cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.5t98jm
title: Occurrence Download

description: A dataset containing 421580 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Year 2021-2021"
 ]
}

 The dataset includes 421580 records from 269 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000158-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12668256
title: Boreal Winter Hadley Cell Contraction in Response to the Incorporation of a Comprehensive Ocean Surface Albedo in CESM2

description: Data for:  The Effect of the Ocean Surface Albedo on the Boreal Winter Hadley Cell Edge in the Fully Coupled CESM2
DOI: 10.5281/zenodo.12668255
title: Boreal Winter Hadley Cell Contraction in Response to the Incorporation of a Comprehensive Ocean Surface Albedo in CESM2

description: Simulated output for:  Boreal Winter Hadley Cell Contraction in Response to the Incorporation of a Comprehensive Ocean Surface Albedo in CESM2
DOI: 10.5281/zenodo.14217357
title: Boreal Winter Hadley Cell Contraction in Response to the Incorporation of a Comprehensive Ocean Surface Albedo in CESM2

description: Simulated output for:  Boreal Winter Hadley Cell Contraction in Response to the Incorporation of a Comprehensive Ocean Surface Albedo in CESM2
DOI: 10.15468/dl.w7hkqk
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is one of (Primulina renifolia (D.Fang & D.H.Qin) J.M.Li & Yin Z.Wang)"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000202-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14205077
title: Benchmarking single-cell imputation algorithms on epigenomic data

description: In sillico sortChIC datasets generated and used in Moreno Gonzalez et al. (2025). Input data is taken from Zeller et al. (2023). Each .RDS file contains sparse matrices at different noise-levels of one scHPTM dataset at the indicated Counts Per Cell (CPC).
DOI: 10.23668/psycharchives.15163
title: Environmental Sensitivity in Brazilian Children: Cultural adaptation of the Highly Sensitive Child Scale (HSCS) to Brazilian Portuguese

description: Environmental Sensitivity (ES) is defined as the ability to register and process external stimuli. Different individuals process these stimuli in varied ways, which can lead to both negative and positive consequences. This study aimed to adapt the Highly Sensitive Child Scale (HSCS) to Portuguese and evaluate its psychometric properties in a Brazilian population. Data were collected from 623 young people aged 8 to 13 years (49.6% female, 68.0% from the Southeast region, and 63.0% white). Confirmatory factor analyses indicated an adequate structure for the three correlated factors of the original scale: aesthetic sensitivity (AES), ease of excitation (EOE), and low sensory threshold (LST). The scale correlated with the factors of the Behavioral Inhibition and Activation Scale (BIS/BAS), consistent with the original validation. Female participants had higher mean scores than males for AES and EOE, but not for LST. Configural and metric invariance with respect to gender was observed; however, scalar invariance was not. A latent class analysis identified three groups among the participants: low (12.1%), moderate (41.2%), and high (46.1%) sensitivity. The results indicate good psychometric qualities and the suitability of the translated scale for application in a Brazilian population.
DOI: 10.5284/1124414
title: Images from a Level 3 Analytical Buildings Survey Record at Chenhall Farm, Crelly, Trenear, Cornwall

description: This digital archive comprises images from a level 3 analytical buildings recording survey of a cottage and farmstead buildings at Chenhall Farm, Crelly, Trenear, TR13 0EY (OS NGR SW6768731938) in advance of a programme of works requiring Listed Building Consent (Cornwall Council reference PA21/10727).
DOI: 10.23668/psycharchives.15166
title: Final Dataset for: Unlocking Socioeconomic Insights through Schools’ Geolocation

description: Final Dataset Used for Multilevel Model Estimation
DOI: 10.15468/dl.83ccc3
title: Occurrence Download

description: A dataset containing 4727 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Zooplankton Species Distribution and Abundance Data, Arctic Marine Biodiversity Observing Network (AMBON) Chukchi Sea research cruise, August 2017"
 ]
}

 The dataset includes 4727 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000205-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tqcqeh
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is one of (Primulina repanda (W.T.Wang) Yin Z.Wang)"
 ]
}

 The dataset includes 7 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000207-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fk2x63
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "DatasetKey is Inventario florístico de las Cactáceas del estado de Tamaulipas, México",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Astrophytum asterias (Zucc.) Lem."
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000209-241125135418005/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.27901977
title: Baseline Data on Students Problem-Solving (PS) Skills: Physics Concept and PS Steps Analysis

description: This dataset has two files. One file contains data from students where they are marked based on how they performed each question (physics concept). Another file contains an analysis based on how students followed each of the seven PS steps.
DOI: 10.15468/dl.934tr8
title: Occurrence Download

description: A dataset listing the 3384 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((1.493 44.692,2.032 44.692,2.032 45.232,1.493 45.232,1.493 44.692))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Tracheophyta",
 "Year 1924-2024"
 ]
}

