cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3974901
title: Dataset: Impact of tall buildings and building-height variability on flow within and above a complex urban canopy in London - Part II

description: This dataset contains Part II of a series of wind-tunnel flow measurements in a 1:200 scale model of a part of the London Borough of Southwark. Part I of the dataset is also published on Zenodo. The data published here (Part II) accompanies analyses in Hertwig et al. (2020):


D. Hertwig, S. Grimmond, S. Kotthaus, C. Vanderwel, H. Gough, M. Haefferlin, A. Robins (2020), "Variability of Physical Meteorology in Urban Areas at Different Scales: Implications for Air Quality", Faraday Discussions, DOI: 10.1039/D0FD00098A .


Flow measurements (based on 2D Laser Doppler Anemometry) were carried out in the boundary-layer wind-tunnel facility of the Environmental Flow (EnFlo) Research Centre, University of Surrey, UK, using the EPSRC MAGIC project model domain and scale model (Song et al., 2018).


This repository contains:



	
wt_ts_part_II_readme.pdf:  Meta information and description of data in 'wt_ts_part_II_data.zip'
	
wt_ts_part_II_data.zip:  Flow measurements (time series and statistics)
description: This research was funded by NERC AirPro (NE/N00700X/1), EPSRC Refresh (EP/K021893/1), EPSRC LoHCool (EP/N009797/1) and by the UK China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund (projects: "High Res City" (AJYG-DX4P1V) and "Next Generation Cities" (P107731)).
DOI: 10.15468/dl.fm9cxy
title: Occurrence Download

description: A dataset containing 1132 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Allenrolfea Kuntze)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1132 records from 94 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007120-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k2jf6z
title: Occurrence Download

description: A dataset containing 6322 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Geotrygon mystacea (Temminck, 1811)"
 ]
}

 The dataset includes 6322 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007122-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.2563699
title: Dataset: Impact of tall buildings and building-height variability on flow within and above a complex urban canopy in London - Part I

description: This dataset contains the first part of a series of wind-tunnel flow measurements in a 1:200 scale model of a part of the London Borough of Southwark. The data published here accompanies analyses in Hertwig et al. (2019):


D. Hertwig, H.L. Gough, S. Grimmond, J.F. Barlow, C.W. Kent, W.E. Lin, A.G. Robins, P. Hayden (2019), "Wake Characteristics of Tall Buildings in a Realistic Urban Canopy", Boundary-Layer Meteorology, DOI: 10.1007/s10546-019-00450-7.


Flow measurements (based on 2D Laser Doppler Anemometry) were carried out in the boundary-layer wind-tunnel facility of the Environmental Flow (EnFlo) Research Centre, University of Surrey, UK, using the EPSRC MAGIC project model domain and scale model (Song et al., 2018).


This repository contains:



	
wt_ts_part_I_readme.pdf:  Meta information and description of data in 'wt_ts_part_I_data.zip'
	
wt_ts_part_I_data.zip:  Flow measurements (time series and statistics)
description: This research was funded by NERC AirPro (NE/N00700X/1), EPSRC Refresh (EP/K021893/1), EPSRC LoHCool (EP/N009797/1) and by the UK China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund (High Res City; AJYG-DX4P1V).
DOI: 10.5281/zenodo.2563700
title: Dataset: Impact of tall buildings and building-height variability on flow within and above a complex urban canopy in London - Part I

description: This dataset contains the first part of a series of wind-tunnel flow measurements in a 1:200 scale model of a part of the London Borough of Southwark. The data published here accompanies analyses in Hertwig et al. (2019):


D. Hertwig, H.L. Gough, S. Grimmond, J.F. Barlow, C.W. Kent, W.E. Lin, A.G. Robins, P. Hayden (2019), "Wake Characteristics of Tall Buildings in a Realistic Urban Canopy", Boundary-Layer Meteorology, DOI: 10.1007/s10546-019-00450-7.


Flow measurements (based on 2D Laser Doppler Anemometry) were carried out in the boundary-layer wind-tunnel facility of the Environmental Flow (EnFlo) Research Centre, University of Surrey, UK, using the EPSRC MAGIC project model domain and scale model (Song et al., 2018).


