cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.wmyyr6
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Placidochromis lukomae)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027896-250811113504898/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.29958008
title: Dynamic control of pure content quality and recommendation intensity on UGC platform considering reference effect

description: Many User-Generated Content (UGC) platforms are transitioning towards a new business model where content creators engage users with pure content, while platforms’ revenue increasingly relies on shoppable content. This paper investigates the strategic balance between pure content and shoppable content on UGC platforms, and how this balance, along with dynamic pure content quality and consumer reference quality uncertainty, affects profit optimization for both UGC platforms and content creators. Employing a game-theoretic framework, we model three scenarios: (1) static pure content quality and recommendation intensity (i.e., the frequency of pure content recommendations or space allocation of pure content recommendations); (2) dynamic quality and recommendation intensity without uncertainty in reference quality; and (3) dynamic scenarios with uncertainty in reference quality. Our findings indicate that adopting dynamic strategies can enhance platform profits compared to the static scenario, but it may reduce content creators’ earnings relative to a static environment. Interestingly, while dynamic uncertainty leads to a decline in profits for the UGC platform, it also offers content creators opportunities to increase their profits. When facing higher uncertainty in reference quality, the UGC platform should increase recommendation intensity, while content creators will reduce the quality of their output.
DOI: 10.6084/m9.figshare.29958008.v1
title: Dynamic control of pure content quality and recommendation intensity on UGC platform considering reference effect

description: Many User-Generated Content (UGC) platforms are transitioning towards a new business model where content creators engage users with pure content, while platforms’ revenue increasingly relies on shoppable content. This paper investigates the strategic balance between pure content and shoppable content on UGC platforms, and how this balance, along with dynamic pure content quality and consumer reference quality uncertainty, affects profit optimization for both UGC platforms and content creators. Employing a game-theoretic framework, we model three scenarios: (1) static pure content quality and recommendation intensity (i.e., the frequency of pure content recommendations or space allocation of pure content recommendations); (2) dynamic quality and recommendation intensity without uncertainty in reference quality; and (3) dynamic scenarios with uncertainty in reference quality. Our findings indicate that adopting dynamic strategies can enhance platform profits compared to the static scenario, but it may reduce content creators’ earnings relative to a static environment. Interestingly, while dynamic uncertainty leads to a decline in profits for the UGC platform, it also offers content creators opportunities to increase their profits. When facing higher uncertainty in reference quality, the UGC platform should increase recommendation intensity, while content creators will reduce the quality of their output.
DOI: 10.15468/dl.a4mfxa
title: Occurrence Download

description: A dataset listing the 55 species recorded in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dasypoda"
 ]
}

 The dataset's 55 records were derived from 240 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027878-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bxmx69
title: Occurrence Download

description: A dataset containing 43467707 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is South Africa",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 43467707 records from 2162 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027837-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uaht7p
title: Occurrence Download

description: A dataset containing 154771 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Belarus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 154771 records from 72 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028771-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17578327
title: Supporting data for van Strien A.J., Meijaard E., Nardiyono, Suief S., Zaini S. (2025). Occupancy estimation of wild species in a palm oil plantation using unstructured data. PLOS ONE, 2025.

description: This dataset accompanies the paper:van Strien A.J., Meijaard E., Nardiyono, Suief S., Zaini S. (2025). Occupancy estimation of wild species in a palm oil plantation using unstructured data. PLOS ONE, 2025.

The dataset contains raw and processed data used for the occupancy estimation analyses described in the paper.

Files included:





data_for_repository.csv – Primary dataset used in the occupancy analysis.




KAL_observers.csv – Observer metadata.




Explanation_Data_repository.docx – Supporting documentation explaining variables, data sources, and structure.



These files are released to promote transparency and reproducibility of research.
DOI: 10.15468/dl.hto6fm
title: Occurrence Download

description: A dataset containing 430520 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Acer pseudoplatanus L."
 ]
}

 The dataset includes 430520 records from 982 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012745-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.img7ec
title: Occurrence Download

description: A dataset containing 952261 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Oxalidales"
 ]
}

 The dataset includes 952261 records from 1606 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015162-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pdbpj4
title: Occurrence Download

description: A dataset containing 933473 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acanthis flammea (Linnaeus, 1758)",
 "HasCoordinate is true",
 "Year is greater than 1989",
 "Year is less than 2026",
 {
 "not" : {
 "OccurrenceStatus" : [
 "is Absent"
 ]
 }
 },
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 933473 records from 238 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002114-250515123054153/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/8378585
title: Doctor’s Handwritten Prescription BD dataset
DOI: 10.15468/dl.ft2vsq
title: Occurrence Download

description: A dataset containing 149811 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Swedish Malaise Trap Project (SMTP) Collection Inventory"
 ]
}

 The dataset includes 149811 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001908-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dfdfnz
title: Occurrence Download

description: A dataset containing 149787 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is DEMNA-DNE : Occurrences of benthic macroinvertebrates in running waters of Wallonia, Belgium"
 ]
}

