cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17755037
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 2m, Global model EC-EARTH3, scenario ssp126 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755038
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 2m, Global model EC-EARTH3, scenario ssp126 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755052
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 2m, Global model EC-EARTH3, scenario ssp245 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755051
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 2m, Global model EC-EARTH3, scenario ssp245 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.15468/dl.7fbpm7
title: Occurrence Download

description: A dataset containing 56355 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Natrix natrix",
 "Year 2018-2025"
 ]
}

 The dataset includes 56355 records from 261 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020163-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57745/749xza
title: Contributions of scenario and model uncertainty sources to Explore2 hydroclimate projections. The effect of a Regional Warming Level analysis

description: Dans un contexte de changement climatique, la modélisation permet de simuler les évolutions futures du climat et des ressources en eau. La combinaison de plusieurs scénarios d’émissions, modèles climatiques globaux et régionaux et modèles hydrologiques conduit à la création d’ensembles multi-modèles de projections hydroclimatiques. Alors que les projections sont traditionnellement analysées en horizons temporels, de récentes politiques publiques ont adopté une approche basée sur des niveaux de réchauffement global. En France, la TRACC (Trajectoire de Référence pour l’Adaptation au Changement Climatique) définit des cibles de réchauffement global auxquelles la société devra s’adapter au cours du XXIe siècle. Le concept de niveau de réchauffement régional y est introduit, correspondant au réchauffement moyenné à l’échelle de la France. Cette étude évalue l’effet d’une analyse en niveau de réchauffement régional sur les projections hydroclimatiques et sur les incertitudes associées. Le questionnement central de ce travail est: «L’utilisation du niveau de réchauffement régional comme variable explicative des projections hydroclimatiques permet-elle de réduire la plage d’incertitude associée aux projections et, par suite, de communiquer un message plus facile à appréhender par les acteurs ?» L’ensemble de projections hydroclimatiques utilisé dans cette étude provient de la base de données Explore2, qui fournit des projections issues de 36 chaînes climatiques et de 4 modèles hydrologiques pour 1735 stations hydrologiques sur la France métropolitaine. La méthode statistique QUALYPSO est utilisée pour distinguer les tendances à long terme de la variabilité interne du climat, et pour décomposer l’incertitude totale de l’ensemble en incertitudes liées au scénario d’émission et aux modèles. Les analyses sont menées pour un niveau de réchauffement régional de 2°C et pour l’année 2037, sur cinq variables climatiques et trois variables hydrologiques. L’étude met en évidence une réduction générale des incertitudes liées aux modèles dans le cadre de l’analyse par niveau de réchauffement régional. Cet effet est particulièrement marqué en été et pour les températures saisonnières. L’incertitude liée aux scénarios est fortement influencée par l’approche en niveau de réchauffement, avec des différences spatiales contrastées de réduction ou d’augmentation. Les comparaisons réalisées dans cette étude soutiennent l’utilisation du niveau de réchauffement régional comme variable explicative plus pertinente que le temps pour l’analyse des projections hydroclimatiques. Cela est particulièrement vrai pour les variables et saisons fortement liées au réchauffement régional, telles que les températures saisonnières et les précipitations estivales.
DOI: 10.5281/zenodo.17755063
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 2m, Global model EC-EARTH3, scenario ssp370 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755062
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 2m, Global model EC-EARTH3, scenario ssp370 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17774176
title: Predicted and Computationally Inferred Coptotermes formosanus cGMP-dependent protein kinase (agr1) mRNA, agr1-wild-type allele, complete cds.

description: This dataset contains a computationally predicted mRNA and complete coding sequence (CDS) for a putative cGMP-dependent protein kinase (“cfagr1”) gene in Coptotermes formosanus.

The sequence was inferred using comparative genomic and proteomic analysis of homologous behavioral-regulation proteins and corresponding genes in the european honeybee Apis mellifera, and the eastern subterranean termite, Reticulitermes flavipes, among other termite species, focusing on conserved PKG/for/agr domains.

The dataset includes the following:



A FASTA file of the predicted sequence

Full manuscript PDF describing background, methods, and rationale

A README summarizing the computational approach

supplementary documentation


This sequence is a theoretical gene model and has not yet been experimentally validated.
DOI: 10.5281/zenodo.17774175
title: Predicted and Computationally Inferred Coptotermes formosanus cGMP-dependent protein kinase (agr1) mRNA, agr1-wild-type allele, complete cds.

description: This dataset contains a computationally predicted mRNA and complete coding sequence (CDS) for a putative cGMP-dependent protein kinase (“cfagr1”) gene in Coptotermes formosanus.

The sequence was inferred using comparative genomic and proteomic analysis of homologous behavioral-regulation proteins and corresponding genes in the european honeybee Apis mellifera, and the eastern subterranean termite, Reticulitermes flavipes, among other termite species, focusing on conserved PKG/for/agr domains.

The dataset includes the following:



A FASTA file of the predicted sequence

Full manuscript PDF describing background, methods, and rationale

A README summarizing the computational approach

supplementary documentation


This sequence is a theoretical gene model and has not yet been experimentally validated.
DOI: 10.15468/dl.9k6ucf
title: Occurrence Download

description: A dataset containing 561 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((2.90659 42.80914,2.90427 42.80434,2.90401 42.79729,2.91436 42.79294,2.92456 42.79241,2.92832 42.7972,2.92908 42.80236,2.92691 42.80642,2.92204 42.81244,2.91295 42.8126,2.90843 42.81142,2.90659 42.80914))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Aves"
 ]
}

 The dataset includes 561 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020209-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17755074
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 2m, Global model EC-EARTH3, scenario ssp585 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755073
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 2m, Global model EC-EARTH3, scenario ssp585 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.15468/dl.dy6vu9
title: Occurrence Download

description: A dataset containing 501537 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is izeltlabuak.hu observations validated to species level"
 ]
}