This repository contains:



	
wt_ts_part_I_readme.pdf:  Meta information and description of data in 'wt_ts_part_I_data.zip'
	
wt_ts_part_I_data.zip:  Flow measurements (time series and statistics)
description: This research was funded by NERC AirPro (NE/N00700X/1), EPSRC Refresh (EP/K021893/1), EPSRC LoHCool (EP/N009797/1) and by the UK China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund (High Res City; AJYG-DX4P1V).
DOI: 10.15468/dl.j4f547
title: Occurrence Download

description: A dataset containing 10704 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hericium erinaceus (Bull.) Pers."
 ]
}

 The dataset includes 10704 records from 189 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007166-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6073/pasta/7be2d728797a8a8e74466c9fc56926f9
title: Harvard Forest Schoolyard LTER Data since 2004

description: In the Harvard Forest Schoolyard LTER program, HF ecologists work directly with teachers from public and private schools across New England (and the eastern U.S.) to learn about and initiate ecological research in their classrooms and schoolyards. More than 3500 students each year from grades 4-12 participate in authentic, field-based research projects that address current and important environmental issues. Projects to date have included tree phenology, the hemlock woolly adelgid, vernal pools, intermittent streams, and long-term forest plots. Participating schools submit data to an online database on the Harvard Forest website where the data are reviewed by HF staff and then made freely available for download and for graphing online. The project is supported by the LTER program at the National Science Foundation, the Highstead Foundation, the Salata Institute for Climate and Sustainability at Harvard University, and private donors.
 For current data, please see: https://harvardforest2.fas.harvard.edu/asp/hf/php/k12/k12_project.php.
DOI: 10.15468/dl.atcfaa
title: Occurrence Download

description: A dataset containing 30105 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Carpobrotus edulis (L.) N.E.Br.)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1945"
 ]
}

 The dataset includes 30105 records from 267 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007123-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tawej2
title: Occurrence Download

description: A dataset containing 62846 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is one of (Brazil, Argentina, Paraguay)",
 "TaxonKey is Chaetura meridionalis Hellmayr, 1907",
 "Year 1000-2024"
 ]
}

 The dataset includes 62846 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007105-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8wen6y
title: Occurrence Download

description: A dataset containing 104787 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Carduus nutans L.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 104787 records from 1178 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007151-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1048319.10fu
title: SH1048319.10FU

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/sh1048320.10fu
title: SH1048320.10FU

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/sh1048325.10fu
title: SH1048325.10FU

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/sh1048326.10fu
title: SH1048326.10FU

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/sh1048328.10fu
title: SH1048328.10FU

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/sh1048329.10fu
title: SH1048329.10FU

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/sh1048330.10fu
title: SH1048330.10FU

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/sh1048332.10fu
title: SH1048332.10FU

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/sh1048333.10fu
title: SH1048333.10FU

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/sh1048335.10fu
title: SH1048335.10FU

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.rdiytk
title: Occurrence Download

description: A dataset containing 24134145 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is Mexico"
 ]
}

 The dataset includes 24134145 records from 2061 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002339-171002173027117/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hs6dj4
title: Occurrence Download

description: A dataset containing 977638 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Russian Federation",
 "DatasetKey is EOD – eBird Observation Dataset"
 ]
}

 The dataset includes 977638 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000112-250225191816552/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hz7wvd
title: Occurrence Download

description: A dataset containing 182390 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mercurialis annua L.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 182390 records from 1412 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000109-250225191816552/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nkxsum
title: Occurrence Download

description: A dataset listing the 25 species recorded in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Evaluación de la ictiofauna en las áreas focales del corredor biológico costero-Yucatán",
 "Geometry POLYGON((-89.62983934193302 21.29158905511405,-89.62796901936913 21.29158905511405,-89.62796901936913 21.293459377677937,-89.62983934193302 21.293459377677937,-89.62983934193302 21.29158905511405))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset's 25 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000023-250225202704447/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9nxs2u
title: Occurrence Download

description: A dataset containing 71820014 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-2.44556 50.51677, -1.26494 50.57817, 0.24189 50.72991, 0.25811 50.73381, 0.96319 50.90358, 1.37454 51.1337, 1.38953 51.14678, 1.76337 52.49223, 1.76781 52.50904, 1.74921 52.59029, 1.72846 52.5967, 1.71658 52.59865, 1.70367 52.5991, 0.04255 52.53469, -2.41509 52.37072, -2.42787 52.36971, -2.43903 52.36675, -2.4493 52.36193, -2.45751 52.35611, -2.9545 51.93715, -2.96416 51.92191, -3.00608 51.83395, -3.10761 51.21385, -3.10354 51.20182, -3.09946 51.19489, -2.65222 50.66888, -2.4539 50.51722, -2.44556 50.51677))"
 ]
}

 The dataset includes 71820014 records from 1181 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000102-250225191816552/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.