cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/76m7p7mvsg.4
title: Data for: Total factor productivity in the INTA Chinandega rice variety

description: The study focused on measuring the impact of the INTA-Chinandega rice variety on the rate of production increase in 40 farms in the North Pacific region of Nicaragua. Data from INTA Pacific North was used and covered the 7 production cycles. The DEA approach was used as a non-parametric programming method to calculate the Malmquist productivity indices. The results showed that the INTA Chinandega variety had a 1% impact on the average rate of change of TFP. The possible causes of this variability are due to the rate of change in technical efficiency rather than due to INTA Chinandega technology. In the municipality of El Viejo, TFP reached a maximum of 13% year-on-year.
DOI: 10.17632/d4zj4gbbkg.1
title: Data for:Hydro geochemical characterization of groundwater in the northern zone of the San Vicente volcano, El Salvador

description: The data describes the main hydrochemical variables of the study area in the municipality of San Vicente El Salvador.
DOI: 10.17632/d4zj4gbbkg.2
title: Data for:Hydro geochemical characterization of groundwater in the northern zone of the San Vicente volcano, El Salvador

description: The data describes the main hydrochemical variables of the study area in the municipality of San Vicente El Salvador.
DOI: 10.17632/gtpf8t5r9w.4
title: Long-term ambient hydrocarbons exposure and incidence of urinary bladder cancer

description: Metadata for research article 'Long-term ambient hydrocarbons exposure and incidence of urinary bladder cancer.'
DOI: 10.17632/gtpf8t5r9w.5
title: Long-term ambient hydrocarbons exposure and incidence of urinary bladder cancer

description: Metadata for research article 'Long-term ambient hydrocarbons exposure and incidence of urinary bladder cancer.'
DOI: 10.17632/gtpf8t5r9w.1
title: Long-term ambient hydrocarbons exposure and incidence of urinary bladder cancer

description: Metadata for research article 'Long-term ambient hydrocarbons exposure and incidence of urinary bladder cancer.'
DOI: 10.17632/gtpf8t5r9w.3
title: Long-term ambient hydrocarbons exposure and incidence of urinary bladder cancer

description: Metadata for research article 'Long-term ambient hydrocarbons exposure and incidence of urinary bladder cancer.'
DOI: 10.17632/gtpf8t5r9w.6
title: Long-term ambient hydrocarbons exposure and incidence of urinary bladder cancer

description: Metadata for research article 'Long-term ambient hydrocarbons exposure and incidence of urinary bladder cancer.'
DOI: 10.17632/hc37pyb44k.1
title: GSK3-DATA-inhibitors

description: Chemical structure of GSK-3 ligands, and their IC50 (nM) and pIC50 (M) values.
DOI: 10.17045/sthlmuni.21360978
title: Data from flowering plants of Cerastium fontanum recorded in 2017 and 2018 in Hengill, a sub-arctic geothermal area in SW-Iceland (64°03’N; 21°18’W, ~360 m.a.s.l.)

description: This data set includes 2 years of data on flowering phenology and fitness of the perennial herb <em>Cerastium fontanum</em>, as well as temperature data recorded at the location of each plant. The data includes information for 245 flowering individuals in 2017, and for 104 individuals in 2018.
DOI: 10.17045/sthlmuni.21360978.v1
title: Data from flowering plants of Cerastium fontanum recorded in 2017 and 2018 in Hengill, a sub-arctic geothermal area in SW-Iceland (64°03’N; 21°18’W, ~360 m.a.s.l.)

description: This data set includes 2 years of data on flowering phenology and fitness of the perennial herb <em>Cerastium fontanum</em>, as well as temperature data recorded at the location of each plant. The data includes information for 245 flowering individuals in 2017, and for 104 individuals in 2018.
DOI: 10.17045/sthlmuni.21362397.v1
title: Temperature data recorded with Thermochron iButton data loggers in 2018 in Hengill, a sub-arctic geothermal area in SW-Iceland (64°03’N; 21°18’W, ~360 m.a.s.l.)

