJ, Maine TR, Belser JA. 2025. Data alchemy, from lab to insight: Transforming in vivo experiments into data science gold. PLoS Pathog, 20(8):e1012460. https://doi.org/10.1371/journal.ppat.1012460

Change / Update Log:
Nov 7, 2024: Corrected typographical errors in Origin column for A/Ohio/13/2017 and A/Hawaii/28/2020

July 1, 2025: Added 3 viruses (A/Texas/36/1991, A/Texas/37/2024, A/Michigan/90/2024, total n=18 new rows)
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description: (Downloaded 1/7/2026)
DOI: 10.15156/bio/sh0185858.10fu
title: SH0185858.10FU

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.18201791
title: Enhancing English Language Learning in Nigerian Secondary Schools Through Contextualized Teaching

description:  

Enhancing English Language Learning in Nigerian Secondary Schools Through Contextualized Teaching
DOI: 10.5281/zenodo.18201792
title: Enhancing English Language Learning in Nigerian Secondary Schools Through Contextualized Teaching

description:  

Enhancing English Language Learning in Nigerian Secondary Schools Through Contextualized Teaching
DOI: 10.15156/bio/sh0185859.10fu
title: SH0185859.10FU

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/sh0185860.10fu
title: SH0185860.10FU

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/sh0185861.10fu
title: SH0185861.10FU

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.kpd3kd
title: Occurrence Download

description: A dataset listing the 6671 species recorded in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Occurrence evidence, Machine Observation)",
 "OccurrenceStatus is Present",
 "StateProvince is one of (Illinois, Wisconsin, Missouri, Iowa, Indiana, Kentucky)",
 "TaxonKey is Plantae"
 ]
}

 The dataset's 6671 records were derived from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001833-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0185862.10fu
title: SH0185862.10FU

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/sh0185863.10fu
title: SH0185863.10FU

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/sh0185864.10fu
title: SH0185864.10FU

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/sh0185865.10fu
title: SH0185865.10FU

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/sh0185866.10fu
title: SH0185866.10FU

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: 10.34740/kaggle/dsv/14282758
title: BOS Kemdikbud
DOI: 10.15468/jrvu7n
title: A new species of the genus Comaroma in China (Araneae: Anapidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Zhang, Z. H., Z. F. Chen (1994): A new species of the genus Comaroma in China (Araneae: Anapidae). J. Hanhzhou Univ. (nat. Sci.) 21: 118-121, URL: http://antbase.org/ants/publications/ZhangChen1994/ZhangChen1994.pdfAbstractThis paper deals with a new species of the Anapidae collected from Zhejiang Province. All types are deposited in the department of Biology Hangzhou Normal College, Hangzhou.
DOI: 10.5281/zenodo.18045757
title: Données Expérimentales : Analyse Cinématique et Énergétique d'un Tronc de Cône sur Support Elliptique

description: Le Fichier Tracker : La capture du mouvement

Ce fichier est le point de départ de l'analyse du mouvement de la vidéo affiliée à cette publication. Dans cet espace, j'ai effectué un travail de métrologie pour effectuer les calculs futurs.

En définissant une échelle réelle sur la règle rendue visible sur la vidéo d'origine, ainsi qu'un repère au point le plus haut atteint par l'une des extrémités du tronc de cône, j'ai pu faire le pointage des 2502 images du début du mouvement, soit environ 42 secondes de vidéo.

Ce logiciel a servi de calculateur primaire pour extraire la vitesse angulaire et l'accélération angulaire (notées respectivement omega et alpha) ainsi que les différents éléments nécessaires à mes calculs.

