cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.x3ru2r
title: Occurrence Download

description: A dataset containing 829 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Theobroma bicolor Humb. & Bonpl."
 ]
}

 The dataset includes 829 records from 116 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000398-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15425779
title: Extracted Data

description: This is the extracted dataset for the article: A scoping review of public reporting systems in healthcare.
DOI: 10.15468/dl.qf3zu4
title: Occurrence Download

description: A dataset containing 8016991 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 8016991 records from 1940 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000387-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28832276
title: Formatted NIH RePORTER Files 2014-2023

description: These files were downloaded from NIH RePORTER 5 July 2024.
DOI: 10.5281/zenodo.15253471
title: Supplement: Arabidopsis thaliana RHAMNOSE 1 condensates in heterologous systems

description: This dataset includes all data used for qualitative and quantitative analysis of human cell micrographs for the associated manuscript. To view images or spreadsheets only, download the folder 'raw_data'. To view the analyzed data, download the folder 'analyzed_data'. To reproduce the data using custom analysis scripts, please see the associated software repository for further information and instructions.
DOI: 10.5281/zenodo.15962526
title: Fast Calorimeter Simulation Challenge 2022 - Submissions Dataset 3

description: These are all the submitted samples to dataset 3 of the “Fast Calorimeter Simulation Challenge 2022”. They each consist of 100k calorimeter showers of electrons with energies sampled from a log-uniform distribution ranging from 1 GeV to 1 TeV.

The training data (based on Geant4) can be found at https://doi.org/10.5281/zenodo.6366324, the paper describing the results is available on arXiv:2410.21611, and further details, in particular helper scripts to parse the data and calculate and visualize basic high-level physics features, are available at https://calochallenge.github.io/homepage/.

The subscripts in the file names corresponds to the individual submissions: 




ID number
Submission name
Original reference


_1
CaloDiffusion
arXiv:2308.03876


_2
L2LFlows-MAF
arXiv:2302.11594, arXiv:2405.20407


_3
conv. L2LFlows
arXiv:2405.20407


_5
MDMA
arXiv:2305.15254, arXiv:2408.04997


_6
CaloClouds
arXiv:2305.04847,  arXiv:2309.05704


_7
Calo-VQ
arXiv:2405.06605


_9
CaloScore distilled
arXiv:2206.11898, arXiv:2308.03847


_10
CaloScore single-shot
arXiv:2206.11898, arXiv:2308.03847


_13
iCaloFlow teacher
arXiv:2305.11934


_14
iCaloFlow student
arXiv:2305.11934


_21
Geant4-Transformer
DOI


_23
CaloPointFlow
arXiv:2403.15782


_27
CaloVAE+INN
arXiv:2312.09290


_31
Calo-VQ(norm)
arXiv:2405.06605


_33
CaloDREAM
arXiv:2405.09629




The samples here can be used to reproduce the results of arXiv:2410.21611 and as benchmarks for new models after the challenge concluded.
DOI: 10.5281/zenodo.15962527
title: Fast Calorimeter Simulation Challenge 2022 - Submissions Dataset 3

description: These are all the submitted samples to dataset 3 of the “Fast Calorimeter Simulation Challenge 2022”. They each consist of 100k calorimeter showers of electrons with energies sampled from a log-uniform distribution ranging from 1 GeV to 1 TeV.

The training data (based on Geant4) can be found at https://doi.org/10.5281/zenodo.6366324, the paper describing the results is available on arXiv:2410.21611, and further details, in particular helper scripts to parse the data and calculate and visualize basic high-level physics features, are available at https://calochallenge.github.io/homepage/.

