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

description: A dataset containing 536879 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sciurus carolinensis Gmelin, 1788"
 ]
}

 The dataset includes 536879 records from 298 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015574-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hz3cke
title: Occurrence Download

description: A dataset containing 14156 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Cyperus odoratus"
 ]
}

 The dataset includes 14156 records from 506 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049078-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v7kd6k
title: Occurrence Download

description: A dataset containing 109 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Euonymus japonicus",
 "Country is France",
 "HasCoordinate is true"
 ]
}

 The dataset includes 109 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049080-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j7gh4t
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Aeschnosoma hamadae",
 "DecimalLongitude is not null",
 "DecimalLatitude is not null"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002765-251120083545085/datasets/export for details.
DOI: 10.5281/zenodo.16989819
title: Lung-PET-CT-Dx-Annotations: Expert annotation of lung tumors for the Lung-PET-CT-Dx collection

description: This collection contains expert annotations of bounding boxes identifying locations of the tumor in the Lung-PET-CT-Dx collection [1] in the individual slices of the images. The annotations are accompanied by the assignment of tumor type.

The annotations were originally shared as XML files attached to the Lung-PET-CT-Dx collection. This dataset contains the earlier shared annotations harmonized into DICOM Structured Report representation. This dataset is available from the NCI Imaging Data Commons (IDC), and can be explored interactively in the IDC Portal using this link:  https://portal.imaging.datacommons.cancer.gov/explore/filters/?analysis_results_id=Lung-PET-CT-Dx-Annotations

The location of each tumor was annotated by five academic thoracic radiologists with expertise in lung cancer to make this dataset a useful tool and resource for developing algorithms for medical diagnosis.  Two of the radiologists had more than 15 years of experience and the others had more than 5 years of experience. After one of the radiologists labeled each subject the other four radiologists performed a verification, resulting in all five radiologists reviewing each annotation file in the dataset. Annotations were originally captured using Labellmg. 

Specific files included in the record can be downloaded using the attached manifests. The suffix of the manifest indicates its content, which is the list of pointers to the public Google Cloud Storage (GCS) or Amazon Web Services (AWS) buckets containing the files included in the collection:





-gcs.s5cmd: GCS-based manifest (to download the files described in the manifest, execute this command: pip install --upgrade idc-index && idc download manifest).




-aws.s5cmd: AWS-based manifest (to download the files described in the manifest, execute this command: pip install --upgrade idc-index && idc download manifest).




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



[1] Li, P., Wang, S., Li, T., Lu, J., HuangFu, Y., & Wang, D. (2020). A Large-Scale CT and PET/CT Dataset for Lung Cancer Diagnosis (Lung-PET-CT-Dx) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/TCIA.2020.NNC2-0461
DOI: 10.5281/zenodo.16989820
title: Lung-PET-CT-Dx-Annotations: Expert annotation of lung tumors for the Lung-PET-CT-Dx collection

description: This collection contains expert annotations of bounding boxes identifying locations of the tumor in the Lung-PET-CT-Dx collection [1] in the individual slices of the images. The annotations are accompanied by the assignment of tumor type.

The annotations were originally shared as XML files attached to the Lung-PET-CT-Dx collection. This dataset contains the earlier shared annotations harmonized into DICOM Structured Report representation. This dataset is available from the NCI Imaging Data Commons (IDC), and can be explored interactively in the IDC Portal using this link:  https://portal.imaging.datacommons.cancer.gov/explore/filters/?analysis_results_id=Lung-PET-CT-Dx-Annotations

The location of each tumor was annotated by five academic thoracic radiologists with expertise in lung cancer to make this dataset a useful tool and resource for developing algorithms for medical diagnosis.  Two of the radiologists had more than 15 years of experience and the others had more than 5 years of experience. After one of the radiologists labeled each subject the other four radiologists performed a verification, resulting in all five radiologists reviewing each annotation file in the dataset. Annotations were originally captured using Labellmg. 

Specific files included in the record can be downloaded using the attached manifests. The suffix of the manifest indicates its content, which is the list of pointers to the public Google Cloud Storage (GCS) or Amazon Web Services (AWS) buckets containing the files included in the collection:





-gcs.s5cmd: GCS-based manifest (to download the files described in the manifest, execute this command: pip install --upgrade idc-index && idc download manifest).




