cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0009073.10fu
title: SH0009073.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0009074.10fu
title: SH0009074.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.5281/zenodo.18152397
title: FoldLink-N — Topology-State Placement für GPU-Cluster

description: FoldLink-N ist ein software-only Prototype für topology-state placement auf GPU-Clustern. Das Tool ingestiert einen neutralen Rank-Kommunikations-Eventstream (JSON), leitet Rank-Communities (“Tiles”) via gewichteter Graph-Partitionierung ab und mappt Ranks auf physische GPU-Slots mittels eines Topologie-Distanzmodells. Output ist ein Placement-Plan (rank→slot) und Objective-Vergleiche gegen Baselines mittels Σ(bytes_ij × distance(slot_i, slot_j)). Optional ist ein alpha/beta-artiger Time-Proxy (Latenz + effektive Bandbreite) für relative Vergleiche enthalten. Das Repository enthält CLI, Notebooks, Beispieldaten sowie einen konfigurierbaren Cost-Model-Simulator für Scaling Sweeps.
DOI: 10.5281/zenodo.18152396
title: FoldLink-N — Topology-State Placement für GPU-Cluster

description: FoldLink-N ist ein software-only Prototype für topology-state placement auf GPU-Clustern. Das Tool ingestiert einen neutralen Rank-Kommunikations-Eventstream (JSON), leitet Rank-Communities (“Tiles”) via gewichteter Graph-Partitionierung ab und mappt Ranks auf physische GPU-Slots mittels eines Topologie-Distanzmodells. Output ist ein Placement-Plan (rank→slot) und Objective-Vergleiche gegen Baselines mittels Σ(bytes_ij × distance(slot_i, slot_j)). Optional ist ein alpha/beta-artiger Time-Proxy (Latenz + effektive Bandbreite) für relative Vergleiche enthalten. Das Repository enthält CLI, Notebooks, Beispieldaten sowie einen konfigurierbaren Cost-Model-Simulator für Scaling Sweeps.
DOI: 10.5281/zenodo.18151276
title: Bulk RNA-Seq Teaching P. berghei

description: This is a dataset that we use for a transcriptomics workshop. The species is Plasmodium berghei, a rodent malaria. A gene of known function was knocked out and the exercise is to define the function of that gene.
DOI: 10.5281/zenodo.18151277
title: Bulk RNA-Seq Teaching P. berghei

description: This is a dataset that we use for a transcriptomics workshop. The species is Plasmodium berghei, a rodent malaria. A gene of known function was knocked out and the exercise is to define the function of that gene.
DOI: 10.5281/zenodo.18152235
title: Non-STEM_TextBook_English

description: The full corpus is curated across multiple 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 22,000+ textbooks in 7 languages (English, Hindi, Arabic, Bahasa, Tamil, Telugu, Kannada)




Question–Answer pairs: 6.5M+ high-quality Q&A pairs of STEM and Non-STEM content 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 dual-channel call center data




Medical datasets: 30M+ files including clinical and diagnostic data such as CT scans, MRI, X-ray, pathology, EHRs, USG reports, and echo reports



This repository includes:





A small preview subset of the Non-STEM English 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



Note: This repository contains sample data only. Access to the complete dataset is available separately under appropriate licensing or partnership terms.For detailed information and domain-specific requirements, please reach out to vipul.mishra@infobay.ai
DOI: 10.5281/zenodo.18152234
title: Non-STEM_TextBook_English

description: The full corpus is curated across multiple 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 22,000+ textbooks in 7 languages (English, Hindi, Arabic, Bahasa, Tamil, Telugu, Kannada)




Question–Answer pairs: 6.5M+ high-quality Q&A pairs of STEM and Non-STEM content 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 dual-channel call center data




Medical datasets: 30M+ files including clinical and diagnostic data such as CT scans, MRI, X-ray, pathology, EHRs, USG reports, and echo reports



This repository includes:





A small preview subset of the Non-STEM English 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



Note: This repository contains sample data only. Access to the complete dataset is available separately under appropriate licensing or partnership terms.For detailed information and domain-specific requirements, please reach out to vipul.mishra@infobay.ai
DOI: 10.15156/bio/sh0009075.10fu
title: SH0009075.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0009076.10fu
title: SH0009076.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0009077.10fu
title: SH0009077.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0009078.10fu
title: SH0009078.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.eem4kg
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.28_1",
 "TaxonKey is Glycyrrhiza pallidiflora"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074546-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18710/gvuzwi
title: Replication Data for: A multivariate account of particle alternation after bare-form try in native varieties of English

description: &lt;b&gt;[Dataset abstract]&lt;/b&gt; This is the data and code from a multifactorial study reviewing the determinants of particle alternation after uninflected try in native varieties of English. The effects of a number of previously discussed and novel predictors (see Section 3.1 of the paper) are probed in data from well-known corpora (ICE, GloWbE, BNC and COCA). The paper is published in English Language and Linguistics (https://www.doi.org/10.1017/S1360674321000393). I used R (R Core Team 2021) for all data analyses, hence the code can best be replicated in R.
description: &lt;b&gt;[Article abstract]&lt;/b&gt; This multifactorial study reviews the determinants of particle alternation after uninflected try in varieties where English is native. The effects of a number of previously discussed and novel predictors are probed in data from well-known corpora. The results confirm the inclinations of North American varieties (try to) in contrast with those of the Australasian, British and Irish varieties (try and in speech but try to in writing). The previously reported general effects of the tense of try, mode and horror aequi are also corroborated. As regards the effect of register, the study contributes the finding that following Latin-based infinitives favor try to in most varieties, especially in writing. The paper discusses the status of the substantiated effects with respect to the notions of conventionalization and entrenchment: crucially, the higher degree of conventionalization of try to in North American varieties (a) makes the use of this variant less conditional on the sequential need to license euphony and (b) neutralizes the general contextual/register distinction for the alternation. From a usage-based viewpoint, the findings suggest that the higher frequency of a multiword sequence in a specific variety, and the higher degree of activation in the language users’ minds, can make it less contingent on general probabilistic constraints.
description: R studio, 1.2.1335
description: R, 4.0.3
description: brms: Bayesian Regression Models using 'Stan', 2.16.1
DOI: 10.18710/gvuzwi/so8mbv
title: ice.csv

