cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15482/usda.adc/26517301
title: Data from: A variety-specific analysis of climate change effects on California winegrapes

description: This folder, titled "Data," contains the MATLAB code, final products, tables, and figures used in Parker, L.E., Zhang, N., Abatzoglou, J.T. <em>et al.</em> A variety-specific analysis of climate change effects on California winegrapes. <em>Int J Biometeorol</em> <strong>68</strong>, 1559–1571 (2024). https://doi.org/10.1007/s00484-024-02684-8  
<br>
<strong>Data Collection:</strong> Climatological data (daily maximum and minimum temperatures, precipitation, and reference evapotranspiration) were obtained from the gridMET dataset for the contemporary period (1991-2020) and from 20 global climate models (GCMs) for the mid-21st century (2040-2069) under RCP 4.5.<strong>Phenology Modeling:</strong> Variety-specific phenology models were developed using published climatic thresholds to assess chill accumulation, budburst, flowering, veraison, and maturity stages for the six winegrape varieties.<strong>Agroclimatic Metrics:</strong> Fourteen viticulturally important agroclimatic metrics were calculated, including Growing Degree Days (GDD), Cold Hardiness, Chilling Degree Days (CDD), Frost Damage Days (FDD), and others.<strong>Analysis Tools:</strong> MATLAB was used for data processing, analysis, and visualization. The MATLAB code provided in this dataset includes scripts for analyzing climate data, running phenology models, and generating visualizations.<strong>MATLAB Code:</strong> Scripts and functions used for data analysis and modeling.<strong>Processed Data:</strong> Results from phenology and agroclimatic analyses, including the projected changes in phenological stages and climate metrics for the selected varieties and AVAs.<strong>Tables:</strong> Detailed results of phenological changes and climate metrics, presented in a clear and structured format.<strong>Figures:</strong> Visual representations of the data and results, including charts and maps illustrating the impacts of climate change on winegrape development stages and agroclimatic conditions.
<br>
<strong>Research Description:</strong> This study investigates the impacts of climate change on the phenology and agroclimatic metrics of six winegrape varieties (Cabernet Sauvignon, Chardonnay, Pinot Noir, Zinfandel, Pinot Gris, Sauvignon Blanc) across multiple California American Viticultural Areas (AVAs). Using climatological data and phenology models, the research quantifies changes in key development stages and viticulturally important climate metrics for the mid-21st century.
<br>
DOI: 10.15482/usda.adc/26517301.v1
title: Data from: A variety-specific analysis of climate change effects on California winegrapes

description: This folder, titled "Data," contains the MATLAB code, final products, tables, and figures used in Parker, L.E., Zhang, N., Abatzoglou, J.T. <em>et al.</em> A variety-specific analysis of climate change effects on California winegrapes. <em>Int J Biometeorol</em> <strong>68</strong>, 1559–1571 (2024). https://doi.org/10.1007/s00484-024-02684-8  
<br>
<strong>Data Collection:</strong> Climatological data (daily maximum and minimum temperatures, precipitation, and reference evapotranspiration) were obtained from the gridMET dataset for the contemporary period (1991-2020) and from 20 global climate models (GCMs) for the mid-21st century (2040-2069) under RCP 4.5.<strong>Phenology Modeling:</strong> Variety-specific phenology models were developed using published climatic thresholds to assess chill accumulation, budburst, flowering, veraison, and maturity stages for the six winegrape varieties.<strong>Agroclimatic Metrics:</strong> Fourteen viticulturally important agroclimatic metrics were calculated, including Growing Degree Days (GDD), Cold Hardiness, Chilling Degree Days (CDD), Frost Damage Days (FDD), and others.<strong>Analysis Tools:</strong> MATLAB was used for data processing, analysis, and visualization. The MATLAB code provided in this dataset includes scripts for analyzing climate data, running phenology models, and generating visualizations.<strong>MATLAB Code:</strong> Scripts and functions used for data analysis and modeling.<strong>Processed Data:</strong> Results from phenology and agroclimatic analyses, including the projected changes in phenological stages and climate metrics for the selected varieties and AVAs.<strong>Tables:</strong> Detailed results of phenological changes and climate metrics, presented in a clear and structured format.<strong>Figures:</strong> Visual representations of the data and results, including charts and maps illustrating the impacts of climate change on winegrape development stages and agroclimatic conditions.
<br>
<strong>Research Description:</strong> This study investigates the impacts of climate change on the phenology and agroclimatic metrics of six winegrape varieties (Cabernet Sauvignon, Chardonnay, Pinot Noir, Zinfandel, Pinot Gris, Sauvignon Blanc) across multiple California American Viticultural Areas (AVAs). Using climatological data and phenology models, the research quantifies changes in key development stages and viticulturally important climate metrics for the mid-21st century.
<br>
DOI: 10.15468/dl.8vp6jv
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leucaena diversifolia",
 "Country is Colombia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019304-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2cm5yx
title: Occurrence Download