 The dataset's 3384 records were derived from 159 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000179-241125135418005/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/9211698
title: Trending Youtube Video Statistics (113 Countries)
DOI: 10.5281/zenodo.12690047
title: DICOM converted Slide Microscopy images for the TCGA-DLBC collection

description: This dataset corresponds to a collection of images and/or image-derived data available from National Cancer Institute
Imaging Data Commons (IDC) [1]. This dataset was converted
into DICOM representation and ingested by the IDC team. You can explore and visualize the corresponding images using
IDC Portal here: TCGA-DLBC. You can use the manifests included in this
Zenodo record to download the content of the collection following the Download instructions below.

Collection description


       There is no available description page for this collection.


      Citation guidelines can be found on the Citing TCGA in Publications and Presentations information page.

Files included

A manifest file's name indicates the IDC data release in which a version of collection data was first introduced.
For example, collection_id-idc_v8-aws.s5cmd corresponds to the contents of the
collection_id collection introduced in IDC data
release v8. If there is a subsequent version of this Zenodo page, it will indicate when a subsequent version of
the corresponding collection was introduced.



tcga_dlbc-idc_v18-aws.s5cmd: manifest of files available for download from public IDC Amazon Web Services buckets

tcga_dlbc-idc_v18-gcs.s5cmd: manifest of files available for download from public IDC Google Cloud Storage buckets

tcga_dlbc-idc_v18-dcf.dcf: Gen3 manifest (for details see https://learn.canceridc.dev/data/organization-of-data/guids-and-uuids)


Note that manifest files that end in -aws.s5cmd reference files stored in Amazon Web Services (AWS) buckets, while -gcs.s5cmd reference
files in Google Cloud Storage. The actual files are identical and are mirrored between AWS and GCP.


Download instructions

Each of the manifests include instructions in the header on how to download the included files.

To download the files using .s5cmd manifests:



install idc-index package: pip install --upgrade idc-index

download the files referenced by manifests included in this dataset by passing the .s5cmd manifest file: idc download manifest.s5cmd.


To download the files using .dcf manifest, see manifest header.


Acknowledgments

Imaging Data Commons team has been funded in whole or in part with Federal funds from the National Cancer Institute,
National Institutes of Health, under Task Order No. HHSN26110071 under Contract No. HHSN261201500003l.


References

[1] Fedorov, A., Longabaugh, W. J. R., Pot, D., Clunie, D. A., Pieper, S. D., Gibbs, D. L., Bridge, C., Herrmann,
M. D., Homeyer, A., Lewis, R., Aerts, H. J. W., Krishnaswamy, D., Thiriveedhi, V. K., Ciausu, C., Schacherer,
D. P., Bontempi, D., Pihl, T., Wagner, U., Farahani, K., Kim, E. & Kikinis, R.
National Cancer Institute Imaging Data Commons: Toward Transparency, Reproducibility, and Scalability in
Imaging Artificial Intelligence. RadioGraphics (2023). https://doi.org/10.1148/rg.230180
DOI: 10.5281/zenodo.12690048
title: DICOM converted Slide Microscopy images for the TCGA-DLBC collection

description: This dataset corresponds to a collection of images and/or image-derived data available from National Cancer Institute
Imaging Data Commons (IDC) [1]. This dataset was converted
into DICOM representation and ingested by the IDC team. You can explore and visualize the corresponding images using
IDC Portal here: TCGA-DLBC. You can use the manifests included in this
Zenodo record to download the content of the collection following the Download instructions below.

Collection description


       There is no available description page for this collection.


      Citation guidelines can be found on the Citing TCGA in Publications and Presentations information page.

Files included

A manifest file's name indicates the IDC data release in which a version of collection data was first introduced.
For example, collection_id-idc_v8-aws.s5cmd corresponds to the contents of the
collection_id collection introduced in IDC data
release v8. If there is a subsequent version of this Zenodo page, it will indicate when a subsequent version of
the corresponding collection was introduced.



tcga_dlbc-idc_v8-aws.s5cmd: manifest of files available for download from public IDC Amazon Web Services buckets

tcga_dlbc-idc_v8-gcs.s5cmd: manifest of files available for download from public IDC Google Cloud Storage buckets

tcga_dlbc-idc_v8-dcf.dcf: Gen3 manifest (for details see https://learn.canceridc.dev/data/organization-of-data/guids-and-uuids)


Note that manifest files that end in -aws.s5cmd reference files stored in Amazon Web Services (AWS) buckets, while -gcs.s5cmd reference
files in Google Cloud Storage. The actual files are identical and are mirrored between AWS and GCP.