-aws.s5cmd: AWS-based manifest (to download the files described in the manifest, execute this command: pip install --upgrade idc-index && idc download manifest).




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



[1] Li, P., Wang, S., Li, T., Lu, J., HuangFu, Y., & Wang, D. (2020). A Large-Scale CT and PET/CT Dataset for Lung Cancer Diagnosis (Lung-PET-CT-Dx) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/TCIA.2020.NNC2-0461
DOI: 10.5281/zenodo.17675781
title: Valoración del taller
DOI: 10.5281/zenodo.17675782
title: Valoración del taller
DOI: 10.34740/kaggle/dsv/13821537
title: Market Prices of Commodities in South Tangerang
DOI: 10.15468/dl.qsdy7m
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Aeschnosoma louissiriusi",
 "DecimalLongitude is not null",
 "DecimalLatitude is not null"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002766-251120083545085/datasets/export for details.
DOI: 10.5281/zenodo.15643312
title: PROSTATEx-Targets: Point annotations of lesion targets for the PROSTATEx collection

description: This collection contains point annotations (targets) of the findings identified in the MRI images of the ProstateX collection [1]. The annotations include the point location of the target, assignment of the prostate region where the target is located, determination of whether the finding is clinically significant or not, and the assignment of the Gleason Grade Group (GGG) for biopsied tissue sampled at the clinically significant targets.

The annotations were originally shared as spreadsheets attached to the ProstateX collection. This dataset contains the earlier shared annotations harmonized into DICOM Structured Report representation. This dataset is available from the NCI Imaging Data Commons (IDC), and can be explored interactively in the IDC Portal using this link: https://portal.imaging.datacommons.cancer.gov/explore/filters/?analysis_results_id=ProstateX-Targets

Specific files included in the record can be downloaded using the attached manifests. The suffix of the manifest indicates its content, which is the list of pointers to the public Google Cloud Storage (GCS) or Amazon Web Services (AWS) buckets containing the files included in the collection:





-gcs.s5cmd: GCS-based manifest (to download the files described in the manifest, execute this command: pip install --upgrade idc-index && idc download manifest).




-aws.s5cmd: AWS-based manifest (to download the files described in the manifest, execute this command: pip install --upgrade idc-index && idc download manifest).




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



[1] Litjens, G., Debats, O., Barentsz, J., Karssemeijer, N., & Huisman, H. (2017). SPIE-AAPM PROSTATEx Challenge Data (Version 2) [dataset]. The Cancer Imaging Archive. https://doi.org/10.7937/K9TCIA.2017.MURS5CL
DOI: 10.5281/zenodo.15643313
title: PROSTATEx-Targets: Point annotations of lesion targets for the PROSTATEx collection

description: This collection contains point annotations (targets) of the findings identified in the MRI images of the ProstateX collection [1]. The annotations include the point location of the target, assignment of the prostate region where the target is located, determination of whether the finding is clinically significant or not, and the assignment of the Gleason Grade Group (GGG) for biopsied tissue sampled at the clinically significant targets.

The annotations were originally shared as spreadsheets attached to the ProstateX collection. This dataset contains the earlier shared annotations harmonized into DICOM Structured Report representation. This dataset is available from the NCI Imaging Data Commons (IDC), and can be explored interactively in the IDC Portal using this link: https://portal.imaging.datacommons.cancer.gov/explore/filters/?analysis_results_id=ProstateX-Targets

Specific files included in the record can be downloaded using the attached manifests. The suffix of the manifest indicates its content, which is the list of pointers to the public Google Cloud Storage (GCS) or Amazon Web Services (AWS) buckets containing the files included in the collection:





-gcs.s5cmd: GCS-based manifest (to download the files described in the manifest, execute this command: pip install --upgrade idc-index && idc download manifest).




-aws.s5cmd: AWS-based manifest (to download the files described in the manifest, execute this command: pip install --upgrade idc-index && idc download manifest).




