cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/rtjbzt5ps2.2
title: Learning Through Experience

description: Consider the establishment of a novel educational initiative focused on experiential landscapes, utilizing a choreographic methodology to convey emotion and solar energy. What experiences should inform the educational curriculum?
DOI: 10.17632/rfd4g9p8sc
title: Non-STEM_QA_English

description: The full corpus is curated across multiple STEM/Non-STEM disciplines and structured for use in LLM training, evaluation, and instruction tuning (SFT/RLHF). This sample represents the structure and quality of the larger dataset.

Dataset composition (full corpus):

Text corpus: 1.6B+ words of curated STEM and Non-STEM educational content across 22000+ textbooks in 7 languages(English, Hindi, Arabic, Bahasa, Tamil, Telegu, Kannada)
Question–Answer pairs: 6.5M+ high-quality Q&A pairs of STEM and Non-STEM in (English, Arabic, Hindi and Indic languages)
Video data: 100K+ hours of STEM Videos and 30K+ hours of UGC.
Audio data: 821K+ hours of Podcasts and Call Center data(Dual Channel)
Medical datasets: 30M+ files including clinical and diagnostic data like CT Scan, MRI, X-ray, Pathology, EHRs, USG Reports and Echo Reports.
This repository includes:

A small preview subset of the STEM English Q&A data
Flat, viewer-friendly schema for inspection
Parquet files suitable for benchmarking and evaluation
Purpose of this dataset:

Dataset preview and validation
Model evaluation and experimentation
Schema and format inspection before full-scale access
⚠️ Note: This repository contains sample data only. Access to the complete dataset is available separately under appropriate licensing or partnership terms. Note: This is not the full dataset.

For further details contact vipul.mishra@infobay.ai
DOI: 10.17632/rfd4g9p8sc.2
title: Non-STEM_QA_English

description: The full corpus is curated across multiple STEM/Non-STEM disciplines and structured for use in LLM training, evaluation, and instruction tuning (SFT/RLHF). This sample represents the structure and quality of the larger dataset.

Dataset composition (full corpus):

Text corpus: 1.6B+ words of curated STEM and Non-STEM educational content across 22000+ textbooks in 7 languages(English, Hindi, Arabic, Bahasa, Tamil, Telegu, Kannada)
Question–Answer pairs: 6.5M+ high-quality Q&A pairs of STEM and Non-STEM in (English, Arabic, Hindi and Indic languages)
Video data: 100K+ hours of STEM Videos and 30K+ hours of UGC.
Audio data: 821K+ hours of Podcasts and Call Center data(Dual Channel)
Medical datasets: 30M+ files including clinical and diagnostic data like CT Scan, MRI, X-ray, Pathology, EHRs, USG Reports and Echo Reports.
This repository includes:

A small preview subset of the STEM English Q&A data
Flat, viewer-friendly schema for inspection
Parquet files suitable for benchmarking and evaluation
Purpose of this dataset:

Dataset preview and validation
Model evaluation and experimentation
Schema and format inspection before full-scale access
⚠️ Note: This repository contains sample data only. Access to the complete dataset is available separately under appropriate licensing or partnership terms. Note: This is not the full dataset.

For further details contact vipul.mishra@infobay.ai
DOI: 10.17632/2jnjsby264
title: STEM_TextBook_Arabic

description: The full corpus is curated across multiple STEM/Non-STEM disciplines and structured for use in LLM training, evaluation, and instruction tuning (SFT/RLHF). This sample represents the structure and quality of the larger dataset.

Dataset composition (full corpus):

Text corpus: 1.6B+ words of curated STEM and Non-STEM educational content across 22000+ texbooks in 7 languages(English, Hindi, Arabic, Bahasa, Tamil, Telegu, Kannada)
Question–Answer pairs: 6.5M+ high-quality Q&A pairs of STEM and Non-STEM in (English, Arabic, Hindi and Indic languages)
Video data: 100K+ hours of STEM Videos and 30K+ hours of UGC.
Audio data: 821K+ hours of Podcasts and Call Center data(Dual Channel)
Medical datasets: 30M+ files including clinical and diagnostic data like CT Scan, MRI, X-ray, Pathology, EHRs, USG Reports and Echo Reports.
This repository includes:

A small preview subset of the STEM Arabic TextBook data
Flat, viewer-friendly schema for inspection
Parquet files suitable for benchmarking and evaluation
Purpose of this dataset:

Dataset preview and validation
Model evaluation and experimentation
Schema and format inspection before full-scale access
warning: Note: This repository contains sample data only. Access to the complete dataset is available separately under appropriate licensing or partnership terms. Note: This is not the full dataset.

