cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.6q99tc
title: Occurrence Download

description: A dataset containing 62 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Geocharis fusiformis (Ridl.) R.M.Sm."
 ]
}

 The dataset includes 62 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009065-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z0exam
title: Occurrence Download

description: A dataset containing 970 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Drymophila caudata (P.L.Sclater, 1855)"
 ]
}

 The dataset includes 970 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039869-180508205500799/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yt8wfc
title: Occurrence Download

description: A dataset containing 637 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Phrynosoma solare Gray, 1845",
 "Year 1900-2000"
 ]
}

 The dataset includes 637 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029916-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15621385
title: Data of Virtual Reality, Cultural Engagement, and Sustainable Tourism: A Mixed-Methods Study of Audience Responses in the Yellow River Region
DOI: 10.5281/zenodo.15621386
title: Data of Virtual Reality, Cultural Engagement, and Sustainable Tourism: A Mixed-Methods Study of Audience Responses in the Yellow River Region
DOI: 10.15468/dl.jk8rjv
title: Occurrence Download

description: A dataset containing 114401131 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "License is CC-BY 4.0",
 "Year 2015-2016"
 ]
}

 The dataset includes 114401131 records from 567 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029907-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dd.gwtatk
title: Borbo fallax Gaede, 1916

description: Summary of datasets contributing records of Borbo fallax Gaede, 1916
DOI: 10.15468/dd.mefvkm
title: Borbo micans Holland, 1896

description: Summary of datasets contributing records of Borbo micans Holland, 1896
DOI: 10.15468/dd.2m5drj
title: Borbo lugens Hopffer, 1855

description: Summary of datasets contributing records of Borbo lugens Hopffer, 1855
DOI: 10.15468/dd.n46cx3
title: Charaxes candiope Godart, 1824

description: Summary of datasets contributing records of Charaxes candiope Godart, 1824
DOI: 10.15468/dd.wf37d8
title: Kedestes callicles Hewitson, 1868

description: Summary of datasets contributing records of Kedestes callicles Hewitson, 1868
DOI: 10.15468/dd.gpn34k
title: Lachnocnema bibulus (Fabricius, 1793)

description: Summary of datasets contributing records of Lachnocnema bibulus (Fabricius, 1793)
DOI: 10.15468/dd.ecefce
title: Graphium antheus (Cramer, 1779)

description: Summary of datasets contributing records of Graphium antheus (Cramer, 1779)
DOI: 10.5281/zenodo.14361220
title: NADA-SynShapes: A synthetic shape benchmark for testing probabilistic deep learning models

description: NADA (Not-A-Database) is an easy-to-use geometric shape data generator that allows users to define non-uniform multivariate parameter distributions to test novel methodologies. The full open-source package is provided at GIT:NA_DAtabase. See Technical Report for details on how to use the provided package.

This database includes 3 repositories:



NADA_Dis: Is the model able to correctly characterize/Disentangle a complex latent space?The repository contains 3x100,000 synthetic black and white images to test the ability of the models to correctly define a proper latent space (e.g., autoencoders) and disentangle it. The first 100,000 images contain 4 shapes and uniform parameter space distributions, while the other images have a more complex underlying distribution (truncated Gaussian and correlated marginal variables).

NADA_OOD: Does the model identify Out-Of-Distribution images?The repository contains 100,000 training images (4 different shapes with 3 possible colors located in the upper left corner of the canvas) and 6x100,000 increasingly different sets of images (changing the color class balance, reducing the radius of the shape, moving the shape to the lower left corner) providing increasingly challenging out-of-distribution images. This can help to test not only the capability of a model, but also methods that produce reliability estimates and should correctly classify OOD elements as "unreliable" as they are far from the original distributions.

NADA_AlEp: Does the model distinguish between different types (Aleatoric/Epistemic) of uncertainties?The repository contains 5x100,000 images with different type of noise/uncertainties:



NADA_AlEp_0_Clean: Dataset clean of noise to use as a possible training set.

NADA_AlEp_1_White_Noise: Epistemic white noise dataset. Each image is perturbed with an amount of white noise randomly sampled from 0% to 90%.

