cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.uhqej8
title: Occurrence Download

description: A dataset containing 66124 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON((19.97998 49.98249,20.25957 49.98249,20.25957 50.13537,19.97998 50.13537,19.97998 49.98249))"
 ]
}

 The dataset includes 66124 records from 89 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024440-240626123714530/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.26303371
title: Informal Leadership and Inclusion in an Informal Subgroup of Managers and Group Effectiveness

description: This study considered: (1) the role manager’s inclusion in an informal subgroup within work groups plays in their informal leadership and (2) direct and indirect connections of informal leadership of managers with group social effectiveness and performance effectiveness. Forty-nine work groups (<i>N</i> = 290 employees) participated. The study was conducted using the GROUP PROFILE (GP) computer program (Sidorenkov & Pavlenko, 2015), which included questionnaires for measuring informal leadership, PE and SE, as well as a formalized algorithm for identifying informal subgroups within a work group, integrated with the corresponding questionnaires.23-28-00099
DOI: 10.6084/m9.figshare.26303371.v1
title: Informal Leadership and Inclusion in an Informal Subgroup of Managers and Group Effectiveness

description: This study considered: (1) the role manager’s inclusion in an informal subgroup within work groups plays in their informal leadership and (2) direct and indirect connections of informal leadership of managers with group social effectiveness and performance effectiveness. Forty-nine work groups (<i>N</i> = 290 employees) participated. The study was conducted using the GROUP PROFILE (GP) computer program (Sidorenkov & Pavlenko, 2015), which included questionnaires for measuring informal leadership, PE and SE, as well as a formalized algorithm for identifying informal subgroups within a work group, integrated with the corresponding questionnaires.23-28-00099
DOI: 10.15468/dl.gmvh24
title: Occurrence Download

description: A dataset listing the 4014931 species recorded in GBIF matching the query:
{ }

 The dataset's 4014931 records were derived from 74944 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024430-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cwdj5h
title: Occurrence Download

description: A dataset containing 2132 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "OccurrenceStatus is Present",
 "TaxonKey is Morus L."
 ]
}

 The dataset includes 2132 records from 58 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024441-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3hq4d9
title: Occurrence Download

description: A dataset containing 115 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Wollemia nobilis W.G.Jones et al."
 ]
}

 The dataset includes 115 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024442-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yusqae
title: Occurrence Download

description: A dataset containing 188 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ascotis imparata (Walker, 1860)"
 ]
}

 The dataset includes 188 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024443-240626123714530/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.26264708
title: Data support for “Forecasting sea surface temperature during typhoon events in the Bohai Sea using spatiotemporal neural networks”

description: Numerical forecasting data in paper “Forecasting sea surface temperature during typhoon events in the Bohai Sea using spatiotemporal neural networks”.See also inHailun He, Benyun Shi, Yingjian Hao, Liu Feng, Xinyan Lyu, Zheng Ling. Forecasting sea surface temperature during typhoon events in the Bohai Sea using spatiotemporal neural networks. Atmospheric Research, 2024: 107578.https://doi.org/10.1016/j.atmosres.2024.107578<br><br>
DOI: 10.15468/dl.hn6nrq
title: Occurrence Download

description: A dataset containing 704 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cherax quadricarinatus (von Martens, 1868)"
 ]
}

 The dataset includes 704 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024445-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6t58wk
title: Occurrence Download

description: A dataset containing 257 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Wodyetia bifurcata A.K.Irvine"
 ]
}

 The dataset includes 257 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024446-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n8bpc3
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is South Africa",
 "OccurrenceStatus is Present",
 "TaxonKey is Bifiditermes Krishna, 1961"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024447-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fpa52r
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((117.13776 -40.63868,187.86224 -40.63868,187.86224 -12.36132,117.13776 -12.36132,117.13776 -40.63868))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Westringia grandifolia F.Muell. ex Benth."
 ]
}

