cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.ftezz9
title: Occurrence Download

description: A dataset containing 68211 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is UK Roadkill Records"
 ]
}

 The dataset includes 68211 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029127-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hub55w
title: Occurrence Download

description: A dataset containing 68211 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is UK Roadkill Records"
 ]
}

 The dataset includes 68211 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029128-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/hp2cdckpdr.1
title: MangoBD: An Extensive Image Dataset of Common Mango Varieties in Bangladesh for Identification and Classification

description: Type of data: 504x1120 px mango images.
Data format: JPEG.
Contents of the dataset: Common varieties of mangoes in Bangladesh.

Number of classes: Fifteen (15) common varieties of mangoes of Bangladesh - (1) Amrapali, (2) Ashshina Classic, (3) Ashshina Zhinuk, (4) Banana Mango, (5) Bari-4, (6) Bari-11, (7) Fazli Classic, (8) Fazli Shurmai, (9) Gourmoti, (10) Harivanga, (11) Himsagor, (12) Katimon, (13) Langra, (14) Rupali, and (15) Shada.

Number of images: Total number of images in the dataset: 28,509. 
(1) Total original (raw) images of mango cultivars (MangoOriginal) = 5,703, 
(2) Total processed images with a blend of both real and virtual backgrounds (MangoRealVirtual) = 5,703, and
(3) Total augmented images (MangoAugmented)= 17,103.

Distribution of instances: 
(1) Original (raw) images in each class of the mango cultivars (MangoOriginal): Amrapali = 135, Ashshina Classic = 571, Ashshina Zhinuk = 1,286, Banana Mango = 83, Bari-4 = 74, Bari-11 = 1,244, Fazli Classic = 171, Fazli Shurmai = 247, Gourmoti = 630, Harivanga = 265, Himsagor = 106, Katimon = 424, Langra = 120, Rupali = 184, and Shada = 163. 
(2) Processed images with a blend of both real and virtual backgrounds (MangoRealVirtual): Amrapali = 135, Ashshina Classic = 571, Ashshina Zhinuk = 1,286, Banana Mango = 83, Bari-4 = 74, Bari-11 = 1,244, Fazli Classic = 171, Fazli Shurmai = 247, Gourmoti = 630, Harivanga = 265, Himsagor = 106, Katimon = 424, Langra = 120, Rupali = 184, and Shada = 163.
(3) Augmented images for each class of the mango cultivars (MangoAugmented): Amrapali = 405, Ashshina Classic = 1,713, Ashshina Zhinuk = 3,848, Banana Mango = 249, Bari-4 = 222, Bari-11 = 3,726, Fazli Classic = 513, Fazli Shurmai = 741, Gourmoti = 1,890, Harivanga = 795, Himsagor = 318, Katimon = 1,272, Langra = 360, Rupali = 552, and Shada = 489.

Dataset size: Total size of the dataset = 1.35 GB and the ZIP compressed size = 1.16 GB.

Data acquisition process: Images of various mango varieties are captured through high-definition smartphone cameras focusing from different angles.

Data source location: Local wholesale and retail fruit markets located in different areas of Dhaka and Rangpur districts in Bangladesh.

Where applicable: Training and evaluating machine learning and deep learning models to identify and classify mango varieties in Bangladesh which can be useful in smart horticulture, precision farming, supply chain automation, ecology and ecosystem health monitoring, and biodiversity and conservation efforts.
DOI: 10.17632/hp2cdckpdr.2
title: MangoImageBD: An Extensive Image Dataset of Common and Popular Mango Varieties in Bangladesh for Identification and Classification

description: Type of data: 504 x 1120 px mango images.
Data format: JPEG.
Contents of the dataset: Images (original, processed, and augmented) of common and popular varieties of mangoes in Bangladesh.

Number of classes: Fifteen (15) common and popular varieties of mangoes in Bangladesh - (1) Amrapali, (2) Ashshina Classic, (3) Ashshina Zhinuk, (4) Banana Mango, (5) Bari-4, (6) Bari-11, (7) Fazli Classic, (8) Fazli Shurmai, (9) Gourmoti, (10) Harivanga, (11) Himsagor, (12) Katimon, (13) Langra, (14) Rupali, and (15) Shada.

