cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.7xy4p8
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.065699 -36.937188, 149.065699 -36.943925, 149.067945 -36.943925, 149.067945 -36.955154, 149.072437 -36.955154, 149.072437 -36.959646, 149.074683 -36.959646, 149.074683 -36.955154, 149.079174 -36.955154, 149.079174 -36.952909, 149.074683 -36.952909, 149.074683 -36.950663, 149.079174 -36.950663, 149.079174 -36.946171, 149.074683 -36.946171, 149.074683 -36.939434, 149.067945 -36.939434, 149.067945 -36.937188, 149.065699 -36.937188))"
 ]
}

 The dataset includes 8 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055180-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7272n4
title: Occurrence Download

description: A dataset containing 20066 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((74 36,75.9 36,75.9 38,74 38,74 36))",
 "TaxonKey is Tracheophyta"
 ]
}

 The dataset includes 20066 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055181-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eygyq9
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Podachaenium chimalapanum B.L.Turner"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055182-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jeunj6
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Bactrocera dorsalis (Hendel, 1912))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1900",
 "BasisOfRecord is one of (Specimen)",
 "Country is one of (Indonesia)",
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than or equal to 20000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055183-240626123714530/datasets/export for details.
DOI: 10.15468/dl.rjs7xb
title: Occurrence Download

description: A dataset containing 42 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((145.198434 -36.939434, 145.198434 -36.946171, 145.202925 -36.946171, 145.202925 -36.939434, 145.198434 -36.939434))"
 ]
}

 The dataset includes 42 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055185-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m5aybw
title: Occurrence Download

description: A dataset containing 43 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((148.641243 -32.544405, 148.650227 -32.544405, 148.650227 -32.551143, 148.656964 -32.551143, 148.656964 -32.548897, 148.652472 -32.548897, 148.652472 -32.544405, 148.665947 -32.544405, 148.665947 -32.548897, 148.679422 -32.548897, 148.679422 -32.542159, 148.681668 -32.542159, 148.681668 -32.551143, 148.683914 -32.551143, 148.683914 -32.537668, 148.67493 -32.537668, 148.67493 -32.542159, 148.672685 -32.542159, 148.672685 -32.544405, 148.668193 -32.544405, 148.668193 -32.542159, 148.661456 -32.542159, 148.661456 -32.537668, 148.65921 -32.537668, 148.65921 -32.542159, 148.652472 -32.542159, 148.652472 -32.537668, 148.645735 -32.537668, 148.645735 -32.535422, 148.641243 -32.535422, 148.641243 -32.537668, 148.643489 -32.537668, 148.643489 -32.542159, 148.641243 -32.542159, 148.641243 -32.544405)), ((148.641243 -32.544405, 148.634506 -32.544405, 148.634506 -32.553388, 148.641243 -32.553388, 148.641243 -32.544405)), ((148.683914 -32.551143, 148.683914 -32.55788, 148.695143 -32.55788, 148.695143 -32.553388, 148.688405 -32.553388, 148.688405 -32.551143, 148.683914 -32.551143)))"
 ]
}

 The dataset includes 43 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055186-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vn8t5t
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.049979 -36.939434, 149.049979 -36.946171, 149.047733 -36.946171, 149.047733 -36.950663, 149.049979 -36.950663, 149.049979 -36.955154, 149.052225 -36.955154, 149.052225 -36.959646, 149.063454 -36.959646, 149.063454 -36.950663, 149.056716 -36.950663, 149.056716 -36.943925, 149.052225 -36.943925, 149.052225 -36.939434, 149.049979 -36.939434))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055187-240626123714530/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.7033577
title: Deep image reconstruction from human brain activity