description: A dataset containing 24561 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is ESP.14_1",
 "OccurrenceStatus is Present",
 "TaxonKey is Columba livia",
 "Year 2010-2025"
 ]
}

 The dataset includes 24561 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019303-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9zxq72
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leucaena diversifolia",
 "Country is Comoros",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019307-250802193616735/datasets/export for details.
DOI: 10.5281/zenodo.16751798
title: Castl: A Consensus Framework for Robust Identification of Spatially Variable Genes in Spatial Transcriptomics

description: Castl is a novel consensus-based analytical framework designed to enhance the accuracy and robustness of spatially variable genes identification for spatially resolved transcriptomics through statistically rigorous algorithms, including rank aggregation, p-value aggregation, and Stabl aggregation. Comprehensive evaluations on both simulated and real-world data demonstrate that Castl consistently identifies biologically meaningful spatial expression patterns, mitigates method-specific biases and effectively controls FDRs across various biological contexts, resolutions, and spatial technologies. This flexible, assumption-free framework offers a robust and standardized foundation for spatially informed feature discovery in complex biological systems.
DOI: 10.5281/zenodo.16751799
title: Castl: A Consensus Framework for Robust Identification of Spatially Variable Genes in Spatial Transcriptomics

description: Castl is a novel consensus-based analytical framework designed to enhance the accuracy and robustness of spatially variable genes identification for spatially resolved transcriptomics through statistically rigorous algorithms, including rank aggregation, p-value aggregation, and Stabl aggregation. Comprehensive evaluations on both simulated and real-world data demonstrate that Castl consistently identifies biologically meaningful spatial expression patterns, mitigates method-specific biases and effectively controls FDRs across various biological contexts, resolutions, and spatial technologies. This flexible, assumption-free framework offers a robust and standardized foundation for spatially informed feature discovery in complex biological systems.
DOI: 10.6084/m9.figshare.29565947.v4
title: benchhub test

description: test
DOI: 10.15468/dl.rnycd7
title: Occurrence Download

description: A dataset containing 89 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Paradoxornis gularis",
 "Country is China",
 "HasCoordinate is true"
 ]
}

 The dataset includes 89 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019309-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qzraya
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Sarkidiornis melanotos)",
 "Country is one of (American Samoa, Australia, Christmas Island, Cocos (Keeling) Islands, Cook Islands, Fiji, French Polynesia, Guam, Heard Island and McDonald Islands, Kiribati, Marshall Islands, Micronesia (Federated States of), Nauru, New Caledonia, New Zealand, Niue, Norfolk Island, Northern Mariana Islands, Palau, Papua New Guinea, Pitcairn, Samoa, Solomon Islands, Tokelau, Tonga, Tuvalu, United States Minor Outlying Islands, Vanuatu, Wallis and Futuna)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019310-250802193616735/datasets/export for details.
DOI: 10.15468/dl.73zjhq
title: Occurrence Download

description: A dataset containing 169 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Sarkidiornis melanotos)",
 "Country is one of (Åland Islands, Albania, Andorra, Austria, Belarus, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Czechia, Denmark, Estonia, Faroe Islands, Finland, France, Germany, Gibraltar, Greece, Guernsey, Holy See, Hungary, Iceland, Ireland, Isle of Man, Italy, Jersey, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Moldova, Republic of, Monaco, Montenegro, Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, Russian Federation, San Marino, Serbia, Slovakia, Slovenia, Spain, Svalbard and Jan Mayen, Sweden, Switzerland, Ukraine, United Kingdom of Great Britain and Northern Ireland)"
 ]
}