For full details, Please contact [Em: vipul.mishra@infobay.ai]
DOI: 10.17632/2jnjsby264.1
title: STEM_TextBook_Arabic

description: The full corpus is curated across multiple STEM/Non-STEM disciplines and structured for use in LLM training, evaluation, and instruction tuning (SFT/RLHF). This sample represents the structure and quality of the larger dataset.

Dataset composition (full corpus):

Text corpus: 1.6B+ words of curated STEM and Non-STEM educational content across 22000+ texbooks in 7 languages(English, Hindi, Arabic, Bahasa, Tamil, Telegu, Kannada)
Question–Answer pairs: 6.5M+ high-quality Q&A pairs of STEM and Non-STEM in (English, Arabic, Hindi and Indic languages)
Video data: 100K+ hours of STEM Videos and 30K+ hours of UGC.
Audio data: 821K+ hours of Podcasts and Call Center data(Dual Channel)
Medical datasets: 30M+ files including clinical and diagnostic data like CT Scan, MRI, X-ray, Pathology, EHRs, USG Reports and Echo Reports.
This repository includes:

A small preview subset of the STEM Arabic TextBook data
Flat, viewer-friendly schema for inspection
Parquet files suitable for benchmarking and evaluation
Purpose of this dataset:

Dataset preview and validation
Model evaluation and experimentation
Schema and format inspection before full-scale access
warning: Note: This repository contains sample data only. Access to the complete dataset is available separately under appropriate licensing or partnership terms. Note: This is not the full dataset.

For full details, Please contact [Em: vipul.mishra@infobay.ai]
DOI: 10.15468/dl.ws9ru7
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_2_GID","value":"IND.26.25_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009470-260108223611665/datasets/export for details.
DOI: 10.17632/mvwm8mvj7s
title: STEM_TextBook_Bahasa

description: The full corpus is curated across multiple STEM/Non-STEM disciplines and structured for use in LLM training, evaluation, and instruction tuning (SFT/RLHF). This sample represents the structure and quality of the larger dataset.

Dataset composition (full corpus):

Text corpus: 1.6B+ words of curated STEM and Non-STEM educational content across 22000+ texbooks in 7 languages(English, Hindi, Arabic, Bahasa, Tamil, Telegu, Kannada)
Question–Answer pairs: 6.5M+ high-quality Q&A pairs of STEM and Non-STEM in (English, Arabic, Hindi and Indic languages)
Video data: 100K+ hours of STEM Videos and 30K+ hours of UGC.
Audio data: 821K+ hours of Podcasts and Call Center data(Dual Channel)
Medical datasets: 30M+ files including clinical and diagnostic data like CT Scan, MRI, X-ray, Pathology, EHRs, USG Reports and Echo Reports.
This repository includes:

A small preview subset of the STEM Textbook Bahasa data
Flat, viewer-friendly schema for inspection
Parquet files suitable for benchmarking and evaluation
Purpose of this dataset:

Dataset preview and validation
Model evaluation and experimentation
Schema and format inspection before full-scale access
⚠️ Note: This repository contains sample data only. Access to the complete dataset is available separately under appropriate licensing or partnership terms. Note: This is not the full dataset.

For further details, Please connect [Em: vipul.mishra@infobay.ai ph: 8303174762]
DOI: 10.17632/mvwm8mvj7s.1
title: STEM_TextBook_Bahasa

description: The full corpus is curated across multiple STEM/Non-STEM disciplines and structured for use in LLM training, evaluation, and instruction tuning (SFT/RLHF). This sample represents the structure and quality of the larger dataset.

