cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.34622/datarepositorium/udzteo
title: "As avaliações de impacto ao serviço da proteção dos direitos fundamentais perante sistemas de inteligência artificial" (#Juniors2Seniors com Victor Mulin Leal, Sofia Wengorovius e Manuel Fernando Silva Rodrigues)

description: "As avaliações de impacto ao serviço da proteção dos direitos fundamentais perante sistemas de inteligência artificial" (#Juniors2Seniors com Victor Mulin Leal, Sofia Wengorovius e Manuel Fernando Silva Rodrigues) Esta edição de #Juniors2Seniors intitula-se “As avaliações de impacto ao serviço da proteção dos direitos fundamentais perante sistemas de inteligência artificial”, sendo protagonizada por Victor Mulin Leal (doutorando da EDUM com bolsa de investigação FCT atribuída pelo JusGov). Este jovem investigador estuda o desenvolvimento de uma IA de confiança, visando compreender em que medida a avaliação de impacto para a proteção de dados pessoais pode atuar tanto na gestão de riscos como na proteção de direitos fundamentais, no âmbito do quadro regulamentar que emerge da leitura combinada do RGPD e do Regulamento IA. Victor Mulin Leal tem como convidados Sofia Wengorovius (jurista, juiz de direito, ex-encarregada de proteção de dados pessoais no Conselho Superior da Magistratura português) e Manuel Fernando Silva Rodrigues (engenheiro informático, investigador do Algoritmi da Escola de Engenharia da UMinho e do LASI - Laboratório Associado de Sistemas Inteligentes). "Impact assessments at the service of the protection of fundamental rights in the face of artificial intelligence systems" (#Juniors2Seniors with Victor Mulin Leal, Sofia Wengorovius and Manuel Fernando Silva Rodrigues) This edition of #Juniors2Seniors is entitled “Impact assessments at the service of the protection of fundamental rights before artificial intelligence systems”, and is led by Victor Mulin Leal (PhD student at School of Law of UMinho with an FCT research grant awarded by JusGov). This young researcher studies the development of trustworthy AI, aiming to understand to what extent the impact assessment for the protection of personal data can act both in risk management and in the protection of fundamental rights, within the regulatory framework that emerges from the combined reading of the GDPR and the AI Regulation. Victor Mulin Leal has as guests Sofia Wengorovius (jurist, judge, former personal data protection officer at the Portuguese Superior Council of the Judiciary) and Manuel Fernando Silva Rodrigues (computer engineer, researcher at Algoritmi of the School of Engineering of UMinho and LASI - Associated Laboratory of Intelligent Systems).
DOI: 10.15468/dl.fzrzf3
title: Occurrence Download

description: A dataset containing 1416 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Salix fragilis L.",
 "Country is Australia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1416 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081455-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kgq2ht
title: Occurrence Download

description: A dataset containing 43 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Salix fragilis L.",
 "Country is Latvia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 43 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081456-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.guv9x4
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Salix fragilis L.",
 "Country is Argentina",
 "HasCoordinate is true"
 ]
}

 The dataset includes 8 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081454-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29416658
title: Code used in the study - "<b>A fused canopy height map of Italy (2004–2024) from spaceborne and airborne LiDAR, and Landsat via deep learning and Bayesian averaging</b> "