Number of images: Total number of images in the dataset: 28,515. 
(1) Total original (raw) images of mango cultivars (MangoOriginal) = 5,703, 
(2) Total processed images with a blend of both real and virtual backgrounds (MangoRealVirtual) = 5,703, and
(3) Total augmented images (MangoAugmented)= 17,109.

Distribution of instances: 
(1) Original (raw) images in each class of the mango cultivars (MangoOriginal): Amrapali = 135, Ashshina Classic = 571, Ashshina Zhinuk = 1,286, Banana Mango = 83, Bari-4 = 74, Bari-11 = 1,244, Fazli Classic = 171, Fazli Shurmai = 247, Gourmoti = 630, Harivanga = 265, Himsagor = 106, Katimon = 424, Langra = 120, Rupali = 184, and Shada = 163. 
(2) Processed images with a blend of both real and virtual backgrounds for each class of the mango cultivars (MangoRealVirtual): Amrapali = 135, Ashshina Classic = 571, Ashshina Zhinuk = 1,286, Banana Mango = 83, Bari-4 = 74, Bari-11 = 1,244, Fazli Classic = 171, Fazli Shurmai = 247, Gourmoti = 630, Harivanga = 265, Himsagor = 106, Katimon = 424, Langra = 120, Rupali = 184, and Shada = 163.
(3) Augmented images for each class of the mango cultivars (MangoAugmented): Amrapali = 405, Ashshina Classic = 1,713, Ashshina Zhinuk = 3,858, Banana Mango = 249, Bari-4 = 222, Bari-11 = 3,732, Fazli Classic = 513, Fazli Shurmai = 741, Gourmoti = 1,890, Harivanga = 795, Himsagor = 318, Katimon = 1,272, Langra = 360, Rupali = 552, and Shada = 489.

Dataset size: Total size of the dataset = 1.35 GB and the compressed ZIP file size = 1.16 GB.

Data acquisition process: Images of various mango varieties are captured through high-definition smartphone cameras focusing from different angles.

Data source location: Local wholesale and retail fruit markets located in six geographically distributed districts of Bangladesh, namely Chapai Nawabganj, Dhaka, Panchagarh, Rajshahi, Rangpur, and Satkhira which are renowned for diverse mango cultivation and availability.

Where applicable: Training and evaluating machine learning and deep learning models to identify and classify mango varieties in Bangladesh which can be useful in smart horticulture, precision farming, supply chain automation, ecology and ecosystem health monitoring, and biodiversity and conservation efforts.
DOI: 10.5281/zenodo.14366144
title: GESTÃO DO CONHECIMENTO E GESTÃO DA CADEIA DE SUPRIMENTOS: REVISÃO SISTEMÁTICA DO ESTADO DA ARTE EM UMA DÉCADA DE PESQUISA

description: Este conjuto de dados se refere ao artigo "GESTÃO DO CONHECIMENTO E GESTÃO DA CADEIA DE SUPRIMENTOS: REVISÃO SISTEMÁTICA DO ESTADO DA ARTE EM UMA DÉCADA DE PESQUISA", submetido à revista Transinformação.

Resumo

Este estudo investiga as inter-relações entre a gestão do conhecimento e a gestão da cadeia de suprimentos por meio de uma revisão sistemática da literatura realizada a partir a aplicação do protocolo ‘Preferred Reporting Items for Systematic Reviews and Meta-Analyses’. Identificou-se 1.154 documentos em bases de dados relevantes, resultando em um corpus final de 91 artigos após critérios de inclusão e exclusão predefinidos no referido protocolo. A análise evidenciou o papel da gestão do conhecimento na integração de processos organizacionais e na criação de vantagem competitiva sustentável nas cadeias de suprimentos, destacando práticas, técnicas e lacunas. Os resultados revelam que a gestão do conhecimento potencializa a eficiência da gestão da cadeia de suprimentos ao promover o compartilhamento de conhecimento, subsidiar a inovação e contribuir para a resiliência, com especial ênfase de alguns setores como agroindústria, manufatura e tecnologia. Este estudo possibilita uma visão abrangente do estado da arte das temáticas estudadas, contribui para o avanço teórico e prático de pesquisadores e profissionais que investigam e aplicam teorias, métodos, técnicas, ferramentas e ações de melhoria. Por último, sugere caminhos para o desenvolvimento de futuras pesquisas sobre a aplicação integrada da gestão do conhecimento e gestão da cadeia de suprimentos em cenários organizacionais globais. 