Les Données XML

Ce fichier XML contient la structure brute de mes données Tracker. On y retrouve l'intégralité des coordonnées de chaque point de ta trajectoire, encapsulées dans un format universel. Sa grande force est l'interopérabilité : Il me permet d'importer mon travail dans un autre logiciel (Python, MATLAB ou R), ce qui garantit que les 2 502 points resteront inchangés, sans aucune perte de précision.
DOI: 10.5281/zenodo.18045758
title: Données Expérimentales : Analyse Cinématique et Énergétique d'un Tronc de Cône sur Support Elliptique

description: Le Fichier Tracker : La capture du mouvement

Ce fichier est le point de départ de l'analyse du mouvement de la vidéo affiliée à cette publication. Dans cet espace, j'ai effectué un travail de métrologie pour effectuer les calculs futurs.

En définissant une échelle réelle sur la règle rendue visible sur la vidéo d'origine, ainsi qu'un repère au point le plus haut atteint par l'une des extrémités du tronc de cône, j'ai pu faire le pointage des 2502 images du début du mouvement, soit environ 42 secondes de vidéo.

Ce logiciel a servi de calculateur primaire pour extraire la vitesse angulaire et l'accélération angulaire (notées respectivement omega et alpha) ainsi que les différents éléments nécessaires à mes calculs.

Les Données XML

Ce fichier XML contient la structure brute de mes données Tracker. On y retrouve l'intégralité des coordonnées de chaque point de ta trajectoire, encapsulées dans un format universel. Sa grande force est l'interopérabilité : Il me permet d'importer mon travail dans un autre logiciel (Python, MATLAB ou R), ce qui garantit que les 2 502 points resteront inchangés, sans aucune perte de précision.
DOI: 10.15468/dl.gehpqx
title: Occurrence Download

description: A dataset containing 85 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Birdrace-Die_Paradiesvögel-Herford"
 ]
}

 The dataset includes 85 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010199-160822134323880/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25582/data.2023-05.2815555/2366469
title: Data for EMSL Project 51287 from May 2023
DOI: 10.15468/dl.92hgyq
title: Occurrence Download

description: A dataset containing 739 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dipterocarpus grandiflorus (Blanco) Blanco"
 ]
}

 The dataset includes 739 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029799-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fqay7h
title: Occurrence Download

description: A dataset containing 56 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Spain",
 "GadmGid is ESP.1_1",
 "OccurrenceStatus is Present",
 "TaxonKey is Maytenus senegalensis (Lam.) Exell"
 ]
}

 The dataset includes 56 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052162-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25582/data.2023-05.2815556/2366470
title: Data for EMSL Project 51287 from May 2023
DOI: 10.15468/dl.su6xx7
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cryptogonimidae",
 "Country is India"
 ]
}

 The dataset includes 12 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010199-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.am9sgt
title: Occurrence Download

description: A dataset containing 1545 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Chaunax pictus Lowe, 1846"
 ]
}

 The dataset includes 1545 records from 58 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029846-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25582/data.2023-05.2815631/2366471
title: Data for EMSL Project 51287 from May 2023
DOI: 10.15468/dl.6azdva
title: Occurrence Download

description: A dataset containing 165 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Spain",
 "TaxonKey is Maytenus senegalensis (Lam.) Exell"
 ]
}

 The dataset includes 165 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052153-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qifxvz
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "BasisOfRecord is Human Observation",
 "BasisOfRecord is Specimen"
 ]
 },
 {
 "or" : [
 "Issue is Coordinate rounded",
 "Issue is Geodetic datum assumed WGS84"
 ]
 },
 "TaxonKey is Drosera adelae F.Muell."
 ]
}

 The dataset includes 17 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013197-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25582/data.2023-05.2815669/2366472
title: Data for EMSL Project 51287 from May 2023
DOI: 10.15468/dl.daqmk6
title: Occurrence Download

description: A dataset containing 8476 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Pitta sordida (Statius Muller, 1776)"
 ]
}

 The dataset includes 8476 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029768-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sskeq9
title: Occurrence Download

description: A dataset containing 2649774 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Spain",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 2649774 records from 464 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052208-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25582/data.2023-05.2815810/2366473
title: Data for EMSL Project 51287 from May 2023