description: Shen, Horikawa, Majima, and Kamitani (2019) Deep image reconstruction from human brain activity. PLos Comput Biol. (bioRxiv preprint)
Here we provide DNN features decoded from human brain activity (decodedfeatures-*.mat files) as well as preprocessed fMRI data used for the decoding (sub-*.h5 files).<br>
Raw fMRI data are available at OpenNeuro.
Demo code is available at GitHub.
History
2022-10-14: Add fMRI data (sub-03) preprocessed by fmriprep (*_fmriprep_volume_native.h5)
2022-10-13: Add fMRI data (sub-01, sub-02) preprocessed by fmriprep (*_fmriprep_volume_native.h5)<br>
2022-01-27: Minor update on fMRI data (v2; "stimulus_name" was added).<br>
2020-09-09: True DNN features (unit activations) of VGG19 for natural image training and test images were added.
2020-09-08: True DNN features (unit activations) of VGG19 (except conv1) for natural image training images were added.
2020-08-05: fMRI data version 2, which applied slightly different preprocessng and ROIs from the original study, were added (for the natural image experiment only; *_perceptionNaturalImageTraining/Test_VC_v2.h5).
2020-05-18: The following fMRI data files of artificial images, letters, and imagery experiments contained incorrect samples and were fixed.

 sub-01_perceptionLetterImage_original_VC.h5
 sub-02_perceptionArtificialImage_original_VC.h5
 sub-02_perceptionLetterImage_original_VC.h5
 sub-02_imagery_original_VC.h5
 sub-03_perceptionArtificialImage_original_VC.h5
 sub-03_perceptionLetterImage_original_VC.h5
 sub-03_imagery_original_VC.h5

<br>
DOI: 10.6084/m9.figshare.7033577.v15
title: Deep image reconstruction from human brain activity

description: Shen, Horikawa, Majima, and Kamitani (2019) Deep image reconstruction from human brain activity. PLos Comput Biol. (bioRxiv preprint)
Here we provide DNN features decoded from human brain activity (decodedfeatures-*.mat files) as well as preprocessed fMRI data used for the decoding (sub-*.h5 files).<br>
Raw fMRI data are available at OpenNeuro.
Demo code is available at GitHub.
History
2022-10-14: Add fMRI data (sub-03) preprocessed by fmriprep (*_fmriprep_volume_native.h5)
2022-10-13: Add fMRI data (sub-01, sub-02) preprocessed by fmriprep (*_fmriprep_volume_native.h5)<br>
2022-01-27: Minor update on fMRI data (v2; "stimulus_name" was added).<br>
2020-09-09: True DNN features (unit activations) of VGG19 for natural image training and test images were added.
2020-09-08: True DNN features (unit activations) of VGG19 (except conv1) for natural image training images were added.
2020-08-05: fMRI data version 2, which applied slightly different preprocessng and ROIs from the original study, were added (for the natural image experiment only; *_perceptionNaturalImageTraining/Test_VC_v2.h5).
2020-05-18: The following fMRI data files of artificial images, letters, and imagery experiments contained incorrect samples and were fixed.

 sub-01_perceptionLetterImage_original_VC.h5
 sub-02_perceptionArtificialImage_original_VC.h5
 sub-02_perceptionLetterImage_original_VC.h5
 sub-02_imagery_original_VC.h5
 sub-03_perceptionArtificialImage_original_VC.h5
 sub-03_perceptionLetterImage_original_VC.h5
 sub-03_imagery_original_VC.h5

<br>
DOI: 10.15468/dl.f4ngf7
title: Occurrence Download

description: A dataset containing 181 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Xylella Wells et al., 1987"
 ]
}

 The dataset includes 181 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055189-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qurgh9
title: Occurrence Download

description: A dataset containing 101 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((149.510368 -32.499489, 149.510368 -32.503981, 149.519351 -32.503981, 149.519351 -32.499489, 149.510368 -32.499489)), ((149.519351 -32.503981, 149.519351 -32.510718, 149.532826 -32.510718, 149.532826 -32.503981, 149.535071 -32.503981, 149.535071 -32.501735, 149.532826 -32.501735, 149.532826 -32.499489, 149.53058 -32.499489, 149.53058 -32.503981, 149.519351 -32.503981)), ((149.532826 -32.510718, 149.532826 -32.519701, 149.53058 -32.519701, 149.53058 -32.526439, 149.526088 -32.526439, 149.526088 -32.528685, 149.523842 -32.528685, 149.523842 -32.53093, 149.526088 -32.53093, 149.526088 -32.535422, 149.53058 -32.535422, 149.53058 -32.53093, 149.532826 -32.53093, 149.532826 -32.535422, 149.535071 -32.535422, 149.535071 -32.537668, 149.539563 -32.537668, 149.539563 -32.544405, 149.535071 -32.544405, 149.535071 -32.548897, 149.539563 -32.548897, 149.539563 -32.551143, 149.541809 -32.551143, 149.541809 -32.548897, 149.548546 -32.548897, 149.548546 -32.542159, 149.5463 -32.542159, 149.5463 -32.537668, 149.541809 -32.537668, 149.541809 -32.53093, 149.535071 -32.53093, 149.535071 -32.519701, 149.539563 -32.519701, 149.539563 -32.51521, 149.535071 -32.51521, 149.535071 -32.510718, 149.532826 -32.510718)))"
 ]
}

