cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.9inixh
title: Occurrence Download

description: A dataset containing 187 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Guatemala",
 "DatasetKey is Inventario florístico y base de datos de la familia Cucurbitaceae en México"
 ]
}

 The dataset includes 187 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017415-181003121212138/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.647k2s
title: Occurrence Download

description: A dataset containing 204414 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Geranium molle L."
 ]
}

 The dataset includes 204414 records from 698 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0210199-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5vhxah
title: Occurrence Download

description: A dataset containing 318 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Kaloula verrucosa Boulenger, 1904"
 ]
}

 The dataset includes 318 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024235-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2bx7gu
title: Occurrence Download

description: A dataset containing 248380 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Turdus fuscater Orbigny & Lafresnaye, 1837"
 ]
}

 The dataset includes 248380 records from 277 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024216-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4bm4nf
title: Occurrence Download

description: A dataset containing 8127 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Turdus olivater (Lafresnaye, 1848)"
 ]
}

 The dataset includes 8127 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024237-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18150/slszib
title: Systematyczne aktywności gwarantem zdrowych kości

description: Badanie wstępne uczestniczek projektu przed rozpoczęciem procedury treningowej
DOI: 10.15468/dl.aupbfv
title: Occurrence Download

description: A dataset containing 3572 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Panicum bisulcatum, Panicum bisulcatum, Panicum bisulcatum Thunb., Panicum bisulcatum Thunb., Panicum bisulcatum Thunb., Panicum bisulcatum Thunberg, Panicum bisulcatum Thunb., Panicum bisulcatum Thunb., Panicum bisulcatum Thunb., Panicum bisulcatum Thunb., Panicum bisulcatum Thunb., Panicum bisulcatum Thunb., Panicum bisulcatum Thunb., Panicum bisulcatum Thunb., Panicum bisulcatum Thunb., Panicum bisulcatum Thunb., Panicum bisulcatum Thunb., Panicum bisulcatum Thunb., Panicum bisulcatum Thunb., Panicum bisulcatum Thunb., Panicum bisulcatum Thunb., Panicum bisulcatum Thunb., Panicum bisulcatum Thunb., Panicum bisulcatum Thunb., Panicum bisulcatum Thunb., Panicum bisulcatum Thunb., 1815, Panicum bisulcatum Thunb., 1815, Aira arundinacea sensu Houtt., Aira arundinacea L., Panicum melananthum F.Muell., Panicum acroanthum Steud., Panicum acroanthum Steud., Panicum acroanthum Steud., Panicum melananthum F.Muell., Panicum melananthum F.Muell., Panicum acroanthum Steud., Panicum melananthum F.Muell., Panicum acroanthum Steud., Panicum acroanthum Steud., Panicum acroanthum Steud., Panicum melananthum F.Muell., Panicum acroanthum Steud., Panicum melananthum F.Muell.)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 3572 records from 132 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024239-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ghtr43
title: Occurrence Download

description: A dataset containing 9694 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "KingdomKey is Animalia",
 {
 "or" : [
 {
 "and" : [
 "Year is 2021",
 "GadmGid is USA.45.1_1"
 ]
 },
 {
 "and" : [
 "Year is 2021",
 "GadmGid is USA.23.28_1"
 ]
 },
 {
 "and" : [
 "Year is 2021",
 "GadmGid is USA.3.14_1"
 ]
 },
 {
 "and" : [
 "Year is 2021",
 "GadmGid is USA.1.51_1"
 ]
 },
 {
 "and" : [
 "Year is 2021",
 "GadmGid is USA.1.2_1"
 ]
 }
 ]
 }
 ]
}

 The dataset includes 9694 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024240-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15074308
title: Garbage Classification Dataset

description: Description:

This dataset contains a collection of 15,150 images, categorized into 12 distinct classes of common household waste. The classes include paper, cardboard, biological waste, metal, plastic, green glass, brown glass, white glass, clothing, shoes, batteries, and general trash. Each category represents a different type of material, contributing to more effective recycling and waste management strategies. Garbage Classification Dataset.

Objective

The purpose of this dataset is to aid in the development of machine learning models designed to automatically classify household waste into its appropriate categories, thus promoting more efficient recycling processes. Proper waste sorting is crucial for maximizing the amount of material that can be recycled, and this dataset is aimed at enhancing automation in this area. The classification of garbage into a broader range of categories, as opposed to the limited classes found in most available datasets (2-6 classes), allows for a more precise recycling process and could significantly improve recycling rates.

