cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.dgdrr2
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pasiphaea grandicula Burukovsky, 1976"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0128616-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vvcpzn
title: Occurrence Download

description: A dataset containing 784 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Aves)",
 "HasCoordinate is one of (true)",
 "Geometry POLYGON ((-73.18412 6.100767, -73.18507 6.100592, -73.18606 6.100475, -73.18728 6.100364, -73.18929 6.099864, -73.19064 6.098957, -73.19098 6.097999, -73.19092 6.097022, -73.19073 6.095489, -73.19148 6.094438, -73.19273 6.091243, -73.19791 6.090054, -73.19737 6.089016, -73.19759 6.08833, -73.19776 6.087727, -73.19779 6.087019, -73.19775 6.086401, -73.19762 6.086043, -73.19728 6.085587, -73.19752 6.085303, -73.19799 6.085096, -73.19845 6.085077, -73.19873 6.08509, -73.19924 6.084742, -73.19972 6.084475, -73.20008 6.084176, -73.2003 6.083864, -73.20043 6.083379, -73.2005 6.082977, -73.20073 6.082037, -73.20049 6.081411, -73.20036 6.08103, -73.20047 6.080461, -73.20049 6.08014, -73.20046 6.079643, -73.19898 6.07914, -73.1968 6.07831, -73.19238 6.076641, -73.18539 6.074244, -73.17461 6.07109, -73.17032 6.069734, -73.16747 6.080622, -73.16252 6.079778, -73.16069 6.079515, -73.16021 6.078001, -73.15792 6.077134, -73.1553 6.073089, -73.14806 6.066666, -73.147 6.075848, -73.14903 6.078148, -73.15026 6.081949, -73.15163 6.082983, -73.14707 6.086398, -73.14696 6.090578, -73.1548 6.094883, -73.15906 6.096774, -73.17046 6.096562, -73.17385 6.101428, -73.18412 6.100767))"
 ]
}

 The dataset includes 784 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072294-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m3z4q3
title: Occurrence Download

description: A dataset containing 2691870 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "Continent is Europe",
 "Year is greater than 1978",
 "Year is less than 2014",
 "HasGeospatialIssue is false",
 "TaxonKey is Erithacus rubecula (Linnaeus, 1758)"
 ]
}

 The dataset includes 2691870 records from 1250 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039077-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.feagny
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Madagascar",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Mantidactylus incognitus Scherz, Crottini, Hutter, Hildenbrand, Andreone, Fulgence, Köhler, Ndriantsoa, Ohler, Preick, Rakotoarison, Rancilhac, Raselimanana, Riemann, Rödel, Rosa, Streicher, Vieites, Köhler, Hofreiter, Glaw & Vences, 2022"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008522-240425142415019/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.c78fk4
title: Occurrence Download

description: A dataset containing 228 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-73.9313826000000063 42.8201374000000001, -73.9313826000000063 42.8230935300000013, -73.9313826000000063 42.8246419700000018, -73.9313826000000063 42.8266127200000000, -73.9313826000000063 42.8301319199999995, -73.9313826000000063 42.8323842100000007, -73.9313826000000063 42.8350587999999988, -73.9289865500000047 42.8350587999999988, -73.9265905000000032 42.8350587999999988, -73.9236306800000023 42.8350587999999988, -73.9208117999999956 42.8350587999999988, -73.9172882000000016 42.8350587999999988, -73.9172882000000016 42.8318211400000024, -73.9172882000000016 42.8291465499999973, -73.9172882000000016 42.8271757999999991, -73.9172882000000016 42.8243604399999995, -73.9172882000000016 42.8218266200000031, -73.9172882000000016 42.8201374000000001, -73.9209527400000042 42.8201374000000001, -73.9251810599999999 42.8201374000000001, -73.9281408899999946 42.8201374000000001, -73.9313826000000063 42.8201374000000001))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1932",
 "BasisOfRecord is one of (Human Observation, Living Specimen, Observation, Specimen, Machine Observation)"
 ]
}

 The dataset includes 228 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0101535-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mx7x9c
title: Occurrence Download

description: A dataset containing 35598 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Poa chaixii Vill."
 ]
}

