cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/cc9fblm
title: CCDC 280940: Experimental Crystal Structure Determination

description: Related Article: Jaeseung Kim, G.Hewitt, P.Carroll, S.McN.Sieburth|2005|J.Org.Chem.|70|5781|doi:10.1021/jo048121v
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc9fc35
title: CCDC 280956: Experimental Crystal Structure Determination

description: Related Article: Cai-Ming Liu, Yong-Hong Huang, De-Qing Zhang, Song Gao, Feng-Chi Jiang, Jian-Ying Zhang, Dao-Ben Zhu|2005|Cryst.Growth Des.|5|1531|doi:10.1021/cg050004l
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc9fc46
title: CCDC 280957: Experimental Crystal Structure Determination

description: Related Article: Cai-Ming Liu, Yong-Hong Huang, De-Qing Zhang, Song Gao, Feng-Chi Jiang, Jian-Ying Zhang, Dao-Ben Zhu|2005|Cryst.Growth Des.|5|1531|doi:10.1021/cg050004l
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15468/dl.qpgdpf
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038593-181108115102211/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sbqfpk
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038598-181108115102211/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fkbynl
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038620-181108115102211/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qny8ei
title: Occurrence Download

description: A dataset containing 955823502 species occurrences available in GBIF matching the query:
{
 "Year" : [
 "1951-2019"
 ]
}

 The dataset includes 955823502 records from 19483 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001187-190307172214381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hkknee
title: Occurrence Download

description: A dataset containing 678974 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "BasisOfRecord is Human Observation",
 "BasisOfRecord is Observation"
 ]
 },
 "Geometry POLYGON((-73.05695 -36.86466,-69.48553 -36.86466,-69.48553 -32.80344,-73.05695 -32.80344,-73.05695 -36.86466))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Aves",
 "Year 2018-2020"
 ]
}

 The dataset includes 678974 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0377201-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2tapiv
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000024-190415153152247/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.84fs8n
title: Occurrence Download

description: A dataset containing 735 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Psophia viridis Spix, 1825"
 ]
}

 The dataset includes 735 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0377217-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.omjyi3
title: Occurrence Download

description: A dataset containing 1346967215 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1346967215 records from 15345 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004538-171002173027117/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18680562
title: Face-shaped Human-Face Jade Form 09 (EANJ_FACE_09): Digital Visual Documentation (Low-Resolution Public Preview)

description: I. Scope and Purpose

This dataset documents a multi-view visual record of an East Asian prehistoric jade object featuring a human-face motif (EANJ_FACE_09). The object represents a single specimen within a systematic digital archiving project comprising multiple human-face–shaped artifacts and forms part of a continuously expanding data collection.

The purpose of this record is to provide independently verifiable baseline visual data through standardized image acquisition and organization, serving as an objective reference foundation for subsequent academic work.

Provided that researchers operate within clearly defined research questions and methodological frameworks, this dataset may be used to support cross-comparative morphological studies, teaching examples, and non-invasive re-analysis based on image-derived evidence.

Access Note:This record constitutes a low-resolution public preview (Public Preview). The high-resolution original image dataset (Record B), including RAW/TIFF files, has been published separately under restricted access. Qualified researchers may apply for access via the following DOI:https://doi.org/10.5281/zenodo.18679131

 

II. Academic Neutrality and Non-Interpretive Disclaimer

This dataset adheres to a principle of non-interpretive description, intended to ensure scientific neutrality and methodological transparency throughout the documentation process.

All textual descriptions and image annotations are strictly limited to directly observable phenomena and do not constitute, imply, or suggest any archaeological attribution, cultural identification, chronological assessment, or historical contextualization.

This record does not address, evaluate, or speculate on the object’s provenance, function, scholarly significance, or commercial value, nor does it represent any form of interpretive or conclusory statement.
DOI: 10.5281/zenodo.18680561
title: Face-shaped Human-Face Jade Form 09 (EANJ_FACE_09): Digital Visual Documentation (Low-Resolution Public Preview)

description: I. Scope and Purpose

This dataset documents a multi-view visual record of an East Asian prehistoric jade object featuring a human-face motif (EANJ_FACE_09). The object represents a single specimen within a systematic digital archiving project comprising multiple human-face–shaped artifacts and forms part of a continuously expanding data collection.

The purpose of this record is to provide independently verifiable baseline visual data through standardized image acquisition and organization, serving as an objective reference foundation for subsequent academic work.