NADA_AlEp_2_Deformation: Dataset with Epistemic deformation noise. Each image is deformed by a randomly amount uniformly sampled between 0% and 90%. 0% corresponds to the original image, while 100% is a full deformation to the circumscribing circle.

NADA_AlEp_3_Label: Dataset with label noise. Formally, 20% of Triangles of a given color are missclassified as a Square with a random color (among Blue, Orange, and Brown) and viceversa (Squares to Triangles). Label noise introduces \textit{Aleatoric Uncertainty} because it is inherent in the data and cannot be reduced.

NADA_AlEp_4_Combined: Combined dataset with all previous sources of uncertainty.




Each image can be used for classification (shape/color) or regression (radius/area) tasks.

All datasets can be modified and adapted to the user's research question using the included open source data generator.
DOI: 10.5281/zenodo.14361221
title: NADA: A synthetic shape benchmark for testing probabilistic deep learning models

description: NADA (Not-A-Database) is an easy-to-use geometric shape data generator that allows users to define non-uniform multivariate parameter distributions to test novel methodologies. The full open-source package is provided at GIT:NA_DAtabase. See Technical Report for details on how to use the provided package.

This database includes 3 repositories:



NADA_Dis: Is the model able to correctly characterize/Disentangle a complex latent space?The repository contains 3x100,000 synthetic black and white images to test the ability of the models to correctly define a proper latent space (e.g., autoencoders) and disentangle it. The first 100,000 images contain 4 shapes and uniform parameter space distributions, while the other images have a more complex underlying distribution (truncated Gaussian and correlated marginal variables).

NADA_OOD: Does the model identify Out-Of-Distribution images?The repository contains 100,000 training images (4 different shapes with 3 possible colors located in the upper left corner of the canvas) and 6x100,000 increasingly different sets of images (changing the color class balance, reducing the radius of the shape, moving the shape to the lower left corner) providing increasingly challenging out-of-distribution images. This can help to test not only the capability of a model, but also methods that produce reliability estimates and should correctly classify OOD elements as "unreliable" as they are far from the original distributions.

NADA_AlEp: Does the model distinguish between different types (Aleatoric/Epistemic) of uncertainties?The repository contains 5x100,000 images with different type of noise/uncertainties:



NADA_AlEp_0_Clean: Dataset clean of noise to use as a possible training set.

NADA_AlEp_1_White_Noise: Epistemic white noise dataset. Each image is perturbed with an amount of white noise randomly sampled from 0% to 90%.

NADA_AlEp_2_Deformation: Dataset with Epistemic deformation noise. Each image is deformed by a randomly amount uniformly sampled between 0% and 90%. 0% corresponds to the original image, while 100% is a full deformation to the circumscribing circle.

NADA_AlEp_3_Label: Dataset with label noise. Formally, 20% of Triangles of a given color are missclassified as a Square with a random color (among Blue, Orange, and Brown) and viceversa (Squares to Triangles). Label noise introduces \textit{Aleatoric Uncertainty} because it is inherent in the data and cannot be reduced.

NADA_AlEp_4_Combined: Combined dataset with all previous sources of uncertainty.




Each image can be used for classification (shape/color) or regression (radius/area) tasks.

All datasets can be modified and adapted to the user's research question using the included open source data generator.
DOI: 10.5281/zenodo.15194187
title: NADA-SynShapes: A synthetic shape benchmark for testing probabilistic deep learning models

description: NADA (Not-A-Database) is an easy-to-use geometric shape data generator that allows users to define non-uniform multivariate parameter distributions to test novel methodologies. The full open-source package is provided at GIT:NA_DAtabase. See Technical Report for details on how to use the provided package.

This database includes 3 repositories:



NADA_Dis: Is the model able to correctly characterize/Disentangle a complex latent space?The repository contains 3x100,000 synthetic black and white images to test the ability of the models to correctly define a proper latent space (e.g., autoencoders) and disentangle it. The first 100,000 images contain 4 shapes and uniform parameter space distributions, while the other images have a more complex underlying distribution (truncated Gaussian and correlated marginal variables).