 The dataset includes 35598 records from 442 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072303-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14064150
title: Data pertaining to 'Tauranga shallow groundwater monitoring, spatial observations and forecast conditions under sea-level rise'

description: Tauranga City in the North Island of New Zealand has many assets and infrastructure sitting on low-lying coastal land, where groundwater is unconfined and close to the surface. Shallow groundwater limits the volume of unsaturated ground available to store rain and runoff, promotes flooding and creates opportunities for infiltration into stormwater and wastewater networks. Groundwater levels are expected to rise as sea level rises, causing greater frequency of flooding and/or direct inundation once it nears the ground surface.  This zipped archive contains an ArcGIS 10.8 geodatabase generated from spatial analysis of data gathered from the Tauranga City Council's shallow groundwater monitoring network between 20/8/2015 and 13/8/2021. A series of statistical surfaces represent the 'present-day' water table elevation and depth to groundwater, and the response to tidal forcing.  Simple geometric models have been developed, following Cox et al. (2025 https://doi.org/10.1029/2024EF004977) methods, using the shape and position of the water table, combined with tidal fluctuations, to forecast the future state of median (p50), mean high water springs (mhws) and storm surge groundwater levels. Future forecast surfaces are provided at 10 cm increments of sea-level rise (up to 1 m), then 20 cm increments (from 1 to 2 m). The geometric models are strongly empirical, with many implicit assumptions and caveats – particularly, they do not account for groundwater flow and possible changes in water-budget mass balance. They assume groundwater will rise at the same rate as sea level, which is a ‘worst-case’ scenario (akin to a flux-controlled or recharge-limited end-member groundwater model). Although many variables and controlling processes are simplified into a single parameter of groundwater elevation, the projected groundwater levels highlight how local variations in water table shape and slope interact locally with the ground elevation or infrastructure networks. They are a first pass conservative analysis of groundwater-related contribution to hazard and how this will evolve over time. Data are provided under Creative Commons Attribution 4.0 (CC-BY-4.0) license without warranty. Further description of these data, and implications from the analysis, can be found in the metadata for individual layers and Cox (2025) GNS Science Report 2024/47 https://doi.org/10.21420/GDWW-6Z50.
DOI: 10.5281/zenodo.14064151
title: Data pertaining to 'Tauranga shallow groundwater monitoring, spatial observations and forecast conditions under sea-level rise'

description: Tauranga City in the North Island of New Zealand has many assets and infrastructure sitting on low-lying coastal land, where groundwater is unconfined and close to the surface. Shallow groundwater limits the volume of unsaturated ground available to store rain and runoff, promotes flooding and creates opportunities for infiltration into stormwater and wastewater networks. Groundwater levels are expected to rise as sea level rises, causing greater frequency of flooding and/or direct inundation once it nears the ground surface.  This zipped archive contains an ArcGIS 10.8 geodatabase generated from spatial analysis of data gathered from the Tauranga City Council's shallow groundwater monitoring network between 20/8/2015 and 13/8/2021. A series of statistical surfaces represent the 'present-day' water table elevation and depth to groundwater, and the response to tidal forcing.  Simple geometric models have been developed, following Cox et al. (2025 https://doi.org/10.1029/2024EF004977) methods, using the shape and position of the water table, combined with tidal fluctuations, to forecast the future state of median (p50), mean high water springs (mhws) and storm surge groundwater levels. Future forecast surfaces are provided at 10 cm increments of sea-level rise (up to 1 m), then 20 cm increments (from 1 to 2 m). The geometric models are strongly empirical, with many implicit assumptions and caveats – particularly, they do not account for groundwater flow and possible changes in water-budget mass balance. They assume groundwater will rise at the same rate as sea level, which is a ‘worst-case’ scenario (akin to a flux-controlled or recharge-limited end-member groundwater model). Although many variables and controlling processes are simplified into a single parameter of groundwater elevation, the projected groundwater levels highlight how local variations in water table shape and slope interact locally with the ground elevation or infrastructure networks. They are a first pass conservative analysis of groundwater-related contribution to hazard and how this will evolve over time. Data are provided under Creative Commons Attribution 4.0 (CC-BY-4.0) license without warranty. Further description of these data, and implications from the analysis, can be found in the metadata for individual layers and Cox (2025) GNS Science Report 2024/47 https://doi.org/10.21420/GDWW-6Z50.
DOI: 10.5281/zenodo.10225563
title: The 30 m land cover dataset for  capturing land cover changes  induced by ecological restoration  from 1990 to 2022 on the Chinese  Loess Plateau

description: Continuous time-series of land cover is critical for attributing runoff, sediment and carbon changes on the Chinese Loess Plateau (CLP). However, current land cover products with annal temporal resolution lack spatial identification accuracy, particularly in capturing authentic changes of cropland, forest and grassland. To address these issues, a 30 m annual land cover dataset was proposed by the Yellow River Conservancy Commission (YRCC_LPLC) for the CLP from 1990 to 2022. Different levels of land cover were classified using different combinations of spectral, monthly and annual temporal and topographic features and Random Forest classifier. Compared to other land cover products (45.64%–73.38%), the accuracy of YRCC_LPLC has a better performance with an overall accuracy of 85.16%. The YRCC_LPLC is capable of capturing not only the explicit spatial variation but also the change direction and change time of land cover, especially for the most critical conversion of cropland into forest and grassland induced by implementation of Grain to Green Program on the CLP.
DOI: 10.5281/zenodo.10225564
title: A 30 m annual land cover dataset of Chinese Loess Plateau from 1990 to 2020

