cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10592499
title: Linked collectors and determiners for: Bees of the family Halictidae Thomson, 1869 from Dominica, Lesser Antilles (Hymenoptera: Apoidea).

description: Natural history specimen data linked to collectors and determiners held within, "Bees of the family Halictidae Thomson, 1869 from Dominica, Lesser Antilles (Hymenoptera: Apoidea)". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/fc4a1f3e-6a1d-45c8-9701-d050d2c334c7 using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/fc4a1f3e-6a1d-45c8-9701-d050d2c334c7. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.12617351
title: Linked collectors and determiners for: Bees of the family Halictidae Thomson, 1869 from Dominica, Lesser Antilles (Hymenoptera: Apoidea).

description: Natural history specimen data linked to collectors and determiners held within, "Bees of the family Halictidae Thomson, 1869 from Dominica, Lesser Antilles (Hymenoptera: Apoidea)". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/fc4a1f3e-6a1d-45c8-9701-d050d2c334c7 using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/fc4a1f3e-6a1d-45c8-9701-d050d2c334c7. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.13128407
title: Linked collectors and determiners for: Bees of the family Halictidae Thomson, 1869 from Dominica, Lesser Antilles (Hymenoptera: Apoidea).

description: Natural history specimen data linked to collectors and determiners held within, "Bees of the family Halictidae Thomson, 1869 from Dominica, Lesser Antilles (Hymenoptera: Apoidea)". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/fc4a1f3e-6a1d-45c8-9701-d050d2c334c7 using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/fc4a1f3e-6a1d-45c8-9701-d050d2c334c7. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.13976932
title: Linked collectors and determiners for: Bees of the family Halictidae Thomson, 1869 from Dominica, Lesser Antilles (Hymenoptera: Apoidea).

description: Natural history specimen data linked to collectors and determiners held within, "Bees of the family Halictidae Thomson, 1869 from Dominica, Lesser Antilles (Hymenoptera: Apoidea)". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/fc4a1f3e-6a1d-45c8-9701-d050d2c334c7 using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/fc4a1f3e-6a1d-45c8-9701-d050d2c334c7. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.10504090
title: Linked collectors and determiners for: Bees of the family Halictidae Thomson, 1869 from Dominica, Lesser Antilles (Hymenoptera: Apoidea).

description: Natural history specimen data linked to collectors and determiners held within, "Bees of the family Halictidae Thomson, 1869 from Dominica, Lesser Antilles (Hymenoptera: Apoidea)". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/fc4a1f3e-6a1d-45c8-9701-d050d2c334c7 using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/fc4a1f3e-6a1d-45c8-9701-d050d2c334c7. Formatted as a Frictionless Data package.
DOI: 10.5281/zenodo.12617352
title: Linked collectors and determiners for: Puntos de presencia en Baja California (Botany).

description: Natural history specimen data linked to collectors and determiners held within, "Puntos de presencia en Baja California (Botany)". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/05da2f31-7301-49f7-b79f-f9e7d12d8b2c using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/05da2f31-7301-49f7-b79f-f9e7d12d8b2c. Formatted as a Frictionless Data package.
DOI: 10.15468/dl.5kpncp
title: Occurrence Download

description: A dataset containing 1206 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Onthophagus punctatus (Illiger, 1803)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1206 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071521-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6q6myt
title: Occurrence Download

description: A dataset containing 140 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "DatasetKey is one of (University of Michigan Herbarium, A global database for the distributions of crop wild relatives, Royal Ontario Museum Green Plant Herbarium (TRT), Central Michigan University Herbarium, G. S. Torrey Herbarium at the University of Connecticut (CONN), Morton Arboretum - Vascular Plants, Field Museum of Natural History (Botany) Seed Plant Collection, CHAS Botany Collection (Arctos), Michigan State University Herbarium Vascular Plants)",
 "Geometry POLYGON((-87.31435 46.51278,-87.46441 41.49606,-81.94034 41.45555,-81.91055 43.48909,-83.58995 46.23723,-84.94429 46.87913,-87.31435 46.51278))",
 "HasGeospatialIssue is false",
 "TaxonKey is Malus coronaria (L.) Mill."
 ]
}