Palavras-Chave: Colaboração Interorganizacional. Gestão da Cadeia de Suprimentos. Gestão do Conhecimento. Inovação. Transferência de Conhecimento.
DOI: 10.5281/zenodo.14366145
title: GESTÃO DO CONHECIMENTO E GESTÃO DA CADEIA DE SUPRIMENTOS: REVISÃO SISTEMÁTICA DO ESTADO DA ARTE EM UMA DÉCADA DE PESQUISA

description: Este conjuto de dados se refere ao artigo "GESTÃO DO CONHECIMENTO E GESTÃO DA CADEIA DE SUPRIMENTOS: REVISÃO SISTEMÁTICA DO ESTADO DA ARTE EM UMA DÉCADA DE PESQUISA", submetido à revista Transinformação.

Resumo

Este estudo investiga as inter-relações entre a gestão do conhecimento e a gestão da cadeia de suprimentos por meio de uma revisão sistemática da literatura realizada a partir a aplicação do protocolo ‘Preferred Reporting Items for Systematic Reviews and Meta-Analyses’. Identificou-se 1.154 documentos em bases de dados relevantes, resultando em um corpus final de 91 artigos após critérios de inclusão e exclusão predefinidos no referido protocolo. A análise evidenciou o papel da gestão do conhecimento na integração de processos organizacionais e na criação de vantagem competitiva sustentável nas cadeias de suprimentos, destacando práticas, técnicas e lacunas. Os resultados revelam que a gestão do conhecimento potencializa a eficiência da gestão da cadeia de suprimentos ao promover o compartilhamento de conhecimento, subsidiar a inovação e contribuir para a resiliência, com especial ênfase de alguns setores como agroindústria, manufatura e tecnologia. Este estudo possibilita uma visão abrangente do estado da arte das temáticas estudadas, contribui para o avanço teórico e prático de pesquisadores e profissionais que investigam e aplicam teorias, métodos, técnicas, ferramentas e ações de melhoria. Por último, sugere caminhos para o desenvolvimento de futuras pesquisas sobre a aplicação integrada da gestão do conhecimento e gestão da cadeia de suprimentos em cenários organizacionais globais. 

Palavras-Chave: Colaboração Interorganizacional. Gestão da Cadeia de Suprimentos. Gestão do Conhecimento. Inovação. Transferência de Conhecimento.
DOI: 10.5281/zenodo.14203527
title: SINFONICA - CCAM Ecosystem Knowledge Graph

description: The end-users and stakeholders needs, expectations, requirements together with their inter-relationships have been structured in a knowledge graph. More specifically:



Classes: 453 defined classes, representing various conceptual entities in the domain.

Object Properties: 71 relationships connecting classes or individuals.

Data Properties: 9 properties describing attributes or data values associated with individuals or classes.

Individuals: 5,222 specific instances of the defined classes.

Relationships: 22,303 triples (subject-predicate-object statements), forming the knowledge base.
DOI: 10.5281/zenodo.14203528
title: SINFONICA - CCAM Ecosystem Knowledge Graph

description: The end-users and stakeholders needs, expectations, requirements together with their inter-relationships have been structured in a knowledge graph. More specifically:



Classes: 453 defined classes, representing various conceptual entities in the domain.

Object Properties: 71 relationships connecting classes or individuals.

Data Properties: 9 properties describing attributes or data values associated with individuals or classes.

Individuals: 5,222 specific instances of the defined classes.

Relationships: 22,303 triples (subject-predicate-object statements), forming the knowledge base.
DOI: 10.17632/wkpfn44sv6.1
title: Cleavage Sequence Specificity of Nsp15

description: Supplemental_DecayAssayGelsandData contains the raw gel images that were used to quantify the percentage of RNA decayed, as well as a tabulation of the quantitative decay results.
Supplemental_DecayAssay_ANOVAValues contains a spreadsheet of the ANOVA values for all possible substrate comparisons
Supplemental_AlphaFold3Models is a .zip file that contains all initially generated AlphaFold3 models & confidence metrics, as well as the 16 models that were chosen to represent the 16 Nsp15-substrate complexes
DOI: 10.3886/hd2a-2881
title: Morocco Employability and Land Compact - Secondary Education: Design Report
DOI: 10.3886/3rhx-8g35
title: Morocco Employability and Land Compact - Secondary Education: Design Report
DOI: 10.15468/dl.zeg6yb
title: Occurrence Download

description: A dataset containing 261 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mammalia",
 "Geometry POLYGON ((-96.73134 19.30259, -96.63575 19.30259, -96.63575 19.39255, -96.73134 19.39255, -96.73134 19.30259))",
 "Year is greater than or equal to 1900",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Material citation)"
 ]
 }
 }
 ]
}

