cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0197193.10fu
title: SH0197193.10FU

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/sh0197194.10fu
title: SH0197194.10FU

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/sh0197195.10fu
title: SH0197195.10FU

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/sh0197196.10fu
title: SH0197196.10FU

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/sh0197197.10fu
title: SH0197197.10FU

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/sh0197198.10fu
title: SH0197198.10FU

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/sh0197199.10fu
title: SH0197199.10FU

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/sh0197200.10fu
title: SH0197200.10FU

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/sh0197201.10fu
title: SH0197201.10FU

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.qgnn8x
title: Occurrence Download

description: A dataset containing 166 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Hoplopagrus guentherii Gill, 1862",
 "Year 2006-2021"
 ]
}

 The dataset includes 166 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000985-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7y4d8m
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pseudotolithus mitsukurii Jordan & Snyder, 1900",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000986-250213122211068/datasets/export for details.
DOI: 10.26093/cds/vizier.36890185
title: JWST/MIRI HR 2562 B images

description: VizieR online Data Catalogue associated with article published in journal Astronomy and Astrophysics with title ' A new atmospheric characterization of the sub-stellar companion HR 2562 B with JWST/MIRI observations.' (bibcode: 2024A&A...689A.185G)
DOI: 10.26093/cds/vizier.36910299
title: Massive star-forming galaxies from JWST and ALMA

description: VizieR online Data Catalogue associated with article published in journal Astronomy and Astrophysics with title ' The structure of massive star-forming galaxies from JWST and ALMA: Dusty, high redshift disk galaxies.' (bibcode: 2024A&A...691A.299G)
DOI: 10.26093/cds/vizier.36910300
title: XMM-SERVS X-ray eXtended Galaxy Cluster catalog

description: VizieR online Data Catalogue associated with article published in journal Astronomy and Astrophysics with title ' XMM-SERVS X-ray eXtended Galaxy Cluster (XVXGC) catalog.' (bibcode: 2024A&A...691A.300X)
DOI: 10.15468/dl.5ym2ha
title: Occurrence Download

description: A dataset containing 370 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Phocoena phocoena (Linnaeus, 1758)",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 370 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000987-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14867903
title: scGeneAI pbmc scATAC dataset
DOI: 10.5281/zenodo.14867904
title: scGeneAI pbmc scATAC dataset
DOI: 10.15468/dl.ncp4jy
title: Occurrence Download

description: A dataset containing 527 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Trachemys dorbigni (Duméril & Bibron, 1835)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 527 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000988-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u3gskr
title: Occurrence Download

description: A dataset containing 469916 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Geometry POLYGON((-85.85 39.42,-69.53 39.42,-69.53 42.38,-85.85 42.38,-85.85 39.42))",
 "HasCoordinate is true",
 "License is one of (CC0 1.0, CC-BY 4.0, CC-BY-NC 4.0)",
 "OccurrenceStatus is Present",
 "TaxonKey is Fungi"
 ]
}

 The dataset includes 469916 records from 178 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000977-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eznkas
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Delphinus phocoena Linnaeus, 1758",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000989-250213122211068/datasets/export for details.
DOI: 10.3886/e219323
title: HUD Data: Low-Income Housing Tax Credit (LIHTC): Property Level Data

description: HUD's LIHTC database contains information on 53,032 projects and 3.65 million housing units placed in service between 1987 and 2022. Data for properties placed in service in 2023 will be collected in the fall of 2024 and added to this database in the spring of 2025. The database includes project address, number of units and low-income units, number of bedrooms, year the credit was allocated, year the project was placed in service, whether the project was new construction or rehab, type of credit provided, and other sources of project financing. The database has been geocoded, enabling researchers to look at the geographical distribution and neighborhood characteristics of tax credit projects. It may also help show how incentives to locate projects in low-income areas and other underserved markets are working. With the continued support of the national LIHTC database, HUD hopes to enable researchers to learn more about the effects of the tax credit program.<br>Summary of filesIn the zip file:LIHTC Data Dictionary 2022.PDF - The data dictionary for the LIHTC database (multiple address data use same formats) in Adobe Acrobat.LIHTCPUB.ACCDB - The LIHTC Database in MS Access format. This file also includes building addresses from HUD’s LIHTC tenant data collection.LIHTCPUB.CSV - The LIHTC Database in CSV format.<br>missing data.PDF - Percent of Projects with Missing Data by Variable and Year Placed in Service<br><br>
description: Virtually all variables are missing in at least a few cases. See the missing data.pdf document <br>
description: property level data for tax credit programs.
DOI: 10.3886/e219323v1
title: HUD Data: Low-Income Housing Tax Credit (LIHTC): Property Level Data

