cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.13988150
title: Unique Property Reference Number (UPRN) indicator: Tree canopy coverage (UPRN_3_1)

description: This is an indicator with the tree canopy coverage for various distances (15m, 25m, 150m, 300m and 500m) from Unique Property Refence Numbers (UPRNs) in the Office for National Statistics (ONS) UPRN directory v2024.07 (Epoch 111). This metric is based on Bluesky’s National Tree Map™, which is the only tree dataset to include trees in Great Britain and the Republic of Ireland that are 3 metres and taller.

Available files



UPRN_3_1_tree_canopy_coverage_cm_with_coords.csv: covers the Cheshire and Merseyside region (England) and includes latitude and longitude for each UPRN.

UPRN_3_1_tree_canopy_coverage_cm.csv: covers the Cheshire and Merseyside region (England).

UPRN_3_1_tree_canopy_coverage_lothian_with_coords.csv: covers the Lothian region (Scotland) and includes latitude and longitude for each UPRN.

UPRN_3_1_tree_canopy_coverage_lothian.csv: covers the Cheshire and Merseyside region (England).


 

Fields






Column name



Description





UPRN



Unique Property Reference Number as per the Office for National Statistics UPRN Directory (ONSUD) v2024.07 (Epoch 111).





n_trees_15m



Number of trees (above 3m) within 15m from the UPRN.





tree_canopy_cover_15m



Percentage of area  covered by tree canopy within 15m from the UPRN. From a maximum area of approximately 707m2.





n_trees_25m



Number of trees (above 3m) within 25m from the UPRN.





tree_canopy_cover_25m



Percentage of area covered by tree canopy within 25m from the UPRN. From a maximum area of approximately 1963m2.





n_trees_150m



Number of trees (above 3m) within 150m from the UPRN.





tree_canopy_cover_150m



Percentage of area  covered by tree canopy within 150m from the UPRN. From a maximum area of approximately 70686m2.





n_trees_300m



Number of trees (above 3m) within 300m from the UPRN.





tree_canopy_cover_300m



Percentage of area  covered by tree canopy within 300m from the UPRN. From a maximum area of approximately 282743m2.





n_trees_500m



Number of trees (above 3m) within 500m from the UPRN.





tree_canopy_cover_500m



Percentage of area  covered by tree canopy within 500m from the UPRN. From a maximum area of approximately 785398m2.





latitude (only version with coordinates)



Latitude of the UPRN, given in decimal degrees, where N is positive and S is negative.





longitude (only version with coordinates)



Longitude of the UPRN, given in decimal degrees, where E is positive and W is negative.





 

Regions

Cheshire and Merseyside (Endgland)

Includes the following local authorities:



Cheshire East

Cheshire West and Chester

Halton

Knowsley

Liverpool

Sefton

St. Helens

Warrington

Wirral


 

Lothian (Scotland)

Includes the following local authorities:



East Lothian

City of Edinburgh

Midlothian

Westlothian
DOI: 10.5281/zenodo.13988151
title: Unique Property Reference Number (UPRN) indicator: Tree canopy coverage (UPRN_3_1)

description: This is an indicator with the tree canopy coverage for various distances (15m, 25m, 150m, 300m and 500m) from Unique Property Refence Numbers (UPRNs) in the Office for National Statistics (ONS) UPRN directory v2024.07 (Epoch 111). This metric is based on Bluesky’s National Tree Map™, which is the only tree dataset to include trees in Great Britain and the Republic of Ireland that are 3 metres and taller.

Available files



UPRN_3_1_tree_canopy_coverage_cm_with_coords.csv: covers the Cheshire and Merseyside region (England) and includes latitude and longitude for each UPRN.

UPRN_3_1_tree_canopy_coverage_cm.csv: covers the Cheshire and Merseyside region (England).

UPRN_3_1_tree_canopy_coverage_lothian_with_coords.csv: covers the Lothian region (Scotland) and includes latitude and longitude for each UPRN.

UPRN_3_1_tree_canopy_coverage_lothian.csv: covers the Cheshire and Merseyside region (England).