Dataset composition (full corpus):

Text corpus: 1.6B+ words of curated STEM and Non-STEM educational content across 22000+ texbooks in 7 languages(English, Hindi, Arabic, Bahasa, Tamil, Telegu, Kannada)
Question–Answer pairs: 6.5M+ high-quality Q&A pairs of STEM and Non-STEM in (English, Arabic, Hindi and Indic languages)
Video data: 100K+ hours of STEM Videos and 30K+ hours of UGC.
Audio data: 821K+ hours of Podcasts and Call Center data(Dual Channel)
Medical datasets: 30M+ files including clinical and diagnostic data like CT Scan, MRI, X-ray, Pathology, EHRs, USG Reports and Echo Reports.
This repository includes:

A small preview subset of the STEM Textbook Bahasa data
Flat, viewer-friendly schema for inspection
Parquet files suitable for benchmarking and evaluation
Purpose of this dataset:

Dataset preview and validation
Model evaluation and experimentation
Schema and format inspection before full-scale access
⚠️ Note: This repository contains sample data only. Access to the complete dataset is available separately under appropriate licensing or partnership terms. Note: This is not the full dataset.

For further details, Please connect [Em: vipul.mishra@infobay.ai ph: 8303174762]
DOI: 10.34740/kaggle/dsv/14499053
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.17632/8c9x9pjw7s
title: Mapping scholarly publishing on school leaders’ digital competence: A bibliometric analysis of Scopus data, 2006–2025

description: This study aimed to analyse research output on school leaders’ digital competence published between 2006 and 2025, with a focus on publication trends, citation impact, thematic clusters, and international collaboration patterns.
DOI: 10.17632/8c9x9pjw7s.1
title: Mapping scholarly publishing on school leaders’ digital competence: A bibliometric analysis of Scopus data, 2006–2025

description: This study aimed to analyse research output on school leaders’ digital competence published between 2006 and 2025, with a focus on publication trends, citation impact, thematic clusters, and international collaboration patterns.
DOI: 10.17632/gh3fxmvz27
title: a unified critical state μ(I) elastoplastic damage constitutive model

description: This data demonstrates the integration of critical-state elastoplasticity, rate-dependent μ(I) rheology, and cohesive damage laws driven by plastic strain into a unified constitutive model for studying the dynamic flow states of avalanches. The model is implemented in MPM to capture large deformations and evolving free surfaces. First, the model's performance is validated by comparisons with analytical solutions of stable homogeneous particle flows on inclined planes and baseline experimental results of particle column collapse. The data also includes idealized avalanche benchmark cases, reproducing cold-dense, warm-shear, warm-plug, and sliding-slab avalanche modes. It also shows how different damage evolution paths control the transition from sliding-plate avalanches to cold-dense or warm-shear avalanches. The included data provide ample evidence for the unified constitutive model's simulation of avalanches.
DOI: 10.17632/gh3fxmvz27.1
title: a unified critical state μ(I) elastoplastic damage constitutive model

description: This data demonstrates the integration of critical-state elastoplasticity, rate-dependent μ(I) rheology, and cohesive damage laws driven by plastic strain into a unified constitutive model for studying the dynamic flow states of avalanches. The model is implemented in MPM to capture large deformations and evolving free surfaces. First, the model's performance is validated by comparisons with analytical solutions of stable homogeneous particle flows on inclined planes and baseline experimental results of particle column collapse. The data also includes idealized avalanche benchmark cases, reproducing cold-dense, warm-shear, warm-plug, and sliding-slab avalanche modes. It also shows how different damage evolution paths control the transition from sliding-plate avalanches to cold-dense or warm-shear avalanches. The included data provide ample evidence for the unified constitutive model's simulation of avalanches.
DOI: 10.17632/gt529sf5jy
title: Non-STEM_TextBook_English

description: The full corpus is curated across multiple STEM/Non-STEM disciplines and structured for use in LLM training, evaluation, and instruction tuning (SFT/RLHF). This sample represents the structure and quality of the larger dataset.

Dataset composition (full corpus):

Text corpus: 1.6B+ words of curated STEM and Non-STEM educational content across 22000+ texbooks in 7 languages(English, Hindi, Arabic, Bahasa, Tamil, Telegu, Kannada)
Question–Answer pairs: 6.5M+ high-quality Q&A pairs of STEM and Non-STEM in (English, Arabic, Hindi and Indic languages)
Video data: 100K+ hours of STEM Videos and 30K+ hours of UGC.
Audio data: 821K+ hours of Podcasts and Call Center data(Dual Channel)
Medical datasets: 30M+ files including clinical and diagnostic data like CT Scan, MRI, X-ray, Pathology, EHRs, USG Reports and Echo Reports.
This repository includes:

A small preview subset of the Non-STEM English Textbooks data
Flat, viewer-friendly schema for inspection
Parquet files suitable for benchmarking and evaluation
Purpose of this dataset:

Dataset preview and validation
Model evaluation and experimentation
Schema and format inspection before full-scale access
warning: Note: This repository contains sample data only. Access to the complete dataset is available separately under appropriate licensing or partnership terms. Note: This is not the full dataset.