 The dataset includes 501537 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020192-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17755080
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 2m, Global model MPI-ESM1-2-HR, scenario Historical -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755081
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 2m, Global model MPI-ESM1-2-HR, scenario Historical -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755099
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 2m, Global model MPI-ESM1-2-HR, scenario ssp126 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755100
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 2m, Global model MPI-ESM1-2-HR, scenario ssp126 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.13140/rg.2.2.23659.60960
title: Earthquake India : Tempestive Thought
DOI: 10.5281/zenodo.17590903
title: Biogeographic rules of arthropod body-size across trees in a forest canopy - data and code

description: These datasets and R scripts are associated with the publication "Biogeographic rules of arthropod body-size across trees in a forest canopy". Detailed information regarding data processing and analysis can be found in the Methods section of the publication.
DOI: 10.5281/zenodo.17590902
title: Biogeographic rules of arthropod body-size across trees in a forest canopy - data and code

description: These datasets and R scripts are associated with the publication "Biogeographic rules of arthropod body-size across trees in a forest canopy". Detailed information regarding data processing and analysis can be found in the Methods section of the publication.
DOI: 10.15468/dl.8ggkb7
title: Occurrence Download

description: A dataset containing 35 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingOrg is one of (a76f8527-23e8-4ba5-bdff-f9821bdac187)",
 "DatasetKey is one of (The Fungal Collection at the Botanische Staatssammlung München)"
 ]
 },
 "HasGeospatialIssue is false",
 "Geometry POLYGON((6.1496 50.19097,6.08368 50.20855,5.95184 50.20503,5.8255 50.12762,5.71564 49.97596,5.68268 49.86632,5.75409 49.75643,5.84747 49.64273,5.77057 49.55729,5.83099 49.49311,5.94635 49.43956,6.05621 49.42527,6.21002 49.4824,6.3913 49.43241,6.41327 49.51808,6.45721 49.60003,6.5506 49.6854,6.56158 49.81318,6.41327 49.86986,6.29242 49.91586,6.2265 49.98302,6.18256 50.05714,6.20453 50.14171,6.1496 50.19097))"
 ]
}

 The dataset includes 35 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020210-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34808/aw67-fq51
title: OntoValidate: OntoNotes 5.0 NER validation dataset

description: OntoValidate dataset consists of 603 randomly chosen raw textsfrom the original OntoNote 5.0 dataset (3637 raw texts in total).
All raw texts are split into 13 subsets. Each subset was manuallyannotated with named entities by at least 10 people. Each annotator followed the official annotation guidelines (OntoNotes Named Entity Guidelines VERSION 14.0)that are distributed together with the OntoNotes 5.0 dataset. 
The OntoValidate dataset allows for a comparison of how different peopleunderstand the named entity recognition task. On the other hand, it also gave ussome insights about the precision of annotation guidelines itself.
Format
Each directory of the OntoValidate dataset represents a separate annotator.The first number in the directory name is the sequence number of the subset, the second isthe sequence number of the annotator. Each directory contains the JSON files that containthe annotations in spaCy JSON format. 
All annotations were created using the NER Text Annotator tool (https://tecoholic.github.io/ner-annotator/).
DOI: 10.5281/zenodo.17755115
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 2m, Global model MPI-ESM1-2-HR, scenario ssp245 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755116
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 2m, Global model MPI-ESM1-2-HR, scenario ssp245 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.17026/dans-zqd-pd4a
title: Aanvullend archeologisch onderzoek in Herpen - Buitenstraat, gemeente Oss

description: &lt;p&gt;Op de locatie Herpen-Buitenstraat heeft in verband met een mogelijke bestemmingsverandering van agrarisch kernrandgebied naar woondoeleinden een Aanvullend Archeologisch Onderzoek plaatsgevonden.&lt;/p&gt;&lt;p&gt;Aanbeveling&lt;br&gt;Tijdens het onderzoek zijn enkele sporen uit de Midden-Bronstijd, IJzertijd en Late Middeleeuwen aangetroffen. Deze konden echter niet in verbanden geplaatst worden. De aanwezigheid van vindplaatsen in de nabijheid van het onderzoeksgebied kan een verklaring bieden voor het voorkomen van de aangetroffen sporen en vondsten.&lt;br&gt;Het vermoeden rijst dat een vindplaats of de randverschijnselen van een vindplaats buiten het plangebied uit de Brons-IJzertijd aanwezig zijn geweest. Het is niet duidelijk of de Laat Middeleeuwse sporen en vondsten toe te wijzen zijn aan bewoning of landbouwactiviteiten. De grootschalige verstoring van de vindplaats door diepploegen, verbruining en subrecente bewoning laat een nadere interpretatie van de sporen niet toe. Het geheel leidt er toe dat geen verder archeologisch onderzoek en/of bescherming voor dit terrein aanbevolen wordt.&lt;/p&gt;
DOI: 10.5281/zenodo.17755128
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 2m, Global model MPI-ESM1-2-HR, scenario ssp370 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755129
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 2m, Global model MPI-ESM1-2-HR, scenario ssp370 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755143
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 2m, Global model MPI-ESM1-2-HR, scenario ssp585 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755144
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 2m, Global model MPI-ESM1-2-HR, scenario ssp585 -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755160
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 50m, Global model EC-EARTH3, scenario Historical -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.
DOI: 10.5281/zenodo.17755161
title: DISTENDER Climate Simulations: Statistical Downscaling for Guimaraes_D2, Vertical level 50m, Global model EC-EARTH3, scenario Historical -  Guimaraes (Portugal)

description: Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping).
More details about the domains, the provided variable, levels and periods are provided in the README file.