 

Fields






Column name



Description





UPRN



Unique Property Reference Number as per the Office for National Statistics UPRN Directory (ONSUD) v2024.07 (Epoch 111).





n_trees_15m



Number of trees (above 3m) within 15m from the UPRN.





tree_canopy_cover_15m



Percentage of area  covered by tree canopy within 15m from the UPRN. From a maximum area of approximately 707m2.





n_trees_25m



Number of trees (above 3m) within 25m from the UPRN.





tree_canopy_cover_25m



Percentage of area covered by tree canopy within 25m from the UPRN. From a maximum area of approximately 1963m2.





n_trees_150m



Number of trees (above 3m) within 150m from the UPRN.





tree_canopy_cover_150m



Percentage of area  covered by tree canopy within 150m from the UPRN. From a maximum area of approximately 70686m2.





n_trees_300m



Number of trees (above 3m) within 300m from the UPRN.





tree_canopy_cover_300m



Percentage of area  covered by tree canopy within 300m from the UPRN. From a maximum area of approximately 282743m2.





n_trees_500m



Number of trees (above 3m) within 500m from the UPRN.





tree_canopy_cover_500m



Percentage of area  covered by tree canopy within 500m from the UPRN. From a maximum area of approximately 785398m2.





latitude (only version with coordinates)



Latitude of the UPRN, given in decimal degrees, where N is positive and S is negative.





longitude (only version with coordinates)



Longitude of the UPRN, given in decimal degrees, where E is positive and W is negative.





 

Regions

Cheshire and Merseyside (Endgland)

Includes the following local authorities:



Cheshire East

Cheshire West and Chester

Halton

Knowsley

Liverpool

Sefton

St. Helens

Warrington

Wirral


 

Lothian (Scotland)

Includes the following local authorities:



East Lothian

City of Edinburgh

Midlothian

Westlothian
DOI: 10.5281/zenodo.7884614
title: Spatially explicit re-harmonized terrestrial carbon densities for calibrating Integrated human-Earth System Models

description: Soil and vegetation carbon densities play a critical role in global and regional human-Earth system models. These densities affect variables such as land use change emissions and also influence land use change pathways under climate mitigation scenarios where terrestrial carbon is assigned a carbon price. Recently, more spatially explicit, fine resolution data have become available for both soil and vegetation carbon. However, for models to effectively use these data the fine resolution data need to be reharmonized to initial land use and land cover conditions represented by these models. Without such reharmonization the carbon values may be very inaccurate for particular land types and places where the source data and the model disagree on the land use/cover type. Here we present reharmonized soil and vegetation carbon densities both at the grid cell level at 5 arcmin resolution and also aggregated to 235 water sheds for 4 different land use and 15 land cover types. These data are particularly useful as initial land carbon conditions for global Multisectoral Dynamic Models (MSD). Moreover, these data include six different statistical states calculated using distinct resampling methods for each of the land use, land cover types. These statistical states are used to define a range of possible carbon values for each land classification, and any state can be used for defining initial conditions of soil and vegetation carbon in MSD models. We make use of these statistical states to calculate spatially distinct uncertainties in the carbon densities by land type. We have implemented these data in a state-of-the-art multi sector dynamics model, namely the Global Change Analysis Model (GCAM), and show that these new data improve several land use responses in the model, especially when terrestrial carbon is assigned a carbon price. The statistical states in our data are validated against similar estimates in the literature both at a grid cell level and at a regional level. 

This is a data record which corresponds to the paper "Spatially explicit re-harmonized terrestrial carbon densities for calibrating Integrated Multisectoral Models" (Narayan et al. 2023, under review)

We have now also added a tabular version of the dataset aggregated to GTAP's AEZ definitions as opposed to GCAM's GLUs
DOI: 10.5281/zenodo.7884615
title: Spatially explicit re-harmonized terrestrial carbon densities for calibrating Integrated human-Earth System Models

description: Soil and vegetation carbon densities play a critical role in global and regional human-Earth system models. These densities affect variables such as land use change emissions and also influence land use change pathways under climate mitigation scenarios where terrestrial carbon is assigned a carbon price. Recently, more spatially explicit, fine resolution data have become available for both soil and vegetation carbon. However, for models to effectively use these data the fine resolution data need to be reharmonized to initial land use and land cover conditions represented by these models. Without such reharmonization the carbon values may be very inaccurate for particular land types and places where the source data and the model disagree on the land use/cover type. Here we present reharmonized soil and vegetation carbon densities both at the grid cell level at 5 arcmin resolution and also aggregated to 235 water sheds for 4 different land use and 15 land cover types. These data are particularly useful as initial land carbon conditions for global Multisectoral Dynamic Models (MSD). Moreover, these data include six different statistical states calculated using distinct resampling methods for each of the land use, land cover types. These statistical states are used to define a range of possible carbon values for each land classification, and any state can be used for defining initial conditions of soil and vegetation carbon in MSD models. We make use of these statistical states to calculate spatially distinct uncertainties in the carbon densities by land type. We have implemented these data in a state-of-the-art multi sector dynamics model, namely the Global Change Analysis Model (GCAM), and show that these new data improve several land use responses in the model, especially when terrestrial carbon is assigned a carbon price. The statistical states in our data are validated against similar estimates in the literature both at a grid cell level and at a regional level. This is a data record which corresponds to the paper "Spatially explicit re-harmonized terrestrial carbon densities for calibrating Integrated Multisectoral Models" (Narayan et al. 2023, in prep)
DOI: 10.5281/zenodo.13988221
title: ptychadena_nilotica_zanfona_1.fasta.gz
DOI: 10.5281/zenodo.13988222
title: ptychadena_nilotica_zanfona_1.fasta.gz
DOI: 10.5281/zenodo.13988229
title: BILINGUAL EDUCATION – ANALYZING ITS ROLE IN COGNITIVE AND LANGUAGE DEVELOPMENT
DOI: 10.5281/zenodo.13988230
title: BILINGUAL EDUCATION – ANALYZING ITS ROLE IN COGNITIVE AND LANGUAGE DEVELOPMENT
DOI: 10.15468/dl.bsxr6p
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Cyclocarya paliurus (Batalin) Iljinsk.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Specimen, Material citation, Material sample)"
 ]
 }
 }
 ]
}

