cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.8urxpy
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((71.935372 24.513134, 71.85819600000001 24.507557, 71.78294099999999 24.490964, 71.711477 24.463769, 71.645577 24.426648, 71.58687399999999 24.380522, 71.536816 24.326537, 71.49663200000001 24.26603, 71.467302 24.200499, 71.449534 24.131564, 71.443747 24.060927, 71.450065 23.990328, 71.46831299999999 23.921504, 71.498024 23.856145, 71.53845200000001 23.795854, 71.588594 23.742109, 71.64721299999999 23.696223, 71.712868 23.659318, 71.783952 23.632295, 71.858728 23.615813, 71.935372 23.610274, 72.012016 23.615813, 72.086792 23.632295, 72.157876 23.659318, 72.22353099999999 23.696223, 72.28215 23.742109, 72.332292 23.795854, 72.37272 23.856145, 72.40243100000001 23.921504, 72.42067900000001 23.990328, 72.426997 24.060927, 72.42121 24.131564, 72.403442 24.200499, 72.374112 24.26603, 72.333928 24.326537, 72.28386999999999 24.380522, 72.225167 24.426648, 72.159267 24.463769, 72.08780299999999 24.490964, 72.012548 24.507557, 71.935372 24.513134))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000148-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.st6j58
title: Occurrence Download

description: A dataset containing 1215 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Antigua and Barbuda",
 "DatasetKey is EOD – eBird Observation Dataset",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Charadriidae",
 "Year 2002-2025"
 ]
}

 The dataset includes 1215 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000149-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18190045
title: VCFcache cache gnomAD v4.1 joint GRCh38 (AF ≥ 0.01) annotated with vep 115.2 -e

description: Abstract VCFcache cache derived from gnomAD v4.1 joint frequency data (GRCh38). Annotation tool: Ensembl VEP 115.2 (via Apptainer). Includes Comprehensive annotation (--everything), HGVS nomenclature (--hgvsg).

Note This upload includes both the annotation cache and its underlying blueprint. The blueprint can be used to build new caches with different annotation recipes.

Contents This underlying blueprint contains 19M high-quality variant sites filtered to allele frequency (AF) ≥ 0.01 (1% or 1 in 100 individuals). All genotype and INFO fields have been removed, retaining only genomic positions (CHROM, POS, REF, ALT). Multiallelic sites have been split into separate records.

Technical detailsCoverage: chr1-22, chrX, chrYSource: gnomAD v4.1.0 joint frequency (807,162 samples)Processing: AF-filtered (≥10%), normalized, GT/INFO removed, multiallelics split, vep annotatedAnnotation tool: Ensembl VEP 115.2VEP cache: Ensembl 115, GRCh38

VEP Annotations Included (CSQ INFO field)Comprehensive annotation (--everything)HGVS nomenclature (--hgvsg)

Setup: vcfcache cache-build --doi <DOI>

Usage: vcfcache annotate -a <cache_dir> -i sample.vcf.gz -o sample_vc.bcf --stats-dir output/

Documentation: VCFcache wiki
DOI: 10.5281/zenodo.18190046
title: VCFcache cache gnomAD v4.1 joint GRCh38 (AF ≥ 0.01) annotated with vep 115.2 -e

description: Abstract VCFcache cache derived from gnomAD v4.1 joint frequency data (GRCh38). Annotation tool: Ensembl VEP 115.2 (via Apptainer). Includes Comprehensive annotation (--everything), HGVS nomenclature (--hgvsg).

Note This upload includes both the annotation cache and its underlying blueprint. The blueprint can be used to build new caches with different annotation recipes.

Contents This underlying blueprint contains 19M high-quality variant sites filtered to allele frequency (AF) ≥ 0.01 (1% or 1 in 100 individuals). All genotype and INFO fields have been removed, retaining only genomic positions (CHROM, POS, REF, ALT). Multiallelic sites have been split into separate records.

Technical detailsCoverage: chr1-22, chrX, chrYSource: gnomAD v4.1.0 joint frequency (807,162 samples)Processing: AF-filtered (≥10%), normalized, GT/INFO removed, multiallelics split, vep annotatedAnnotation tool: Ensembl VEP 115.2VEP cache: Ensembl 115, GRCh38

VEP Annotations Included (CSQ INFO field)Comprehensive annotation (--everything)HGVS nomenclature (--hgvsg)

Setup: vcfcache cache-build --doi <DOI>

Usage: vcfcache annotate -a <cache_dir> -i sample.vcf.gz -o sample_vc.bcf --stats-dir output/

Documentation: VCFcache wiki
DOI: 10.15468/dl.mjh7uk
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Indonesia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Saccharum",
 "Year 2016-2026"
 ]
}