description: This data set includes temperature data recorded with Thermochron iButton data loggers in 2018. The data comprises 40 pairs of data loggers of which one was located belowground (buried at 10 cm depth) in order to measure soil temperature, and one was located aboveground (10 cm aboveground, on the top of white plastic tubes stuck in the ground, and covered with grey duct tape) in order to measure air temperature. The loggers recorded temperature every 3 hours from October 2017 until June 5th, 2018. The data also includes a measure of instant soil temperature measured in May at the same point where the pair of loggers was located. <br>
DOI: 10.17045/sthlmuni.21362397
title: Temperature data recorded with Thermochron iButton data loggers in 2018 in Hengill, a sub-arctic geothermal area in SW-Iceland (64°03’N; 21°18’W, ~360 m.a.s.l.)

description: This data set includes temperature data recorded with Thermochron iButton data loggers in 2018. The data comprises 40 pairs of data loggers of which one was located belowground (buried at 10 cm depth) in order to measure soil temperature, and one was located aboveground (10 cm aboveground, on the top of white plastic tubes stuck in the ground, and covered with grey duct tape) in order to measure air temperature. The loggers recorded temperature every 3 hours from October 2017 until June 5th, 2018. The data also includes a measure of instant soil temperature measured in May at the same point where the pair of loggers was located. <br>
DOI: 10.5281/zenodo.4272064
title: Labels for Emergency Response Imagery from Hurricane Florence, Hurricane Michael, and Hurricane Isaias

description: The csv file contains human-generated labels for Emergency Response Imagery collected by US National Oceanic and Atmospheric Administration (NOAA) after Hurricane Florence (2018), Hurricane Michael (2018) and Hurricane Isaias (2020). The 7 authors all labeled each of the 300 images (2100 labels total) using an online labeling tool (Rafique et al., 2020). The csv provides the userID (the ID of the anonymous labeler), the NOAA flight, the NOAA image, and 6 labels — allWater (if the image was all water), devType (if the image had human development), washoverType (if the image had washover deposits), dmgType (if the image showed damage to built environment), impactType (if the labeler could identify the coastal impact, using the Storm Impact Scale from Sallenger, 2000), and terrainType (the type of physical environment). Images labeled here correspond to 3 NOAA flights — Florence 20180917a , Michael 20181011a, Isaias 20200804a. These images can be downloaded directly from NOAA (https://storms.ngs.noaa.gov/) or using Moretz et al. (2020a, 2020b). Note also that there is another companion dataset to this, with slightly different labels (Goldstein et al., 2020)
description: {"references": ["Moretz et al. 2020b: https://doi.org/10.21105/joss.02075", "Moretz et al. 2020b: http://doi.org/10.5281/zenodo.3687347", "Goldstein et al 2020: https://doi.org/10.6084/m9.figshare.11604192.v1", "Rafique et al., 2020: http://doi.org/10.5281/zenodo.4000221", "Sallenger, 2000: https://www.jstor.org/stable/4300099"]}
DOI: 10.5281/zenodo.4541480
title: Labels for Emergency Response Imagery from Hurricane Florence, Hurricane Michael, and Hurricane Isaias

