cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.haz33n
title: Occurrence Download

description: A dataset listing the 4258 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((1.54126 54.30601,1.54126 51.60114,10.52441 51.60114,10.52441 54.30601,1.54126 54.30601))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Lepidoptera",
 "Year 1000-2024"
 ]
}

 The dataset's 4258 records were derived from 189 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037595-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wb6qr6
title: Occurrence Download

description: A dataset containing 142534 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tracheophyta",
 "DecimalLatitude is greater than or equal to 49.085278",
 "DecimalLatitude is less than or equal to 54.085278",
 "DecimalLongitude is greater than or equal to 105.0",
 "DecimalLongitude is less than or equal to 110.0",
 "HasCoordinate is TRUE",
 "HasGeospatialIssue is FALSE"
 ]
}

 The dataset includes 142534 records from 102 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037581-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j8uh5w
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((119.472 -0.771817, 119.401731 -0.777383, 119.333191 -0.793945, 119.268068 -0.821095, 119.207964 -0.858164, 119.15436 -0.904241, 119.108575 -0.95819, 119.071736 -1.018685, 119.04475 -1.084235, 119.028283 -1.153227, 119.022741 -1.223962, 119.02826 -1.294699, 119.044706 -1.363696, 119.071675 -1.429255, 119.108503 -1.489759, 119.154285 -1.54372, 119.207893 -1.589809, 119.268007 -1.626888, 119.333146 -1.654046, 119.401707 -1.670614, 119.472 -1.676182, 119.542293 -1.670614, 119.610854 -1.654046, 119.675993 -1.626888, 119.736107 -1.589809, 119.789715 -1.54372, 119.835497 -1.489759, 119.872325 -1.429255, 119.899294 -1.363696, 119.91574 -1.294699, 119.921259 -1.223962, 119.915717 -1.153227, 119.89925 -1.084235, 119.872264 -1.018685, 119.835425 -0.95819, 119.78964 -0.904241, 119.736036 -0.858164, 119.675932 -0.821095, 119.610809 -0.793945, 119.542269 -0.777383, 119.472 -0.771817))"},{"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/0037617-251120083545085/datasets/export for details.
DOI: 10.15468/dl.5vx45m
title: Occurrence Download

description: A dataset containing 58 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sus cebifrons",
 "HasCoordinate is TRUE"
 ]
}

 The dataset includes 58 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037619-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pjkh8y
title: Occurrence Download

description: A dataset containing 30743 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is Vespa velutina",
 "Year is one of (2024, 2025)",
 "HasCoordinate is true",
 "Geometry POLYGON((3.5 43.5, 12.5 43.5, 12.5 50.5, 3.5 50.5, 3.5 43.5))"
 ]
}

 The dataset includes 30743 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037618-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17855969
title: DRFT: A Corpus of Draft–Review–Final Triples for Modeling and Evaluating the Peer-Review Cycle

description:  



DRFT: Draft–Review–Final Triples Dataset

 




📌 Overview


DRFT (Draft–Review–Final Triples) is a curated dataset of 225 triplets that capture the peer-review cycle in scientific publishing.Each instance contains:



The initial draft (submission)

The peer reviews (concatenated comments and/or meta-review)

The final published version (arXiv)


The dataset is distributed as a single .csv file with standardized schema and evaluation signals.

 





📊 Key Features




225 aligned draft–review–final triplets (ICLR + PeerRead).

Two automatic metrics included:



BERTScore (draft ↔ final) – semantic preservation

G-Eval (review → final, GPT-5o-mini) – review uptake with justification



Compact, high-value benchmark for:



Review-conditioned edit planning

Evaluating automatic revisions vs. human finals

Analyzing review facets and revision magnitude





 



📝 Schema (Fields)


Each row in the .csv dataset contains:



base_text → Full text of the initial submission

review → Concatenated peer-review comments/meta-review

final_text → Final version (arXiv)

source → Data source (ICLR/OpenReview, PeerRead)

bertscore → Semantic similarity score (draft ↔ final)

g_eval_score → Review uptake score (1–10)

g_eval_justification → Short justification generated by GPT-5o-mini




 

📈 Corpus Statistics




Base text length (tokens): mean ≈ 4700

Final text length (tokens): mean ≈ 4600

BERTScore: mean ≈ 0.82

G-Eval: mean ≈ 8.31

Correlation: r ≈ –0.33 (complementarity between metrics)


                   



🔧 Usage


Typical research use cases include:



Review-conditioned edit planningGenerate structured edit plans based on review feedback.

