cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0181366.10fu
title: SH0181366.10FU

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/sh0181367.10fu
title: SH0181367.10FU

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/sh0181368.10fu
title: SH0181368.10FU

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/sh0181369.10fu
title: SH0181369.10FU

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/sh0181370.10fu
title: SH0181370.10FU

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/sh0181371.10fu
title: SH0181371.10FU

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/sh0181372.10fu
title: SH0181372.10FU

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/sh0181373.10fu
title: SH0181373.10FU

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/sh0181374.10fu
title: SH0181374.10FU

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/sh0181375.10fu
title: SH0181375.10FU

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.3mpdz5
title: Occurrence Download

description: A dataset containing 24 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Pavonia candida (Moc. & Sessé ex DC.) Fryxell)",
 "BasisOfRecord is one of (Human Observation, Observation, Living Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Continent is North America"
 ]
}

 The dataset includes 24 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016499-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.23641/asha.28098206
title: Bilingual students’ Mandarin tone productions (Lin et al., 2025)

description: <b>Purpose: </b>This study investigates how Mandarin–English bilingual students in Canada produce Mandarin tones and how this is influenced by factors such as tone complexity, cross-linguistic influences, and speech input.<b>Method: </b>Participants were 82 students enrolled in a Chinese bilingual program in Western Canada. Students were recruited from Grades 1, 3, and 5 and divided into two groups based on their home language backgrounds: The heritage language group had early and strong input in Mandarin, and the second language (L2) group received mostly English input at home. Single-word tone productions were audio-recorded and transcribed by Mandarin-native listeners for match (accuracy) and pattern analyses. Acoustic measurements were extracted to provide phonetic details.<b>Results: </b>First, Tone3 (dipping tone) was challenging across groups due to its complexity. Second, L2 students’ productions were more influenced by English as a nontonal language and showed signs of categorical confusion. Third, increased tone match rates were related to both home input and school input, but bilingual students did not reach more than 90% of match rates in Grade 5. Instead, L2 students produced phonetic features less accurately in higher grades. This was attributed to reduced pronunciation instruction and limited home input.<b>Conclusions: </b>Bilingual students’ speech development in a minority language indicates unique influences of home and school input but also the universal influences of tone complexity. This study provides evidence for bilingual speech theories in the suprasegmental domain and has implications for the pedagogy of a minority language in the context of bilingual education.<b>Supplemental Material S1. </b>Mean duration of tone productions in each subgroup to convert equal normalized durations to differentiated normalized durations.<b>Supplemental Material S2.</b> Details of the selected optimal logistic mixed model for tone match.<b>Supplemental Material S3.</b> Details of the selected optimal GAMM for <i>F</i>0 contours.<b>Supplemental Material S4.</b> Details of the selected optimal linear mixed model for tone duration.Lin, Y., Pollock, K. E., & Li, F. (2025). Speech production of Mandarin lexical tones among Canadian elementary students enrolled in Mandarin–English bilingual schools. <i>Journal of Speech, Language, and Hearing Research</i>, <i>68</i>(2), 435–455. https://doi.org/10.1044/2024_JSLHR-24-00150
DOI: 10.23641/asha.28098206.v1
title: Bilingual students’ Mandarin tone productions (Lin et al., 2025)

description: <b>Purpose: </b>This study investigates how Mandarin–English bilingual students in Canada produce Mandarin tones and how this is influenced by factors such as tone complexity, cross-linguistic influences, and speech input.<b>Method: </b>Participants were 82 students enrolled in a Chinese bilingual program in Western Canada. Students were recruited from Grades 1, 3, and 5 and divided into two groups based on their home language backgrounds: The heritage language group had early and strong input in Mandarin, and the second language (L2) group received mostly English input at home. Single-word tone productions were audio-recorded and transcribed by Mandarin-native listeners for match (accuracy) and pattern analyses. Acoustic measurements were extracted to provide phonetic details.<b>Results: </b>First, Tone3 (dipping tone) was challenging across groups due to its complexity. Second, L2 students’ productions were more influenced by English as a nontonal language and showed signs of categorical confusion. Third, increased tone match rates were related to both home input and school input, but bilingual students did not reach more than 90% of match rates in Grade 5. Instead, L2 students produced phonetic features less accurately in higher grades. This was attributed to reduced pronunciation instruction and limited home input.<b>Conclusions: </b>Bilingual students’ speech development in a minority language indicates unique influences of home and school input but also the universal influences of tone complexity. This study provides evidence for bilingual speech theories in the suprasegmental domain and has implications for the pedagogy of a minority language in the context of bilingual education.<b>Supplemental Material S1. </b>Mean duration of tone productions in each subgroup to convert equal normalized durations to differentiated normalized durations.<b>Supplemental Material S2.</b> Details of the selected optimal logistic mixed model for tone match.<b>Supplemental Material S3.</b> Details of the selected optimal GAMM for <i>F</i>0 contours.<b>Supplemental Material S4.</b> Details of the selected optimal linear mixed model for tone duration.Lin, Y., Pollock, K. E., & Li, F. (2025). Speech production of Mandarin lexical tones among Canadian elementary students enrolled in Mandarin–English bilingual schools. <i>Journal of Speech, Language, and Hearing Research</i>, <i>68</i>(2), 435–455. https://doi.org/10.1044/2024_JSLHR-24-00150
DOI: 10.5281/zenodo.14799940
title: Supplementary Data for "Incorporating Community Knowledge into Analysis of Air Quality Monitoring Network Data"

description: These are the underlying data sets needed to perform the peak analysis and create the land-use regression (LUR) models described in the paper. There are four datasets:



"RAMP_Location.csv": Locations and IDs of the low-cost sensors used in this work. [NOTE: latitudes and longitudes for the sensor deployments have been intentionally rounded to protect the location of volunteer sensor hosts.]