 The dataset includes 169 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019308-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kgc88q
title: Occurrence Download

description: A dataset containing 107636 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Peucaea carpalis)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "License is one of (CC-BY 4.0, CC0 1.0)"
 ]
}

 The dataset includes 107636 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019283-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18167/dvn1/0g4g28
title: Characterization of boiled yam textural properties of a Dioscorea alata diversity panel in Guadeloupe

description: This file contain instrumental textural data (TPA and penetrometry) of boiled yam that was collected by CIRAD team in Neufchateau, Guadeloupe.
DOI: 10.15468/dl.u75buw
title: Occurrence Download

description: A dataset containing 28 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Allmaniopsis"
 ]
}

 The dataset includes 28 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019312-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qr4yha
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is BOLD:AAC5781"
 ]
}

 The dataset includes 16 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019313-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u4ywkj
title: Occurrence Download

description: A dataset containing 265 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Ichthyomyzon greeleyi)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 265 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019317-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.an7t56
title: Occurrence Download

description: A dataset containing 31419 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Sarkidiornis melanotos)",
 "Country is one of (Algeria, Angola, Benin, Botswana, British Indian Ocean Territory, Burkina Faso, Burundi, Cabo Verde, Cameroon, Central African Republic, Chad, Comoros, Congo, Congo, Democratic Republic of the, Côte d’Ivoire, Djibouti, Egypt, Equatorial Guinea, Eritrea, Eswatini, Ethiopia, French Southern Territories, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Libya, Madagascar, Malawi, Mali, Mauritania, Mauritius, Mayotte, Morocco, Mozambique, Namibia, Niger, Nigeria, Réunion, Rwanda, Saint Helena, Ascension and Tristan da Cunha, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, Somalia, South Africa, South Sudan, Sudan, Tanzania, United Republic of, Togo, Tunisia, Uganda, Western Sahara, Zambia, Zimbabwe)"
 ]
}

 The dataset includes 31419 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019311-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.14466/cefasdatahub.101
title: Zooplankton abundance data derived from the Plankton Imager system from the Western English Channel and Eastern Irish Sea from 2016 to 2019

description: These data are abundances (in numbers per meters cubed) of zooplankton taxa, calculated from the analysis of images taken using the Plankton Imager system also included are station positions and sampling date / times. The images where collected using the PI (formerly known as Plankton Image Analyser (PIA)), during the PELTIC (Pelagic ecosystem in the western English Channel and eastern Celtic Sea) surveys from 2016 to 2019, on board the RV Cefas Endeavour. Zooplankton samples and images were collected during night hours only at stations which were selected to match the collection of other environmental parameters. The Plankton Imager is a high-speed colour line scan-based imaging instrument connected to the ships water supply and can take images of all zooplankton of size above 20 microns passing through a cell at a 27 litre per minute flow rate. The flow cell is 25mm brass tube that has two quartz optical windows halfway along its length. The flow cell at the windows is square, with the same cross-sectional area as the 25mm tube. A Basler 2048-70kc camera, sampling at 70K lines per second, images the water running through the flow cell. The flow rate is monitored by a Bell electro-magnetic flow meter. Colour images are captured using an EPIX E4 frame store. RGB composite images are constructed by joining consecutive lines together, thresholding and extracting a region of interest ROI, or vignette, that is saved to hard drive as a TIF file. Raw images are stored to maximize dynamic range of the captured particles. These are converted to 8-bit resolution through a process of scaling and conversion from 12 to 8-bit resolution, for viewing and for subsequent processing. Due to operational requirements (continuous image processing while maintaining manageable file-size), only those particles within the mesozooplankton range 200 microns – 2cm were processed and saved. In order to reproduce the sub-sampling procedure used for physical samples (as collected with a ring net), random images were extracted until each sample contained approximately 200 mesozooplankton individuals and then identified using the with the Plankton Imager software to derive taxon groupings which were then validated by an expert taxonomist manually. The following paper describes the Plankton Imager system in further detail. Pitois et al. (2018). Comparison of a Cost-Effective Integrated Plankton Sampling and Imaging Instrument with Traditional Systems for Mesozooplankton Sampling in the Celtic Sea. Frontiers in Marine Science. 5. 10.3389/fmars.2018.00005.
DOI: 10.15468/dl.xweaar
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leucaena diversifolia",
 "Country is Congo",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019316-250802193616735/datasets/export for details.
DOI: 10.5281/zenodo.13911632
title: Data from filter-based sampler from the ground and on-board of an uncrewed aerial vehicle during the Pallas Cloud Experiment 2022