 The dataset includes 140 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071522-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/10479218
title: Adidas Webstore Shoe Data
DOI: 10.15468/dl.z7smbt
title: Occurrence Download

description: A dataset containing 687 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Lepidurus packardi Simon, 1886"
 ]
}

 The dataset includes 687 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071524-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a2bydp
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Onthophagus sericatus Reitter, 1892",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 14 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071526-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.njbvuj
title: Occurrence Download

description: A dataset containing 83080 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Geometry POLYGON((-5.43889 37.7895,-7.0275 36.9794,-6.3636 35.71906,-4.68015 36.12229,-4.06368 36.56156,-5.43889 37.7895))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 83080 records from 146 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071523-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/s5hx9n2jc3.1
title: Multi-Weather-based Pothole Detection

description: The Multi-Weather-Based Pothole Detection Dataset is a comprehensive collection of images designed to aid in developing and evaluating deep learning models for detecting road surface anomalies, particularly potholes, under diverse environmental conditions. Images captured under normal weather, and rainy conditions include variations in lighting, such as daytime, twilight, and nighttime settings. We tried to add high-quality images to ensure the clarity of road surface details. It facilitates the detection of small and partially obscured potholes. In the dataset, potholes are precisely annotated with bounding boxes. This dataset is meticulously curated to reflect weather scenarios, ensuring robust and adaptable pothole detection systems.
DOI: 10.17632/mk9vzs3m2d
title: Intercropping Hevea brasiliensis (Willd. ex A. Juss.) Müll. Arg. can significantly promote the growth and quality improvement of Pandanus amaryllifolius Roxb.

description: This study aims to clarify the agronomic traits, photosynthetic properties and quality changes of pandan under the rubber-intercropping mode. It will elucidate the key environmental factors and physiological-ecological processes through which rubber intercropping enhances the quality of pandan. The findings of this study will provide a theoretical basis for the application and popularization of the rubber-pandan intercropping mode, thereby supporting the sustainable development of both the rubber and pandan industries.
DOI: 10.17632/mk9vzs3m2d.1
title: Intercropping Hevea brasiliensis (Willd. ex A. Juss.) Müll. Arg. can significantly promote the growth and quality improvement of Pandanus amaryllifolius Roxb.

description: This study aims to clarify the agronomic traits, photosynthetic properties and quality changes of pandan under the rubber-intercropping mode. It will elucidate the key environmental factors and physiological-ecological processes through which rubber intercropping enhances the quality of pandan. The findings of this study will provide a theoretical basis for the application and popularization of the rubber-pandan intercropping mode, thereby supporting the sustainable development of both the rubber and pandan industries.
DOI: 10.17632/s5hx9n2jc3.2
title: Multi-Weather Pothole Detection (MWPD)

description: The Multi-Weather-Based Pothole Detection Dataset is a comprehensive collection of images designed to aid in developing and evaluating deep learning models for detecting road surface anomalies, particularly potholes, under diverse environmental conditions. Images captured under normal weather, and rainy conditions include variations in lighting, such as daytime, twilight, and nighttime settings. We tried to add high-quality images to ensure the clarity of road surface details. It facilitates the detection of small and partially obscured potholes. In the dataset, potholes are precisely annotated with bounding boxes. This dataset is meticulously curated to reflect weather scenarios, ensuring robust and adaptable pothole detection systems.
DOI: 10.17632/7vdby39yst.1
title: Data containing Thelaziasis in Cattle

description: This data contains bovine thelaziasis in Ethiopia
DOI: 10.17632/v9hw2y3nvb.1
title: Data for: Widespread Diagenesis at Unconformities in Gale Crater as Observed from the Curiosity Rover and from Orbit

description: CRISM spectra for: Widespread Diagenesis at Unconformities in Gale Crater as Observed from the Curiosity Rover and from Orbit
DOI: 10.17632/v9hw2y3nvb.2
title: Data for: Widespread Diagenesis at Unconformities in Gale Crater as Observed from the Curiosity Rover and from Orbit

description: CRISM spectra for: Widespread Diagenesis at Unconformities in Gale Crater as Observed from the Curiosity Rover and from Orbit
DOI: 10.17632/v9hw2y3nvb.3
title: Data for: Widespread Diagenesis at Unconformities in Gale Crater as Observed from the Curiosity Rover and from Orbit

description: CRISM spectra for: Widespread Diagenesis at Unconformities in Gale Crater as Observed from the Curiosity Rover and from Orbit
ROIs are from projected CRISM files drawn in ENVI
DOI: 10.15468/dl.t9kmpu
title: Occurrence Download

description: A dataset containing 699 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Onthophagus stylocerus Graëlls, 1851",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 699 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071530-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xg5s7j
title: Occurrence Download

description: A dataset containing 51 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Elaphrus viridis G.Horn, 1878"
 ]
}