NADA_OOD: Does the model identify Out-Of-Distribution images?The repository contains 100,000 training images (4 different shapes with 3 possible colors located in the upper left corner of the canvas) and 6x100,000 increasingly different sets of images (changing the color class balance, reducing the radius of the shape, moving the shape to the lower left corner) providing increasingly challenging out-of-distribution images. This can help to test not only the capability of a model, but also methods that produce reliability estimates and should correctly classify OOD elements as "unreliable" as they are far from the original distributions.

NADA_AlEp: Does the model distinguish between different types (Aleatoric/Epistemic) of uncertainties?The repository contains 5x100,000 images with different type of noise/uncertainties:



NADA_AlEp_0_Clean: Dataset clean of noise to use as a possible training set.

NADA_AlEp_1_White_Noise: Epistemic white noise dataset. Each image is perturbed with an amount of white noise randomly sampled from 0% to 90%.

NADA_AlEp_2_Deformation: Dataset with Epistemic deformation noise. Each image is deformed by a randomly amount uniformly sampled between 0% and 90%. 0% corresponds to the original image, while 100% is a full deformation to the circumscribing circle.

NADA_AlEp_3_Label: Dataset with label noise. Formally, 20% of Triangles of a given color are missclassified as a Square with a random color (among Blue, Orange, and Brown) and viceversa (Squares to Triangles). Label noise introduces \textit{Aleatoric Uncertainty} because it is inherent in the data and cannot be reduced.

NADA_AlEp_4_Combined: Combined dataset with all previous sources of uncertainty.




Each image can be used for classification (shape/color) or regression (radius/area) tasks.

All datasets can be modified and adapted to the user's research question using the included open source data generator.
DOI: 10.15468/dl.7z0ul9
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Illigera platyandra Dunn",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 17 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054351-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bwwc3d
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Miconia canoi Michelang. & Paredes"
 ]
}

 The dataset includes 7 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0172009-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dekdm2
title: Occurrence Download

description: A dataset containing 5727 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Croatia",
 "TaxonKey is Lepidoptera"
 ]
}

 The dataset includes 5727 records from 50 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008136-190415153152247/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f3d2wj
title: Occurrence Download

description: A dataset containing 28 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Centaurea stoebe Ledeb."
 ]
}

 The dataset includes 28 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026665-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.homjtb
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Illigera platyandra Dunn",
 "HasCoordinate is true"
 ]
}

 The dataset includes 18 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054352-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ems726
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Masdevallia decumana Königer"
 ]
}

 The dataset includes 10 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0172010-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u67hm8
title: Occurrence Download

description: A dataset containing 17582 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Thlaspi perfoliatum L."
 ]
}

 The dataset includes 17582 records from 197 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0086026-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vdj9rd
title: Occurrence Download

description: A dataset containing 28135 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lithobates catesbeianus (Shaw, 1802)"
 ]
}

 The dataset includes 28135 records from 145 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054355-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sq2f6m
title: Occurrence Download