Evaluating automatic revisionsBenchmark against human final versions using BERTScore + G-Eval.

Analyzing review facetsStudy how specific feedback drives textual changes.


 



📜 How to Load the Dataset


We provide a helper script drft_loader.py to make it easy to load the dataset into a pandas DataFrame.



Example:




from scripts.drft_loader import load_drft_dataset

# Load the dataset
df = load_drft_dataset("DRFT_dataset.csv")

# Explore
print(df.shape)
print(df.head())
DOI: 10.15468/dl.wdsubf
title: Occurrence Download

description: A dataset containing 620 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Harmothoe rarispina",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 620 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037620-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17603046
title: DRFT: A Corpus of Draft–Review–Final Triples for Modeling and Evaluating the Peer-Review Cycle

description:  



DRFT: Draft–Review–Final Triples Dataset

 




📌 Overview


DRFT (Draft–Review–Final Triples) is a curated dataset of 225 triplets that capture the peer-review cycle in scientific publishing.Each instance contains:



The initial draft (submission)

The peer reviews (concatenated comments and/or meta-review)

The final published version (arXiv)


The dataset is distributed as a single .csv file with standardized schema and evaluation signals.

 





📊 Key Features




225 aligned draft–review–final triplets (ICLR + PeerRead).

Two automatic metrics included:



BERTScore (draft ↔ final) – semantic preservation

G-Eval (review → final, GPT-5o-mini) – review uptake with justification



Compact, high-value benchmark for:



Review-conditioned edit planning

Evaluating automatic revisions vs. human finals

Analyzing review facets and revision magnitude





 



📝 Schema (Fields)


Each row in the .csv dataset contains:



base_text → Full text of the initial submission

review → Concatenated peer-review comments/meta-review

final_text → Final version (arXiv)

source → Data source (ICLR/OpenReview, PeerRead)

bertscore → Semantic similarity score (draft ↔ final)

g_eval_score → Review uptake score (1–10)

g_eval_justification → Short justification generated by GPT-5o-mini




 

📈 Corpus Statistics




Base text length (tokens): mean ≈ 4700

Final text length (tokens): mean ≈ 4600

BERTScore: mean ≈ 0.82

G-Eval: mean ≈ 8.31

Correlation: r ≈ –0.33 (complementarity between metrics)


                   



🔧 Usage


Typical research use cases include:



Review-conditioned edit planningGenerate structured edit plans based on review feedback.

Evaluating automatic revisionsBenchmark against human final versions using BERTScore + G-Eval.

Analyzing review facetsStudy how specific feedback drives textual changes.


 



📜 How to Load the Dataset


We provide a helper script drft_loader.py to make it easy to load the dataset into a pandas DataFrame.



Example:




from scripts.drft_loader import load_drft_dataset

# Load the dataset
df = load_drft_dataset("DRFT_dataset.csv")

# Explore
print(df.shape)
print(df.head())
DOI: 10.5281/zenodo.17821967
title: Geometries for "The role of charge resonances in the benzene dimer"

description: Stacked benzene dimer geometries for the horizontal displacement and intermolecular separation generated based on the geometry provided in Table S3 of the Supporting Information of Sinnokrot and Sherrill, J. Phys. Chem. A 2004, 108, 10200–10207.

Horizontal displacement geometries:

benz_ABC.xyz has displacement D = A.BC Å relative to the sandwiched configuration. The intermolecular separation is R = 3.6 Å

Intermolecular separation geometries:

benz_perp_ABC.xyz has separation R = A.BC Å. The displacement for all these calculations is d = 1.6 Å.
DOI: 10.5281/zenodo.17821966
title: Geometries for "The role of charge resonances in the benzene dimer"

description: Stacked benzene dimer geometries for the horizontal displacement and intermolecular separation generated based on the geometry provided in Table S3 of the Supporting Information of Sinnokrot and Sherrill, J. Phys. Chem. A 2004, 108, 10200–10207.