description: Due to current published land cover products cannot accurately captured authentic vegetation type dynamic change induced by ecological restoration projects on Chinese Loess Plateau, the annual land cover of Chinese Loess Plateau from 1990 to 2020 was produced by Yellow River Conservancy Commission.
DOI: 10.5281/zenodo.14066899
title: The 30 m land cover dataset for  capturing land cover changes  induced by ecological restoration  from 1990 to 2022 on the Chinese  Loess Plateau

description: Continuous time-series of land cover is critical for attributing runoff, sediment and carbon changes on the Chinese Loess Plateau (CLP). However, current land cover products with annal temporal resolution lack spatial identification accuracy, particularly in capturing authentic changes of cropland, forest and grassland. To address these issues, a 30 m annual land cover dataset was proposed by the Yellow River Conservancy Commission (YRCC_LPLC) for the CLP from 1990 to 2022. Different levels of land cover were classified using different combinations of spectral, monthly and annual temporal and topographic features and Random Forest classifier. Compared to other land cover products (45.64%–73.38%), the accuracy of YRCC_LPLC has a better performance with an overall accuracy of 85.16%. The YRCC_LPLC is capable of capturing not only the explicit spatial variation but also the change direction and change time of land cover, especially for the most critical conversion of cropland into forest and grassland induced by implementation of Grain to Green Program on the CLP.
DOI: 10.5281/zenodo.14889350
title: SplenoCT-KAUH dataset
title: مجموعة بيانات لتصنيف تضخم الطحال وأسبابه باستخدام التصوير المقطعي المحوسب

description: This single-institutional retrospective study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board (IRB) at King Abdullah University Hospital and Jordan University of Science and Technology, Jordan (Ref. 16/154/2023). The requirement for informed consent was waived due to the retrospective nature of the study. The personal data of patients were protected and anonymized in accordance with relevant guidelines. The researchers have the right to publish the data publicly.
description: This dataset comprises 249 de-identified CT scans and corresponding patient data from 249 adult subjects (42% female), with a mean age of 48.2 years (ranging from 18 to 91 years). It includes cases both with and without splenomegaly, representing a diverse spectrum of diagnoses such as liver cirrhosis, lymphoma, leukemia, myeloproliferative neoplasms (MPNs), and thalassemia. We anticipate that this data will serve as a valuable resource for medical physicists and data scientists, fostering further research and advancements in diagnostic applications related to hematology and liver diseases where splenomegaly is a prominent radiological feature.
DOI: 10.5281/zenodo.14889351
title: SplenoCT-KAUH dataset
title: مجموعة بيانات لتصنيف تضخم الطحال وأسبابه باستخدام التصوير المقطعي المحوسب

description: This single-institutional retrospective study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board (IRB) at King Abdullah University Hospital and Jordan University of Science and Technology, Jordan (Ref. 16/154/2023). The requirement for informed consent was waived due to the retrospective nature of the study. The personal data of patients were protected and anonymized in accordance with relevant guidelines. The researchers have the right to publish the data publicly.
description: This dataset comprises 249 de-identified CT scans and corresponding patient data from 249 adult subjects (42% female), with a mean age of 48.2 years (ranging from 18 to 91 years). It includes cases both with and without splenomegaly, representing a diverse spectrum of diagnoses such as liver cirrhosis, lymphoma, leukemia, myeloproliferative neoplasms (MPNs), and thalassemia. We anticipate that this data will serve as a valuable resource for medical physicists and data scientists, fostering further research and advancements in diagnostic applications related to hematology and liver diseases where splenomegaly is a prominent radiological feature.
DOI: 10.15468/dl.vrkjsk
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Epidendrum attenuatum Lindl."
 ]
}

 The dataset includes 16 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000779-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25318/1810016601-eng
title: Investment banking services price index, annual

description: Investment banking services price index (IBSPI) measures the change in price of investment banking services. Annual data are available from 2010. The table presents data for the most recent reference period and the last four periods. Data is available in a Fisher, Laspeyres or Paasche index. The base period for the index is 2017=100.
DOI: 10.5281/zenodo.14853835
title: Reductions in the future agricultural workday due to climate change

description: Description

This repository contains workflows, scripts, and datasets that estimate the heat stress exposure of the global agricultural workforce at high spatial and temporal resolution for Ormaza-Zulueta et al. (2025). The data integrates downscaled CMIP6 climate projections from Williams et al. (2024) with global agricultural workforce estimates from Ormaza-Zulueta et al. (2024) to quantify the impact of climate change on unsafe working conditions for 2000, 2030 and 2050, under different Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5).