description: The dataset contains the ice-nucleating particle concentration as a function of the nucleation temperature, determined with the Ice Nucleation Spectrometer of the Karlsruhe Institute of Technology (INSEKT). There are three types of filters analyzed: filters taken with a mobile setup on the ground (denoted by SkwGN), filters taken onboard of an uncrewed aerial vehicle (denoted by Skw), and a handling blank filter (denoted by BLANK). Handling blanks are filters that are taken to measure the contamination happening during handling of the filters, no active air flow is created along the filter.
DOI: 10.5281/zenodo.16752129
title: Data from filter-based sampler from the ground and on-board of an uncrewed aerial vehicle during the Pallas Cloud Experiment 2022

description: The dataset contains the ice-nucleating particle concentration as a function of the nucleation temperature, determined with the Ice Nucleation Spectrometer of the Karlsruhe Institute of Technology (INSEKT). There are three types of filters analyzed: filters taken with a mobile setup on the ground (denoted by SkwGN), filters taken onboard of an uncrewed aerial vehicle (denoted by Skw), and a handling blank filter (denoted by BLANK). Handling blanks are filters that are taken to measure the contamination happening during handling of the filters, no active air flow is created along the filter.
DOI: 10.5281/zenodo.16752132
title: Levels of evidence in clincial practice guidelines

description: Full dataset for the paper, 'Levels of evidence supporting recommendations in clinical practice guidelines: meta-epidemiological study'.

The dataset consists of one Excel file (3 sheets).

Last updated 6 August 2025.
DOI: 10.5281/zenodo.16752133
title: Levels of evidence in clincial practice guidelines

description: Full dataset for the paper, 'Levels of evidence supporting recommendations in clinical practice guidelines: meta-epidemiological study'.

The dataset consists of one Excel file (3 sheets).

Last updated 6 August 2025.
DOI: 10.15468/dl.envsrb
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leucaena diversifolia",
 "Country is Congo, Democratic Republic of the",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019321-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m33unm
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leucaena diversifolia",
 "Country is Côte d’Ivoire",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019320-250802193616735/datasets/export for details.
DOI: 10.15468/dl.za58x3
title: Occurrence Download

description: A dataset containing 682 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is ESP.14_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Oryctolagus cuniculus",
 "Year 2010-2025"
 ]
}

 The dataset includes 682 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019322-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sexuvz
title: Occurrence Download

description: A dataset containing 74 records in GBIF matching the query:
SELECT "year", GBIF_EEARGCode( 1000, decimalLatitude, decimalLongitude, COALESCE(coordinateUncertaintyInMeters, 1000) ) AS eeaCellCode, classKey, class, genusKey, genus, COUNT(*) AS occurrences, MIN(COALESCE(coordinateUncertaintyInMeters, 1000)) AS minCoordinateUncertaintyInMeters, MIN(GBIF_TemporalUncertainty(eventDate, null)) AS minTemporalUncertainty FROM occurrence WHERE occurrenceStatus = 'PRESENT' AND genusKey IN (2284443, 2202786, 2161911, 2161467, 7652364, 2176168, 3092125, 2771094, 8782549, 2457378, 2453882, 2457825, 2454645, 2465626, 2466496, 2459675, 2444141, 2444221, 2447418, 2441658, 2442664, 3266899, 2473221, 2445496, 5221394, 2443339, 4553469) AND countrycode = 'BE' AND "year" &gt;= 1900 AND hasCoordinate = TRUE AND genusKey IS NOT NULL AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE') AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE') AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID') AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH') AND (LOWER(identificationVerificationStatus) NOT IN ( 'unverified', 'unvalidated', 'not validated', 'under validation', 'not able to validate', 'control could not be conclusive due to insufficient knowledge', 'uncertain', 'unconfirmed', 'unconfirmed - not reviewed', 'validation requested' ) OR identificationVerificationStatus IS NULL) AND COALESCE(coordinateUncertaintyInMeters, 1000) &lt;= 10000 GROUP BY "year", eeaCellCode, classKey, class, genusKey, genus ORDER BY "year" DESC, eeaCellCode ASC, genusKey ASC;

 The dataset's 74 records were derived from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019300-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.