cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.11360889
title: Raw data of Octopus maya embryos along the development: wet weight, oxygen consumption, antioxidant defence mechanisms and oxidative damage.

description: Raw data on oxygen consumption and antioxidant defense mechanisms of Octopus maya embryos were maintained in laboratory conditions at 24°C. Those data were obtained during the embryo development. The antioxidant defense mechanisms and oxidant damage were also obtained from the ovary and the un-spawned eggs, allowing to us known how is the oxidant damage translated from the females to embryos in this octopus species.
DOI: 10.15468/dl.asr7nb
title: Occurrence Download

description: A dataset containing 24919 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Dysphania ambrosioides (L.) Mosyakin & Clemants"
 ]
}

 The dataset includes 24919 records from 711 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065453-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u3kpwg
title: Occurrence Download

description: A dataset containing 1161 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "TaxonKey is one of (Plethodon variolatus (Gilliams, 1818))"
 ]
}

 The dataset includes 1161 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018286-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cc2pfw
title: Occurrence Download

description: A dataset containing 33487 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((118.03623 61.61232,89.82428 68.4221,27.23913 76.85326,-11.02536 67.125,-11.02536 34.04891,15.88949 35.34601,95.98551 36.31884,118.03623 61.61232))",
 "TaxonKey is Ulmus laevis Pall."
 ]
}

 The dataset includes 33487 records from 532 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000511-250225085111116/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.28pcaf
title: Occurrence Download

description: A dataset containing 4847 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is France",
 "OccurrenceStatus is Present",
 "TaxonKey is Procambarus clarkii (Girard, 1852)",
 "Year 2020-2025"
 ]
}

 The dataset includes 4847 records from 181 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000514-250225085111116/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xy7ftm
title: Occurrence Download

description: A dataset containing 103 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Congo, Democratic Republic of the",
 "OccurrenceStatus is Present",
 "TaxonKey is Loxodonta africana (Blumenbach, 1797)"
 ]
}

 The dataset includes 103 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000515-250225085111116/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2ag6kg
title: Occurrence Download

description: A dataset containing 52514 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Xanthium strumarium L."
 ]
}

 The dataset includes 52514 records from 937 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000513-250225085111116/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1047219.10fu
title: SH1047219.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1047220.10fu
title: SH1047220.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1047222.10fu
title: SH1047222.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1047225.10fu
title: SH1047225.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1047226.10fu
title: SH1047226.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1047229.10fu
title: SH1047229.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1047230.10fu
title: SH1047230.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1047232.10fu
title: SH1047232.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.5281/zenodo.14031950
title: Liu Farm (RGB) - October 24, 2024

description: This orthomosaic of Malojloj, Guam was created from 57 images taken on October 24 2024, at 200 ft AGL, with a M350. The mission was planned using the DJI Pilot application and post-processed using Drone Deploy.This project was made possible through funding by the following grant(s): NASA Guam EPSCoR (30-2F-311184-R-5), NASA Guam Space Grant (30-2F-315105-R), and PI-CASC (30-2F-315100-R-5).
description: Disclaimer: The following aerial imagery is intended solely for research purposes related to the assessment of the captured area. It is strictly prohibited to distribute this imagery to any unauthorized individuals or third-party entities without prior authorization.The University of Guam Drone Corps funded by NASA Guam Space Grant and NASA Guam EPSCoR retain all rights to the aerial imagery, including but not limited to copyrights and intellectual property rights. Any unauthorized modification, reproduction, or distribution of the imagery is strictly prohibited.By using this data, you acknowledge and agree to abide by the terms and conditions set forth in this disclaimer. Privacy Disclaimer: The aerial imagery captured for assessment may inadvertently include images of private property and individuals. While every effort has been made to respect privacy, it is possible that identifiable information or sensitive locations may be visible in the imagery. University of Guam Drone Corps and related parties disclaim any responsibility for the unintentional collection or dissemination of such information. The recipient(s) of this imagery are urged to handle it with due care and take necessary precautions to protect the privacy rights of individuals and comply with applicable privacy laws and regulations.
DOI: 10.5281/zenodo.14031951
title: Liu Farm (RGB) - October 24, 2024

description: This orthomosaic of Malojloj, Guam was created from 57 images taken on October 24 2024, at 200 ft AGL, with a M350. The mission was planned using the DJI Pilot application and post-processed using Drone Deploy.This project was made possible through funding by the following grant(s): NASA Guam EPSCoR (30-2F-311184-R-5), NASA Guam Space Grant (30-2F-315105-R), and PI-CASC (30-2F-315100-R-5).
description: Disclaimer: The following aerial imagery is intended solely for research purposes related to the assessment of the captured area. It is strictly prohibited to distribute this imagery to any unauthorized individuals or third-party entities without prior authorization.The University of Guam Drone Corps funded by NASA Guam Space Grant and NASA Guam EPSCoR retain all rights to the aerial imagery, including but not limited to copyrights and intellectual property rights. Any unauthorized modification, reproduction, or distribution of the imagery is strictly prohibited.By using this data, you acknowledge and agree to abide by the terms and conditions set forth in this disclaimer. Privacy Disclaimer: The aerial imagery captured for assessment may inadvertently include images of private property and individuals. While every effort has been made to respect privacy, it is possible that identifiable information or sensitive locations may be visible in the imagery. University of Guam Drone Corps and related parties disclaim any responsibility for the unintentional collection or dissemination of such information. The recipient(s) of this imagery are urged to handle it with due care and take necessary precautions to protect the privacy rights of individuals and comply with applicable privacy laws and regulations.
DOI: 10.6084/m9.figshare.30997191
title: Statistical outputs (Tables S1 to S3) from The geological imprint of neodymium isotopes in marine gastropods