 The dataset includes 149787 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001907-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cmhp8x
title: Occurrence Download

description: A dataset containing 19259 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"TAXON_KEY","value":"9685907","matchCase":false},{"type":"equals","key":"BASIS_OF_RECORD","value":"Preserved Specimen","matchCase":false}]}

 The dataset includes 19259 records from 192 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012804-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5wc3tq
title: Occurrence Download

description: A dataset containing 19259 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"TAXON_KEY","value":"9685907","matchCase":false},{"type":"equals","key":"BASIS_OF_RECORD","value":"Preserved Specimen","matchCase":false}]}

 The dataset includes 19259 records from 192 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012805-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/ktwmmcrp5y
title: PRC_Leopard_India

description: PRC leopard India
DOI: 10.17632/ktwmmcrp5y.1
title: PRC_Leopard_India

description: PRC leopard India
DOI: 10.17632/brydkz7snf.1
title: Dataset_Enhanced Molybdenum Recovery Achieved by A Complex of Porous Material-Immobilized Surface-Engineered Yeast on Development of a Sustainable Biosorption Technology

description: This folder include the result of Mo-adsorption by PS, and the supplementary figures about the cell retention and yeast cell number after immobilized in PS
DOI: 10.17632/vxvc9r7cpr.1
title: Dataset Tourism SDGs South Sumatra

description: This dataset is used for the purpose of further research on tourism developments that are juxtaposed with the objectives of the Sustainable Development Goals with the structure of the Electronic-Based Government System Architecture (SPBE) in Indonesia.
DOI: 10.15468/dl.7yrd3y
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Persicaria odorata (Lour.) Soják"
 ]
}

 The dataset includes 25 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002308-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fdktz8
title: Occurrence Download

description: A dataset containing 283 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is France",
 "TaxonKey is Alternanthera philoxeroides (Mart.) Griseb."
 ]
}

 The dataset includes 283 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002310-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15118517
title: Volcano Plumbing System Simulation SEM-2D

description: The velocity and density models describe the magmatic plumbing system as developed by Melnik et al. Melnik, O. E., Utkin, I. S., & Bindeman, I. N. (2021). Magma chamber formation by dike accretion and crustal melting: 2D thermo-compositional model with emphasis on eruptions and implication for zircon records. Journal of Geophysical Research: Solid Earth, 126(12), e2021JB023008.. The model consists of 5 m grid elements and a free surface must be considered at the top.

Seismograms Generated by Vertical and Horizontal Force Sources

Seismograms are generated from sources expressed as vertical and horizontal forces. In the case of horizontal forces, the seismogram file is labeled with the suffix "_hor". Five sources are positioned at the surface at the following locations:





x₁ = 6 km




x₂ = 8 km




x₃ = 12 km




x₄ = 12.5 km




x₅ = 17 km



A total of 7,800 receivers are arranged in a regular grid with 100 m spacing, covering the range:





x_min = 10 km, x_max = 16.5 km




z_min = 2.5 km, z_max = 14.5 km



The source function is a Ricker wavelet centered at 3 Hz.
DOI: 10.5281/zenodo.15118518
title: Volcano Plumbing System Simulation SEM-2D

description: The velocity and density models describe the magmatic plumbing system as developed by Melnik et al. Melnik, O. E., Utkin, I. S., & Bindeman, I. N. (2021). Magma chamber formation by dike accretion and crustal melting: 2D thermo-compositional model with emphasis on eruptions and implication for zircon records. Journal of Geophysical Research: Solid Earth, 126(12), e2021JB023008.. The model consists of 5 m grid elements and a free surface must be considered at the top.

Seismograms Generated by Vertical and Horizontal Force Sources

Seismograms are generated from sources expressed as vertical and horizontal forces. In the case of horizontal forces, the seismogram file is labeled with the suffix "_hor". Five sources are positioned at the surface at the following locations:





x₁ = 6 km




x₂ = 8 km




x₃ = 12 km




x₄ = 12.5 km




x₅ = 17 km



A total of 7,800 receivers are arranged in a regular grid with 100 m spacing, covering the range:





x_min = 10 km, x_max = 16.5 km




z_min = 2.5 km, z_max = 14.5 km



The source function is a Ricker wavelet centered at 3 Hz.
DOI: 10.17632/jv6tnm4t5c.1
title: A Curated Dataset of Eggplant Leaves: Healthy Specimens and Six Major Disease Conditions

description: This dataset comprises high-resolution images of eggplant (Solanum melongena) leaves, curated to support research in plant disease detection and classification using machine learning techniques. The images were collected under natural field conditions, providing a diverse set of images with varying lighting, angles, and backgrounds. This dataset is specifically designed for training machine learning models for plant disease detection, image classification, and precision agriculture applications.