For full details, Please contact [Em: vipul.mishra@infobay.ai]
DOI: 10.17632/gt529sf5jy.1
title: Non-STEM_TextBook_English

description: The full corpus is curated across multiple STEM/Non-STEM disciplines and structured for use in LLM training, evaluation, and instruction tuning (SFT/RLHF). This sample represents the structure and quality of the larger dataset.

Dataset composition (full corpus):

Text corpus: 1.6B+ words of curated STEM and Non-STEM educational content across 22000+ texbooks in 7 languages(English, Hindi, Arabic, Bahasa, Tamil, Telegu, Kannada)
Question–Answer pairs: 6.5M+ high-quality Q&A pairs of STEM and Non-STEM in (English, Arabic, Hindi and Indic languages)
Video data: 100K+ hours of STEM Videos and 30K+ hours of UGC.
Audio data: 821K+ hours of Podcasts and Call Center data(Dual Channel)
Medical datasets: 30M+ files including clinical and diagnostic data like CT Scan, MRI, X-ray, Pathology, EHRs, USG Reports and Echo Reports.
This repository includes:

A small preview subset of the Non-STEM English Textbooks data
Flat, viewer-friendly schema for inspection
Parquet files suitable for benchmarking and evaluation
Purpose of this dataset:

Dataset preview and validation
Model evaluation and experimentation
Schema and format inspection before full-scale access
warning: Note: This repository contains sample data only. Access to the complete dataset is available separately under appropriate licensing or partnership terms. Note: This is not the full dataset.

For full details, Please contact [Em: vipul.mishra@infobay.ai]
DOI: 10.17632/97b62wn98x
title: Raw data for HS-GC-IMS volatiles in thawed large yellow croaker under different thawing methods

description: This dataset supports the manuscript entitled “High-voltage electrostatic field thawing stabilizes water immobilization and preserves ventral-skin golden appearance in frozen large yellow croaker (Larimichthys crocea)”. It contains the semi-quantitative HS-GC-IMS results for 38 identified volatile compounds across the five thawing treatments (RT, WB, UAT, MW, and HVEF), reported as mean ± SEM. Compounds not detected are labeled as ND and were excluded from significance lettering, with statistical comparisons performed among detected groups only. The values in this dataset correspond directly to the volatile data presented in Table 3 of the main text and Table S1 in the Supplementary Material.
DOI: 10.5281/zenodo.18247713
title: Baccharis pseudotenuifolia Malag. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:42
DOI: 10.17632/97b62wn98x.1
title: Raw data for HS-GC-IMS volatiles in thawed large yellow croaker under different thawing methods

description: This dataset supports the manuscript entitled “High-voltage electrostatic field thawing stabilizes water immobilization and preserves ventral-skin golden appearance in frozen large yellow croaker (Larimichthys crocea)”. It contains the semi-quantitative HS-GC-IMS results for 38 identified volatile compounds across the five thawing treatments (RT, WB, UAT, MW, and HVEF), reported as mean ± SEM. Compounds not detected are labeled as ND and were excluded from significance lettering, with statistical comparisons performed among detected groups only. The values in this dataset correspond directly to the volatile data presented in Table 3 of the main text and Table S1 in the Supplementary Material.
DOI: 10.5281/zenodo.18247712
title: Baccharis pseudotenuifolia Malag. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:42
DOI: 10.15468/dl.mgx6dn
title: Occurrence Download

description: A dataset containing 1371 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_2_GID","value":"USA.34.92_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 1371 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009471-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/7s74hc57d2
title: Non-STEM_TextBook_Arabic

description: The full corpus is curated across multiple STEM/Non-STEM disciplines and structured for use in LLM training, evaluation, and instruction tuning (SFT/RLHF). This sample represents the structure and quality of the larger dataset.