 The dataset includes 19 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024448-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13120/5784540a-982a-477d-a9ff-ff39b576fab9
title: Baltic Sea - Contaminants aggregated datasets 1972/2021 v2024
title: Baltic_Sea_Contaminants_aggregated_datasets_1972/2021_v2024

description: EMODnet Chemistry aims to provide access to marine chemistry datasets and derived data products concerning eutrophication, acidity and contaminants. The importance of the selected substances and other parameters relates to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on potential hazardous substances, despite the fact that some data might not be related to pollution (e.g. collected by deep corer). Temperature, salinity and additional parameters are included when available. It covers the Baltic Sea. Data were harmonised and validated by the ‘Swedish Meteorological and Hydrological Institute (SMHI)’ in Sweden. 
The dataset contains water, sediment and biota profiles. The temporal coverage is 1987–2021 for water measurements, 1974–2021 for sediment measurements and 1972-2021 for biota measurements.
Regional datasets concerning contaminants are automatically harvested and the resulting collections are harmonised and validated using ODV Software and following a common methodology for all sea regions ( https://doi.org/10.6092/8b52e8d7-dc92-4305-9337-7634a5cae3f4). Parameter names are based on P01 vocabulary, which relates to BODC Parameter Usage Vocabulary and is available at: https://vocab.nerc.ac.uk/search_nvs/P01/.
The harmonised dataset can be downloaded as as an ODV spreadsheet, which is composed of a metadata header followed by tab separated values. This spreadsheet can be imported into ODV Software for visualisation (more information can be found at: https://www.seadatanet.org/Software/ODV). In addition, the same dataset is offered also as a txt file in a long/vertical format, in which each P01 measurement is a record line. Additionally, there are a series of columns that split P01 terms into subcomponents (substance, CAS number, matrix...).This transposed format is more adapted to worksheet applications (e.g. LibreOffice Calc).
DOI: 10.15468/dl.vcgb3s
title: Occurrence Download

description: A dataset containing 138 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-180 60, -180 90, 180 90, 180 60, -180 60))"
 ]
}

 The dataset includes 138 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024444-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13120/7937cf99-f2a8-44d6-8a72-1732e09e8570
title: Arctic Ocean - Eutrophication and Acidity aggregated datasets 1923/2023 v2024
title: Arctic_Ocean_aggregated_eutrophication_and_acidity_datasets_1923-2023_v2024

description: EMODnet Chemistry aims to provide access to marine chemistry datasets and derived data products concerning eutrophication, acidity and contaminants. The importance of the selected substances and other parameters relates to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on eutrophication and acidity, and covers the Norwegian Sea, Barents Sea, Greenland Sea and Icelandic Waters. Data were aggregated and quality controlled by 'Institute of Marine Research - Norwegian Marine Data Centre (NMD)' in Norway.
ITS-90 water temperature and water body salinity variables have also been included ('as are') to complete the eutrophication and acidity data. If you use these variables for calculations, please refer to SeaDataNet for the quality flags: https://www.seadatanet.org/Products/Aggregated-datasets.
Regional datasets concerning eutrophication and acidity are automatically harvested, and the resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all sea regions ( https://doi.org/10.13120/8xm0-5m67). Parameter names are based on P35 vocabulary, which relates to EMODnet Chemistry aggregated parameter names and is available at: https://vocab.nerc.ac.uk/search_nvs/P35/.
When not present in original data, water body nitrate plus nitrite was calculated by summing all nitrate and nitrite parameters. The same procedure was applied for water body dissolved inorganic nitrogen (DIN), which was calculated by summing all nitrate, nitrite, and ammonium parameters. Concentrations per unit mass were converted to a unit volume using a constant density of 1.25 kg/L.
The aggregated dataset can also be downloaded as an ODV collection and spreadsheet, which is composed of a metadata header followed by tab separated values. This spreadsheet can be imported to ODV Software for visualisation (more information can be found at: https://www.seadatanet.org/Software/ODV).
DOI: 10.13120/353c90c6-dbfe-49e7-a572-5691acde4014
title: North East Atlantic Ocean - Contaminants aggregated datasets 1966/2022 v2024
title: North_East_Atlantic_Ocean_Contaminants_aggregated_datasets_1966/2022_v2024