description: The csv file contains human-generated labels for Emergency Response Imagery collected by US National Oceanic and Atmospheric Administration (NOAA) after Hurricane Florence (2018), Hurricane Michael (2018) and Hurricane Isaias (2020). All authors contributed to labeling the imagery. There are 4500 labels total for 900 images. All labeling was done with an online labeling tool (Rafique et al., 2020). The csv provides the userID (the ID of the anonymous labeler), the NOAA flight, the NOAA image, and 6 labels — allWater (if the image was all water), devType (if the image had human development), washoverType (if the image had washover deposits), dmgType (if the image showed damage to built environment), impactType (if the labeler could identify the coastal impact, using the Storm Impact Scale from Sallenger, 2000), and terrainType (the type of physical environment). Images labeled here correspond to 3 NOAA flights — Florence 20180917a , Michael 20181011a, Isaias 20200804a. These images can be downloaded directly from NOAA (https://storms.ngs.noaa.gov/) or using Moretz et al. (2020a, 2020b). Note also that there is another companion dataset to this, with slightly different labels (Goldstein et al., 2020)
description: {"references": ["Moretz et al. 2020b: https://doi.org/10.21105/joss.02075", "Moretz et al. 2020b: http://doi.org/10.5281/zenodo.3687347", "Goldstein et al 2020: https://doi.org/10.6084/m9.figshare.11604192.v1", "Rafique et al., 2020: http://doi.org/10.5281/zenodo.4000221", "Sallenger, 2000: https://www.jstor.org/stable/4300099"]}
DOI: 10.5281/zenodo.4694325
title: Labels for Emergency Response Imagery from Hurricane Florence, Hurricane Michael, and Hurricane Isaias

description: The csv file contains human-generated labels for Emergency Response Imagery collected by US National Oceanic and Atmospheric Administration (NOAA) after Hurricane Florence (2018), Hurricane Michael (2018) and Hurricane Isaias (2020). All authors contributed to labeling the imagery. There are 6200 labels total for 1500 images. All labeling was done with an online labeling tool (Rafique et al., 2020). The csv provides the userID (the ID of the anonymous labeler), the NOAA flight, the NOAA image, and 6 labels — allWater (if the image was all water), devType (if the image had buildings/development), washoverType (if the image had washover deposits), dmgType (if the image showed damage to built environment), impactType (if the labeler could identify the coastal impact, using the Storm Impact Scale from Sallenger, 2000), and terrainType (the type of physical environment). Images labeled here correspond to 3 NOAA flights — Florence 20180917a , Michael 20181011a, Isaias 20200804a. These images can be downloaded directly from NOAA (https://storms.ngs.noaa.gov/) or using Moretz et al. (2020a, 2020b). Note also that there is another companion dataset to this, with slightly different labels (Goldstein et al., 2020)
description: {"references": ["Moretz et al. 2020b: https://doi.org/10.21105/joss.02075", "Moretz et al. 2020b: http://doi.org/10.5281/zenodo.3687347", "Goldstein et al 2020: https://doi.org/10.6084/m9.figshare.11604192.v1", "Rafique et al., 2020: http://doi.org/10.5281/zenodo.4000221", "Sallenger, 2000: https://www.jstor.org/stable/4300099"]}
DOI: 10.5281/zenodo.4272063
title: Labels for Emergency Response Imagery from Hurricane Barry, Delta, Dorian, Florence, Ida, Isaias, Laura, Michael, Sally, Zeta, and Tropical Storm Gordon