The subscripts in the file names corresponds to the individual submissions: 




ID number
Submission name
Original reference


_1
CaloDiffusion
arXiv:2308.03876


_2
L2LFlows-MAF
arXiv:2302.11594, arXiv:2405.20407


_3
conv. L2LFlows
arXiv:2405.20407


_5
MDMA
arXiv:2305.15254, arXiv:2408.04997


_6
CaloClouds
arXiv:2305.04847,  arXiv:2309.05704


_7
Calo-VQ
arXiv:2405.06605


_9
CaloScore distilled
arXiv:2206.11898, arXiv:2308.03847


_10
CaloScore single-shot
arXiv:2206.11898, arXiv:2308.03847


_13
iCaloFlow teacher
arXiv:2305.11934


_14
iCaloFlow student
arXiv:2305.11934


_21
Geant4-Transformer
DOI


_23
CaloPointFlow
arXiv:2403.15782


_27
CaloVAE+INN
arXiv:2312.09290


_31
Calo-VQ(norm)
arXiv:2405.06605


_33
CaloDREAM
arXiv:2405.09629




The samples here can be used to reproduce the results of arXiv:2410.21611 and as benchmarks for new models after the challenge concluded.
DOI: 10.15468/dl.27kkvr
title: Occurrence Download

description: A dataset containing 5517 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Betula platyphylla",
 "Year 1950-2025"
 ]
}

 The dataset includes 5517 records from 93 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014384-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wr6kke
title: Occurrence Download

description: A dataset containing 80382 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Muscicapa adusta)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "License is one of (CC-BY 4.0, CC0 1.0)"
 ]
}

 The dataset includes 80382 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014357-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15961727
title: Fast Calorimeter Simulation Challenge 2022 - Submissions Dataset 1 Photons

description: These are all the submitted samples to dataset 1 (photons) of the “Fast Calorimeter Simulation Challenge 2022”. They each consist of 121,000 calorimeter showers of photons with energies ranging from 256 MeV to 4.2 TeV.

The training data (based on Geant4) can be found at  https://doi.org/10.5281/zenodo.8099322 the paper describing the results is available on arXiv:2410.21611, and further details, in particular helper scripts to parse the data and calculate and visualize basic high-level physics features, are available at https://calochallenge.github.io/homepage/.

The subscripts in the file names corresponds to the individual submissions: 




ID number
Submission name
Original reference


_1
CaloDiffusion
arXiv:2308.03876


_4
CaloINN
arXiv:2312.09290


_7
Calo-VQ
arXiv:2405.06605


_8
CaloScore
arXiv:2206.11898, arXiv:2308.03847


_9
CaloScore distilled
arXiv:2206.11898, arXiv:2308.03847


_10
CaloScore single-shot
arXiv:2206.11898, arXiv:2308.03847


_11
CaloFlow teacher
arXiv:2210.14245


_12
CaloFlow student
arXiv:2210.14245


_16
CaloMan
arXiv:2211.15380


_17
BoloGAN
ATL-SOFT-PUB-2020-006


_25
CaloShower2GAN
arXiv:2309.06515


_26
CaloShower3GAN
arXiv:2309.06515


_27
CaloVAE+INN
arXiv:2312.09290


_28
CaloForest
arXiv:2408.16046


_29
CaloGraph
arxiv:2402.11575




The samples here can be used to reproduce the results of arXiv:2410.21611 and as benchmarks for new models after the challenge concluded.
DOI: 10.5281/zenodo.15961728
title: Fast Calorimeter Simulation Challenge 2022 - Submissions Dataset 1 Photons

description: These are all the submitted samples to dataset 1 (photons) of the “Fast Calorimeter Simulation Challenge 2022”. They each consist of 121,000 calorimeter showers of photons with energies ranging from 256 MeV to 4.2 TeV.

The training data (based on Geant4) can be found at  https://doi.org/10.5281/zenodo.8099322 the paper describing the results is available on arXiv:2410.21611, and further details, in particular helper scripts to parse the data and calculate and visualize basic high-level physics features, are available at https://calochallenge.github.io/homepage/.

The subscripts in the file names corresponds to the individual submissions: 




ID number
Submission name
Original reference


_1
CaloDiffusion
arXiv:2308.03876


_4
CaloINN
arXiv:2312.09290


_7
Calo-VQ
arXiv:2405.06605


_8
CaloScore
arXiv:2206.11898, arXiv:2308.03847


_9
CaloScore distilled
arXiv:2206.11898, arXiv:2308.03847


_10
CaloScore single-shot
arXiv:2206.11898, arXiv:2308.03847


_11
CaloFlow teacher
arXiv:2210.14245


_12
CaloFlow student
arXiv:2210.14245


_16
CaloMan
arXiv:2211.15380


_17
BoloGAN
ATL-SOFT-PUB-2020-006


_25
CaloShower2GAN
arXiv:2309.06515


_26
CaloShower3GAN
arXiv:2309.06515


_27
CaloVAE+INN
arXiv:2312.09290


_28
CaloForest
arXiv:2408.16046


_29
CaloGraph
arxiv:2402.11575




The samples here can be used to reproduce the results of arXiv:2410.21611 and as benchmarks for new models after the challenge concluded.
DOI: 10.15468/dl.3fcmsk
title: Occurrence Download

description: A dataset containing 4979 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Germany",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Martes foina",
 "Year 2018-2025"
 ]
}