Provided that researchers operate within clearly defined research questions and methodological frameworks, this dataset may be used to support cross-comparative morphological studies, teaching examples, and non-invasive re-analysis based on image-derived evidence.

Access Note:This record constitutes a low-resolution public preview (Public Preview). The high-resolution original image dataset (Record B), including RAW/TIFF files, has been published separately under restricted access. Qualified researchers may apply for access via the following DOI:https://doi.org/10.5281/zenodo.18679131

 

II. Academic Neutrality and Non-Interpretive Disclaimer

This dataset adheres to a principle of non-interpretive description, intended to ensure scientific neutrality and methodological transparency throughout the documentation process.

All textual descriptions and image annotations are strictly limited to directly observable phenomena and do not constitute, imply, or suggest any archaeological attribution, cultural identification, chronological assessment, or historical contextualization.

This record does not address, evaluate, or speculate on the object’s provenance, function, scholarly significance, or commercial value, nor does it represent any form of interpretive or conclusory statement.
DOI: 10.15468/dd.zg8yf3
title: Dataset generated from Esri tool

description: Derived dataset generated by Esri geoprocessing tool using GBIF API
DOI: 10.5281/zenodo.18680616
title: Dataset: Air Quality Dataset for Depok (2022-08-01 to 2026-02-18)

description: This dataset contains historical air quality time series for Depok covering 2022-08-01 to 2026-02-18. It includes key air pollution indicators such as AQI indices and major pollutants, plus city metadata including coordinates, administrative areas, and population. Use this dataset to analyze long-run air quality trends in Depok, compare Depok with other cities, and build models that link air quality to urban characteristics. Air quality values are retrieved from the Open-Meteo Air Quality service using the cams_global domain, and city metadata is derived from the GeoNames city list. Nitiraj Kulkarni
DOI: 10.5281/zenodo.18114231
title: BreastDCEDL: A Deep Learning–Ready Breast DCE-MRI Dataset

description: BreastDCEDL: A Dynamic Contrast-Enhanced Breast MRI Dataset

demo https://colab.research.google.com/github/naomifridman/BreastDCEDL/blob/main/BrestDCEDL_zenodo_demo.ipynb

BreastDCEDL is a curated, deep learning–ready dataset of 3D DCE-MRI scans from 2,070 breast cancer patients across three major clinical trials (I-SPY1, I-SPY2, Duke) available through The Cancer Imaging Archive (TCIA). The dataset includes pre-treatment MRI volumes, 3D tumor segmentations, and harmonized clinical and demographic metadata, including pathologic complete response (pCR), hormone receptor (HR), and HER2 status. This resource supports advanced AI research in breast cancer, enabling training and evaluation of transformer-based and other deep learning models.

2070 patients from TCIA clinical trials3D MRI scans · Tumor segmentations · Clinical metadataLabels: pCR, HR, HER2, age, race

Citation

@article{fridman2026breastdcedl,  author    = {Fridman, N. and Solway, B. and Fridman, T. and others},  title     = {BreastDCEDL: A standardized deep learning-ready breast DCE-MRI dataset of 2,070 patients},  journal   = {Scientific Data},  year      = {2026},  doi       = {10.1038/s41597-026-06589-6},  url       = {https://doi.org/10.1038/s41597-026-06589-6}}

Keywords: breast cancer, DCE-MRI, tumor segmentation, deep learning, clinical metadata, ViT, pCR prediction, pCR,HR,HER2,YCIA,ISPY1,DUKE,ISPY2

License Information

This dataset is released under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license. The source data were obtained from The Cancer Imaging Archive (TCIA) under the following licenses: I-SPY 1 (CC BY 3.0), I-SPY 2 (CC BY 4.0), and Duke Breast Cancer MRI (CC BY-NC 4.0). To comply with the most restrictive source license (Duke), this derivative dataset adopts the CC BY-NC 4.0 license. Users may share and adapt the data with appropriate attribution, but commercial use is not permitted. For commercial applications, users should contact the original data providers through TCIA.
DOI: 10.5281/zenodo.18680615
title: Dataset: Air Quality Dataset for Depok (2022-08-01 to 2026-02-18)