description: Analyzed corpus data extracted from five ICE components (Australia, Canada, Great Britain, Ireland and New Zealand)
DOI: 10.18710/gvuzwi/5doj9i
title: bnc.csv

description: Analyzed corpus data extracted from BNC
DOI: 10.18710/gvuzwi/xhtar8
title: coca.csv

description: Analyzed corpus data extracted from COCA
DOI: 10.18710/gvuzwi/fuklx6
title: glowbe.csv

description: Analyzed corpus data extracted from six sections of GloWbE (Australia, Canada, Great Britain, Ireland, New Zealand and United States)
DOI: 10.18710/gvuzwi/tgpbxr
title: COCA_Note_on_Copyright.pdf
DOI: 10.18710/gvuzwi/0tgzvq
title: ICE-NZ_License_Agreement.pdf
DOI: 10.18710/gvuzwi/5ketma
title: ICE_License_Agreement.pdf
DOI: 10.18710/gvuzwi/vor6sr
title: ICE-GB_License_Agreement.pdf
DOI: 10.18710/gvuzwi/efzmsp
title: tryandto_data.RData

description: R data frames for ICE, GloWbE, BNC and COCA data
DOI: 10.18710/gvuzwi/kksn84
title: BNC_End_User_Licence.pdf
DOI: 10.18710/gvuzwi/fsawvj
title: tryandto_bnc-model.R

description: Bayesian mixed-effects logistic regression model for 'construction' (try to vs. try and) in BNC dataset, and visualizations of the results
DOI: 10.18710/gvuzwi/trlrrx
title: tryandto_coca-model.R

description: Bayesian mixed-effects logistic regression model for 'construction' (try to vs. try and) in COCA dataset, and visualizations of the results
DOI: 10.18710/gvuzwi/bllrmg
title: tryandto_glowbe-model.R

description: Bayesian mixed-effects logistic regression model for 'construction' (try to vs. try and) in GloWbE dataset, and visualizations of the results
DOI: 10.18710/gvuzwi/a3ga9t
title: tryandto_ice-model.R

description: Bayesian mixed-effects logistic regression model for 'construction' (try to vs. try and) in ICE dataset, and visualizations of the results
DOI: 10.18710/gvuzwi/koewxh
title: 00_ReadMe_tryandto.txt

description: Description of the dataset
DOI: 10.15156/bio/sh0009079.10fu
title: SH0009079.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0009080.10fu
title: SH0009080.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.5281/zenodo.18099815
title: Data from Skills2Capabilities WP3 Interviews in Italy

description: This dataset includes the summaries of semi-structured expert interviews of Skills2Capabilities WP3 on the responsiveness and proactiveness of VET systems in Italy.
DOI: 10.5281/zenodo.18099814
title: Data from Skills2Capabilities WP3 Interviews in Italy

description: This dataset includes the summaries of semi-structured expert interviews of Skills2Capabilities WP3 on the responsiveness and proactiveness of VET systems in Italy.
DOI: 10.5281/zenodo.18109621
title: Data from Skills2Capabilities WP6 Interviews in Italy

description: This dataset includes the summaries of semi-structured expert interviews of Skills2Capabilities WP6 on work-based learning in Italy.
DOI: 10.5281/zenodo.18109620
title: Data from Skills2Capabilities WP6 Interviews in Italy

description: This dataset includes the summaries of semi-structured expert interviews of Skills2Capabilities WP6 on work-based learning in Italy.
DOI: 10.4121/1a649ecf-3165-47a9-b794-3f02ff42cc80
title: Data underlying the publication "Determining the Reverse Bias Breakdown Voltage of Perovskite Solar Cells".

description: In the corresponding publication, the methodology of determining and describing the reverse bias breakdown voltage of perovskite solar cells is described. This data collection contains additional data that was not required in this much detail in the main text. This includes the results of RB-JV measurements of a whole batch of solar cells that is treated in the main text, the three RB-JV curves used as examples, the Matlab scripts to extract breakdown voltages from raw data, and the detailed overview of measurement parameters and conditions found in literature.
DOI: 10.4121/1a649ecf-3165-47a9-b794-3f02ff42cc80.v1
title: Data underlying the publication "Determining the Reverse Bias Breakdown Voltage of Perovskite Solar Cells".

description: In the corresponding publication, the methodology of determining and describing the reverse bias breakdown voltage of perovskite solar cells is described. This data collection contains additional data that was not required in this much detail in the main text. This includes the results of RB-JV measurements of a whole batch of solar cells that is treated in the main text, the three RB-JV curves used as examples, the Matlab scripts to extract breakdown voltages from raw data, and the detailed overview of measurement parameters and conditions found in literature.
DOI: 10.15156/bio/sh0009081.10fu
title: SH0009081.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0009082.10fu
title: SH0009082.10FU

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