 The dataset includes 4979 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014385-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15961923
title: Fast Calorimeter Simulation Challenge 2022 - Submissions Dataset 1 Pions

description: These are all the submitted samples to dataset 1 (pions) of the “Fast Calorimeter Simulation Challenge 2022”. They each consist of 120,800 calorimeter showers of pions with energies ranging from 256 MeV to 4.2 TeV.

The training data (based on Geant4) can be found at  https://doi.org/10.5281/zenodo.8099322 the paper describing the results is available on arXiv:2410.21611, and further details, in particular helper scripts to parse the data and calculate and visualize basic high-level physics features, are available at https://calochallenge.github.io/homepage/.

The subscripts in the file names corresponds to the individual submissions: 




ID number
Submission name
Original reference


_1
CaloDiffusion
arXiv:2308.03876


_4
CaloINN
arXiv:2312.09290


_7
Calo-VQ
arXiv:2405.06605


_11
CaloFlow teacher
arXiv:2210.14245


_12
CaloFlow student
arXiv:2210.14245


_16
CaloMan
arXiv:2211.15380


_17
BoloGAN
ATL-SOFT-PUB-2020-006


_20
DNNCaloSim
thesis, arXiv:2210.06204


_24
CaloShowerGAN
arXiv:2309.06515


_27
CaloVAE+INN
arXiv:2312.09290


_28
CaloForest
arXiv:2408.16046


_29
CaloGraph
arxiv:2402.11575




The samples here can be used to reproduce the results of arXiv:2410.21611 and as benchmarks for new models after the challenge concluded.
DOI: 10.5281/zenodo.15961924
title: Fast Calorimeter Simulation Challenge 2022 - Submissions Dataset 1 Pions

description: These are all the submitted samples to dataset 1 (pions) of the “Fast Calorimeter Simulation Challenge 2022”. They each consist of 120,800 calorimeter showers of pions with energies ranging from 256 MeV to 4.2 TeV.

The training data (based on Geant4) can be found at  https://doi.org/10.5281/zenodo.8099322 the paper describing the results is available on arXiv:2410.21611, and further details, in particular helper scripts to parse the data and calculate and visualize basic high-level physics features, are available at https://calochallenge.github.io/homepage/.

The subscripts in the file names corresponds to the individual submissions: 




ID number
Submission name
Original reference


_1
CaloDiffusion
arXiv:2308.03876


_4
CaloINN
arXiv:2312.09290


_7
Calo-VQ
arXiv:2405.06605


_11
CaloFlow teacher
arXiv:2210.14245


_12
CaloFlow student
arXiv:2210.14245


_16
CaloMan
arXiv:2211.15380


_17
BoloGAN
ATL-SOFT-PUB-2020-006


_20
DNNCaloSim
thesis, arXiv:2210.06204


_24
CaloShowerGAN
arXiv:2309.06515


_27
CaloVAE+INN
arXiv:2312.09290


_28
CaloForest
arXiv:2408.16046


_29
CaloGraph
arxiv:2402.11575




The samples here can be used to reproduce the results of arXiv:2410.21611 and as benchmarks for new models after the challenge concluded.
DOI: 10.15468/dl.rw936n
title: Occurrence Download

description: A dataset containing 50118 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is one of (Europe, Africa, Asia)",
 "MediaType is Audio",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Cicadidae, Orthoptera)"
 ]
}