description: Statistical outputs (Tables S1 to S3)
DOI: 10.6084/m9.figshare.30997191.v1
title: Statistical outputs (Tables S1 to S3) from The geological imprint of neodymium isotopes in marine gastropods

description: Statistical outputs (Tables S1 to S3)
DOI: 10.6084/m9.figshare.30997194
title: Raw data from The geological imprint of neodymium isotopes in marine gastropods

description: Raw data
DOI: 10.6084/m9.figshare.30997194.v1
title: Raw data from The geological imprint of neodymium isotopes in marine gastropods

description: Raw data
DOI: 10.5281/zenodo.13678532
title: Ugum (RGB) - August 23 2024

description: This orthomosaic of Talofofo, Guam was created from 921 images taken on August 23 2024, at 400 ft AGL, with a M350. The mission was planned using the DJI Pilot application and post-processed using DroneDeploy.This project was made possible through funding by the following grant(s): NASA Guam EPSCoR (80NSSC22M0052), NASA Guam Space Grant (80NSSC20M0039 / UH Subaward: MA1550), and PI-CASC (G19AC00087).
description: Disclaimer: The following aerial imagery is intended solely for research purposes related to the assessment of the captured area. It is strictly prohibited to distribute this imagery to any unauthorized individuals or third-party entities without prior authorization.The University of Guam Drone Corps funded by NASA Guam Space Grant and NASA Guam EPSCoR retain all rights to the aerial imagery, including but not limited to copyrights and intellectual property rights. Any unauthorized modification, reproduction, or distribution of the imagery is strictly prohibited.By using this data, you acknowledge and agree to abide by the terms and conditions set forth in this disclaimer. Privacy Disclaimer: The aerial imagery captured for assessment may inadvertently include images of private property and individuals. While every effort has been made to respect privacy, it is possible that identifiable information or sensitive locations may be visible in the imagery. University of Guam Drone Corps and related parties disclaim any responsibility for the unintentional collection or dissemination of such information. The recipient(s) of this imagery are urged to handle it with due care and take necessary precautions to protect the privacy rights of individuals and comply with applicable privacy laws and regulations.
DOI: 10.5281/zenodo.13678531
title: Ugum (RGB) - August 23 2024

description: This orthomosaic of Talofofo, Guam was created from 921 images taken on August 23 2024, at 400 ft AGL, with a M350. The mission was planned using the DJI Pilot application and post-processed using DroneDeploy.This project was made possible through funding by the following grant(s): NASA Guam EPSCoR (80NSSC22M0052), NASA Guam Space Grant (80NSSC20M0039 / UH Subaward: MA1550), and PI-CASC (G19AC00087).
description: Disclaimer: The following aerial imagery is intended solely for research purposes related to the assessment of the captured area. It is strictly prohibited to distribute this imagery to any unauthorized individuals or third-party entities without prior authorization.The University of Guam Drone Corps funded by NASA Guam Space Grant and NASA Guam EPSCoR retain all rights to the aerial imagery, including but not limited to copyrights and intellectual property rights. Any unauthorized modification, reproduction, or distribution of the imagery is strictly prohibited.By using this data, you acknowledge and agree to abide by the terms and conditions set forth in this disclaimer. Privacy Disclaimer: The aerial imagery captured for assessment may inadvertently include images of private property and individuals. While every effort has been made to respect privacy, it is possible that identifiable information or sensitive locations may be visible in the imagery. University of Guam Drone Corps and related parties disclaim any responsibility for the unintentional collection or dissemination of such information. The recipient(s) of this imagery are urged to handle it with due care and take necessary precautions to protect the privacy rights of individuals and comply with applicable privacy laws and regulations.
DOI: 10.5281/zenodo.15209825
title: GloCE v1.0: Global CO2 Enhancement Dataset 2019-2023

description: We present a globally consistent, satellite-derived dataset of CO_2 enhancement (ΔXCO_2), quantifying the spatially resolved excess in atmospheric CO_2 concentrations as a collective consequence of anthropogenic emissions and terrestrial carbon uptake. This dataset is generated from the deviations of NASA's OCO-3 satellite retrievals comprising 54 million observations across more than 200 countries from 2019 to 2023.



The dataset is now encrypted and will be openly accessable once the article review process completes. 

If you are eager for early access of the dataset, please email <your name, affiliation, and data use> to yulunzhou@hku.hk. We will carefully consider your request. 


 

Dear reviewers, please download the datasets here and access using the password enclosed in the review documents. Many thanks!

 

Data Descriptions ----------------------------------------- 



CO2_enhancement_global.nc contains all enhancement data globally. 

CO2_enhancement_cities.nc contains all enhancement data in global urban areas. 

Each data row contains the following columns: <latitude, longitude, time, xco2, co2_enhancement>

Datasets are stored in netcdf files and can be accessed using the Python code below:




# install pre-requests

! pip install netcdf4! pip install h5netcdf

# read co2 enhancement dataimport xarray as xrfn = './CO2_Enhancements_Global.nc'data = xr.open_dataset(fn)type(data)




please refer to xarray documentation for basic xarray operations. https://docs.xarray.dev/en/latest/generated/xarray.Dataset.html


 

Please cite at least one of the following for any use of the CO2E dataset.



Zhou, Y.*, Fan, P., Liu, J., Xu, Y., Huang, B., Webster, C. (2025). GloCE v1.0: Global CO2 Enhancement Dataset 2019-2023 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.15209825

Fan, P., Liu, J., Xu, Y., Huang, B., Webster, C., & Zhou, Y*. (Under Review) A global dataset of CO2 enhancements during 2019-2023. 


 

For any data inquiries, please email Yulun Zhou at yulunzhou@hku.hk.