Download Dataset

Dataset Composition and Collection Process

The dataset was primarily collected through web scraping, as simulating a real-world garbage collection scenario (such as placing a camera above a conveyor belt) was not feasible at the time of collection. The goal was to obtain images that closely resemble actual garbage. For example, images in the biological waste category include rotten fruits, vegetables, and food remnants. Similarly, categories such as glass and metal consist of images of bottles, cans, and containers typically found in household trash. While the images for some categories, like clothes or shoes, were harder to find specifically as garbage, they still represent the items that may end up in waste streams.

In an ideal setting, a conveyor system could be used to gather real-time data by capturing images of waste in a continuous flow. Such a setup would enhance the dataset by providing authentic waste images for all categories. However, until that setup is available, this dataset serves as a significant step toward automating garbage classification and improving recycling technologies.

Potential for Future Improvements

While this dataset provides a strong foundation for household waste classification, there is potential for further improvements. For example, real-time data collection using conveyor systems or garbage processing plants could provide higher accuracy and more contextual images. Additionally, future datasets could expand to include more specialized categories, such as electronic waste, hazardous materials, or specific types of plastic.

Conclusion

The Garbage Classification dataset offers a broad and diverse collection of household waste images, making it a valuable resource for researchers and developers working in environmental sustainability, machine learning, and recycling automation. By improving the accuracy of waste classification systems, we can contribute to a cleaner, more sustainable future.

This dataset is sourced from Kaggle.
DOI: 10.5281/zenodo.15074309
title: Garbage Classification Dataset

description: Description:

This dataset contains a collection of 15,150 images, categorized into 12 distinct classes of common household waste. The classes include paper, cardboard, biological waste, metal, plastic, green glass, brown glass, white glass, clothing, shoes, batteries, and general trash. Each category represents a different type of material, contributing to more effective recycling and waste management strategies. Garbage Classification Dataset.

Objective

The purpose of this dataset is to aid in the development of machine learning models designed to automatically classify household waste into its appropriate categories, thus promoting more efficient recycling processes. Proper waste sorting is crucial for maximizing the amount of material that can be recycled, and this dataset is aimed at enhancing automation in this area. The classification of garbage into a broader range of categories, as opposed to the limited classes found in most available datasets (2-6 classes), allows for a more precise recycling process and could significantly improve recycling rates.

Download Dataset

Dataset Composition and Collection Process

The dataset was primarily collected through web scraping, as simulating a real-world garbage collection scenario (such as placing a camera above a conveyor belt) was not feasible at the time of collection. The goal was to obtain images that closely resemble actual garbage. For example, images in the biological waste category include rotten fruits, vegetables, and food remnants. Similarly, categories such as glass and metal consist of images of bottles, cans, and containers typically found in household trash. While the images for some categories, like clothes or shoes, were harder to find specifically as garbage, they still represent the items that may end up in waste streams.

In an ideal setting, a conveyor system could be used to gather real-time data by capturing images of waste in a continuous flow. Such a setup would enhance the dataset by providing authentic waste images for all categories. However, until that setup is available, this dataset serves as a significant step toward automating garbage classification and improving recycling technologies.

Potential for Future Improvements

While this dataset provides a strong foundation for household waste classification, there is potential for further improvements. For example, real-time data collection using conveyor systems or garbage processing plants could provide higher accuracy and more contextual images. Additionally, future datasets could expand to include more specialized categories, such as electronic waste, hazardous materials, or specific types of plastic.

Conclusion

The Garbage Classification dataset offers a broad and diverse collection of household waste images, making it a valuable resource for researchers and developers working in environmental sustainability, machine learning, and recycling automation. By improving the accuracy of waste classification systems, we can contribute to a cleaner, more sustainable future.