description: The csv files contain human-generated labels for Emergency Response Imagery collected by US National Oceanic and Atmospheric Administration (NOAA) after Hurricane Barry, Delta, Dorian, Florence, Ida, Isaias, Laura, Michael, Sally, Zeta, and Tropical Storm Gordon. All authors contributed to labeling the imagery. All labeling was done with an open-source labeling tool (Rafique et al., 2020). All csv files provide the userID (the ID of the anonymous labeler), the NOAA flight, the NOAA image, and 6 labels — allWater (if the image was all water), devType (if the image had buildings/development), washoverType (if the image had washover deposits), dmgType (if the image showed damage to built environment), impactType (if the labeler could identify the coastal impact, using the Storm Impact Scale from Sallenger, 2000), and terrainType (the type of physical environment). Images labeled here correspond to multiple NOAA flights — all listed in the csv file for each jpeg image. These jpeg images can be downloaded directly from NOAA (https://storms.ngs.noaa.gov/) or using Moretz et al. (2020a, 2020b). There are three csv files: ReleaseData_10172022.csv has 10,237 labels for 4250 images. These labels were generated by coastal scientists. The csv also contains the Latitude and Longitude of the image center (from NOAA). ReleaseDataQuads.csv has 400 labels for 100 images. These labels were generated by coastal scientists. The images labeled in this set correspond to original NOAA images that have been split into quadrants. Splitting images was done with ImageMagick. The command used to split the images was: `magick mogrify -crop 2x2@ +repage -path ../quadrants *.jpg` The naming convention corresponds to the image quarter — the *-0.jpg is upper left, *-1.jpg is upper right, *-2.jpg is lower left, and *-3.jpg is the lower right. ReleaseDataNCE.csv has 400 labels for 100 images. These images were labeled by non-coastal scientists. Note that the 100 images were also labeled by coastal scientists — those labels can be found in ReleaseData_v3.csv. There is another companion dataset to this, with slightly different labels (Goldstein et al., 2020). A zip file of images is also provided for demonstration purposes (images.zip). These are resized copies made with imagemagick, with the longest dimension set at 2000 pixels ( `mogrify -resize 2000x2000`). For full size images, please download the jpegs directly from NOAA.
description: {"references": ["Moretz et al. 2020b: https://doi.org/10.21105/joss.02075", "Moretz et al. 2020b: http://doi.org/10.5281/zenodo.3687347", "Goldstein et al 2020: https://doi.org/10.6084/m9.figshare.11604192.v1", "Rafique et al., 2020: http://doi.org/10.5281/zenodo.4000221", "Sallenger, 2000: https://www.jstor.org/stable/4300099"]}
DOI: 10.5281/zenodo.4967050
title: Labels for Emergency Response Imagery from Hurricane Florence, Hurricane Michael, and Hurricane Isaias

description: The csv files contain human-generated labels for Emergency Response Imagery collected by US National Oceanic and Atmospheric Administration (NOAA) after Hurricane Florence (2018), Hurricane Michael (2018) and Hurricane Isaias (2020). All authors contributed to labeling the imagery. There are 6600 labels total for 1600 images. All labeling was done with an online labeling tool (Rafique et al., 2020). Both csv files provide the userID (the ID of the anonymous labeler), the NOAA flight, the NOAA image, and 6 labels — allWater (if the image was all water), devType (if the image had buildings/development), washoverType (if the image had washover deposits), dmgType (if the image showed damage to built environment), impactType (if the labeler could identify the coastal impact, using the Storm Impact Scale from Sallenger, 2000), and terrainType (the type of physical environment). Images labeled here correspond to 3 NOAA flights — Florence 20180917a , Michael 20181011a, Isaias 20200804a. These images can be downloaded directly from NOAA (https://storms.ngs.noaa.gov/) or using Moretz et al. (2020a, 2020b). The labels in the `ReleaseDataQuads.csv` corresponds to image files that have been split into quadrants. Splitting images was done with ImageMagick. The command used to split the images was:<br> <br> `magick mogrify -crop 2x2@ +repage -path ../quadrants *.jpg` The naming convention corresponds to the image quarter — the *-0.jpg is upper left, *-1.jpg is upper right, *-2.jpg is lower left, and *-3.jpg is the lower right. Note also that there is another companion dataset to this, with slightly different labels (Goldstein et al., 2020)
description: {"references": ["Moretz et al. 2020b: https://doi.org/10.21105/joss.02075", "Moretz et al. 2020b: http://doi.org/10.5281/zenodo.3687347", "Goldstein et al 2020: https://doi.org/10.6084/m9.figshare.11604192.v1", "Rafique et al., 2020: http://doi.org/10.5281/zenodo.4000221", "Sallenger, 2000: https://www.jstor.org/stable/4300099"]}
DOI: 10.5281/zenodo.5172799
title: Labels for Emergency Response Imagery from Hurricane Florence, Hurricane Michael, and Hurricane Isaias