description: This is the initial version of the data and code used in the paper, "<b>A fused canopy height map of Italy (2004–2024) from spaceborne and airborne LiDAR, and Landsat via deep learning and Bayesian averaging</b>".<b>Authors</b>Yang Su <sup>a, b, c</sup>, Nikola Besic <sup>d</sup>, Xianglin Zhang <sup>c</sup>, Yidi Xu <sup>b</sup>, Saverio Francini <sup>e</sup>, Giovanni D'Amico <sup>f</sup>, Gherardo Chirici <sup>g, h</sup>, Martin Schwartz <sup>b</sup>, Ibrahim Fayad <sup>b</sup>, Sara Brood <sup>b</sup>, Agnes Pellissier-tanon <sup>b</sup>, Ke Yu <sup>b</sup>, Haotian Chen <sup>i, c</sup>, Songchao Chen <sup>j</sup>, Alexandre d'Aspremont <sup>a</sup>, Philippe Ciais <sup>b</sup><br><b>Affiliations</b><sup>a</sup> CNRS & Département d'Informatique, École Normale Supérieure – PSL, 45 Rue d'Ulm, 75005 Paris, France<sup>b</sup> Laboratoire des Sciences du Climat et de l’Environnement, CEA CNRS UVSQ Orme des Merisiers, 91190 Gif-sur-Yvette, France<sup>c </sup>Université Paris-Saclay, AgroParisTech, INRAE, UMR ECOSYS, 91120 Palaiseau, France<sup>d </sup>IGN, ENSG, Laboratoire d'inventaire forestier (LIF), 54000 Nancy, France<sup>e </sup>Department of Science and Technology of Agriculture and Environment (DISTAL), University of Bologna, 40126 Bologna, Italy<sup>f </sup>Department of Agriculture, Food, Environment and Forestry, Università degli Studi di Firenze, Via San Bonaventura, 13, 50145 Firenze, Italy<sup>g </sup>Fondazione per il Futuro delle Città, Florence, Italy<sup>h </sup>CNR Istituto dei Sistemi Complessi, Sesto Fiorentino (Florence), Italy<sup>i </sup>Institute of Crop Sciences, Chinese Academy of Agricultural Sciences / Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs of China, Beijing 100081, China<sup>j</sup> College of Environmental and Resource Sciences, Zhejiang University, 310058 Hangzhou, China<br><b>Corresponding Author</b>Yang Suyang.su@ens.fr+33 1 89 10 07 67École normale supérieure - PSL<br>To use the data and code, please cite this study, and in case of difficulties when using the model and data, please contact the corresponding author for further details and possible assistance.FundingArtificial Intelligence for forest monitoring from space – AI4ForestsAgence Nationale de la RechercheFind out more...
DOI: 10.6084/m9.figshare.29416658.v1
title: Code used in the study - "<b>A fused canopy height map of Italy (2004–2024) from spaceborne and airborne LiDAR, and Landsat via deep learning and Bayesian averaging</b> "

description: This is the initial version of the data and code used in the paper, "<b>A fused canopy height map of Italy (2004–2024) from spaceborne and airborne LiDAR, and Landsat via deep learning and Bayesian averaging</b>".<b>Authors</b>Yang Su <sup>a, b, c</sup>, Nikola Besic <sup>d</sup>, Xianglin Zhang <sup>c</sup>, Yidi Xu <sup>b</sup>, Saverio Francini <sup>e</sup>, Giovanni D'Amico <sup>f</sup>, Gherardo Chirici <sup>g, h</sup>, Martin Schwartz <sup>b</sup>, Ibrahim Fayad <sup>b</sup>, Sara Brood <sup>b</sup>, Agnes Pellissier-tanon <sup>b</sup>, Ke Yu <sup>b</sup>, Haotian Chen <sup>i, c</sup>, Songchao Chen <sup>j</sup>, Alexandre d'Aspremont <sup>a</sup>, Philippe Ciais <sup>b</sup><br><b>Affiliations</b><sup>a</sup> CNRS & Département d'Informatique, École Normale Supérieure – PSL, 45 Rue d'Ulm, 75005 Paris, France<sup>b</sup> Laboratoire des Sciences du Climat et de l’Environnement, CEA CNRS UVSQ Orme des Merisiers, 91190 Gif-sur-Yvette, France<sup>c </sup>Université Paris-Saclay, AgroParisTech, INRAE, UMR ECOSYS, 91120 Palaiseau, France<sup>d </sup>IGN, ENSG, Laboratoire d'inventaire forestier (LIF), 54000 Nancy, France<sup>e </sup>Department of Science and Technology of Agriculture and Environment (DISTAL), University of Bologna, 40126 Bologna, Italy<sup>f </sup>Department of Agriculture, Food, Environment and Forestry, Università degli Studi di Firenze, Via San Bonaventura, 13, 50145 Firenze, Italy<sup>g </sup>Fondazione per il Futuro delle Città, Florence, Italy<sup>h </sup>CNR Istituto dei Sistemi Complessi, Sesto Fiorentino (Florence), Italy<sup>i </sup>Institute of Crop Sciences, Chinese Academy of Agricultural Sciences / Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs of China, Beijing 100081, China<sup>j</sup> College of Environmental and Resource Sciences, Zhejiang University, 310058 Hangzhou, China<br><b>Corresponding Author</b>Yang Suyang.su@ens.fr+33 1 89 10 07 67École normale supérieure - PSL<br>To use the data and code, please cite this study, and in case of difficulties when using the model and data, please contact the corresponding author for further details and possible assistance.FundingArtificial Intelligence for forest monitoring from space – AI4ForestsAgence Nationale de la RechercheFind out more...
DOI: 10.15468/dl.b3w8y5
title: Occurrence Download

description: A dataset containing 15346 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lepanthes Sw."
 ]
}