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



[1] Litjens, G., Debats, O., Barentsz, J., Karssemeijer, N., & Huisman, H. (2017). SPIE-AAPM PROSTATEx Challenge Data (Version 2) [dataset]. The Cancer Imaging Archive. https://doi.org/10.7937/K9TCIA.2017.MURS5CL
DOI: 10.5281/zenodo.14277143
title: Above-canopy precipitation measurements at Hartheim Forest Research Site (DE-Har) from 2006-01-01 to 2006-12-31 [L2]

description: Quality controlled and gap-filled continuous precipitation measurements above the forest canopy at Hartheim Forest Research Site (ICOS Associate Ecosystem Site DE-Har, UFR Code: HARTHM, 7.59814ºE, 47.93391ºN, 201 m) measured using a heated ombrometer Model 5.4031 (Adolf Thies GmbH & Co. KG, Göttingen, Germany). The ombrometer is operated on a 18 m tower just above the top of the canopy.



Quality controlled above-canopy precipitation data are available and aggregated at 10min, 30min, hourly, daily, monthly and yearly resolution for the year 2006.

Precipitation sums are provided on hourly, daily, monthly and annual scales.

Number of hours with precipitation >0.1 mm/hr, >1 mm/hr, >2.5 mm/hr, >5 mm/hr, >10 mm/hr, >20 mm/hr, and > 50 mm/hr provided on daily, monthly, and annual scale.

Number of days with precipitation >0.1 mm/day, >1 mm/day, >2.5 mm/day, >5 mm/day, >10 mm/day, >20 mm/day and >50 mm/day provided on monthly, and annual scale.

Precipitation does not distinguish between form (e.g. snow vs. rain)

Detailed information on gap-filled data is provided.

Note: All times are provided in UTC, not local time.


For more details read `HARTHM_2006_Precipitation_MetaData.txt`.

Version 1.1.0



corrects for an error in the file "HARTHM_2006_Precipitation_10min_UTC.csv" where in the previous version (1.0.0) the time axis encountered an overflow after August 15. This did not affect other files at 30 min, hourly, daily, monthly and yearly resolutions. Version 1.1.0 also fixes a minor column labelling issue in the yearly file "HARTHM_2006_Precipitation_Yearly_UTC.csv".


Version 1.2.0



displays times according to ISO 8610 to unambiguously identify that all times are given in UTC. Further, the column headers for the time periods have been changed to "From" and "To" to indicate the start and end of the aggregation periods.
description: COPYRIGHT



Creative Commons Attribution 4.0 International. Copyright Albert-Ludwigs-Universität Freiburg, Professur für Umweltmeteorologie, Werthmannstrasse 10, Freiburg, Germany.


CREATOR

This work was created by the University of Freiburg, Germany.

ATTRIBUTION

The site is operated as part of the Integrated Carbon Observation System (ICOS).

Instruments and sensors in the dataset were operated by the Chair of Environmental Meteorology, University of Freiburg, Germany.

DISCLAIMER

The use of the work is at the user's own risk. The authors and/or the involved institutions, accept no liability for material or non-material damage arising from the use or non-use or from the use of incorrect or incomplete information in this work. The author and/or the involved institutions are not responsible for any use that may be made of the information in this work. The legal provisions remain unaffected.

MATERIAL NOTICE

The notices cover data in databases, text and images contained in the work.

MATERIAL URI

Hartheim Forest Research Site

DE-Har in the ICOS Carbon Portal
DOI: 10.5281/zenodo.17675791
title: Above-canopy precipitation measurements at Hartheim Forest Research Site (DE-Har) from 2006-01-01 to 2006-12-31 [L2]

description: Quality controlled and gap-filled continuous precipitation measurements above the forest canopy at Hartheim Forest Research Site (ICOS Associate Ecosystem Site DE-Har, UFR Code: HARTHM, 7.59814ºE, 47.93391ºN, 201 m) measured using a heated ombrometer Model 5.4031 (Adolf Thies GmbH & Co. KG, Göttingen, Germany). The ombrometer is operated on a 18 m tower just above the top of the canopy.



Quality controlled above-canopy precipitation data are available and aggregated at 10min, 30min, hourly, daily, monthly and yearly resolution for the year 2006.

Precipitation sums are provided on hourly, daily, monthly and annual scales.

Number of hours with precipitation >0.1 mm/hr, >1 mm/hr, >2.5 mm/hr, >5 mm/hr, >10 mm/hr, >20 mm/hr, and > 50 mm/hr provided on daily, monthly, and annual scale.

Number of days with precipitation >0.1 mm/day, >1 mm/day, >2.5 mm/day, >5 mm/day, >10 mm/day, >20 mm/day and >50 mm/day provided on monthly, and annual scale.