description: The csv files contain human-generated labels for Emergency Response Imagery collected by US National Oceanic and Atmospheric Administration (NOAA) after Hurricane Florence (2018), Hurricane Michael (2018) and Hurricane Isaias (2020). All authors contributed to labeling the imagery. All labeling was done with an open-source labeling tool (Rafique et al., 2020). All csv files provide the userID (the ID of the anonymous labeler), the NOAA flight, the NOAA image, and 6 labels — allWater (if the image was all water), devType (if the image had buildings/development), washoverType (if the image had washover deposits), dmgType (if the image showed damage to built environment), impactType (if the labeler could identify the coastal impact, using the Storm Impact Scale from Sallenger, 2000), and terrainType (the type of physical environment). Images labeled here correspond to 3 NOAA flights — Florence 20180917a , Michael 20181011a, Isaias 20200804a. These images can be downloaded directly from NOAA (https://storms.ngs.noaa.gov/) or using Moretz et al. (2020a, 2020b). There are three csv files: ReleaseData_v3.csv has 6200 labels for 1500 images. These labels were generated by trained coastal scientists. ReleaseDataQuads.csv has 400 labels for 100 images. These labels were generated by trained coastal scientists. The images labeled in this set correspond to original NOAA images that have been split into quadrants. Splitting images was done with ImageMagick. The command used to split the images was: `magick mogrify -crop 2x2@ +repage -path ../quadrants *.jpg` The naming convention corresponds to the image quarter — the *-0.jpg is upper left, *-1.jpg is upper right, *-2.jpg is lower left, and *-3.jpg is the lower right. ReleaseDataNCE.csv has 400 labels for 100 images. These images were labeled by non-coastal scientists. Note that the 100 images were also labeled by coastal scientists — those labels can be found in ReleaseData_v3.csv. There is another companion dataset to this, with slightly different labels (Goldstein et al., 2020)
description: {"references": ["Moretz et al. 2020b: https://doi.org/10.21105/joss.02075", "Moretz et al. 2020b: http://doi.org/10.5281/zenodo.3687347", "Goldstein et al 2020: https://doi.org/10.6084/m9.figshare.11604192.v1", "Rafique et al., 2020: http://doi.org/10.5281/zenodo.4000221", "Sallenger, 2000: https://www.jstor.org/stable/4300099"]}
DOI: 10.5281/zenodo.7217621
title: Labels for Emergency Response Imagery from Hurricane Barry, Delta, Dorian, Florence, Ida, Isaias, Laura, Michael, Sally, Zeta, and Tropical Storm Gordon

description: The csv files contain human-generated labels for Emergency Response Imagery collected by US National Oceanic and Atmospheric Administration (NOAA) after Hurricane Barry, Delta, Dorian, Florence, Ida, Isaias, Laura, Michael, Sally, Zeta, and Tropical Storm Gordon. All authors contributed to labeling the imagery. All labeling was done with an open-source labeling tool (Rafique et al., 2020). All csv files provide the userID (the ID of the anonymous labeler), the NOAA flight, the NOAA image, and 6 labels — allWater (if the image was all water), devType (if the image had buildings/development), washoverType (if the image had washover deposits), dmgType (if the image showed damage to built environment), impactType (if the labeler could identify the coastal impact, using the Storm Impact Scale from Sallenger, 2000), and terrainType (the type of physical environment). Images labeled here correspond to multiple NOAA flights — all listed in the csv file for each jpeg image. These jpeg images can be downloaded directly from NOAA (https://storms.ngs.noaa.gov/) or using Moretz et al. (2020a, 2020b). There are three csv files: ReleaseData_10172022.csv has 10,237 labels for 4250 images. These labels were generated by coastal scientists. The csv also contains the Latitude and Longitude of the image center (from NOAA). ReleaseDataQuads.csv has 400 labels for 100 images. These labels were generated by coastal scientists. The images labeled in this set correspond to original NOAA images that have been split into quadrants. Splitting images was done with ImageMagick. The command used to split the images was: `magick mogrify -crop 2x2@ +repage -path ../quadrants *.jpg` The naming convention corresponds to the image quarter — the *-0.jpg is upper left, *-1.jpg is upper right, *-2.jpg is lower left, and *-3.jpg is the lower right. ReleaseDataNCE.csv has 400 labels for 100 images. These images were labeled by non-coastal scientists. Note that the 100 images were also labeled by coastal scientists — those labels can be found in ReleaseData_v3.csv. There is another companion dataset to this, with slightly different labels (Goldstein et al., 2020). A zip file of images is also provided for demonstration purposes (images.zip). These are resized copies made with imagemagick, with the longest dimension set at 2000 pixels ( `mogrify -resize 2000x2000`). For full size images, please download the jpegs directly from NOAA.
description: {"references": ["Moretz et al. 2020b: https://doi.org/10.21105/joss.02075", "Moretz et al. 2020b: http://doi.org/10.5281/zenodo.3687347", "Goldstein et al 2020: https://doi.org/10.6084/m9.figshare.11604192.v1", "Rafique et al., 2020: http://doi.org/10.5281/zenodo.4000221", "Sallenger, 2000: https://www.jstor.org/stable/4300099"]}
DOI: 10.17632/xvt393v275.1
title: The data of Potential carbon emissions reduction from fleet schedule reconfiguration of China’s and India’s external routes