 The dataset includes 19 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000150-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bnq5ma
title: Occurrence Download

description: A dataset containing 34059 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is EOD – eBird Observation Dataset",
 "Geometry POLYGON((-123.80732 40.9164,-123.55359 40.9164,-123.55359 41.19144,-123.80732 41.19144,-123.80732 40.9164))",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 34059 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000151-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cv8q2z
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((71.81464699999999 24.379235, 71.73755300000001 24.373658, 71.66237700000001 24.357065, 71.590988 24.329871, 71.52515699999999 24.292749, 71.466515 24.246623, 71.416509 24.192638, 71.37636500000001 24.13213, 71.347064 24.066599, 71.329313 23.997664, 71.323531 23.927025, 71.32984 23.856425, 71.348068 23.787599, 71.377746 23.722238, 71.418132 23.661946, 71.46822299999999 23.608199, 71.526781 23.562311, 71.59236900000001 23.525405, 71.66338 23.498381, 71.73808099999999 23.481898, 71.81464699999999 23.476359, 71.89121299999999 23.481898, 71.965914 23.498381, 72.036925 23.525405, 72.102513 23.562311, 72.16107100000001 23.608199, 72.211162 23.661946, 72.251548 23.722238, 72.281226 23.787599, 72.299454 23.856425, 72.305763 23.927025, 72.299981 23.997664, 72.28223 24.066599, 72.25292899999999 24.13213, 72.212785 24.192638, 72.162779 24.246623, 72.10413699999999 24.292749, 72.03830600000001 24.329871, 71.966917 24.357065, 71.891741 24.373658, 71.81464699999999 24.379235))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000152-260108223611665/datasets/export for details.
DOI: 10.15468/dl.3z58sf
title: Occurrence Download

description: A dataset containing 599 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Distribución histórica, prospección actual y áreas potenciales para reintroducir lobo mexicano (Canis lupus baileyi) en Durango, sur de la Sierra Madre Occidental, México"
 ]
}

 The dataset includes 599 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000153-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18189987
title: Anonymized Donor–Recipient Clinical Dataset for Artificial Intelligence Models in Liver Transplantation (São Paulo State, 2007–2022)

description: This repository contains an anonymized clinical dataset used in the study “A Study on the Use of Artificial Intelligence in Predicting the Life Expectancy of Liver Graft Recipients”. The data originate from the liver transplant registry of the State of São Paulo, Brazil, and include donor–recipient pairs collected between 2007 and 2022.

The dataset was constructed to support the development and evaluation of machine learning models for predicting 12-month post-transplant survival. It includes demographic, clinical, laboratory, and transplant-related variables that are typically available to transplant teams at the time of organ allocation. After data cleaning, cohort construction, and exclusion criteria, the final dataset comprises 6,982 liver transplant cases.

All personal identifiers were removed, and the data were fully anonymized in compliance with Brazil’s General Data Protection Law (LGPD). The study was approved by the appropriate ethics committee, with a waiver of informed consent due to the use of anonymized registry data.

The dataset can be used for:





Development and benchmarking of predictive models for post-transplant survival




Research on donor–recipient matching and graft allocation




Studies on class imbalance and clinical decision support systems




Reproducibility and validation of results reported in the associated publication



This dataset is provided for research and educational purposes only and is not intended for direct clinical decision-making without appropriate validation.
DOI: 10.5281/zenodo.18189988
title: Anonymized Donor–Recipient Clinical Dataset for Artificial Intelligence Models in Liver Transplantation (São Paulo State, 2007–2022)

description: This repository contains an anonymized clinical dataset used in the study “A Study on the Use of Artificial Intelligence in Predicting the Life Expectancy of Liver Graft Recipients”. The data originate from the liver transplant registry of the State of São Paulo, Brazil, and include donor–recipient pairs collected between 2007 and 2022.

The dataset was constructed to support the development and evaluation of machine learning models for predicting 12-month post-transplant survival. It includes demographic, clinical, laboratory, and transplant-related variables that are typically available to transplant teams at the time of organ allocation. After data cleaning, cohort construction, and exclusion criteria, the final dataset comprises 6,982 liver transplant cases.

All personal identifiers were removed, and the data were fully anonymized in compliance with Brazil’s General Data Protection Law (LGPD). The study was approved by the appropriate ethics committee, with a waiver of informed consent due to the use of anonymized registry data.

