cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.12605695
title: SD4EO - Physically Based Rendering images of crop fields (Sentinel-2 B2B3B4B8B11 & Sentinel-1 SAR)

description: This dataset contains part of the results of the SD4EO project, including images corresponding to the use case of crop fields identification. The dataset contains images that have been simulated corresponding to different sensors of the Sentinel 1 and Sentinel 2 satellites and regarding 9 different types of crops. Each image in the dataset includes pixel-level labels for each element present in the image, ensuring perfect accuracy due to the synthetic nature of the images. This eliminates common errors in manual or semi-automatic labeling processes.

Multispectral images included

Sentinel 1: SAR (Synthetic Aperture Radar) images.Sentinel 2: Images from bands 2, 3, 4, 8, and 11.

Image labeling








Crop



R



G



B





Alfalfa or lucerne



47



255



0





Barley



35



192



0





Fallow and bare soil



25



135



0





Oats



118



178



105





Other grain leguminous



38



79



29





Peas



44



217



70





Sunflower



78



123



68





Vetch



33



58



28





Wheat



130



255



102






Image name convention

The name convention follows the next schema of fields, separated by the character “_”

-          ID number

-          Meters per pixel resolution

-          Month

-          Type of image (Sentinel 2 band, Sentinel 1 SAR or labels): B2B3B4, B8, B11, SAR, labels

Image formats

TIFF format is used to save each band with floating point precision in the original range of the satellite images.

PNG format is used to display each band in normalized values [0..1].






Type of data



PNG range



TIFF range





B2



0 - 255



0 - 2000





B3



0 - 255



0 - 2500





B4



0 - 255



0 - 3000





B8



0 - 255



1180 - 5736





B11



0 - 255



859 - 5648





SAR



0 - 255



-31.45273 - -14.23931





Creation and funding

All the images have been generated using a tool developed in Unity. This tool will be soon available to enable the generation of new datasets.

This research work has been funded by the European Space Agency (ESA) under the FutureEO program and the SD4EO project (Contract No.: 4000142334/23/I-DT), supervised by the ESA Φ-lab.

License and attribution

This dataset is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

When using the images from this dataset, please attribute them as follows: "Synthetic images created by the research group ARTEC - IRTIC - University of Valencia".
DOI: 10.5281/zenodo.12605696
title: SD4EO - Physically Based Rendering images of crop fields (Sentinel-2 B2B3B4B8B11 & Sentinel-1 SAR)

description: This dataset contains part of the results of the SD4EO project, including images corresponding to the use case of crop fields identification. The dataset contains images that have been simulated corresponding to different sensors of the Sentinel 1 and Sentinel 2 satellites and regarding 9 different types of crops. Each image in the dataset includes pixel-level labels for each element present in the image, ensuring perfect accuracy due to the synthetic nature of the images. This eliminates common errors in manual or semi-automatic labeling processes.

Multispectral images included

Sentinel 1: SAR (Synthetic Aperture Radar) images.Sentinel 2: Images from bands 2, 3, 4, 8, and 11.

Image labeling








Crop



R



G



B





Alfalfa or lucerne



47



255



0





Barley



35



192



0





Fallow and bare soil



25



135



0





Oats



118



178



105





Other grain leguminous



38



79



29





Peas



44



217



70





Sunflower



78



123



68





Vetch



33



58



28





Wheat



130



255



102






Image name convention

The name convention follows the next schema of fields, separated by the character “_”

-          ID number

-          Meters per pixel resolution

-          Month

-          Type of image (Sentinel 2 band, Sentinel 1 SAR or labels): B2B3B4, B8, B11, SAR, labels

Image formats

TIFF format is used to save each band with floating point precision in the original range of the satellite images.

PNG format is used to display each band in normalized values [0..1].






Type of data



PNG range



TIFF range





B2



0 - 255



0 - 2000





B3



0 - 255



0 - 2500





B4



0 - 255



0 - 3000





B8



0 - 255



1180 - 5736





B11



0 - 255



859 - 5648





SAR



0 - 255



-31.45273 - -14.23931





Creation and funding

All the images have been generated using a tool developed in Unity. This tool will be soon available to enable the generation of new datasets.

This research work has been funded by the European Space Agency (ESA) under the FutureEO program and the SD4EO project (Contract No.: 4000142334/23/I-DT), supervised by the ESA Φ-lab.