description: The data sources and specific steps for data collection are in Table S1. The CCD and LTO carbon emissions of each route and airline are shown in Tables S2 (China-foreign routes) and S3 (India-foreign routes). The specific calculation steps of carbon emission intensity are listed in Table S4. Finally, the carbon emission intensities of each aircraft type can be found in Tables S5 (China-foreign routes) and S6 (India-foreign routes).
DOI: 10.17632/kt97bwfxvk.1
title: Supplemental data files for: Lithospheric structure, rheology, and tectonic dynamics beneath the Lhasa-Gangdese terrane (southern Tibet) based on a 3-D electrical resistivity model

description: Data files for a Magnetotellurics array study on the deep geo-electrical structure of the lithospheric structure in the Lhasa terrane, conducted by China University of Geosciences in Beijing.  W1, W2, E1 and E2 are the four seperated parts of the 3-D inversion.
DOI: 10.17632/kt97bwfxvk.2
title: Supplemental data files for: Lithospheric structure, rheology, and tectonic dynamics beneath the Lhasa-Gangdese terrane (southern Tibet) based on a 3-D electrical resistivity model

description: Data files for a Magnetotellurics array study on the deep geo-electrical structure of the lithospheric structure in the Lhasa terrane, conducted by China University of Geosciences in Beijing.  W1, W2, E1 and E2 are the four seperated parts of the 3-D inversion.
DOI: 10.17632/kt97bwfxvk.3
title: Supplemental data files for: Relationship of the crustal structure, rheology, and tectonic dynamics beneath the Lhasa-Gangdese terrane (southern Tibet) based on a 3-D electrical model

description: Data files for a Magnetotellurics array study on the deep geo-electrical structure of the lithospheric structure in the Lhasa terrane, conducted by China University of Geosciences in Beijing.  W1, W2, E1 and E2 are the four seperated parts of the 3-D inversion.
DOI: 10.17632/kt97bwfxvk.4
title: Supplemental data files for: Relationship of the crustal structure, rheology, and tectonic dynamics beneath the Lhasa-Gangdese terrane (southern Tibet) based on a 3-D electrical model

description: Data files for a Magnetotellurics array study on the deep geo-electrical structure of the lithospheric structure in the Lhasa terrane, conducted by China University of Geosciences in Beijing.  W1, W2, E1 and E2 are the four seperated parts of the 3-D inversion.
DOI: 10.17632/kt97bwfxvk.5
title: Supplemental data files for: Relationship of the crustal structure, rheology, and tectonic dynamics beneath the Lhasa-Gangdese terrane (southern Tibet) based on a 3-D electrical model

description: Data files for a Magnetotellurics array study on the deep geo-electrical structure of the lithospheric structure in the Lhasa terrane, conducted by China University of Geosciences in Beijing.  W1, W2, E1 and E2 are the four seperated parts of the 3-D inversion.