The dataset includes seven distinct classes of eggplant leaf conditions:

 1. Healthy: Leaves that show no signs of disease or damage, representing a normal, healthy state of the plant.
 2. Insect Pest: Leaves affected by insect pests, showing damage such as holes, discoloration, or deformation 
 caused by feeding activities.
 3. Leaf Spot: Leaves exhibiting various forms of leaf spot diseases, characterized by round or irregular lesions, 
 often caused by fungal or bacterial pathogens.
 4. Mosaic Virus: Leaves infected by mosaic viruses, displaying mottled or variegated patterns with yellow or light 
 green patches, commonly associated with viral diseases.
 5. Small Leaf: Leaves that are smaller than normal, resulting from environmental stress, nutrient deficiencies, or 
 genetic factors leading to stunted growth.
 6. White Mold: Leaves showing symptoms of white mold, with white, cotton-like fungal growth on the surface, 
 caused by Sclerotinia spp.
 7. Wilt: Leaves that appear droopy and dehydrated, exhibiting wilting, often due to root damage, water stress, or 
 vascular infections.

Each class contains 200 high-quality images, totaling 1,400 images in the dataset. The images are in JPG format with varying resolutions, making them suitable for training deep learning models to automatically detect and classify plant diseases. The dataset is intended for use in agricultural research, specifically in developing machine learning models for early disease detection and crop management.
DOI: 10.15468/dl.5md2qt
title: Occurrence Download

description: A dataset containing 150 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Ningaloo Outlook Whale Shark tracking (aggregated per 1-degree cell)"
 ]
}

 The dataset includes 150 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002314-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/c9jxp3447k
title: Lane-level Traffic Flow Prediction by Integrating Heterogeneous Data and Dynamic Graphs: An Adaptive Multi-scale Spatio-Temporal Convolutional Network and Reinforcement Learning Collaborative Optimization Method

description: The dataset covers data from multiple cities and regions, including various scenarios such as urban roads and highways. The data sources are diverse, encompassing historical traffic flow, real-time vehicle speeds, traffic events, weather conditions, and road conditions. The data is collected from various sources, including traffic monitoring systems, vehicle sensors, traffic management departments, and meteorological departments. These data enable the paper to capture the spatio-temporal characteristics of traffic flow, micro-driving behavior, and external environmental factors in multiple dimensions. All the data undergoes precise spatio-temporal alignment. Time alignment is performed using linear interpolation to unify real-time vehicle speed and traffic flow data to the same timestamp. Spatial alignment uses GIS (Geographic Information System) technology to ensure the data is accurately matched to each lane, ensuring spatial precision.
DOI: 10.17632/c9jxp3447k.1
title: Lane-level Traffic Flow Prediction by Integrating Heterogeneous Data and Dynamic Graphs: An Adaptive Multi-scale Spatio-Temporal Convolutional Network and Reinforcement Learning Collaborative Optimization Method

description: The dataset covers data from multiple cities and regions, including various scenarios such as urban roads and highways. The data sources are diverse, encompassing historical traffic flow, real-time vehicle speeds, traffic events, weather conditions, and road conditions. The data is collected from various sources, including traffic monitoring systems, vehicle sensors, traffic management departments, and meteorological departments. These data enable the paper to capture the spatio-temporal characteristics of traffic flow, micro-driving behavior, and external environmental factors in multiple dimensions. All the data undergoes precise spatio-temporal alignment. Time alignment is performed using linear interpolation to unify real-time vehicle speed and traffic flow data to the same timestamp. Spatial alignment uses GIS (Geographic Information System) technology to ensure the data is accurately matched to each lane, ensuring spatial precision.
DOI: 10.15468/dl.ybyme8
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Odocoileus virginianus",
 "Country is Saint Kitts and Nevis",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0085455-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/602-9rp-1tw
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/131-033-ae3
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/vws-d9t-3nx
title: Bovidae Gray, 1821

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/6wy-dhp-g99
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/bzt-0qh-8se
title: Bovidae Gray, 1821

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/36w-xcp-9b3
title: Maianthemum F.H.Wigg.

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/hxw-3v2-rq0
title: Bovidae Gray, 1821

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/adn-43s-7tc
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/qz4-dtf-lsg
title: Muntiacus muntjak (Zimmermann, 1780)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/5b5-0wj-lfp
title: Muntiacus muntjak (Zimmermann, 1780)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/5jv-ydf-06s
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/8pd-czk-9xf
title: Capricornis sumatraensis (Bechstein, 1799)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/43g-7l8-kfe
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/xlc-9mw-yfe
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/87d-kkd-nkd
title: Orthiopteris Copel.

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/w7g-9fv-vbl
title: Orthiopteris Copel.

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/x32-mqf-114
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/xen-1gb-yja
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/hqr-ams-3xh
title: Orthiopteris Copel.

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/k61-we1-dyz
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/5a3-wv2-6gm
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/7vm-bxh-a7l
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/yca-8k6-def
title: †Spiroclypeus tidoenganensis van der Vlerk, 1925

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/e4g-fbp-dlt
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/4y8-rsv-2dz
title: Orthiopteris Copel.

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/hyp-l8q-ggf
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/xy9-pg7-yxl
title: Plantae

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/4h9-fxn-gtt
title: Orthiopteris Copel.

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.