Download instructions

Each of the manifests include instructions in the header on how to download the included files.

To download the files using .s5cmd manifests:



install idc-index package: pip install --upgrade idc-index

download the files referenced by manifests included in this dataset by passing the .s5cmd manifest file: idc download manifest.s5cmd.


To download the files using .dcf manifest, see manifest header.


Acknowledgments

Imaging Data Commons team has been funded in whole or in part with Federal funds from the National Cancer Institute,
National Institutes of Health, under Task Order No. HHSN26110071 under Contract No. HHSN261201500003l.


References

[1] Fedorov, A., Longabaugh, W. J. R., Pot, D., Clunie, D. A., Pieper, S. D., Gibbs, D. L., Bridge, C., Herrmann,
M. D., Homeyer, A., Lewis, R., Aerts, H. J. W., Krishnaswamy, D., Thiriveedhi, V. K., Ciausu, C., Schacherer,
D. P., Bontempi, D., Pihl, T., Wagner, U., Farahani, K., Kim, E. & Kikinis, R.
National Cancer Institute Imaging Data Commons: Toward Transparency, Reproducibility, and Scalability in
Imaging Artificial Intelligence. RadioGraphics (2023). https://doi.org/10.1148/rg.230180
DOI: 10.5281/zenodo.13346208
title: DICOM converted Slide Microscopy images for the TCGA-DLBC collection

description: This dataset corresponds to a collection of images and/or image-derived data available from National Cancer Institute
Imaging Data Commons (IDC) [1]. This dataset was converted
into DICOM representation and ingested by the IDC team. You can explore and visualize the corresponding images using
IDC Portal here: TCGA-DLBC. You can use the manifests included in this
Zenodo record to download the content of the collection following the Download instructions below.

Collection description


       There is no available description page for this collection.


      Citation guidelines can be found on the Citing TCGA in Publications and Presentations information page.

Files included

A manifest file's name indicates the IDC data release in which a version of collection data was first introduced.
For example, collection_id-idc_v8-aws.s5cmd corresponds to the contents of the
collection_id collection introduced in IDC data
release v8. If there is a subsequent version of this Zenodo page, it will indicate when a subsequent version of
the corresponding collection was introduced.



tcga_dlbc-idc_v10-aws.s5cmd: manifest of files available for download from public IDC Amazon Web Services buckets

tcga_dlbc-idc_v10-gcs.s5cmd: manifest of files available for download from public IDC Google Cloud Storage buckets

tcga_dlbc-idc_v10-dcf.dcf: Gen3 manifest (for details see https://learn.canceridc.dev/data/organization-of-data/guids-and-uuids)


Note that manifest files that end in -aws.s5cmd reference files stored in Amazon Web Services (AWS) buckets, while -gcs.s5cmd reference
files in Google Cloud Storage. The actual files are identical and are mirrored between AWS and GCP.


Download instructions

Each of the manifests include instructions in the header on how to download the included files.

To download the files using .s5cmd manifests:



install idc-index package: pip install --upgrade idc-index

download the files referenced by manifests included in this dataset by passing the .s5cmd manifest file: idc download manifest.s5cmd.


To download the files using .dcf manifest, see manifest header.


Acknowledgments

Imaging Data Commons team has been funded in whole or in part with Federal funds from the National Cancer Institute,
National Institutes of Health, under Task Order No. HHSN26110071 under Contract No. HHSN261201500003l.


References

[1] Fedorov, A., Longabaugh, W. J. R., Pot, D., Clunie, D. A., Pieper, S. D., Gibbs, D. L., Bridge, C., Herrmann,
M. D., Homeyer, A., Lewis, R., Aerts, H. J. W., Krishnaswamy, D., Thiriveedhi, V. K., Ciausu, C., Schacherer,
D. P., Bontempi, D., Pihl, T., Wagner, U., Farahani, K., Kim, E. & Kikinis, R.
National Cancer Institute Imaging Data Commons: Toward Transparency, Reproducibility, and Scalability in
Imaging Artificial Intelligence. RadioGraphics (2023). https://doi.org/10.1148/rg.230180
DOI: 10.5281/zenodo.13346263
title: DICOM converted Slide Microscopy images for the TCGA-DLBC collection

description: This dataset corresponds to a collection of images and/or image-derived data available from National Cancer Institute
Imaging Data Commons (IDC) [1]. This dataset was converted
into DICOM representation and ingested by the IDC team. You can explore and visualize the corresponding images using
IDC Portal here: TCGA-DLBC. You can use the manifests included in this
Zenodo record to download the content of the collection following the Download instructions below.