"RAMP_data.zip": This contains the csv files of calibrated PM2.5, NO, NO2, CO and O3 measurements for the entire study period across all low-cost sensor sites.

"Vancouver_Population_Density_2016.zip": Shapefile of the population within each Dissemination Area from the 2016 Canadian Census. This information was originally extracted from the Canadian Census Analyser supported by the University of Toronto.

"smell_van_data.csv": Contains the locations, date, and description of odor reports during the monitoring period from the Smell Vancouver website (https://smell-vancouver.ca)


There is also sample code in Python to perform the peak analysis and create the LURs. [NOTE: we have intentionally excluded uploading the exact data sets imported by this code; our original data contains exact locations of sensor host volunteers and thus cannot be shared.]



"Peak_analysis_geohealth.py": A Python script to perform the peak analysis from the paper.

"LUR_strathcona_geohealth.py": A Python script to create the LURs and maps of LUR results from the paper.


Links to other data used in the code from publicly available sources:



Railway locations - https://opendata.vancouver.ca/explore/dataset/railways/information/

Public streets - https://opendata.vancouver.ca/explore/dataset/public-streets/information/

Land use - https://open-data-portal-metrovancouver.hub.arcgis.com/datasets/metrovancouver::landuse-2016-code-description/about

Bus stops - https://abacus.library.ubc.ca/dataset.xhtml?persistentId=hdl:11272.1/AB2/QQLSCJ

Block outlines - https://opendata.vancouver.ca/explore/dataset/block-outlines/information/
DOI: 10.5281/zenodo.14799941
title: Supplementary Data for "Incorporating Community Knowledge into Analysis of Air Quality Monitoring Network Data"

description: These are the underlying data sets needed to perform the peak analysis and create the land-use regression (LUR) models described in the paper. There are four datasets:



"RAMP_Location.csv": Locations and IDs of the low-cost sensors used in this work. [NOTE: latitudes and longitudes for the sensor deployments have been intentionally rounded to protect the location of volunteer sensor hosts.]

"RAMP_data.zip": This contains the csv files of calibrated PM2.5, NO, NO2, CO and O3 measurements for the entire study period across all low-cost sensor sites.

"Vancouver_Population_Density_2016.zip": Shapefile of the population within each Dissemination Area from the 2016 Canadian Census. This information was originally extracted from the Canadian Census Analyser supported by the University of Toronto.

"smell_van_data.csv": Contains the locations, date, and description of odor reports during the monitoring period from the Smell Vancouver website (https://smell-vancouver.ca)


There is also sample code in Python to perform the peak analysis and create the LURs. [NOTE: we have intentionally excluded uploading the exact data sets imported by this code; our original data contains exact locations of sensor host volunteers and thus cannot be shared.]



"Peak_analysis_geohealth.py": A Python script to perform the peak analysis from the paper.

"LUR_strathcona_geohealth.py": A Python script to create the LURs and maps of LUR results from the paper.


Links to other data used in the code from publicly available sources:



Railway locations - https://opendata.vancouver.ca/explore/dataset/railways/information/

Public streets - https://opendata.vancouver.ca/explore/dataset/public-streets/information/

Land use - https://open-data-portal-metrovancouver.hub.arcgis.com/datasets/metrovancouver::landuse-2016-code-description/about

Bus stops - https://abacus.library.ubc.ca/dataset.xhtml?persistentId=hdl:11272.1/AB2/QQLSCJ

Block outlines - https://opendata.vancouver.ca/explore/dataset/block-outlines/information/
DOI: 10.15468/dl.ysghnb
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Pavonia malacophylla (Link & Otto) Hemsl.)",
 "BasisOfRecord is one of (Human Observation, Observation, Living Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Continent is North America"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016501-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cwcnrr
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Pavonia pleuranthera (Moc. & Sessé ex DC.) Fryxell)",
 "BasisOfRecord is one of (Human Observation, Observation, Living Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Continent is North America"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016502-250127130748423/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.28351895.v1
title: Figure 1 - concatenated marker gene phylogeny

description: Files for the concatenated marker gene phylogeny of the Nitrospirales, shown in Kop et al.
DOI: 10.15468/dl.kvuv5q
title: Occurrence Download

description: A dataset listing the 67 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is Endemic vascular plants of the Ukrainian Carpathians"
 ]
}

 The dataset's 67 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016492-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.