License and attribution

This dataset is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

When using the images from this dataset, please attribute them as follows: "Synthetic images created by the research group ARTEC - IRTIC - University of Valencia".
DOI: 10.5281/zenodo.12606090
title: Dataset for '3D printing of customizable transient bioelectronics and sensors'

description: This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the recent publication entitled “3D printing of customizable transient bioelectronics and sensors”.

This work aims to study and demonstrate the fabrication by 3D printing of devices made of transient materials, i.e. materials that can break down and degrade in an environment of choice. Biodegradable electronic devices have potential in tackling the issue of electronic waste and present an opportunity for new types of implantable and/or wearable devices that can resorb after their lifecycle is completed. A bioresorbable elastomer and a conductive carbon-based ink are printed by direct-ink writing, thanks to an in depth study of their dispense behavior. Several sensors are shown as demonstrators (strain, pressure, electrodes). The data that was collected in the frame of this work is present in this repository. More information about the contents of the dataset is present in the included README file.
DOI: 10.5281/zenodo.12606091
title: Dataset for '3D printing of customizable transient bioelectronics and sensors'

description: This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the recent publication entitled “3D printing of customizable transient bioelectronics and sensors”.

This work aims to study and demonstrate the fabrication by 3D printing of devices made of transient materials, i.e. materials that can break down and degrade in an environment of choice. Biodegradable electronic devices have potential in tackling the issue of electronic waste and present an opportunity for new types of implantable and/or wearable devices that can resorb after their lifecycle is completed. A bioresorbable elastomer and a conductive carbon-based ink are printed by direct-ink writing, thanks to an in depth study of their dispense behavior. Several sensors are shown as demonstrators (strain, pressure, electrodes). The data that was collected in the frame of this work is present in this repository. More information about the contents of the dataset is present in the included README file.
DOI: 10.6084/m9.figshare.25990438
title: Review of environmental airborne pyrene/benzo[a]pyrene levels from industrial emissions for the improvement of 1-hydroxypyrene biomonitoring interpretation

description: Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous pollutants of significant public health concern, with several that are highly toxic to humans, including some proven or suspected carcinogens. To account for the high variability of PAH mixtures encountered in occupational settings, adjusting urinary 1-hydroxypyrene (1-OHP) levels by the total airborne pyrene (PyrT)/benzo[a]pyrene (BaP) ratio is essential for human biomonitoring (HBM). Given the complexity and cost of systematically monitoring atmospheric levels, alternative approaches to simultaneous airborne and HBM are required. The aim of this review was to catalog airborne PyrT/BaP ratios measured during different industrial activities and recommend 1-OHP-dedicated biological guidance values (BGV). A literature search was conducted. Seventy-one studies were included, with 5619 samples pertaining to 15 industrial sectors, 79 emission processes, and 213 occupational activities. This review summarized more than 40 years of data from almost 20 countries and highlighted the diversity and evolution of PAH emissions. PyrT/BaP ratios were highly variable, ranging from 0.8 in coke production to nearly 40 in tire and rubber production. A single PyrT/BaP value cannot apply to all occupational contexts, raising the question of the relevance of defining a single biological limit value for 1-OHP in industrial sectors where the PyrT/BaP ratio variability is high. Based upon the inventory, a practical approach is proposed for systematic PAH exposure and risk assessment, with a simple frame to follow based upon specific 1-OHP BGVs depending upon the occupational context and setup of a free PAH HBM interactive tool.
DOI: 10.6084/m9.figshare.25990438.v1
title: Review of environmental airborne pyrene/benzo[a]pyrene levels from industrial emissions for the improvement of 1-hydroxypyrene biomonitoring interpretation

description: Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous pollutants of significant public health concern, with several that are highly toxic to humans, including some proven or suspected carcinogens. To account for the high variability of PAH mixtures encountered in occupational settings, adjusting urinary 1-hydroxypyrene (1-OHP) levels by the total airborne pyrene (PyrT)/benzo[a]pyrene (BaP) ratio is essential for human biomonitoring (HBM). Given the complexity and cost of systematically monitoring atmospheric levels, alternative approaches to simultaneous airborne and HBM are required. The aim of this review was to catalog airborne PyrT/BaP ratios measured during different industrial activities and recommend 1-OHP-dedicated biological guidance values (BGV). A literature search was conducted. Seventy-one studies were included, with 5619 samples pertaining to 15 industrial sectors, 79 emission processes, and 213 occupational activities. This review summarized more than 40 years of data from almost 20 countries and highlighted the diversity and evolution of PAH emissions. PyrT/BaP ratios were highly variable, ranging from 0.8 in coke production to nearly 40 in tire and rubber production. A single PyrT/BaP value cannot apply to all occupational contexts, raising the question of the relevance of defining a single biological limit value for 1-OHP in industrial sectors where the PyrT/BaP ratio variability is high. Based upon the inventory, a practical approach is proposed for systematic PAH exposure and risk assessment, with a simple frame to follow based upon specific 1-OHP BGVs depending upon the occupational context and setup of a free PAH HBM interactive tool.
DOI: 10.5281/zenodo.12579171
title: SD4EO - Physically Based Rendering images of human settlements for solar panel detection