This dataset is sourced from Kaggle.
DOI: 10.15468/dl.rq9pb3
title: Occurrence Download

description: A dataset containing 197612570 records in GBIF matching the query:
SELECT catalognumber, scientificname, publishingorgkey, institutioncode, datasetkey, gbifid, decimallatitude, decimallongitude, 
 recordedby, identifiedby, eventdate, kingdomkey, phylumkey, classkey, orderkey, familykey, genuskey, subgenuskey, specieskey
 FROM occurrence WHERE
 phylumkey = 7707728 AND classkey = 220 AND orderkey NOT IN (414, 422, 1353) 
 AND taxonomicstatus = 'ACCEPTED' //newly added 12Feb2025
 AND hascoordinate = 1
 AND hasgeospatialissues = 0
 AND specieskey IS NOT NULL
 AND occurrencestatus = 'PRESENT'
 -- AND (
 -- basisofrecord = 'HUMAN_OBSERVATION'
 -- OR basisofrecord = 'MACHINE_OBSERVATION'
 -- OR basisofrecord = 'OCCURRENCE'
 -- OR basisofrecord = 'LIVING_SPECIMEN'
 -- OR basisofrecord = 'MATERIAL_SAMPLE'
 -- )
 AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE') AND datasetkey NOT IN ('040c5662-da76-4782-a48e-cdea1892d14c') 

 The dataset's 197612570 records were derived from 10910 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024225-250310093411724/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gq8d7j
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Masdevallia ingridiana Luer & J.Portilla"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020061-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h939g4
title: Occurrence Download

description: A dataset listing the 26109 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((25 -10,40 -10,40 5,25 5,25 -10))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Tracheophyta"
 ]
}

 The dataset's 26109 records were derived from 238 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0257796-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xvyzr4
title: Occurrence Download

description: A dataset containing 495 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Hemidactylus frenatus Schlegel, 1836)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 495 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0070023-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wdpzvx
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Desmodium guianense DC."
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034923-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rbjyeg
title: Occurrence Download

description: A dataset containing 456671 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-31.565747 48.58410666666667, 2.479608666666667 48.58410666666667, 2.479608666666667 65.67073733333334, -31.565747 65.67073733333334, -31.565747 48.58410666666667))",
 "EventDate is 2013-05-01,2013-05-31"
 ]
}

 The dataset includes 456671 records from 508 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025631-240216155721649/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dbrhkp
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is incertae sedis",
 "Year is greater than 2013",
 "Geometry MULTIPOLYGON (((12.275761 44.613323,12.276389 44.609483,12.276871 44.606215,12.277044 44.603833,12.277362 44.603129,12.277275 44.602401,12.277266 44.602328,12.276143 44.602901,12.275823 44.603064,12.274446 44.604054,12.273995 44.604473,12.2725 44.605865,12.272111 44.60631,12.269711 44.609053,12.267091 44.612529,12.265139 44.615601,12.262289 44.619559,12.261825 44.620413,12.260968 44.622527,12.260811 44.622914,12.2607 44.623188,12.260709 44.6232,12.261034 44.623654,12.263743 44.625404,12.269881 44.629836,12.270287 44.629904,12.270811 44.629992,12.271517 44.629789,12.272161 44.629405,12.272508 44.629212,12.272843 44.628801,12.275103 44.62709,12.275135 44.62676,12.275566 44.626236,12.275967 44.626078,12.27621 44.625852,12.27646 44.625735,12.276652 44.62551,12.277146 44.624289,12.277428 44.622928,12.277362 44.62176,12.276955 44.620894,12.276208 44.619453,12.275695 44.617603,12.275637 44.615666,12.275761 44.613323)))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034929-230530130749713/datasets/export for details.
DOI: 10.15468/dl.r5e62t
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dendropanax lancifolius (Ridl.) Ridl."
 ]
}

 The dataset includes 7 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0257846-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.syqneu
title: Occurrence Download

description: A dataset containing 152 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Alchemilla firma Buser"
 ]
}

 The dataset includes 152 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025573-240216155721649/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m9ex4h
title: Occurrence Download

description: A dataset containing 14506 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Opiliaceae"
 ]
}

 The dataset includes 14506 records from 418 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034921-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.82144/d1229e66
title: Happywhale - Hawksbill Sea Turtle in North Atlantic Ocean

description: Original provider:
Happywhale

Dataset credits:
Happywhale and contributors

Abstract:
Happywhale.com is a resource to help you know whales as individuals, and to benefit conservation science with rich data about individual whales.
DOI: 10.15468/dl.qpuj6c
title: Occurrence Download

description: A dataset containing 337549876 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tracheophyta"
 ]
}