Final products



Output:  Output.zip. 



Daily heat stress exceedances. Folder: Output/Daily. WBGT thresholds of 28C and 30C) for baseline (2000) and future projections (2030, 2050) under SSP2-4.5 and SSP5-8.5 averaged across 10-year span. 



Resolution



Spatial: 0.05° grids



Map projection



Dimensions: 7200 x 2600 cell grid

CRS: EPSG:4326 - WGS 84 - Geographic

Cell size: 0.05 degrees

Layer extent: 



Top : 70

Left: -180

Right: 180

Bottom: -60







Estimated unsafe working days for each hour of the day (0 to 23). Folder: Output/Hourly. 



 Averaged for different agricultural seasons (harvesting, planting), administrative units (levels 0, 1 and 2) and for different WBGT thresholds (28C, 30C, 32C).



Agricultural workfroce predictions (baseline + future), merged with heat stress exposure. Folder: Output/Ag_WBGT.




 



Code and workflows: Folder: ag_workforce_heat_stress.zip.



 Comes with a README file to reproduce the analysis, including climate data processing, hourly temperature computation, heat stress calculations and workforce projection adjustments.
DOI: 10.5281/zenodo.14853836
title: Reductions in the future agricultural workday due to climate change

description: Description

This repository contains workflows, scripts, and datasets that estimate the heat stress exposure of the global agricultural workforce at high spatial and temporal resolution for Ormaza-Zulueta et al. (2025). The data integrates downscaled CMIP6 climate projections from Williams et al. (2024) with global agricultural workforce estimates from Ormaza-Zulueta et al. (2024) to quantify the impact of climate change on unsafe working conditions for 2000, 2030 and 2050, under different Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5).

Final products



Output:  Output.zip. 



Daily heat stress exceedances. Folder: Output/Daily. WBGT thresholds of 28C and 30C) for baseline (2000) and future projections (2030, 2050) under SSP2-4.5 and SSP5-8.5 averaged across 10-year span. 



Resolution



Spatial: 0.05° grids



Map projection



Dimensions: 7200 x 2600 cell grid

CRS: EPSG:4326 - WGS 84 - Geographic

Cell size: 0.05 degrees

Layer extent: 



Top : 70

Left: -180

Right: 180

Bottom: -60







Estimated unsafe working days for each hour of the day (0 to 23). Folder: Output/Hourly. 



 Averaged for different agricultural seasons (harvesting, planting), administrative units (levels 0, 1 and 2) and for different WBGT thresholds (28C, 30C, 32C).



Agricultural workfroce predictions (baseline + future), merged with heat stress exposure. Folder: Output/Ag_WBGT.




 



Code and workflows: Folder: ag_workforce_heat_stress.zip.



 Comes with a README file to reproduce the analysis, including climate data processing, hourly temperature computation, heat stress calculations and workforce projection adjustments.
DOI: 10.25318/1810016601-fra
title: Indice des prix des services bancaires d'investissement, annuel

description: Indice des prix des services bancaires d'investissement (IPSBI) mesure la variation des prix des services bancaires d'investissement. Les données annuelles sont disponibles à partir de 2010. Le tableau présente les données de la période de référence la plus récente et des quatre dernières périodes. Le calcul de l'indice est disponible dans les indices de prix de Fisher, de Paasche et de Laspeyres. La période de base de l’indice est 2017=100.
DOI: 10.15468/dl.9cruvh
title: Occurrence Download

description: A dataset containing 10236 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "CoordinateUncertaintyInMeters 0.0-1000.0",
 "Geometry POLYGON((-166.83367 25.34321,-47.76442 25.34321,-47.76442 74.87752,-166.83367 74.87752,-166.83367 25.34321))",
 "TaxonKey is Cytisus scoparius (L.) Link"
 ]
}

 The dataset includes 10236 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000780-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5fr2rs
title: Occurrence Download

description: A dataset containing 8174 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "CoordinateUncertaintyInMeters 0.0-1060.0",
 "Geometry POLYGON((-158.84166 9.46265,-40.2272 9.46265,-40.2272 64.30258,-158.84166 64.30258,-158.84166 9.46265))",
 "TaxonKey is Sorghum halepense (L.) Pers."
 ]
}

 The dataset includes 8174 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000781-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vsfvu4
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Country is Belize",
 "DatasetKey is Tropicos MO Specimen Data",
 "OccurrenceStatus is Present",
 "TaxonKey is Crescentia linearifolia Miers"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000782-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d483xy
title: Occurrence Download

description: A dataset containing 289 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "TaxonKey is Ananas comosus (L.) Merr."
 ]
}

 The dataset includes 289 records from 49 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000783-250218110819086/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.