description: This dataset contains part of the results of the SD4EO project, including images corresponding to the use case of solar panel detection on human settlements. The dataset contains images that have been simulated corresponding to low altitude aerial images. Each image in the dataset includes pixel-level labels for each element present in the image, ensuring perfect accuracy due to the synthetic nature of the images. This eliminates common errors in manual or semi-automatic labeling processes.

Image labeling

(Open Street Map color code)








Element



R



G



B





Road



255



255



255





Building



196



182



171





Highway



232



146



162





Industrial zone



234



203



228





Parking



238



238



238





Railway



112



112



112





Residential zone



224



223



223





Vegetation



174



223



163





Water



170



211



223






For solar panels masks white color is used to mark the pixels corresponding to solar panels.

Image name convention

The name convention follows the next schema of fields, separated by the character “_”

-          ID number

-          Sub ID number

-          Meters per pixel resolution

-          Type of image: color, labels, solarpanels

Creation and funding

All the images have been generated using a tool developed in Unity. This tool will be soon available to enable the generation of new datasets.

This research work has been funded by the European Space Agency (ESA) under the FutureEO program and the SD4EO project (Contract No.: 4000142334/23/I-DT), supervised by the ESA Φ-lab.

License and attribution

This dataset is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

When using the images from this dataset, please attribute them as follows: "Synthetic images created by the research group ARTEC - IRTIC - University of Valencia".
DOI: 10.5281/zenodo.12579172
title: SD4EO - Physically Based Rendering images of human settlements for solar panel detection

description: This dataset contains part of the results of the SD4EO project, including images corresponding to the use case of solar panel detection on human settlements. The dataset contains images that have been simulated corresponding to low altitude aerial images. Each image in the dataset includes pixel-level labels for each element present in the image, ensuring perfect accuracy due to the synthetic nature of the images. This eliminates common errors in manual or semi-automatic labeling processes.

Image labeling

(Open Street Map color code)








Element



R



G



B





Road



255



255



255





Building



196



182



171





Highway



232



146



162





Industrial zone



234



203



228





Parking



238



238



238





Railway



112



112



112





Residential zone



224



223



223





Vegetation



174



223



163





Water



170



211



223






For solar panels masks white color is used to mark the pixels corresponding to solar panels.

Image name convention

The name convention follows the next schema of fields, separated by the character “_”

-          ID number

-          Sub ID number

-          Meters per pixel resolution

-          Type of image: color, labels, solarpanels

Creation and funding

All the images have been generated using a tool developed in Unity. This tool will be soon available to enable the generation of new datasets.

This research work has been funded by the European Space Agency (ESA) under the FutureEO program and the SD4EO project (Contract No.: 4000142334/23/I-DT), supervised by the ESA Φ-lab.

License and attribution

This dataset is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

When using the images from this dataset, please attribute them as follows: "Synthetic images created by the research group ARTEC - IRTIC - University of Valencia".
DOI: 10.15468/dl.2ujvhe
title: Occurrence Download

description: A dataset containing 9726 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Populus fremontii S.Watson"
 ]
}

 The dataset includes 9726 records from 160 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006662-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nyvje8
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is New Zealand Biodiversity Recording Network",
 "HasGeospatialIssue is false",
 "Country is New Zealand",
 "Modified is 2024-05"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006665-240626123714530/datasets/export for details.
DOI: 10.15468/dl.syvkee
title: Occurrence Download

description: A dataset containing 262 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Hibiscus microcarpus Garcke"
 ]
}

 The dataset includes 262 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006664-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fy5vwh
title: Occurrence Download

description: A dataset containing 262 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Hibiscus microcarpus Garcke"
 ]
}

 The dataset includes 262 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006666-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3ax8u4
title: Occurrence Download

description: A dataset containing 61 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hibiscus marlothianus K.Schum."
 ]
}

 The dataset includes 61 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006668-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3dh3r4
title: Occurrence Download

description: A dataset containing 9726 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Populus fremontii S.Watson"
 ]
}