 The dataset includes 50118 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014370-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.65hpzc
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Capra falconeri)",
 "Country is one of (Bermuda, Canada, Greenland, Saint Pierre and Miquelon, United States of America)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014387-250802193616735/datasets/export for details.
DOI: 10.5517/ccdc.csd.cc2np9g4
title: CCDC 2463336: Experimental Crystal Structure Determination

description: Related Article: Jorge Sangrador-Pérez, Patricia Jiménez-Hernández, Mar García Hernández, E. Carolina Sañudo, Jose Sanchez Costa, Esther Resines-Urien|2025|CrystEngComm|27|5286|doi:10.1039/D5CE00600G
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15468/dl.crwz3n
title: Occurrence Download

description: A dataset containing 57 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Capra falconeri)",
 "Country is one of (Afghanistan, Armenia, Azerbaijan, Bahrain, Bangladesh, Bhutan, Brunei Darussalam, Cambodia, China, Cyprus, Georgia, Hong Kong, India, Indonesia, Iran (Islamic Republic of), Iraq, Israel, Japan, Jordan, Kazakhstan, Korea (Democratic People’s Republic of), Korea, Republic of, Kuwait, Kyrgyzstan, Lao People’s Democratic Republic, Lebanon, Macao, Malaysia, Maldives, Mongolia, Myanmar, Nepal, Oman, Pakistan, Palestine, State of, Philippines, Qatar, Saudi Arabia, Singapore, Sri Lanka, Syrian Arab Republic, Tajikistan, Thailand, Timor-Leste, Türkiye, Turkmenistan, United Arab Emirates, Uzbekistan, Viet Nam, Yemen)"
 ]
}

 The dataset includes 57 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014388-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc2nztvb
title: CCDC 2472493: Experimental Crystal Structure Determination

description: Related Article: Constantin G. Daniliuc, Zhongbiao Jian, Gerhard Erker|2025|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.34740/kaggle/dsv/12679274
title: Daily Public Opinion on Israel-Palestine War
DOI: 10.15468/dl.3pmyjn
title: Occurrence Download

description: A dataset containing 4577 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Muscigralla brevicauda)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "License is one of (CC-BY 4.0, CC0 1.0)"
 ]
}

 The dataset includes 4577 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014386-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15962049
title: Fast Calorimeter Simulation Challenge 2022 - Submissions Dataset 2

description: These are all the submitted samples to dataset 2 of the “Fast Calorimeter Simulation Challenge 2022”. They each consist of 100k calorimeter showers of electrons with energies sampled from a log-uniform distribution ranging from 1 GeV to 1 TeV.

The training data (based on Geant4) can be found at https://doi.org/10.5281/zenodo.6366271 the paper describing the results is available on arXiv:2410.21611, and further details, in particular helper scripts to parse the data and calculate and visualize basic high-level physics features, are available at https://calochallenge.github.io/homepage/.

The subscripts in the file names corresponds to the individual submissions: 




ID number
Submission name
Original reference


_1
CaloDiffusion
arXiv:2308.03876


_3
conv. L2LFlows
arXiv:2405.20407


_4
CaloINN
arXiv:2312.09290


_5
MDMA
arXiv:2305.15254 arXiv:2408.04997


_7
Calo-VQ
arXiv:2405.06605


_8
CaloScore
arXiv:2206.11898, arXiv:2308.03847


_9
CaloScore distilled
arXiv:2206.11898, arXiv:2308.03847


_10
CaloScore single-shot
arXiv:2206.11898, arXiv:2308.03847


_13
iCaloFlow teacher
arXiv:2305.11934


_14
iCaloFlow student
arXiv:2305.11934


_15
SuperCalo
arXiv:2308.11700


_22
DeepTree
arXiv:2311.12616, arXiv:2312.00042


_23
CaloPointFlow
arXiv:2403.15782


_27
CaloVAE+INN
arXiv:2312.09290


_30
CaloLatent
ML4PS@NeurIPS


_32
CaloDiT
ACAT


_33
CaloDREAM
arXiv:2405.09629




The samples here can be used to reproduce the results of arXiv:2410.21611 and as benchmarks for new models after the challenge concluded.
DOI: 10.5281/zenodo.15962050
title: Fast Calorimeter Simulation Challenge 2022 - Submissions Dataset 2

description: These are all the submitted samples to dataset 2 of the “Fast Calorimeter Simulation Challenge 2022”. They each consist of 100k calorimeter showers of electrons with energies sampled from a log-uniform distribution ranging from 1 GeV to 1 TeV.