 The dataset includes 261 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029131-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dgqky2
title: Occurrence Download

description: A dataset containing 308 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Saguinus imperator (Goeldi, 1907)"
 ]
}

 The dataset includes 308 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029130-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5fhfef
title: Occurrence Download

description: A dataset containing 79 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Opopanax hispidus (Friv.) Griseb., Ferula opopanax Spreng., Johrenia lycaonica Bornm., Opopanax syriacum Boiss., Opopanax chironium Guss., Ferula hispida Friv., Ferula opoponax (L.) Spreng., Opopanax siculus A.Huet ex Nyman, Malabaila orientalis Benth. & Hook.f., Pastinaca involucrata Stokes, Opopanax siculus A.Huet, Opopanax orientalis Boiss., Peucedanum syriacum (Boiss.) M.Hiroe, Pastinaca hispida (Friv.) Fenzl)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2000"
 ]
}

 The dataset includes 79 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029132-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14363993
title: OpenM3Chest

description: OpenM3Chest  is a medical multimodal multitask dataset for diagnosing chest abnormalities with a focus on lung cancer screening. The raw data are from NLST and MIDRC, and the corresponding imaging data can be obtained from https://www.cancerimagingarchive.net/collection/nlst/ and https://www.midrc.org/
DOI: 10.5281/zenodo.14363994
title: OpenM3Chest

description: OpenM3Chest  is a medical multimodal multitask dataset for diagnosing chest abnormalities with a focus on lung cancer screening. The raw data are from NLST and MIDRC, and the corresponding imaging data can be obtained from https://www.cancerimagingarchive.net/collection/nlst/ and https://www.midrc.org/
DOI: 10.15468/dl.tqz32c
title: Occurrence Download

description: A dataset containing 337 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Origanum onites L., Origanum pallidum Desf., Onites tomentosus Raf., Origanum smyrnaeum L., Origanum tragoriganum Zucc., Majorana cretica Mill., Origanum tragoriganum Zucc. ex Steud., Origanum heracleoticum W.D.J.Koch, Origanum orega Vogel, Majorana cretica var. silvestris Alef., Majorana oreja Walp., Origanum album Salisb., Schizocalyx smyrnaeus (L.) Scheele, Majorana smyrnaea (L.) T.Nees, Majorana onites (L.) Benth., Majorana orega (Vogel) Briq.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2000"
 ]
}

 The dataset includes 337 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029133-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.82pj5y
title: Occurrence Download

description: A dataset containing 187 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Orlaya daucorlaya Murb., Daucus daucorlaya (Murb.) Fiori, Daucus daucorlaya (Murb.) Drude)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2000"
 ]
}

 The dataset includes 187 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029134-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r56ga4
title: Occurrence Download

description: A dataset containing 16460 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Nereocystis luetkeana (K.Mertens) Postels & Ruprecht)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 16460 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029135-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wc864c
title: Occurrence Download

description: A dataset containing 188 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Saguinus labiatus (É.Geoffroy Saint-Hilaire, 1812)"
 ]
}

 The dataset includes 188 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029137-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pzxy2x
title: Occurrence Download

description: A dataset containing 70637 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Aves",
 "Geometry POLYGON ((-96.11957 19.03224, -96.0259 19.03224, -96.0259 19.12156, -96.11957 19.12156, -96.11957 19.03224))",
 "Year is greater than or equal to 1900",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Material citation)"
 ]
 }
 }
 ]
}