description: This dataset contains historical air quality time series for Depok covering 2022-08-01 to 2026-02-18. It includes key air pollution indicators such as AQI indices and major pollutants, plus city metadata including coordinates, administrative areas, and population. Use this dataset to analyze long-run air quality trends in Depok, compare Depok with other cities, and build models that link air quality to urban characteristics. Air quality values are retrieved from the Open-Meteo Air Quality service using the cams_global domain, and city metadata is derived from the GeoNames city list. Nitiraj Kulkarni
DOI: 10.5281/zenodo.15627232
title: BreastDCEDL: A Deep Learning–Ready Breast DCE-MRI Dataset

description: BreastDCEDL: A Dynamic Contrast-Enhanced Breast MRI Dataset

demo https://colab.research.google.com/github/naomifridman/BreastDCEDL/blob/main/BrestDCEDL_zenodo_demo.ipynb

BreastDCEDL is a curated, deep learning–ready dataset of 3D DCE-MRI scans from 2,070 breast cancer patients across three major clinical trials (I-SPY1, I-SPY2, Duke) available through The Cancer Imaging Archive (TCIA). The dataset includes pre-treatment MRI volumes, 3D tumor segmentations, and harmonized clinical and demographic metadata, including pathologic complete response (pCR), hormone receptor (HR), and HER2 status. This resource supports advanced AI research in breast cancer, enabling training and evaluation of transformer-based and other deep learning models.

2070 patients from TCIA clinical trials3D MRI scans · Tumor segmentations · Clinical metadataLabels: pCR, HR, HER2, age, race

Citation

@article{fridman2026breastdcedl,  author    = {Fridman, N. and Solway, B. and Fridman, T. and others},  title     = {BreastDCEDL: A standardized deep learning-ready breast DCE-MRI dataset of 2,070 patients},  journal   = {Scientific Data},  year      = {2026},  doi       = {10.1038/s41597-026-06589-6},  url       = {https://doi.org/10.1038/s41597-026-06589-6}}

Keywords: breast cancer, DCE-MRI, tumor segmentation, deep learning, clinical metadata, ViT, pCR prediction, pCR,HR,HER2,YCIA,ISPY1,DUKE,ISPY2

License Information

This dataset is released under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license. The source data were obtained from The Cancer Imaging Archive (TCIA) under the following licenses: I-SPY 1 (CC BY 3.0), I-SPY 2 (CC BY 4.0), and Duke Breast Cancer MRI (CC BY-NC 4.0). To comply with the most restrictive source license (Duke), this derivative dataset adopts the CC BY-NC 4.0 license. Users may share and adapt the data with appropriate attribution, but commercial use is not permitted. For commercial applications, users should contact the original data providers through TCIA.
DOI: 10.5281/zenodo.18680604
title: MODERN APPROACHES TO ENHANCING STUDENTS' PROFESSIONAL TRAINING IN DEVELOPING CHILDREN'S SOCIAL ADAPTATION SKILLS

description: This article explores modern methods for improving students’ professional training in fostering social adaptation skills in children. It discusses innovative pedagogical approaches, practical training, digital tools, and mentorship strategies that enhance future educators’ ability to support children’s social, emotional, and behavioral development. The study emphasizes effective practices for preparing students to guide children in developing social competence and successful interaction in early childhood settings.
DOI: 10.5281/zenodo.18680605
title: MODERN APPROACHES TO ENHANCING STUDENTS' PROFESSIONAL TRAINING IN DEVELOPING CHILDREN'S SOCIAL ADAPTATION SKILLS

description: This article explores modern methods for improving students’ professional training in fostering social adaptation skills in children. It discusses innovative pedagogical approaches, practical training, digital tools, and mentorship strategies that enhance future educators’ ability to support children’s social, emotional, and behavioral development. The study emphasizes effective practices for preparing students to guide children in developing social competence and successful interaction in early childhood settings.
DOI: 10.15468/dl.t7qmnu
title: Occurrence Download

description: A dataset containing 742 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Khaya ivorensis"
 ]
}

 The dataset includes 742 records from 64 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027100-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xugg2h
title: Occurrence Download

description: A dataset containing 17680 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "OccurrenceStatus is Present",
 "TaxonKey is Laminaria digitata",
 "Year 1950-2026"
 ]
}