The training data (based on Geant4) can be found at https://doi.org/10.5281/zenodo.6366271 the paper describing the results is available on arXiv:2410.21611, and further details, in particular helper scripts to parse the data and calculate and visualize basic high-level physics features, are available at https://calochallenge.github.io/homepage/.

The subscripts in the file names corresponds to the individual submissions: 




ID number
Submission name
Original reference


_1
CaloDiffusion
arXiv:2308.03876


_3
conv. L2LFlows
arXiv:2405.20407


_4
CaloINN
arXiv:2312.09290


_5
MDMA
arXiv:2305.15254 arXiv:2408.04997


_7
Calo-VQ
arXiv:2405.06605


_8
CaloScore
arXiv:2206.11898, arXiv:2308.03847


_9
CaloScore distilled
arXiv:2206.11898, arXiv:2308.03847


_10
CaloScore single-shot
arXiv:2206.11898, arXiv:2308.03847


_13
iCaloFlow teacher
arXiv:2305.11934


_14
iCaloFlow student
arXiv:2305.11934


_15
SuperCalo
arXiv:2308.11700


_22
DeepTree
arXiv:2311.12616, arXiv:2312.00042


_23
CaloPointFlow
arXiv:2403.15782


_27
CaloVAE+INN
arXiv:2312.09290


_30
CaloLatent
ML4PS@NeurIPS


_32
CaloDiT
ACAT


_33
CaloDREAM
arXiv:2405.09629




The samples here can be used to reproduce the results of arXiv:2410.21611 and as benchmarks for new models after the challenge concluded.
DOI: 10.5281/zenodo.10060518
title: Replication package for the study "Broken Windows: Correlating historical and new code quality"

description: Is the quality of existing code correlated with the quality of subsequent changes? According to the (controversial) broken windows theory, which inspired this study, disorder sets descriptive norms and signals behavior that further increases it. From a large code corpus, we examine whether code history does indeed affect the evolution of code quality. We examine C code quality metrics and Java code smells in specific files, and see whether subsequent commits by developers continue on that path.  We check whether developers tailor the quality of their commits based on the quality of the file they commit to.  Our results show that history matters, that developers behave differently depending on some aspects of the code quality they encounter, and that programming style inconsistency is not necessarily related to structural qualities. These findings have implications for both software practice and research.
This replication package contains the data and source code used in the study.
DOI: 10.5281/zenodo.10060519
title: Replication package for the study "Broken Windows: Correlating historical and new code quality"

description: Is the quality of existing code correlated with the quality of subsequent changes? According to the (controversial) broken windows theory, which inspired this study, disorder sets descriptive norms and signals behavior that further increases it. From a large code corpus, we examine whether code history does indeed affect the evolution of code quality. We examine C code quality metrics and Java code smells in specific files, and see whether subsequent commits by developers continue on that path.  We check whether developers tailor the quality of their commits based on the quality of the file they commit to.  Our results show that history matters, that developers behave differently depending on some aspects of the code quality they encounter, and that programming style inconsistency is not necessarily related to structural qualities. These findings have implications for both software practice and research.
This replication package contains the data and source code used in the study.
DOI: 10.15468/dl.h3qy7a
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Capra falconeri)",
 "Country is one of (Anguilla, Antigua and Barbuda, Argentina, Aruba, Bahamas, Barbados, Belize, Bolivia (Plurinational State of), Bonaire, Sint Eustatius and Saba, Bouvet Island, Brazil, Cayman Islands, Chile, Colombia, Costa Rica, Cuba, Curaçao, Dominica, Dominican Republic, Ecuador, El Salvador, Falkland Islands (Malvinas), French Guiana, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Montserrat, Nicaragua, Panama, Paraguay, Peru, Puerto Rico, Saint Barthélemy, Saint Kitts and Nevis, Saint Lucia, Saint Martin (French part), Saint Vincent and the Grenadines, Sint Maarten (Dutch part), South Georgia and the South Sandwich Islands, Suriname, Trinidad and Tobago, Turks and Caicos Islands, Uruguay, Venezuela (Bolivarian Republic of), Virgin Islands (British), Virgin Islands (U.S.))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014389-250802193616735/datasets/export for details.