 The dataset includes 101 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055190-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5a6kym
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((143.09412 -36.943925, 143.09412 -36.946171, 143.100857 -36.946171, 143.100857 -36.943925, 143.09412 -36.943925))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0055191-240626123714530/datasets/export for details.
DOI: 10.5281/zenodo.7844587
title: data for Es layer simulations

description: This data comes from the ES layer simulation manuscript titled by "<strong>Numerical simulations of metallic ion density perturbations in sporadic E layers caused by gravity waves</strong>". it contains neutral wind from HIAMCM, GAIA, and WACCM-X and initial Fe ion density distribution from WACCM-Fe.
DOI: 10.5281/zenodo.7844586
title: data for Es layer simulations

description: This data comes from the  Es layer simulation manuscript titled by "Numerical simulations of metallic ion density perturbations in sporadic E layers caused by gravity waves". it contains neutral wind and initial Fe ion density distribution.  Yu Tao is the corresponding author.
DOI: 10.15156/bio/sh0176213.10fu
title: SH0176213.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0176214.10fu
title: SH0176214.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0176215.10fu
title: SH0176215.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0176216.10fu
title: SH0176216.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0176217.10fu
title: SH0176217.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0176218.10fu
title: SH0176218.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.7910/dvn/wfx1fj
title: TerraClimate

description: TerraClimate provides monthly climate and climatic water balance data during the time period from 1958 to 2024. The dataset covers global land surfaces with spatial resolution of ~4 km (1/24th degree). Variables include maximum temperature, minimum temperature, precipitation, wind speed, runoff, and soil moisture, among others. TerraClimate data can be used in various ecological and hydrological applications, such as species distribution modeling, environment impact analyses, and wildfire activity pattern studies. The climate data is produced using climatically aided interpolation with a combination of a higher spatial resolution dataset (WorldClim) and two long-term higher temporal resolution datasets (CRU Ts4.0 and JRA-55). The climatic water balance data is produced using a water balance model with extractable soil water storage capacity data.
description: <b>Intended Use</b>Geospatial exposure model developmentLongitudinal studiesLong-term studiesLarge-scale studiesOtherEnvironmental impact assessmentsEcological, hydrological and/or agricultural modelingWildfire management related analyses<br><b>Strengths</b>Dataset supports analysis of differences in monthly climate variables over multiple decades across global locationsDataset spatial resolution (~4 km) supports analysis of spatial variability in climate variables at local scalesTerraClimate accuracy has been assessed using weather station measurementsTerraClimate is a readily available source of global climate data with multiple tools supporting data download and visualization<br><b>Limitations</b>TerraClimate uses a water balance model that does not account for differences in vegetationTerraClimate data inherit uncertainties and other limitations from its input climate datasetsTerraClimate validation information is limited in geographic regions with sparsely available weather station dataData coverage is limited to land surfacesTerraClimate uses a water balance model that does not account for differences in vegetationTerraClimate data inherit uncertainties and other limitations from its input climate datasetsTerraClimate validation information is limited in geographic regions with sparsely available weather station dataData coverage is limited to land surfaces<br><b>Suggested Audience</b>ResearcherGeneral Public<br>
DOI: 10.15156/bio/sh0176219.10fu
title: SH0176219.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0176220.10fu
title: SH0176220.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.