 The dataset includes 51 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071531-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/10479252
title: Vietnam SARS-CoV-2 | COVID-19 Data
DOI: 10.17632/xkbjx8959c.1
title: A Large-Scale Dataset for Fruit Classification: Insights into Fresh, Rotten, and Formalin-mixed Samples

description: This dataset, initially consisting of 10,154 high-resolution images of five fruit types—apple, banana, mango, orange, and grapes—has been expanded to over 81,000 using advanced augmentation techniques like rotation, scaling, and brightness adjustment. The images are classified into three key categories: fresh, rotten, and formalin-mixed. This dataset offers a unique opportunity for researchers in computer vision, agriculture, and food safety to develop machine learning and deep learning models for tasks such as real-time fruit quality assessment, contamination detection, and automating food inspection processes. Its extensive and diverse collection makes it a valuable resource for innovations in public health, export quality control, and agricultural productivity.

(1) Everyone seeks fresh and high-quality fruits, as fruits naturally degrade over time, leading to spoilage. It is estimated that roughly one-third of harvested fruits rot, causing significant financial loss. Additionally, the sale of fruits is impacted by consumer concerns over the health risks associated with consuming spoiled or chemically treated fruits. The manual classification of fresh and rotten fruits by individuals is inefficient, particularly for farmers, sellers, and the fruit processing industry.
(2) In recent years, computer vision techniques have shown great promise in automating tasks like classification and detection of fresh and rotten fruits.
(3) To aid in the development of computer vision-based algorithms, we present an extensive fruit dataset containing five fruit classes: Fresh Apple, Rotten Apple, Formalin-mixed Apple, Fresh Banana, Rotten Banana, Formalin-mixed Banana, Fresh Grape, Rotten Grape, Formalin-mixed Grape, Fresh Mango, Rotten Mango, Formalin-mixed Mango, Fresh Orange, Rotten Orange, and Formalin-mixed Orange. Classification into fresh, rotten, and formalin-treated categories was carried out with the assistance of agricultural experts.
DOI: 10.17632/xkbjx8959c.2
title: FruitVision: A Benchmark Dataset for Fresh, Rotten, and Formalin-mixed Fruit Detection

description: This dataset, initially consisting of 10,154 high-resolution images of five fruit types—apple, banana, mango, orange, and grapes—has been expanded to over 81,000 using advanced augmentation techniques like rotation, scaling, and brightness adjustment. The images are classified into three key categories: fresh, rotten, and formalin-mixed. This dataset offers a unique opportunity for researchers in computer vision, agriculture, and food safety to develop machine learning and deep learning models for tasks such as real-time fruit quality assessment, contamination detection, and automating food inspection processes. Its extensive and diverse collection makes it a valuable resource for innovations in public health, export quality control, and agricultural productivity.

(1) Everyone seeks fresh and high-quality fruits, as fruits naturally degrade over time, leading to spoilage. It is estimated that roughly one-third of harvested fruits rot, causing significant financial loss. Additionally, the sale of fruits is impacted by consumer concerns over the health risks associated with consuming spoiled or chemically treated fruits. The manual classification of fresh and rotten fruits by individuals is inefficient, particularly for farmers, sellers, and the fruit processing industry.
(2) In recent years, computer vision techniques have shown great promise in automating tasks like classification and detection of fresh and rotten fruits.
(3) To aid in the development of computer vision-based algorithms, we present an extensive fruit dataset containing five fruit classes: Fresh Apple, Rotten Apple, Formalin-mixed Apple, Fresh Banana, Rotten Banana, Formalin-mixed Banana, Fresh Grape, Rotten Grape, Formalin-mixed Grape, Fresh Mango, Rotten Mango, Formalin-mixed Mango, Fresh Orange, Rotten Orange, and Formalin-mixed Orange. Classification into fresh, rotten, and formalin-treated categories was carried out with the assistance of agricultural experts.
DOI: 10.17632/39w5khrg87.1
title: BanglaTense: A Large-Scale Dataset of Bangla Sentences Categorized by Tense: Past, Present, and Future