The dataset can be used for:





Development and benchmarking of predictive models for post-transplant survival




Research on donor–recipient matching and graft allocation




Studies on class imbalance and clinical decision support systems




Reproducibility and validation of results reported in the associated publication



This dataset is provided for research and educational purposes only and is not intended for direct clinical decision-making without appropriate validation.
DOI: 10.15468/dl.ez7qdy
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((71.959222 24.549117, 71.882024 24.54354, 71.806748 24.526947, 71.735263 24.499752, 71.66934500000001 24.462631, 71.610626 24.416505, 71.560554 24.36252, 71.520359 24.302013, 71.491021 24.236482, 71.473248 24.167548, 71.46746 24.096911, 71.47378 24.026312, 71.49203300000001 23.957488, 71.521753 23.89213, 71.56219299999999 23.83184, 71.61234899999999 23.778095, 71.670984 23.732209, 71.73665699999999 23.695304, 71.807761 23.668282, 71.88255700000001 23.6518, 71.959222 23.646261, 72.035887 23.6518, 72.11068299999999 23.668282, 72.181787 23.695304, 72.24746 23.732209, 72.306095 23.778095, 72.356251 23.83184, 72.396691 23.89213, 72.426411 23.957488, 72.444664 24.026312, 72.45098400000001 24.096911, 72.445196 24.167548, 72.427423 24.236482, 72.39808499999999 24.302013, 72.35789 24.36252, 72.307818 24.416505, 72.249099 24.462631, 72.183181 24.499752, 72.11169599999999 24.526947, 72.03642000000001 24.54354, 71.959222 24.549117))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000154-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3z9fp3
title: Occurrence Download

description: A dataset containing 10814 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Aruba",
 "DatasetKey is EOD – eBird Observation Dataset",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Charadriidae",
 "Year 2002-2025"
 ]
}

 The dataset includes 10814 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000155-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25921/pqwh-nb17
title: EK80 Water Column Sonar Data Collected During NF2505_Leg4
DOI: 10.15468/dl.zcwgdw
title: Occurrence Download

description: A dataset containing 3519511 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Canada",
 "DatasetKey is EOD – eBird Observation Dataset",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Scolopacidae",
 "Year 2002-2025"
 ]
}

 The dataset includes 3519511 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000126-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k4yaqf
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((71.76283100000001 24.466258, 71.68568399999999 24.460681, 71.610456 24.444088, 71.539019 24.416893, 71.47314299999999 24.379772, 71.414462 24.333646, 71.364422 24.27966, 71.324252 24.219153, 71.294932 24.153622, 71.27717 24.084688, 71.271385 24.01405, 71.2777 23.94345, 71.29594 23.874626, 71.32564000000001 23.809266, 71.36605299999999 23.748975, 71.416177 23.695229, 71.47477499999999 23.649342, 71.540407 23.612437, 71.611465 23.585413, 71.68621400000001 23.568931, 71.76283100000001 23.563392, 71.839448 23.568931, 71.914197 23.585413, 71.985255 23.612437, 72.050887 23.649342, 72.10948500000001 23.695229, 72.159609 23.748975, 72.200022 23.809266, 72.229722 23.874626, 72.247962 23.94345, 72.254277 24.01405, 72.248492 24.084688, 72.23072999999999 24.153622, 72.20141 24.219153, 72.16124000000001 24.27966, 72.1112 24.333646, 72.052519 24.379772, 71.986643 24.416893, 71.915206 24.444088, 71.839978 24.460681, 71.76283100000001 24.466258))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000156-260108223611665/datasets/export for details.
DOI: 10.5281/zenodo.18050685
title: Regional divergence and threshold responses in ecosystem resilience to drought under planetary biosphere pressure gradient

description: This repository includes Python scripts and data needed for the manuscript: "Regional divergence and threshold responses in ecosystem resilience to drought under planetary biosphere pressure gradient".
DOI: 10.6084/m9.figshare.27715404.v2
title: CIWW1km: China's 1 km and monthly IWW depth and volume from 2000 to 2020

description: Using knowledge-informed machine learning and multisource data, we developed a new monthly irrigation withdrawal product for China (2000-2020) at a 1 km resolution, named CIWW1km. The product provides both the irrigation withdrawal depth (in mm/year) and volume (in km³/year) for each 1 km grid.Any questions please feel free to contact: zhanglingky@lzb.ac.cn
DOI: 10.6084/m9.figshare.31032910
title: Datasets for DFT and HSE+SOC calculations on halide perovskite materials

description: Theoretical study of the upward band gap bowing effect in halide perovskite materials based on density functional theory (DFT) and hybrid functional (HSE+SOC).
DOI: 10.6084/m9.figshare.31032910.v1
title: Datasets for DFT and HSE+SOC calculations on halide perovskite materials

description: Theoretical study of the upward band gap bowing effect in halide perovskite materials based on density functional theory (DFT) and hybrid functional (HSE+SOC).
DOI: 10.6084/m9.figshare.27715404
title: CIWW1km: China High-Resolution Monthly Irrigation Water Withdrawal Dataset (2000–2020)