 The dataset includes 337549876 records from 5661 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015988-210819072339941/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.c.3791032_d2.v1
title: Additional file 2: of Multiscalar cellular automaton simulates in-vivo tumour-stroma patterns calibrated from in-vitro assay data

description: mainTSM_Code: Main script for the Tumour-Stroma Model (TSM). This script is a stand-alone script that simulates the model given certain parameter values and initial conditions. (CPP 9.34 kb)
DOI: 10.6084/m9.figshare.c.3791032_d2
title: Additional file 2: of Multiscalar cellular automaton simulates in-vivo tumour-stroma patterns calibrated from in-vitro assay data

description: mainTSM_Code: Main script for the Tumour-Stroma Model (TSM). This script is a stand-alone script that simulates the model given certain parameter values and initial conditions. (CPP 9.34 kb)
DOI: 10.6084/m9.figshare.c.3791032_d3.v1
title: Additional file 3: of Multiscalar cellular automaton simulates in-vivo tumour-stroma patterns calibrated from in-vitro assay data

description: PEM_Code: Compressed folder containing the codes for the Parameter Estimation Model algorithms and example figures. These scrips are stand-alone and contain all the necessary information to replicate the data in the manuscript. (7Z 8793 kb)
DOI: 10.15468/dl.tqs4ks
title: Occurrence Download

description: A dataset containing 406 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carcharhinus brevipinna (Müller & Henle, 1839)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900",
 "CoordinateUncertaintyInMeters is less than or equal to 10000"
 ]
}

 The dataset includes 406 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039211-241126133413365/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.c.3791032_d3
title: Additional file 3: of Multiscalar cellular automaton simulates in-vivo tumour-stroma patterns calibrated from in-vitro assay data

description: PEM_Code: Compressed folder containing the codes for the Parameter Estimation Model algorithms and example figures. These scrips are stand-alone and contain all the necessary information to replicate the data in the manuscript. (7Z 8793 kb)
DOI: 10.25345/c5fj29r1w
title: MassIVE MSV000096690 - Boni_FGFR1mutations_P127_TripleTOF6600
title: This dataset consists of 44 raw MS files and associated peak lists and result files, acquired on AB SCIEX 6600 TripleTOF mass spectrometer operated in Data Dependent Acquisition mode. Controls are shared with MassIVE dataset MSV000083695. Samples were generated by Cassandra Wong. Affinity purification and mass spectrometry acquisition was performed by Cassandra J. Wong. Analysis was performed by Cassandra J. Wong, HyeRim Han, Jonathan Boulais, Jacopo Boni, and Anne-Claude Gingras. The files are associated with a manuscript submitted for publication by Jacopo Boni et al. The main goal of this paper was to identify how FGFR1 mutations in low-grade glioneuronal tumors contribute to tumorigenicity. Barbara Rivera is the corresponding author of the manuscript (brivera@idibell.cat); Anne-Claude Gingras should be contacted for questions on this dataset (gingras@lunenfeld.ca). This submission is associated with 2 Supplementary Files (in addition to this README file) Table 1 describes the composition of this dataset Table 2 lists all the peptide identification evidence (as per iProphet)
DOI: 10.48366/r764380
title: What are the applications of Business Model Canvas by Osterwalder

description: Business Model Canvas is a versatile tool that can be applied across industries and business stages, from startups to established enterprises, to enhance strategic clarity, foster innovation, and drive sustainable growth (OpenAI. (2024). ChatGPT (3.5) [Large language model]. https://chatgpt.com)
DOI: 10.48597/ds9q-k3k3
title: Hydrogen_sulfide at Broomfield Soaring Eagle Park

description: Measurement of Hydrogen_sulfide at Broomfield Soaring Eagle Park
DOI: 10.48597/uqj4-an3q
title: Measurement of Hydrogen_sulfide at Broomfield Soaring Eagle Park

description: Measurement of Hydrogen_sulfide at Broomfield Soaring Eagle Park
DOI: 10.48597/7dc5-jx79
title: Measurement of Hydrogen_sulfide at Broomfield Soaring Eagle Park

description: Measurement of Hydrogen_sulfide at Broomfield Soaring Eagle Park
DOI: 10.6084/m9.figshare.c.3791137_d1.v1
title: Additional file 1: of The validity and psychometric properties of the Japanese version of the Compulsive Internet Use Scale (CIUS)

description: Translation and back translation of Japanese version of Compulsive Internet Use Scale (CIUS). (XLSX 13Â kb)