Collection description


       There is no available description page for this collection.


      Citation guidelines can be found on the Citing TCGA in Publications and Presentations information page.

Files included

A manifest file's name indicates the IDC data release in which a version of collection data was first introduced.
For example, collection_id-idc_v8-aws.s5cmd corresponds to the contents of the
collection_id collection introduced in IDC data
release v8. If there is a subsequent version of this Zenodo page, it will indicate when a subsequent version of
the corresponding collection was introduced.



tcga_dlbc-idc_v18-aws.s5cmd: manifest of files available for download from public IDC Amazon Web Services buckets

tcga_dlbc-idc_v18-gcs.s5cmd: manifest of files available for download from public IDC Google Cloud Storage buckets

tcga_dlbc-idc_v18-dcf.dcf: Gen3 manifest (for details see https://learn.canceridc.dev/data/organization-of-data/guids-and-uuids)


Note that manifest files that end in -aws.s5cmd reference files stored in Amazon Web Services (AWS) buckets, while -gcs.s5cmd reference
files in Google Cloud Storage. The actual files are identical and are mirrored between AWS and GCP.


Download instructions

Each of the manifests include instructions in the header on how to download the included files.

To download the files using .s5cmd manifests:



install idc-index package: pip install --upgrade idc-index

download the files referenced by manifests included in this dataset by passing the .s5cmd manifest file: idc download manifest.s5cmd.


To download the files using .dcf manifest, see manifest header.


Acknowledgments

Imaging Data Commons team has been funded in whole or in part with Federal funds from the National Cancer Institute,
National Institutes of Health, under Task Order No. HHSN26110071 under Contract No. HHSN261201500003l.


References

[1] Fedorov, A., Longabaugh, W. J. R., Pot, D., Clunie, D. A., Pieper, S. D., Gibbs, D. L., Bridge, C., Herrmann,
M. D., Homeyer, A., Lewis, R., Aerts, H. J. W., Krishnaswamy, D., Thiriveedhi, V. K., Ciausu, C., Schacherer,
D. P., Bontempi, D., Pihl, T., Wagner, U., Farahani, K., Kim, E. & Kikinis, R.
National Cancer Institute Imaging Data Commons: Toward Transparency, Reproducibility, and Scalability in
Imaging Artificial Intelligence. RadioGraphics (2023). https://doi.org/10.1148/rg.230180
DOI: 10.15468/dl.nufgb9
title: Occurrence Download

description: A dataset containing 2643 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-41.04695 -20.38467,-41.03147 -20.3957,-41.01227 -20.39106,-41.00773 -20.37635,-41.02383 -20.36222,-41.04613 -20.36706,-41.04695 -20.38467))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 2643 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0076098-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gcyryr
title: Occurrence Download

description: A dataset containing 30 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Dialium gossweileri Baker f.)"
 ]
}

 The dataset includes 30 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0076099-240626123714530/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.26503963
title: Supplementary from Generalised eigenfunction expansion and singularity expansion methods for two-dimensional acoustic time-domain wave scattering problems

description: SupplementaryMaterial.zip
DOI: 10.6084/m9.figshare.26503963.v1
title: Supplementary from Generalised eigenfunction expansion and singularity expansion methods for two-dimensional acoustic time-domain wave scattering problems

description: SupplementaryMaterial.zip
DOI: 10.15468/dl.x4used
title: Occurrence Download

description: A dataset containing 32885160 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 32885160 records from 4786 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0076085-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7pfy9a
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hypericum hircinum",
 "Country is Portugal",
 "HasCoordinate is true"
 ]
}

 The dataset includes 20 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052846-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bnz99k
title: Occurrence Download

description: A dataset containing 153 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Gnetopsida)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((60 0,90 0,90 30,60 30,60 0))"
 ]
}

 The dataset includes 153 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052847-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.daexkq
title: Occurrence Download

description: A dataset containing 4454 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Cercidiphyllum japonicum)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 4454 records from 159 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052848-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kczq4p
title: Occurrence Download

description: A dataset containing 1058 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Gnetopsida)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((90 0,120 0,120 30,90 30,90 0))"
 ]
}

 The dataset includes 1058 records from 51 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052850-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.