 The dataset includes 12 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000587-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u6syue
title: Occurrence Download

description: A dataset containing 48 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Leitneria floridana Chapm., Leitneria pilosa J.A.Schrad. & W.R.Graves)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Specimen, Material citation, Material sample)"
 ]
 }
 }
 ]
}

 The dataset includes 48 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000588-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yugga4
title: Occurrence Download

description: A dataset containing 61 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Erythrolamprus taeniurus (Tschudi, 1845)"
 ]
}

 The dataset includes 61 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000589-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fpsz7w
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Chenopodium nesodendron Skottsb.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Specimen, Material citation, Material sample)"
 ]
 }
 }
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000590-241024112534372/datasets/export for details.
DOI: 10.5281/zenodo.13988242
title: SHARQ ALLOMALARI QARASHLARIDA EMOTSIONAL INTELLEKT
DOI: 10.5281/zenodo.13988243
title: SHARQ ALLOMALARI QARASHLARIDA EMOTSIONAL INTELLEKT
DOI: 10.15468/dl.dxeq6n
title: Occurrence Download

description: A dataset containing 49 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Monopsis flava (C.Presl) E.Wimm."
 ]
}

 The dataset includes 49 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000592-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nyv7ga
title: Occurrence Download

description: A dataset containing 4498 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Flora of Japan Specimen Database"
 ]
}

 The dataset includes 4498 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000593-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13784989
title: Unique Property Reference Number (UPRN) indicator: Flood risk (UPRN_1_1)

description: This indicator covers three main flooding risks in the UK: fluvial (rivers and streams), coastal and surface water. The indicators were computed for all the Unique Property Reference Numbers (UPRNs) in the NHS Cheshire and Merseyside Integrated Care Board region (North West England). This region is formed by the following Local Authorities: Chester and Cheshire East, Cheshire West, Halton, Knowsley, Liverpool, Sefton, St. Helens, Warrington and Wirral.
DOI: 10.5281/zenodo.13784990
title: Unique Property Reference Number (UPRN) indicator: Flood risk (UPRN_1_1)

description: This indicator covers three main flooding risks in the UK: fluvial (rivers and streams), coastal and surface water. The indicators were computed for all the Unique Property Reference Numbers (UPRNs) in the NHS Cheshire and Merseyside Integrated Care Board region (North West England). This region is formed by the following Local Authorities: Chester and Cheshire East, Cheshire West, Halton, Knowsley, Liverpool, Sefton, St. Helens, Warrington and Wirral.
DOI: 10.15468/dl.ufrukx
title: Occurrence Download

description: A dataset containing 223 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Fossil",
 "DatasetKey is University of Florida Vertebrate Paleontology",
 "Geometry POLYGON((-107.93135 5.07156,-75.28542 5.07156,-86.13935 23.37179,-103.72327 19.12261,-107.93135 5.07156))",
 "TaxonKey is Mammalia"
 ]
}

 The dataset includes 223 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000594-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2697vx
title: Occurrence Download

description: A dataset listing the 47216 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-78.33285 -7.36320,-54.11840 -7.36320,-54.11840 2.31800,-78.33285 2.31800,-78.33285 -7.36320))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset's 47216 records were derived from 571 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000585-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25345/c5qf8jx08
title: MassIVE MSV000096198 - SysQuan: repurposing SILAC mice for affordable absolute quantitation of the human proteome
title: We have repurposed SILAC mouse tissues/biofluids as system-wide internal standards for matched human samples to enable absolute quantitation (AbsQuan) of theoretically &gt;2/3 of the human proteome using 132,380 shared tryptic peptides. We demonstrate that SysQuan enables quantifying 70% and 31% of the largest liver and plasma reference proteomes, respectively. We exemplify for 14 metabolic proteins that abundant standard isotope labeled mouse tissues enable cost-effective reverse AbsQuan in - theoretically 1000s of - human samples. Moreover, 10,000s of light/heavy doublets in untargeted SysQuan datasets enable unique post-acquisition AbsQuan.
DOI: 10.15468/dl.94k8j9
title: Occurrence Download

description: A dataset containing 1037 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Halesia carolina L., Halesia diptera J.Ellis ex L.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Specimen, Material citation, Material sample)"
 ]
 }
 }
 ]
}