description: EMODnet Chemistry aims to provide access to marine chemistry datasets and derived data products concerning eutrophication, acidity and contaminants. The importance of the selected substances and other parameters relates to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on potential hazardous substances, despite the fact that some data might not be related to pollution (e.g. collected by deep corer). Temperature, salinity and additional parameters are included when available. It covers the Northeast Atlantic Ocean (40W). Data were harmonised and validated by the '‘IFREMER / IDM / SISMER - Scientific Information Systems for the SEA’ in France.
The dataset contains water (profiles), sediment (profiles and timeseries) and biota (timeseries). The temporal coverage is 1974–2018 for water measurements, 1966–2020 for sediment measurements and 1979–2022 for biota measurements.
Regional datasets concerning contaminants are automatically harvested and the resulting collections are harmonised and validated using ODV Software and following a common methodology for all sea regions ( https://doi.org/10.6092/8b52e8d7-dc92-4305-9337-7634a5cae3f4). Parameter names are based on P01 vocabulary, which relates to BODC Parameter Usage Vocabulary and is available at: https://vocab.nerc.ac.uk/search_nvs/P01/.
The harmonised dataset can be downloaded as as an ODV spreadsheet, which is composed of a metadata header followed by tab separated values. This spreadsheet can be imported into ODV Software for visualisation (more information can be found at: https://www.seadatanet.org/Software/ODV). In addition, the same dataset is offered also as a txt file in a long/vertical format, in which each P01 measurement is a record line. Additionally, there are a series of columns that split P01 terms into subcomponents (substance, CAS number, matrix...).This transposed format is more adapted to worksheet applications (e.g. LibreOffice Calc).
DOI: 10.15468/dl.7unn2c
title: Occurrence Download

description: A dataset containing 3722 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((107.07345 -42.55635,184.92655 -42.55635,184.92655 -11.44365,107.07345 -11.44365,107.07345 -42.55635))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Corymbia trachyphloia (F.Muell.) K.D.Hill & L.A.S.Johnson"
 ]
}

 The dataset includes 3722 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024449-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13120/7b7a4443-3135-4fc8-ad48-664b8dfd7e75
title: Black Sea - Eutrophication and Acidity aggregated datasets 1935/2023 v2024
title: Black_Sea_-_Eutrophication_and_Acidity_aggregated_datasets_1935/2023_v2024

description: EMODnet Chemistry aims to provide access to marine chemistry datasets and derived data products concerning eutrophication, acidity and contaminants. The importance of the selected substances and other parameters relates to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on eutrophication and acidity, and covers the Black Sea, Marmara Sea and Sea of Azov. Data were aggregated and quality controlled by 'National Institute for Marine Research and Development 'Grigore Antipa' in Romania.
ITS-90 water temperature and water body salinity variables have also been included ('as are') to complete the eutrophication and acidity data. If you use these variables for calculations, please refer to SeaDataNet for the quality flags: https://www.seadatanet.org/Products/Aggregated-datasets.
Regional datasets concerning eutrophication and acidity are automatically harvested, and the resulting collections are aggregated and quality controlled using ODV Software and following a common methodology for all sea regions ( https://doi.org/10.13120/8xm0-5m67). Parameter names are based on P35 vocabulary, which relates to EMODnet Chemistry aggregated parameter names and is available at: https://vocab.nerc.ac.uk/search_nvs/P35/.
When not present in original data, water body nitrate plus nitrite was calculated by summing all nitrate and nitrite parameters. The same procedure was applied for water body dissolved inorganic nitrogen (DIN), which was calculated by summing all nitrate, nitrite, and ammonium parameters. Concentrations per unit mass were converted to a unit volume using a constant density of 1.25 kg/L.
The aggregated dataset can also be downloaded as an ODV collection and spreadsheet, which is composed of a metadata header followed by tab separated values. This spreadsheet can be imported to ODV Software for visualisation (more information can be found at: https://www.seadatanet.org/Software/ODV).
DOI: 10.5281/zenodo.12720545
title: Benchmark x-ray computed tomography datasets of glass and carbon fibre-reinforced composites at varying resolution, noise and contrast levels

description: Both glass fibre-reinforced polymer (GFRP) and carbon fibre-reinforced polymer (CFRP) samples are imaged as high and low contrast datasets respectively. The GFRP comprises unidirectional E-glass non-crimp fabric embedded in epoxy using vacuum-assisted resin transfer moulding (VARTM). The layup involves stitched 0 degree unidirectional bundles (tex=600g/km) to low tex 90 degree backing bundles. The CFRP, also manufactured through VARTM, features low tex stitched backing bundles of glass fibres instead of carbon fibres.

The benchmark x-ray CT scans were acquired using a Zeiss Versa 520 scanner at the Henry Moseley X-ray Imaging Facility. Each scan yielded cubical volume datasets, which were extracted in two formats: full-field scans (Glass 1, Glass 2, Glass 3, Glass 4) and sub-volumes (Glass 1 - Sub, Glass 2 - Sub, Glass 3 - Sub, Glass 4 - Sub). The sub-volumes correspond to the same material region-of-interest (RoI) and have been appropriately cropped.
DOI: 10.5281/zenodo.12720546
title: Benchmark x-ray computed tomography datasets of glass and carbon fibre-reinforced composites at varying resolution, noise and contrast levels

description: Both glass fibre-reinforced polymer (GFRP) and carbon fibre-reinforced polymer (CFRP) samples are imaged as high and low contrast datasets respectively. The GFRP comprises unidirectional E-glass non-crimp fabric embedded in epoxy using vacuum-assisted resin transfer moulding (VARTM). The layup involves stitched 0 degree unidirectional bundles (tex=600g/km) to low tex 90 degree backing bundles. The CFRP, also manufactured through VARTM, features low tex stitched backing bundles of glass fibres instead of carbon fibres.