description: The CIWW1km dataset was developed based on an innovative physics-constrained estimation framework. By integrating multi-source remote sensing observations (including evapotranspiration and soil moisture products) with reanalysis meteorological data, and grounding the analysis in the soil water balance principle, this framework achieves physically consistent estimates of irrigation water withdrawal components (Zhang, Che*, et al., 2026). Building upon this, interpretable machine learning methods were introduced to optimize the spatiotemporal representation of the physical model outputs, thereby enhancing the overall estimation accuracy (Zhang* et al., 2025). CIWW1km systematically characterizes the spatiotemporal evolution of irrigation water withdrawal in China over the past two decades, providing a critical data foundation for water resources management, agricultural planning, and research on the hydrological cycle under human influence.The dataset provides two key variables at the pixel scale: Irrigation Water Withdrawal Depth (mm, water use per unit area) and Irrigation Water Withdrawal Volume (km³, total water use per grid cell). The data is provided in .tif format. Examples of the file naming convention are as follows:• CIWW_1km_depth_mm_2000_v2.tif (Represents the irrigation water withdrawal depth for the year 2000; "v2" indicates the version number.)• CIWW_1km_depth_mm_2000_01_v2.tif (Represents the irrigation water withdrawal depth for January 2000.)• CIWW_1km_depth_km3_2000_v2.tif (Represents the irrigation water withdrawal volume for the year 2000.)• CIWW_1km_depth_km3_2000_01_v2.tif (Represents the irrigation water withdrawal volume for January 2000.)Any questions please feel free to contact: zhanglingky@lzb.ac.cn or chetao@lzb.ac.cn· Zhang Ling*, Ma Hui, Hu Yingyi, Wang Yixiao, Ma Qimin, Zhao Yanbo. On the Use of Knowledge-Informed Machine Learning and Multisource Data for Spatially Explicit Estimation of Irrigation Water Withdrawal. Earth's Future. 2025. 13(12). e2025E-e6704E.· Zhang Ling, Che Tao*, Zhang Kun, Zheng Donghai, Li Xin. A novel framework for pixel-wise estimation of irrigation water use by integrating remote sensing and reanalysis data. Agricultural Water Management. 2026. 323. 110077
DOI: 10.6084/m9.figshare.27715404.v4
title: CIWW1km: China High-Resolution Monthly Irrigation Water Withdrawal Dataset (2000–2020)

description: The CIWW1km dataset was developed based on an innovative physics-constrained estimation framework. By integrating multi-source remote sensing observations (including evapotranspiration and soil moisture products) with reanalysis meteorological data, and grounding the analysis in the soil water balance principle, this framework achieves physically consistent estimates of irrigation water withdrawal components (Zhang, Che*, et al., 2026). Building upon this, interpretable machine learning methods were introduced to optimize the spatiotemporal representation of the physical model outputs, thereby enhancing the overall estimation accuracy (Zhang* et al., 2025). CIWW1km systematically characterizes the spatiotemporal evolution of irrigation water withdrawal in China over the past two decades, providing a critical data foundation for water resources management, agricultural planning, and research on the hydrological cycle under human influence.The dataset provides two key variables at the pixel scale: Irrigation Water Withdrawal Depth (mm, water use per unit area) and Irrigation Water Withdrawal Volume (km³, total water use per grid cell). The data is provided in .tif format. Examples of the file naming convention are as follows:• CIWW_1km_depth_mm_2000_v2.tif (Represents the irrigation water withdrawal depth for the year 2000; "v2" indicates the version number.)• CIWW_1km_depth_mm_2000_01_v2.tif (Represents the irrigation water withdrawal depth for January 2000.)• CIWW_1km_depth_km3_2000_v2.tif (Represents the irrigation water withdrawal volume for the year 2000.)• CIWW_1km_depth_km3_2000_01_v2.tif (Represents the irrigation water withdrawal volume for January 2000.)Any questions please feel free to contact: zhanglingky@lzb.ac.cn or chetao@lzb.ac.cn· Zhang Ling*, Ma Hui, Hu Yingyi, Wang Yixiao, Ma Qimin, Zhao Yanbo. On the Use of Knowledge-Informed Machine Learning and Multisource Data for Spatially Explicit Estimation of Irrigation Water Withdrawal. Earth's Future. 2025. 13(12). e2025E-e6704E.· Zhang Ling, Che Tao*, Zhang Kun, Zheng Donghai, Li Xin. A novel framework for pixel-wise estimation of irrigation water use by integrating remote sensing and reanalysis data. Agricultural Water Management. 2026. 323. 110077