 The dataset includes 15346 records from 242 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081458-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wgm727
title: Occurrence Download

description: A dataset containing 186 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Material sample)"
 ]
 }
 },
 "TaxonKey is Melaenornis annamarulae Forbes-Watson, 1970",
 "Continent is one of (Africa)",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 186 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081460-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ksbdyn
title: Occurrence Download

description: A dataset containing 3025 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingOrg is 862f7ec3-3134-4dce-ab5a-03c81f54bd72",
 {
 "and" : [
 "PublishingOrg is 28eb1a3f-1c15-4a95-931a-4af90ecb574d",
 "Country is Uruguay"
 ]
 }
 ]
 },
 "StateProvince is one of (colonia)"
 ]
}

 The dataset includes 3025 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081461-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qusyg8
title: Occurrence Download

description: A dataset containing 39 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Salix fragilis L.",
 "Country is South Africa",
 "HasCoordinate is true"
 ]
}

 The dataset includes 39 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081464-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.crt43n
title: Occurrence Download

description: A dataset containing 949 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Salix fragilis L.",
 "Country is New Zealand",
 "HasCoordinate is true"
 ]
}

 The dataset includes 949 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081462-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qeu2b8
title: Occurrence Download

description: A dataset containing 476 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Salix fragilis L.",
 "Country is Norway",
 "HasCoordinate is true"
 ]
}

 The dataset includes 476 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081463-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.28xkyf
title: Occurrence Download

description: A dataset containing 1622 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Machine Observation, Human Observation, Specimen)",
 "Continent is Asia",
 "Country is Iran (Islamic Republic of)",
 "DatasetKey is one of (iNaturalist Research-grade Observations, Natural History Museum (London) Collection Specimens)",
 "Geometry POLYGON((44.04 24.86,63.33 24.86,63.33 39.78,44.04 39.78,44.04 24.86))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "IucnRedListCategory is one of (VU, EN, EX, EW, CR, NT, LC, DD, NE)",
 "License is one of (CC0 1.0, CC-BY-NC 4.0)",
 "Month is January",
 "PublishingOrg is one of (28eb1a3f-1c15-4a95-931a-4af90ecb574d, 19456090-b49a-11d8-abeb-b8a03c50a862)",
 "Year 1891-2025"
 ]
}

 The dataset includes 1622 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081465-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29438270
title: Dados da cronobiologia de Euschistus heros

description: Understanding the chemical and behavioral ecology of the Neotropical brown stink bug, <i>Euschistus</i> <i>heros</i> (Hemiptera: Pentatomidae), is essential for developing effective integrated pest management (IPM) strategies in South American soybean production. This study investigated the courtship behavior and diel periodicity of sex pheromone emission, comparing variations in laboratory-reared (LR) and field-collected (FC) strains of <i>E</i>. <i>heros.</i> Courtship was categorized into distinct sequential stages, and pheromone emissions were analyzed over a 24-hour period using dynamic headspace collection. LR males exhibited a pronounced peak in pheromone release between 15:00 and 18:00 hours, with no significant differences observed between the two strains. Courtship followed a consistent sequence, including antennal contact, female acceptance, and mounting. This study provides the first detailed characterization of the diel pattern of sex pheromone emission and a comprehensive ethogram of <i>E. heros</i> courtship. These findings advance our understanding of reproductive behavior, and pheromone-mediated communication in this pest species, offering practical insights for optimizing behavioral manipulation strategies in IPM programs.
DOI: 10.6084/m9.figshare.29438270.v1
title: Dados da cronobiologia de Euschistus heros

description: Understanding the chemical and behavioral ecology of the Neotropical brown stink bug, <i>Euschistus</i> <i>heros</i> (Hemiptera: Pentatomidae), is essential for developing effective integrated pest management (IPM) strategies in South American soybean production. This study investigated the courtship behavior and diel periodicity of sex pheromone emission, comparing variations in laboratory-reared (LR) and field-collected (FC) strains of <i>E</i>. <i>heros.</i> Courtship was categorized into distinct sequential stages, and pheromone emissions were analyzed over a 24-hour period using dynamic headspace collection. LR males exhibited a pronounced peak in pheromone release between 15:00 and 18:00 hours, with no significant differences observed between the two strains. Courtship followed a consistent sequence, including antennal contact, female acceptance, and mounting. This study provides the first detailed characterization of the diel pattern of sex pheromone emission and a comprehensive ethogram of <i>E. heros</i> courtship. These findings advance our understanding of reproductive behavior, and pheromone-mediated communication in this pest species, offering practical insights for optimizing behavioral manipulation strategies in IPM programs.
DOI: 10.5281/zenodo.15775692
title: Satellite pixel-based classification maps for placer occurrence

description: Abstract

Maps of targets for placer occurrences produced from various satellite data (Sentinel-2, Landsat-9, EnMAP, WorldView-3) sources using a pixel-based approach.

This depository contains data generated within the European S34 project.