The benchmark x-ray CT scans were acquired using a Zeiss Versa 520 scanner at the Henry Moseley X-ray Imaging Facility. Each scan yielded cubical volume datasets, which were extracted in two formats: full-field scans (Glass 1, Glass 2, Glass 3, Glass 4) and sub-volumes (Glass 1 - Sub, Glass 2 - Sub, Glass 3 - Sub, Glass 4 - Sub). The sub-volumes correspond to the same material region-of-interest (RoI) and have been appropriately cropped.
DOI: 10.5281/zenodo.12743155
title: Benchmark x-ray computed tomography datasets of glass and carbon fibre-reinforced composites at varying resolution, noise and contrast levels

description: Both glass fibre-reinforced polymer (GFRP) and carbon fibre-reinforced polymer (CFRP) samples are imaged as high and low contrast datasets respectively. The GFRP comprises unidirectional E-glass non-crimp fabric embedded in epoxy using vacuum-assisted resin transfer moulding (VARTM). The layup involves stitched 0 degree unidirectional bundles (tex=600g/km) to low tex 90 degree backing bundles. The CFRP, also manufactured through VARTM, features low tex stitched backing bundles of glass fibres instead of carbon fibres.

The benchmark x-ray CT scans were acquired using a Zeiss Versa 520 scanner at the Henry Moseley X-ray Imaging Facility. Each scan yielded cubical volume datasets, which were extracted in two formats: full-field scans (Glass 1, Glass 2, Glass 3, Glass 4) and sub-volumes (Glass 1 - Sub, Glass 2 - Sub, Glass 3 - Sub, Glass 4 - Sub). The sub-volumes correspond to the same material region-of-interest (RoI) and have been appropriately cropped.
DOI: 10.13120/6bfed137-5135-4091-bc9e-120b985138f7
title: Greater North Sea and Celtic Seas - Contaminants aggregated datasets 1973/2021 v2024
title: Greater_North_Sea_Contaminants_aggregated_datasets_1973/2021_v2024

description: EMODnet Chemistry aims to provide access to marine chemistry datasets and derived data products concerning eutrophication, acidity and contaminants. The importance of the selected substances and other parameters relates to the Marine Strategy Framework Directive (MSFD). This aggregated dataset contains all unrestricted EMODnet Chemistry data on potential hazardous substances, despite the fact that some data might not be related to pollution (e.g. collected by deep corer). Temperature, salinity and additional parameters are included when available. It covers the Greater North Sea and Celtic Seas. Data were harmonised and validated by the 'Aarhus University, Department of Bioscience, Marine Ecology Roskilde' in Denmark.
The dataset contains water (profiles), sediment (profiles) and biota (profiles and timeseries). The temporal coverage is 1970–2021 for water measurements, 1973–2021 for sediment measurements and 1979–2021 for biota measurements.
Regional datasets concerning contaminants are automatically harvested and the resulting collections are harmonised and validated using ODV Software and following a common methodology for all sea regions ( https://doi.org/10.6092/8b52e8d7-dc92-4305-9337-7634a5cae3f4). Parameter names are based on P01 vocabulary, which relates to BODC Parameter Usage Vocabulary and is available at: https://vocab.nerc.ac.uk/search_nvs/P01/.
The harmonised dataset can be downloaded as as an ODV spreadsheet, which is composed of a metadata header followed by tab separated values. This spreadsheet can be imported into ODV Software for visualisation (more information can be found at: https://www.seadatanet.org/Software/ODV). In addition, the same dataset is offered also as a txt file in a long/vertical format, in which each P01 measurement is a record line. Additionally, there are a series of columns that split P01 terms into subcomponents (substance, CAS number, matrix...).This transposed format is more adapted to worksheet applications (e.g. LibreOffice Calc).
DOI: 10.15468/dl.mu54yf
title: Occurrence Download

description: A dataset containing 2196 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Vitex trifolia L."
 ]
}

 The dataset includes 2196 records from 122 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024450-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.