Dataset composition (full corpus):

Text corpus: 1.6B+ words of curated STEM and Non-STEM educational content across 22000+ texbooks in 7 languages(English, Hindi, Arabic, Bahasa, Tamil, Telegu, Kannada)
Question–Answer pairs: 6.5M+ high-quality Q&A pairs of STEM and Non-STEM in (English, Arabic, Hindi and Indic languages)
Video data: 100K+ hours of STEM Videos and 30K+ hours of UGC.
Audio data: 821K+ hours of Podcasts and Call Center data(Dual Channel)
Medical datasets: 30M+ files including clinical and diagnostic data like CT Scan, MRI, X-ray, Pathology, EHRs, USG Reports and Echo Reports.
This repository includes:

A small preview subset of the Non-STEM Arabic TextBook data
Flat, viewer-friendly schema for inspection
Parquet files suitable for benchmarking and evaluation
Purpose of this dataset:

Dataset preview and validation
Model evaluation and experimentation
Schema and format inspection before full-scale access
warning: Note: This repository contains sample data only. Access to the complete dataset is available separately under appropriate licensing or partnership terms. Note: This is not the full dataset.

For full details, Please contact [Em: vipul.mishra@infobay.ai]
DOI: 10.17632/7s74hc57d2.1
title: Non-STEM_TextBook_Arabic

description: The full corpus is curated across multiple STEM/Non-STEM disciplines and structured for use in LLM training, evaluation, and instruction tuning (SFT/RLHF). This sample represents the structure and quality of the larger dataset.

Dataset composition (full corpus):

Text corpus: 1.6B+ words of curated STEM and Non-STEM educational content across 22000+ texbooks in 7 languages(English, Hindi, Arabic, Bahasa, Tamil, Telegu, Kannada)
Question–Answer pairs: 6.5M+ high-quality Q&A pairs of STEM and Non-STEM in (English, Arabic, Hindi and Indic languages)
Video data: 100K+ hours of STEM Videos and 30K+ hours of UGC.
Audio data: 821K+ hours of Podcasts and Call Center data(Dual Channel)
Medical datasets: 30M+ files including clinical and diagnostic data like CT Scan, MRI, X-ray, Pathology, EHRs, USG Reports and Echo Reports.
This repository includes:

A small preview subset of the Non-STEM Arabic TextBook data
Flat, viewer-friendly schema for inspection
Parquet files suitable for benchmarking and evaluation
Purpose of this dataset:

Dataset preview and validation
Model evaluation and experimentation
Schema and format inspection before full-scale access
warning: Note: This repository contains sample data only. Access to the complete dataset is available separately under appropriate licensing or partnership terms. Note: This is not the full dataset.

For full details, Please contact [Em: vipul.mishra@infobay.ai]
DOI: 10.17632/24dxycb9gm
title: Non-STEM_TextBook_Bahasa

description: The full corpus is curated across multiple STEM/Non-STEM disciplines and structured for use in LLM training, evaluation, and instruction tuning (SFT/RLHF). This sample represents the structure and quality of the larger dataset.

Dataset composition (full corpus):

Text corpus: 1.6B+ words of curated STEM and Non-STEM educational content across 22000+ texbooks in 7 languages(English, Hindi, Arabic, Bahasa, Tamil, Telegu, Kannada)
Question–Answer pairs: 6.5M+ high-quality Q&A pairs of STEM and Non-STEM in (English, Arabic, Hindi and Indic languages)
Video data: 100K+ hours of STEM Videos and 30K+ hours of UGC.
Audio data: 821K+ hours of Podcasts and Call Center data(Dual Channel)
Medical datasets: 30M+ files including clinical and diagnostic data like CT Scan, MRI, X-ray, Pathology, EHRs, USG Reports and Echo Reports.
This repository includes:

A small preview subset of the Non-STEM Bahasa Textbook data
Flat, viewer-friendly schema for inspection
Parquet files suitable for benchmarking and evaluation
Purpose of this dataset:

Dataset preview and validation
Model evaluation and experimentation
Schema and format inspection before full-scale access
warning: Note: This repository contains sample data only. Access to the complete dataset is available separately under appropriate licensing or partnership terms. Note: This is not the full dataset.

For full details, Please contact [Em: vipul.mishra@infobay.ai]