Precipitation does not distinguish between form (e.g. snow vs. rain)

Detailed information on gap-filled data is provided.

Note: All times are provided in UTC, not local time.


For more details read `HARTHM_2006_Precipitation_MetaData.txt`.

Version 1.1.0



corrects for an error in the file "HARTHM_2006_Precipitation_10min_UTC.csv" where in the previous version (1.0.0) the time axis encountered an overflow after August 15. This did not affect other files at 30 min, hourly, daily, monthly and yearly resolutions. Version 1.1.0 also fixes a minor column labelling issue in the yearly file "HARTHM_2006_Precipitation_Yearly_UTC.csv".


Version 1.2.0



displays times according to ISO 8610 to unambiguously identify that all times are given in UTC. Further, the column headers for the time periods have been changed to "From" and "To" to indicate the start and end of the aggregation periods.
description: COPYRIGHT



Creative Commons Attribution 4.0 International. Copyright Albert-Ludwigs-Universität Freiburg, Professur für Umweltmeteorologie, Werthmannstrasse 10, Freiburg, Germany.


CREATOR

This work was created by the University of Freiburg, Germany.

ATTRIBUTION

The site is operated as part of the Integrated Carbon Observation System (ICOS).

Instruments and sensors in the dataset were operated by the Chair of Environmental Meteorology, University of Freiburg, Germany.

DISCLAIMER

The use of the work is at the user's own risk. The authors and/or the involved institutions, accept no liability for material or non-material damage arising from the use or non-use or from the use of incorrect or incomplete information in this work. The author and/or the involved institutions are not responsible for any use that may be made of the information in this work. The legal provisions remain unaffected.

MATERIAL NOTICE

The notices cover data in databases, text and images contained in the work.

MATERIAL URI

Hartheim Forest Research Site

DE-Har in the ICOS Carbon Portal
DOI: 10.15468/dl.w29f8d
title: Occurrence Download

description: A dataset containing 152 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Colombia",
 {
 "and" : [
 "Country is Colombia",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 }
 ]
 },
 {
 "and" : [
 "StateProvince is one of (Cundinamarca, Boyacá)",
 "TaxonKey is one of (Eremophilus mutisii [GBIF Backbone Taxonomy])"
 ]
 }
 ]
}

 The dataset includes 152 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002769-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vdr5nj
title: Occurrence Download

description: A dataset containing 96055 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Mosquito Occurrence Dataset",
 "InstitutionCode is usnm",
 "Issue is Institution match fuzzy"
 ]
}

 The dataset includes 96055 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002759-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bj8dxy
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Amazoneura juruaensis",
 "DecimalLongitude is not null",
 "DecimalLatitude is not null"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002771-251120083545085/datasets/export for details.
DOI: 10.34740/kaggle/dsv/13821552
title: Booru.org Top Leaderboard
DOI: 10.15468/dl.phmgk6
title: Occurrence Download

description: A dataset containing 1388 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "Geometry POLYGON((-178.23610 2.19547,-66.51323 2.19547,-66.51323 46.92386,-178.23610 46.92386,-178.23610 2.19547))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Vitex mollis"
 ]
}

 The dataset includes 1388 records from 69 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002770-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5683/sp3/qwlxxm
title: Foot, Talocrural Joint, and Ankle-Foot Unified Deformable Power from Walking and Running

description: The dataset provides the experimental data presented in: "Reconciling how positive foot power drives the arch recoil mechanism" (in review). It includes power produced by the structures in the foot, talocrural joint, and ankle-foot during walking and running, calculated using the unified deformable power model. Additionally, it contains the "rotational" and "translational" components of the foot power, which is used in our paper to explain our results. Experimental collection included bone kinematics from biplanar videoradiography image sequences of the right foot time- and space- synced with ground reaction forces. It was collected in 2019 in the Skeletal Observation Lab at Queen's University.
DOI: 10.5683/sp3/hcx4tp
title: Simple Foot Model

description: The dataset provides the source code to run the simple foot model presented in: "Reconciling how positive foot power drives the arch recoil mechanism". It includes data for a single participant, a "main" driver script, and the three functions required to run the model. It is written in MATLAB.
DOI: 10.15468/dl.eg75fw
title: Occurrence Download

description: A dataset containing 1487 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Salamandrina perspicillata"
 ]
}

 The dataset includes 1487 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002772-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.