 The dataset includes 9726 records from 160 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006663-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18112/openneuro.ds004305.v1.0.2
title: Mapping neuroinflammation in vivo with diffusion-MRI in rats given a systemic lipopolysaccharide challenge
DOI: 10.15468/dl.zru35j
title: Occurrence Download

description: A dataset containing 61 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hibiscus marlothianus K.Schum."
 ]
}

 The dataset includes 61 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006670-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x378ss
title: Occurrence Download

description: A dataset containing 634 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Acanthus ebracteatus Vahl"
 ]
}

 The dataset includes 634 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006669-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10699488
title: Assessing and Correcting Neighborhood Socioeconomic Spatial Sampling Biases in Citizen Science Mosquito Data Collection

description: Reporting data from the Mosquito Alert citizen science system used in "Assessing and Correcting Neighborhood Socioeconomic Spatial Sampling Biases in Citizen Science Mosquito Data Collection." The file named mosquito_alert_adult_bite_reports_Barcelona_2014_2023.Rds includes all adult mosquito and mosquito bite reports received from Barcelona Municipality from the start of the Mosqiuto Alert project in 2014 through the end of 2023. The file named mosquito_alert_validated_albopictus_reports_Barcelona_2014_23.Rds includes all expert-validated Ae. albopictus reports received from Barcelona Municipality during the same time period. The data is stored as RDS files and contain the following fields:



year - the year in which the report was made. Class = dbl.

date - the date om which the report was made. Class = date.

type - the report type, either adult mosquito ("adult") or mosquito breeding site ("site"). Class = chr.

lon - the longitude of the report location. Class = dbl.

lat - the latitude of the report location. Class = dbl.

validation_score - Entolab validation score. Either 1 (possible Ae. albopictus) or 2 (probable Ae. albopictus). This field is present only in the validated reports data.
DOI: 10.15468/dl.bkvz7e
title: Occurrence Download

description: A dataset containing 28 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Hibiscus mastersianus Hiern"
 ]
}

 The dataset includes 28 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006671-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10214868
title: Supplementary Data for 'Crossing host boundaries: the evolutionary drivers and correlates of viral host jumps'

description: Maximum likelihood trees, reconstructed ancestral sequences, and visualisation of the trees, produced for viral cliques identified in https://doi.org/10.1101/2023.09.01.555953.
DOI: 10.5281/zenodo.12606377
title: Supplementary Data for 'Crossing host boundaries: the evolutionary drivers and correlates of viral host jumps'

description: This version provides the raw maximum likelihood trees with ancestral host states annotated, as described in Tan et al. 2024 (https://doi.org/10.1038/s41559-024-02353-4). 

 

Tip labels are formatted as {genbank accession}|{host}|{collection_date}|{country}.

Nodel labels are formatted as follows:



rooted_trees_simplified: {node name}|{host}, where {host} is the most likely ancestral state (i.e., highest ancestral state likelihood)




rooted_trees: {node name}|{host1}:{likelihood1}|{host2}:{likelihood2}...|{hostn}:{likelihoodn}, which provides the raw ancestral state likelihoods for each host state. 

All node names correspond to those provided in the Supplementary Tables in Tan et al. 2024.
DOI: 10.5281/zenodo.10214867
title: Supplementary Data for 'Crossing host boundaries: the evolutionary drivers and correlates of viral host jumps'

description: This version provides the raw maximum likelihood trees with ancestral host states annotated, as described in Tan et al. 2024 (https://doi.org/10.1038/s41559-024-02353-4). 

 

Tip labels are formatted as {genbank accession}|{host}|{collection_date}|{country}.

Nodel labels are formatted as follows:



rooted_trees_simplified: {node name}|{host}, where {host} is the most likely ancestral state (i.e., highest ancestral state likelihood)




rooted_trees: {node name}|{host1}:{likelihood1}|{host2}:{likelihood2}...|{hostn}:{likelihoodn}, which provides the raw ancestral state likelihoods for each host state. 

All node names correspond to those provided in the Supplementary Tables in Tan et al. 2024.
DOI: 10.5281/zenodo.10497734
title: Supplementary Data for 'Crossing host boundaries: the evolutionary drivers and correlates of viral host jumps'

description: Maximum likelihood trees, reconstructed ancestral sequences, and visualisation of the trees, produced for viral cliques identified in https://doi.org/10.1101/2023.09.01.555953.
DOI: 10.15468/dl.f2q7ww
title: Occurrence Download

description: A dataset containing 28 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Hibiscus mastersianus Hiern"
 ]
}

 The dataset includes 28 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006672-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.