description: HUD's LIHTC database contains information on 53,032 projects and 3.65 million housing units placed in service between 1987 and 2022. Data for properties placed in service in 2023 will be collected in the fall of 2024 and added to this database in the spring of 2025. The database includes project address, number of units and low-income units, number of bedrooms, year the credit was allocated, year the project was placed in service, whether the project was new construction or rehab, type of credit provided, and other sources of project financing. The database has been geocoded, enabling researchers to look at the geographical distribution and neighborhood characteristics of tax credit projects. It may also help show how incentives to locate projects in low-income areas and other underserved markets are working. With the continued support of the national LIHTC database, HUD hopes to enable researchers to learn more about the effects of the tax credit program.<br>Summary of filesIn the zip file:LIHTC Data Dictionary 2022.PDF - The data dictionary for the LIHTC database (multiple address data use same formats) in Adobe Acrobat.LIHTCPUB.ACCDB - The LIHTC Database in MS Access format. This file also includes building addresses from HUD’s LIHTC tenant data collection.LIHTCPUB.CSV - The LIHTC Database in CSV format.<br>missing data.PDF - Percent of Projects with Missing Data by Variable and Year Placed in Service<br><br>
description: Virtually all variables are missing in at least a few cases. See the missing data.pdf document <br>
description: property level data for tax credit programs.
DOI: 10.5281/zenodo.14867928
title: Leaf water potential and meteorological data for three semi-arid tree species in west Texas

description: Data collected for Juniperius ashei, Quercus laceii, and Pinus remota near Rocksprings, Texas. Data includes continuous, half-hourly meteorological and soil moisture data alongside discrete leaf water potential observations.
DOI: 10.5281/zenodo.14867929
title: Leaf water potential and meteorological data for three semi-arid tree species in west Texas

description: Data collected for Juniperius ashei, Quercus laceii, and Pinus remota near Rocksprings, Texas. Data includes continuous, half-hourly meteorological and soil moisture data alongside discrete leaf water potential observations.
DOI: 10.5281/zenodo.14867937
title: Leaf water potential and meteorological data for three semi-arid tree species in west Texas

description: Data collected for Juniperius ashei, Quercus laceii, and Pinus remota near Rocksprings, Texas. Data includes continuous, half-hourly meteorological and soil moisture data alongside discrete leaf water potential observations.
DOI: 10.15468/dl.5h873k
title: Occurrence Download

description: A dataset containing 190 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Callionymus curvicornis Valenciennes, 1837",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 190 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000991-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25910/mk2j-2b44
title: Soil Moisture daily data for the Llara Landscape Rehydration Project

description: Landscape rehydration is a method that aims to regenerate the agricultural landsacpe while remaining productive. This dataset consists of data from uncalibrated soil moisture probes installed at Llara in Narrabri on the landscape rehydration project. The data is collected from 32 soil moisture probes in two 40 ha experimental pasture fields down to 1m20 and 1m60 depth and summarised to daily values. The two fields called Weir West and Weir East consist of one half "control" and one half "treatment" where landscape rehydration practices have been implemented. The data covers 2022 - 2024, but will be updated over time.
DOI: 10.15468/dl.sx4wpn
title: Occurrence Download

description: A dataset containing 105 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Repomucenus curvicornis (Valenciennes, 1837)",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 105 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000993-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pwn4r5
title: Occurrence Download

description: A dataset containing 1450 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-94.64328 15.68271,-92.79476 15.50466,-92.60991 17.27796,-91.22352 18.15837,-87.34164 18.94696,-87.43407 22.14862,-96.67664 25.0281,-100.83581 25.7795,-103.42373 28.33083,-106.56621 31.06019,-112.29661 31.06019,-118.90135 31.64599,-114.72963 22.27761,-98.83737 14.55714,-94.64328 15.68271))",
 "HasGeospatialIssue is false",
 "TaxonKey is Leopardus pardalis (Linnaeus, 1758)"
 ]
}

 The dataset includes 1450 records from 50 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000992-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14852864
title: Long-Term Performance of Six Air Sensor Types

description: From July 2019 until January 2021, six models of air sensors were operated at seven air quality monitoring sites across the U.S. in Phoenix, Arizona, Denver, Colorado, Wilmington, Delaware, Decatur, Georgia, Research Triangle Park, North Carolina, Oklahoma City, Oklahoma, and Milwaukee, Wisconsin. Sensors testing included the Aeroqual AQY, Clarity Node, Clarity Node-S, Applied Particle Technology Maxima, PurpleAir PA-II-SD, Sensit RAPM, and Aerodyne Arisense. This dataset includes the raw datasets from the sensors and was used in the paper "Evaluation of Long-Term Performance of Six PM2.5 Sensor Types".
DOI: 10.5281/zenodo.14852865
title: Long-Term Performance of Six Air Sensor Types

description: From July 2019 until January 2021, six models of air sensors were operated at seven air quality monitoring sites across the U.S. in Phoenix, Arizona, Denver, Colorado, Wilmington, Delaware, Decatur, Georgia, Research Triangle Park, North Carolina, Oklahoma City, Oklahoma, and Milwaukee, Wisconsin. Sensors testing included the Aeroqual AQY, Clarity Node, Clarity Node-S, Applied Particle Technology Maxima, PurpleAir PA-II-SD, Sensit RAPM, and Aerodyne Arisense. This dataset includes the raw datasets from the sensors and was used in the paper "Evaluation of Long-Term Performance of Six PM2.5 Sensor Types".
DOI: 10.15468/dl.k8a6y9
title: Occurrence Download

description: A dataset containing 36 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Atopsyche lobosa Ross & King, 1952"
 ]
}

 The dataset includes 36 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000995-250213122211068/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.