 The dataset includes 1037 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000596-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.623k22
title: Occurrence Download

description: A dataset containing 8085 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Artocarpus altilis (Parkinson) Fosberg"
 ]
}

 The dataset includes 8085 records from 319 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000598-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13988250
title: HARBIY XIZMATCHILARNI O'Q OTISH TAYYORGARLIGI – BU O'QITISHNING TASHKILLASHTIRILGAN JARAYONI
DOI: 10.5281/zenodo.13988251
title: HARBIY XIZMATCHILARNI O'Q OTISH TAYYORGARLIGI – BU O'QITISHNING TASHKILLASHTIRILGAN JARAYONI
DOI: 10.5281/zenodo.5142647
title: Articles on PC extraction: subject areas, countries, relatives NER/LRA and A/P

description: Relative number of articles in each technological route (<em>Saponification, Solvent Extraction, Transesterification, Molecular distillation, Supercritical CO<sub>2,,</sub>Ultrasonic-assisted</em>), by <strong>Main Subject Areas (</strong>In terms of peer-reviewed articles from the Scopus database) and <strong>Prominent Countries </strong>(In terms of publications, considering the Scopus and WoS mix), on October 27, 2020. The last two columns estimate the ratio between the relative weights of the New Experimental Results and the Literature Review Articles, and between articles and patents on policosanol extraction.
description: Work conducted during a scholarship supported by the Institutional Sandwich Doctorate Program Abroad (PDSE) at the Federal University of Bahia (UFBA), Salvador, Brazil, and University of Valladolid (UVA), Palencia, Spanish. This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (Capes) - Finance Code 001.
DOI: 10.5281/zenodo.5153942
title: Studies and patents on policosanol extraction: main subject areas, prominent countries, relatives NER/LRA and LRA/P

description: Relative number of articles on policosanol extraction in each technological route (<em>Saponification, Solvent Extraction, Transesterification, Molecular distillation, Supercritical CO<sub>2,,</sub>Ultrasonic-assisted</em>), by Main Subject Areas<strong> (i</strong>n terms of peer-reviewed articles from the Scopus database) and Prominent Countries<strong> </strong>(In terms of publications, considering the Scopus and WoS mix).. The last two columns estimate the ratio between the relative weights of the New Experimental Results (NER) and the Literature Review Articles (LRA), and between articles and patents on policosanol extraction. The Ibero-American countries surveyed (with available databases) are, in alphabetical order of acronyms: AR - Argentina, BR - Brazil, CL - Chile, CO - Colombia, CR - Cota Rica, CU - Cuba, DO - Dominican Republic, EC - Ecuador, ES - Spain, GT - Guatemala, HN - Honduras, MX - Mexico, NI - Nicaragua, PA - Panama, PE - Peru, PT - Portugal, SV - El Salvador, UY - Uruguay. The data from Bolivia, Haiti, Paraguay and Venezuela are unavailable. Work conducted during a scholarship supported by the Institutional Sandwich Doctorate Program Abroad (PDSE) at the Federal University of Bahia (UFBA), Salvador, Brazil, and University of Valladolid (UVA), Palencia, Spanish.
description: Salvador, Bahia; Vilafranca del Penedès, Barcelona: CEALA, 2021. Acknowledgment: To Questel, for the kind permission to use and free training of the Orbit. To the University of Valladolid for receiving us, support and training. To MsC D. Kouloukoui, MsC F. Santos, MsC D. Silva and Me. S. Talabante for technical advice. Funding: This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (Capes) - Finance Code 001.
DOI: 10.25810/s7n-vh24.56
title: African Newspaper Coverage of Climate Change or Global Warming, 2004-2024 September 2024

description: The Media and Climate Change Observatory Data monitors 117 sources (across newspapers, radio and TV) in 55 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://sciencepolicy.colorado.edu/media_coverage.
DOI: 10.15468/dl.xrh954
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Erythrolamprus vitti (Dixon, 2000)"
 ]
}

 The dataset includes 25 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000603-241024112534372/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.