 The dataset includes 70637 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029136-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h5frbr
title: Occurrence Download

description: A dataset containing 1408 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Ornithogalum orthophyllum subsp. kochii (Parl.) Zahar., Ornithogalum ruthenicum Bouché, Ornithogalum kochii subsp. urumovianum Stoj., Ornithogalum umbellatum f. angustifolium Batt. & Trab., Ornithogalum kochii Parl., Ornithogalum kodjuricum var. pluriflorum Parsa, Ornithogalum kochii var. elongatum Maire, Ornithogalum kodjuricum Parsa, Ornithogalum ruthenicum Bouché ex Kunth, Ornithogalum umbellatum subsp. tenuifolium Bonnier & Layens, Ornithogalum orthophyllum subsp. kochii (Parl.) Maire & Weiller, Ornithogalum umbellatum subsp. kochii (Parl.) Maire & Weiller, Hyacinthus kochii (Parl.) E.H.L.Krause, Ornithogalum umbellatum var. elongatum (Maire) Maire)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2000"
 ]
}

 The dataset includes 1408 records from 97 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029138-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fapbfw
title: Occurrence Download

description: A dataset containing 70637 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Aves",
 "Geometry POLYGON ((-96.11957 19.03224, -96.0259 19.03224, -96.0259 19.12156, -96.11957 19.12156, -96.11957 19.03224))",
 "Year is greater than or equal to 1900",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Material citation)"
 ]
 }
 }
 ]
}

 The dataset includes 70637 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029139-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eq9qmn
title: Occurrence Download

description: A dataset containing 1228921 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "GadmGid is BRA.24_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1228921 records from 710 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029109-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xxkrnh
title: Occurrence Download

description: A dataset containing 53029739 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Aves, Tracheophyta, Mammalia, Amphibia, Squamata, Hymenoptera)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry MULTIPOLYGON (((-4.3077 39.9428, -3.0743 39.9428, -3.0743 40.8483, -4.3077 40.8483, -4.3077 39.9428)), ((-91.1775 38.4551, -90.062 38.4551, -90.062 39.104, -91.1775 39.104, -91.1775 38.4551)), ((-80.7321 42.8463, -79.7804 42.8463, -79.7804 43.4659, -80.7321 43.4659, -80.7321 42.8463)), ((120.0444 23.1718, 120.8738 23.1718, 120.8738 23.7903, 120.0444 23.7903, 120.0444 23.1718)), ((14.6823 58.9409, 15.7302 58.9409, 15.7302 59.6265, 14.6823 59.6265, 14.6823 58.9409)), ((-88.401 42.2381, -87.3587 42.2381, -87.3587 42.91, -88.401 42.91, -88.401 42.2381)), ((-112.5736 40.2292, -111.3277 40.2292, -111.3277 41.0732, -112.5736 41.0732, -112.5736 40.2292)), ((-2.2154 53.95453, -2.2154 54.0918, -3.1891 54.0918, -3.1891 53.59971, -3.3727 53.5991, -3.3727 52.9616, -3.3546 52.96167, -3.3546 52.8736, -2.4326 52.8736, -2.4326 52.96175, -2.3941 52.9616, -2.3941 53.27584, -1.8527 53.275, -1.8527 53.9537, -2.2154 53.95453)), ((-2.813 51.0598, -1.9291 51.0598, -1.9291 51.6969, -2.813 51.6969, -2.813 51.0598)), ((-114.8759 50.5793, -113.3068 50.5793, -113.3068 51.4552, -114.8759 51.4552, -114.8759 50.5793)), ((-105.5891 40.0949, -104.5884 40.0949, -104.5884 40.7225, -105.5891 40.7225, -105.5891 40.0949)), ((6.5566 43.2379, 7.7181 43.2379, 7.7181 44.0787, 6.5566 44.0787, 6.5566 43.2379)), ((-80.7486 40.2381, -79.7363 40.2381, -79.7363 41.0372, -80.7486 41.0372, -80.7486 40.2381)), ((-1.7164 52.7857, -0.7415 52.7857, -0.7415 53.4713, -1.7164 53.4713, -1.7164 52.7857)), ((-79.7255 42.8282, -78.7498 42.8282, -78.7498 43.5116, -79.7255 43.5116, -79.7255 42.8282)), ((27.6684 -26.2003, 28.3546 -26.2003, 28.3546 -26.18367, 28.4385 -26.1835, 28.4385 -25.6361, 27.7524 -25.6361, 27.7524 -25.66147, 27.6684 -25.6613, 27.6684 -26.2003)))"
 ]
}

 The dataset includes 53029739 records from 1865 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034793-230810091245214/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.