Horizontal displacement geometries:

benz_ABC.xyz has displacement D = A.BC Å relative to the sandwiched configuration. The intermolecular separation is R = 3.6 Å

Intermolecular separation geometries:

benz_perp_ABC.xyz has separation R = A.BC Å. The displacement for all these calculations is d = 1.6 Å.
DOI: 10.6084/m9.figshare.30820247
title: Database Influence PA in menstrutation

description: Database of study Influence PA in menstrutation<br>
DOI: 10.6084/m9.figshare.30820247.v1
title: Database Influence PA in menstrutation

description: Database of study Influence PA in menstrutation<br>
DOI: 10.5281/zenodo.17855458
title: Tridacna carbon isotope

description: Modern Tridacna δ13C records, including seasonal δ13C values and monthly δ13C values.
DOI: 10.5281/zenodo.17855457
title: Tridacna carbon isotope

description: Modern Tridacna δ13C records, including seasonal δ13C values and monthly δ13C values.
DOI: 10.6084/m9.figshare.30819974.v2
title: Experimenta Data

description: Experimenta Data for Manuscript
DOI: 10.15468/dl.kwmkth
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((110.523 -0.763817, 110.452731 -0.769383, 110.384191 -0.785945, 110.319068 -0.813095, 110.258965 -0.850164, 110.205361 -0.896241, 110.159575 -0.950191, 110.122737 -1.010685, 110.095751 -1.076235, 110.079284 -1.145227, 110.073742 -1.215962, 110.079261 -1.2867, 110.095707 -1.355697, 110.122676 -1.421255, 110.159504 -1.48176, 110.205286 -1.535721, 110.258894 -1.581809, 110.319007 -1.618888, 110.384147 -1.646047, 110.452708 -1.662614, 110.523 -1.668182, 110.593292 -1.662614, 110.661853 -1.646047, 110.726993 -1.618888, 110.787106 -1.581809, 110.840714 -1.535721, 110.886496 -1.48176, 110.923324 -1.421255, 110.950293 -1.355697, 110.966739 -1.2867, 110.972258 -1.215962, 110.966716 -1.145227, 110.950249 -1.076235, 110.923263 -1.010685, 110.886425 -0.950191, 110.840639 -0.896241, 110.787035 -0.850164, 110.726932 -0.813095, 110.661809 -0.785945, 110.593269 -0.769383, 110.523 -0.763817))"},{"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/0037621-251120083545085/datasets/export for details.
DOI: 10.15468/dl.6quasf
title: Occurrence Download

description: A dataset containing 50 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Netherlands",
 "Geometry POLYGON((4.6016 51.8565,4.60449 51.8484,4.5746 51.85553,4.55739 51.83226,4.56717 51.81355,4.62414 51.79583,4.62768 51.76079,4.68772 51.77627,4.73309 51.78903,4.73881 51.80375,4.74847 51.82003,4.73725 51.83569,4.65995 51.85807,4.6016 51.8565))",
 "HasGeospatialIssue is false",
 "TaxonKey is Accipiter nisus",
 "Year 2014-2014"
 ]
}

 The dataset includes 50 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037622-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q5hc9f
title: Occurrence Download

description: A dataset containing 37 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sus celebensis",
 "HasCoordinate is TRUE"
 ]
}

 The dataset includes 37 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037623-251120083545085/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.cc2qcdgz
title: CCDC 2513401: Experimental Crystal Structure Determination

description: Related Article: Babacar DIOP, Ousmane DIOUF, James B. Orton, Ibrahima Elhadji THIAM|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: 10.5517/ccdc.csd.cc2qcdh0
title: CCDC 2513402: Experimental Crystal Structure Determination

description: Related Article: Babacar DIOP, Ousmane DIOUF, James B. Orton, Ibrahima Elhadji THIAM|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: 10.5517/ccdc.csd.cc2qcf8t
title: CCDC 2513426: Experimental Crystal Structure Determination

description: Related Article: bin Liu|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: 10.5517/ccdc.csd.cc2qcf9v
title: CCDC 2513427: Experimental Crystal Structure Determination

description: Related Article: bin Liu|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: 10.15468/dl.kbkujs
title: Occurrence Download

description: A dataset containing 380 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Harmothoe reticulata",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 380 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037624-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17855229
title: Podcast Transcripts (BOW)

description: Description:

This dataset provides bag-of-words (BOW) representations of podcast transcripts derived from a large-scale corpus of English-language podcasts. The corpus spans all 19 Apple Podcasts genres and includes over 15,000 episodes from approximately 1,900 shows.

Transcripts were generated using Hugging Face's Distil-Whisper-Large-v3 automatic speech recognition model. Text is lowercased but otherwise unprocessed.