description: A dataset containing 8919454 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Pueraria montana (Lour.) Merr., Pyracantha coccinea M.Roem., Pyracantha crenulata (D.Don) M.Roem., Pyrus calleryana Decne., Pyrus communis L., Quercus acutissima Carruth., Ranunculus acris L., Ranunculus bulbosus L., Ranunculus repens L., Raphanus raphanistrum L., Rapistrum rugosum (L.) All., Reynoutria japonica Houtt., Rhamnus cathartica L., Leuzea repens (L.) D.J.N.Hind, Ribes rubrum L., Ricinus communis L., Robinia hispida L., Robinia pseudoacacia L., Rorippa amphibia (L.) Besser, Rorippa austriaca (Crantz) Besser, Rorippa sylvestris (L.) Besser, Rosa gallica L., Rosa laevigata Michx., Rosa luciae Franch. & Rochebr. ex Crép., Rosa multiflora Thunb., Rosa rubiginosa L., Rosa rugosa Thunb., Rottboellia cochinchinensis (Lour.) Clayton, Koenigia polystachya (Wall. ex Meisn.) T.M.Schust. & Reveal, Rubus bifrons Vest ex Tratt., Rubus illecebrosus Focke, Rubus niveus Thunb., Rubus phoenicolasius Maxim., Rubus ulmifolius Schott, Rubus vestitus Weihe, Ruellia blechum L., Rumex acetosella L., Rumex crispus L., Rumex longifolius DC., Rumex obtusifolius L., Saccharum ravennae Bleb., Saccharum spontaneum L., Sagina procumbens L., Sagittaria sagittifolia L., Salix alba L., Salix caprea L., Salix cinerea L., Salix pentandra L., Salix purpurea L., Salsola collina Pall., Salsola kali L., Salsola paulsenii Litv., Salsola soda Weinm., 1822, Salsola tragus L., Salvia aethiopis L., Salvia pratensis L., Salvia sclarea L., Salvinia minima Baker, Dracaena hyacinthoides (L.) Mabb., Saponaria officinalis L., Sixalix atropurpurea subsp. atropurpurea, Scaevola taccada (Gaertn.) Roxb., Heptapleurum actinophyllum (Endl.) Lowry & G.M.Plunkett, Schinus molle L., Schinus terebinthifolia Raddi, Schismus arabicus Nees, Schismus barbatus (L.) Thell., Schoenoplectiella mucronata (L.) J.Jung & H.K.Choi, Scolymus hispanicus L., Leontodon autumnalis Oeder, 1816, Secale cereale L., Coronilla varia L., Senecio elegans L., Senecio inaequidens DC., Senecio madagascariensis Poir.)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 8919454 records from 5408 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025422-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.y4h4dr
title: Occurrence Download

description: A dataset containing 5923 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Persea americana Mill.",
 "HasCoordinate is true",
 "Year is greater than or equal to 1900",
 "BasisOfRecord is one of (Human Observation, Specimen, Unknown evidence)"
 ]
}

 The dataset includes 5923 records from 337 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064045-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/pcra-c14-39198
title: Flames of fire, [vol. 2], nos. 23-33, Jan. - Nov./Dec. 1915

description: [description english/roman)] All 11 issues subtitled "with which is incorporated tidings from Tibet and other lands".
DOI: 10.15468/dl.tgmrpg
title: Occurrence Download

description: A dataset containing 299 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Elassoma okefenokee Böhlke, 1956"
 ]
}

 The dataset includes 299 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0337897-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tyywf6
title: Occurrence Download

description: A dataset containing 148 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Atelopus mindoensis Peters, 1973)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 148 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064082-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/pcra-c14-39214
title: Flames of fire, [vol. 2], nos. 23-33, Jan. - Nov./Dec. 1915

description: [description english/roman)] All 11 issues subtitled "with which is incorporated tidings from Tibet and other lands".
DOI: 10.15468/dl.k7tfn9
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Paraschistura microlabra (Mirza & Nalbant, 1981)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0337889-210914110416597/datasets/export for details.
DOI: 10.15468/dl.5ze8ny
title: Occurrence Download

description: A dataset containing 103625 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Muskrat captures in Flanders, Belgium"
 ]
}

 The dataset includes 103625 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0149980-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.smjwyk
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Genetta cristata Hayman In Sanborn, 1940)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063979-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5sfybs
title: Occurrence Download

description: A dataset containing 268 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Country is China",
 "Country is Chinese Taipei"
 ]
 },
 "TaxonKey is Glycyrrhiza uralensis Fisch. ex DC."
 ]
}

 The dataset includes 268 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0252156-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fzjvm6
title: Occurrence Download

description: A dataset containing 2148632 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Bombus Latreille, 1802"
 ]
}

 The dataset includes 2148632 records from 1172 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0189239-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/pcra-c14-39227
title: Flames of fire, [vol. 2], nos. 23-33, Jan. - Nov./Dec. 1915

description: [description english/roman)] All 11 issues subtitled "with which is incorporated tidings from Tibet and other lands".
DOI: 10.15468/dl.um28me
title: Occurrence Download

description: A dataset containing 405 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Amolops wuyiensis (Liu & Hu, 1975))",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 405 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064019-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.