 The dataset includes 17680 records from 177 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027101-260208012135463/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/14877959
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.5281/zenodo.18680634
title: Dataset: Air Quality Dataset for Paris (2013-01-01 to 2026-02-18)

description: This dataset contains historical air quality time series for Paris covering 2013-01-01 to 2026-02-18. It includes key air pollution indicators such as AQI indices and major pollutants, plus city metadata including coordinates, administrative areas, and population. Use this dataset to analyze long-run air quality trends in Paris, compare Paris with other cities, and build models that link air quality to urban characteristics. Air quality values are retrieved from the Open-Meteo Air Quality service using the cams_europe domain, and city metadata is derived from the GeoNames city list. Nitiraj Kulkarni
DOI: 10.5281/zenodo.18680635
title: Dataset: Air Quality Dataset for Paris (2013-01-01 to 2026-02-18)

description: This dataset contains historical air quality time series for Paris covering 2013-01-01 to 2026-02-18. It includes key air pollution indicators such as AQI indices and major pollutants, plus city metadata including coordinates, administrative areas, and population. Use this dataset to analyze long-run air quality trends in Paris, compare Paris with other cities, and build models that link air quality to urban characteristics. Air quality values are retrieved from the Open-Meteo Air Quality service using the cams_europe domain, and city metadata is derived from the GeoNames city list. Nitiraj Kulkarni
DOI: 10.5281/zenodo.18680647
title: Dataset: Air Quality Dataset for Coimbatore (2022-08-01 to 2026-02-18)

description: This dataset contains historical air quality time series for Coimbatore covering 2022-08-01 to 2026-02-18. It includes key air pollution indicators such as AQI indices and major pollutants, plus city metadata including coordinates, administrative areas, and population. Use this dataset to analyze long-run air quality trends in Coimbatore, compare Coimbatore with other cities, and build models that link air quality to urban characteristics. Air quality values are retrieved from the Open-Meteo Air Quality service using the cams_global domain, and city metadata is derived from the GeoNames city list. Nitiraj Kulkarni
DOI: 10.5281/zenodo.18680648
title: Dataset: Air Quality Dataset for Coimbatore (2022-08-01 to 2026-02-18)

description: This dataset contains historical air quality time series for Coimbatore covering 2022-08-01 to 2026-02-18. It includes key air pollution indicators such as AQI indices and major pollutants, plus city metadata including coordinates, administrative areas, and population. Use this dataset to analyze long-run air quality trends in Coimbatore, compare Coimbatore with other cities, and build models that link air quality to urban characteristics. Air quality values are retrieved from the Open-Meteo Air Quality service using the cams_global domain, and city metadata is derived from the GeoNames city list. Nitiraj Kulkarni
DOI: 10.15468/dl.v484mt
title: Occurrence Download

description: A dataset containing 367734 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is GUYASOILeDNA – Eukaryota 18S"
 ]
}

 The dataset includes 367734 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027084-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d7c6fv
title: Occurrence Download

description: A dataset containing 767275 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is GUYASOILeDNA - Bacteria 16S"
 ]
}

 The dataset includes 767275 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027085-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18679907
title: AXRPD Fcalc, NMR and UV-Vis data for ZSM-5

description: Calculated anomalous X-ray powder diffraction structure factors, CIF files, raw UV-Vis spectrum, and fitted MAS NMR data.
DOI: 10.5281/zenodo.18680661
title: Dataset: Air Quality Dataset for Gaziantep (2013-01-01 to 2026-02-18)

description: This dataset contains historical air quality time series for Gaziantep covering 2013-01-01 to 2026-02-18. It includes key air pollution indicators such as AQI indices and major pollutants, plus city metadata including coordinates, administrative areas, and population. Use this dataset to analyze long-run air quality trends in Gaziantep, compare Gaziantep with other cities, and build models that link air quality to urban characteristics. Air quality values are retrieved from the Open-Meteo Air Quality service using the cams_europe domain, and city metadata is derived from the GeoNames city list. Nitiraj Kulkarni
DOI: 10.5281/zenodo.18680662
title: Dataset: Air Quality Dataset for Gaziantep (2013-01-01 to 2026-02-18)

description: This dataset contains historical air quality time series for Gaziantep covering 2013-01-01 to 2026-02-18. It includes key air pollution indicators such as AQI indices and major pollutants, plus city metadata including coordinates, administrative areas, and population. Use this dataset to analyze long-run air quality trends in Gaziantep, compare Gaziantep with other cities, and build models that link air quality to urban characteristics. Air quality values are retrieved from the Open-Meteo Air Quality service using the cams_europe domain, and city metadata is derived from the GeoNames city list. Nitiraj Kulkarni