 

Metadata information






Identification



 





Full Title



Satellite pixel-based classification maps for placer occurrence from Ria de Vigo (Spain) pilot site





Abstract



Maps of targets for placer occurrences produced from various satellite data (Sentinel-2, Landsat-9, EnMAP, WorldView-3) sources using a pixel-based approach.





Keywords



Earth observation; critical raw materials; marine placer deposits; mineral exploration; remote sensing





Pilot area



Ria de Vigo (Spain)





Associated resources



 https://doi.org/10.5281/zenodo.14652199





Language



English





URL



 





Categories



Remote sensing, geology





Temporal reference



 





Creation date (dd.mm.yyyy)



30.06.2025





Revision date (dd.mm.yyyy)



 





Quality and validity



 





Representation type



Vector and raster data, spectral library





Format



*.shp

*.tiff

*.png (preview maps)

*.hdr

*.sli





Lineage



 





Spatial resolution



 1.6 m (WorldView-3); 30 m (EnMap)





Positional accuracy



 





Maintenance information



 





Coordinate system



EPSG:32629 - WGS 84 / UTM zone 29N





Constraints related to access and use



 





Use limitation



None





Access constraint



None





Public/Private



Public





Responsible organisation



 





Responsible Contact



Joana Cardoso Fernandes | joana.fernandes@fc.up.pt





Responsible Party



UPORTO





Metadata on metadata



 





Contact



Joana Cardoso Fernandes | joana.fernandes@fc.up.pt





Metadata language



English
DOI: 10.5281/zenodo.15775691
title: Satellite pixel-based classification maps for placer occurrence

description: Abstract

Maps of targets for placer occurrences produced from various satellite data (Sentinel-2, Landsat-9, EnMAP, WorldView-3) sources using a pixel-based approach.

This depository contains data generated within the European S34 project.

 

Metadata information






Identification



 





Full Title



Satellite pixel-based classification maps for placer occurrence from Ria de Vigo (Spain) pilot site





Abstract



Maps of targets for placer occurrences produced from various satellite data (Sentinel-2, Landsat-9, EnMAP, WorldView-3) sources using a pixel-based approach.





Keywords



Earth observation; critical raw materials; marine placer deposits; mineral exploration; remote sensing





Pilot area



Ria de Vigo (Spain)





Associated resources



 https://doi.org/10.5281/zenodo.14652199





Language



English





URL



 





Categories



Remote sensing, geology





Temporal reference



 





Creation date (dd.mm.yyyy)



30.06.2025





Revision date (dd.mm.yyyy)



 





Quality and validity



 





Representation type



Vector and raster data, spectral library





Format



*.shp

*.tiff

*.png (preview maps)

*.hdr

*.sli





Lineage



 





Spatial resolution



 1.6 m (WorldView-3); 30 m (EnMap)





Positional accuracy



 





Maintenance information



 





Coordinate system



EPSG:32629 - WGS 84 / UTM zone 29N





Constraints related to access and use



 





Use limitation



None





Access constraint



None





Public/Private



Public





Responsible organisation



 





Responsible Contact



Joana Cardoso Fernandes | joana.fernandes@fc.up.pt





Responsible Party



UPORTO





Metadata on metadata



 





Contact



Joana Cardoso Fernandes | joana.fernandes@fc.up.pt





Metadata language



English
DOI: 10.15468/dl.u7uhd8
title: Occurrence Download

description: A dataset containing 1466 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Material sample)"
 ]
 }
 },
 "TaxonKey is Melaenornis ardesiacus Berlioz, 1936",
 "Continent is one of (Africa)",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 1466 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081466-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15115247
title: Building a Predator: Macroevolutionary Patterns in the Skull of Abelisauridae

description: Here, there is the supplementary information (R scripts and tps files) from Building a Predator: Macroevolutionary Patterns in the Skull of Abelisauridae. The main goal of this work was elucidate phylogenetic modularity and integrations pattersn in the Abelisauridae skull. Additionally, we determinate the morphological disparity over the time and estimate evolutionary rates for each cranial region allowing us to infer the macroevolutionary trends in the Abelisauridae skull.
DOI: 10.5281/zenodo.15775973
title: Building a Predator: Macroevolutionary Patterns in the Skull of Abelisauridae

description: Here, there is the supplementary information (R scripts and tps files) from Building a Predator: Macroevolutionary Patterns in the Skull of Abelisauridae. The main goal of this work was elucidate phylogenetic modularity and integrations pattersn in the Abelisauridae skull. Additionally, we determinate the morphological disparity over the time and estimate evolutionary rates for each cranial region allowing us to infer the macroevolutionary trends in the Abelisauridae skull.
DOI: 10.34740/kaggle/dsv/12332229
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.p5aand
title: Occurrence Download

description: A dataset containing 1434 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Salix fragilis L.",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1434 records from 91 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0081467-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.