 

Files:



bow_matrix.npz — Sparse bag-of-words matrix (scipy sparse format, documents × terms)

metadata.csv — Podcast title, episode title, and description for each document (row indices correspond to matrix rows)

vocabulary.csv — Terms in the vocabulary (column indices correspond to matrix


 

Usage:







 





from scipy import sparse
import pandas as pd

bow_matrix = sparse.load_npz('bow_matrix.npz')
metadata = pd.read_csv('metadata.csv')
vocabulary = pd.read_csv('vocabulary.csv')['term'].tolist()

Related publication:

For a detailed description of the data collection and transcription process, see:

Verreyen, L. (2025). Podcasts as Data: Building a Dataset for Large-Scale Audio Content Analysis. In T. Arnold, M. Fantoli, & R. Ros (Eds.), Computational Humanities Research 2025 (Vol. 3, pp. 231–248). Anthology of Computers and the Humanities. https://doi.org/10.63744/QgeF94c0fP7D
DOI: 10.5281/zenodo.17855228
title: Podcast Transcripts (BOW)

description: Description:

This dataset provides bag-of-words (BOW) representations of podcast transcripts derived from a large-scale corpus of English-language podcasts. The corpus spans all 19 Apple Podcasts genres and includes over 15,000 episodes from approximately 1,900 shows.

Transcripts were generated using Hugging Face's Distil-Whisper-Large-v3 automatic speech recognition model. Text is lowercased but otherwise unprocessed.

 

Files:



bow_matrix.npz — Sparse bag-of-words matrix (scipy sparse format, documents × terms)

metadata.csv — Podcast title, episode title, and description for each document (row indices correspond to matrix rows)

vocabulary.csv — Terms in the vocabulary (column indices correspond to matrix


 

Usage:







 





from scipy import sparse
import pandas as pd

bow_matrix = sparse.load_npz('bow_matrix.npz')
metadata = pd.read_csv('metadata.csv')
vocabulary = pd.read_csv('vocabulary.csv')['term'].tolist()

Related publication:

For a detailed description of the data collection and transcription process, see:

Verreyen, L. (2025). Podcasts as Data: Building a Dataset for Large-Scale Audio Content Analysis. In T. Arnold, M. Fantoli, & R. Ros (Eds.), Computational Humanities Research 2025 (Vol. 3, pp. 231–248). Anthology of Computers and the Humanities. https://doi.org/10.63744/QgeF94c0fP7D
DOI: 10.6084/m9.figshare.28151093.v1
title: Database of study fitness users based on health consciousness and UTAUT2

description: This is the data base of the study:Segmentation of fitness users based on health consciousness: Implications for digital sport management
DOI: 10.15468/dl.dqqt95
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((122.519 -0.763817, 122.448731 -0.769383, 122.380191 -0.785945, 122.315068 -0.813095, 122.254965 -0.850164, 122.201361 -0.896241, 122.155575 -0.950191, 122.118737 -1.010685, 122.091751 -1.076235, 122.075284 -1.145227, 122.069742 -1.215962, 122.075261 -1.2867, 122.091707 -1.355697, 122.118676 -1.421255, 122.155504 -1.48176, 122.201286 -1.535721, 122.254894 -1.581809, 122.315007 -1.618888, 122.380147 -1.646047, 122.448708 -1.662614, 122.519 -1.668182, 122.589292 -1.662614, 122.657853 -1.646047, 122.722993 -1.618888, 122.783106 -1.581809, 122.836714 -1.535721, 122.882496 -1.48176, 122.919324 -1.421255, 122.946293 -1.355697, 122.962739 -1.2867, 122.968258 -1.215962, 122.962716 -1.145227, 122.946249 -1.076235, 122.919263 -1.010685, 122.882425 -0.950191, 122.836639 -0.896241, 122.783035 -0.850164, 122.722932 -0.813095, 122.657809 -0.785945, 122.589269 -0.769383, 122.519 -0.763817))"},{"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/0037625-251120083545085/datasets/export for details.
DOI: 10.5281/zenodo.17855936
title: DATASET
DOI: 10.5281/zenodo.17855935
title: DATASET
DOI: 10.15468/dl.dbz9m2
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sus oliveri",
 "HasCoordinate is TRUE"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037627-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yuavga
title: Occurrence Download

description: A dataset containing 30743 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is Vespa velutina",
 "Year is one of (2024, 2025)",
 "HasCoordinate is true",
 "Geometry POLYGON((3.5 43.5, 12.5 43.5, 12.5 50.5, 3.5 50.5, 3.5 43.5))"
 ]
}

 The dataset includes 30743 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037626-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8muyej
title: Occurrence Download

description: A dataset containing 30743 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is Vespa velutina",
 "Year is one of (2024, 2025)",
 "HasCoordinate is true",
 "Geometry POLYGON((3.5 43.5, 12.5 43.5, 12.5 50.5, 3.5 50.5, 3.5 43.5))"
 ]
}

 The dataset includes 30743 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037628-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.