description: The BanglaTense dataset is a comprehensive collection of Bangla (Bengali) sentences meticulously categorized based on their tense: Past, Present, and Future. The dataset comprises a total of 17, 819 annotated sentences with three distinct tense types. This dataset is designed to facilitate research and development in natural language processing (NLP) and computational linguistics, particularly for Bangla, a widely spoken language in Bangladesh and parts of India. With applications spanning tense detection, text classification, language modeling, and educational tools, BanglaTense is a valuable resource for the Bangla NLP community, facilitating advancements in temporal analysis and robust NLP model development.
DOI: 10.17632/39w5khrg87.2
title: BanglaTense: A Large-Scale Dataset of Bangla Sentences Categorized by Tense: Past, Present, and Future

description: The BanglaTense dataset is a comprehensive collection of Bangla (Bengali) sentences meticulously categorized based on their tense: Past, Present, and Future. The dataset comprises a total of 17, 819 annotated sentences with three distinct tense types. This dataset is designed to facilitate research and development in natural language processing (NLP) and computational linguistics, particularly for Bangla, a widely spoken language in Bangladesh and parts of India. With applications spanning tense detection, text classification, language modeling, and educational tools, BanglaTense is a valuable resource for the Bangla NLP community, facilitating advancements in temporal analysis and robust NLP model development.
DOI: 10.17632/39w5khrg87.3
title: BanglaTense: A Large-Scale Dataset of Bangla Sentences Categorized by Tense: Past, Present, and Future

description: The BanglaTense dataset is a comprehensive collection of Bangla (Bengali) sentences meticulously categorized based on their tense: Past, Present, and Future. The dataset comprises a total of 17,819 annotated sentences with three distinct tense types: 5,629 in the past tense, 6,101 in the present tense, and 6,089 in the future tense. This dataset is designed to facilitate research and development in natural language processing (NLP) and computational linguistics, particularly for Bangla, a widely spoken language in Bangladesh and parts of India. With applications spanning tense detection, text classification, language modeling, and educational tools, BanglaTense is a valuable resource for the Bangla NLP community, facilitating advancements in temporal analysis and robust NLP model development.
DOI: 10.17632/39w5khrg87.4
title: BanglaTense: A Large-Scale Dataset of Bangla Sentences Categorized by Tense: Past, Present, and Future

description: The BanglaTense dataset is a comprehensive collection of Bangla (Bengali) sentences meticulously categorized based on their tense: Past, Present, and Future. The dataset comprises a total of 17,819 annotated sentences with three distinct tense types: 5,629 in the past tense, 6,101 in the present tense, and 6,089 in the future tense. This dataset is designed to facilitate research and development in natural language processing (NLP) and computational linguistics, particularly for Bangla, a widely spoken language in Bangladesh and parts of India. With applications spanning tense detection, text classification, language modeling, and educational tools, BanglaTense is a valuable resource for the Bangla NLP community, facilitating advancements in temporal analysis and robust NLP model development.
DOI: 10.15468/dl.6yu33x
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Onthophagus trigibber Reitter, 1892",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 9 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071533-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qem8w2
title: Occurrence Download

description: A dataset containing 64 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Myzopoda aurita A.Milne-Edwards & A.Grandidier, 1878"
 ]
}

 The dataset includes 64 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071534-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/9w9pgcpn4x.1
title: Supplementary Materials: High rates of potentially unnecessary topical antifungal prescribing in a large commercial health insurance claims database, United States

description: This dataset provides supplementary methods and a supplementary table for an article entitled: “High rates of potentially unnecessary topical antifungal prescribing in a large commercial health insurance claims database, United States.” The supplementary table provides International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) and Current Procedural Terminology (CPT) codes used to identify diagnoses and procedures of interest.
DOI: 10.17632/p2kyhxx888.1
title: Price dispersion two sided platform

description: Dados disponíveis para pesquisas em marketing e economia.