cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.23642/usn.13078898/xrtrkx
title: Data_Dry weight.csv

description: Data_Dry weight.csv
DOI: 10.23642/usn.13078898/erop0l
title: Data_Fatty acid production.csv

description: Data_Fatty acid production.csv
DOI: 10.23642/usn.13078898/ktolji
title: Data_Freshwater green microalgae of inland waters in southern Norway.xlsx

description: Data_Freshwater green microalgae of inland waters in southern Norway.xlsx
DOI: 10.23642/usn.13078898/fdev8l
title: Data_Optical density and growth rate.csv

description: Data_Optical density and growth rate.csv
DOI: 10.23642/usn.13078898/tokcl3
title: Desmodesmus alignment.meg

description: Desmodesmus alignment.meg
DOI: 10.23642/usn.13078898/urvzst
title: Desmodesmus elegans B1.jpg

description: Desmodesmus elegans B1.jpg
DOI: 10.23642/usn.13078898/pwd5ia
title: Desmudesmus elegans A12.jpg

description: Desmudesmus elegans A12.jpg
DOI: 10.23642/usn.13078898/usarnf
title: Desmodesmus sp. A2.jpg

description: Desmodesmus sp. A2.jpg
DOI: 10.23642/usn.13078898/0jhro0
title: Kirchneriella obesa E7.jpg

description: Kirchneriella obesa E7.jpg
DOI: 10.23642/usn.13078898/v93izj
title: Lobochlamys segnis F12.jpg

description: Lobochlamys segnis F12.jpg
DOI: 10.23642/usn.13078898/obbylv
title: Readme.txt

description: Readme.txt
DOI: 10.23642/usn.13078898/zyhetv
title: Selenastraceae alignment.meg

description: Selenastraceae alignment.meg
DOI: 10.23642/usn.13078898/tua8oa
title: Tetradesmus algnment.meg

description: Tetradesmus algnment.meg
DOI: 10.23642/usn.13078898/ftsxth
title: Tetradesmus obliquus D1.jpg

description: Tetradesmus obliquus D1.jpg
DOI: 10.23642/usn.13078898/tk9cga
title: Tetradesmus obliquus A5.jpg

description: Tetradesmus obliquus A5.jpg
DOI: 10.23642/usn.13078898/rsur5t
title: Tetradesmus obliquus H1.jpg

description: Tetradesmus obliquus H1.jpg
DOI: 10.23642/usn.13078898/zfzxus
title: Tetradesmus wisconsinensis A1.jpg

description: Tetradesmus wisconsinensis A1.jpg
DOI: 10.15468/dl.ppuqqh
title: Occurrence Download

description: A dataset containing 417 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Aneides iecanus"
 ]
}

 The dataset includes 417 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063009-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18018680
title: SIRKULYAR IQTISODIYOTDA TEKSTIL KORXONALARIDA CHIQINDILARNI QAYTA ISHLASH
DOI: 10.5281/zenodo.18018679
title: SIRKULYAR IQTISODIYOTDA TEKSTIL KORXONALARIDA CHIQINDILARNI QAYTA ISHLASH
DOI: 10.5281/zenodo.7084148
title: TriosCompass Test Dataset

description: Here is a drafted description for the dataset to be uploaded to Zenodo.

 

TriosCompass Workflow Test Dataset

 

This dataset provides a complete test case for the TriosCompass workflow, a powerful tool designed for human whole-genome sequencing (WGS) analysis. The dataset is optimized for a quick and comprehensive test run, ensuring the workflow is set up correctly and produces the expected results.

 

Dataset Contents

 

The TriosCompass_test_case.zip archive includes all necessary components to run the test case. Below is a description of the directory structure and files:





bam/: Mini-BAM files extracted from the GIAB 40X dataset, covering the genomic region chr17:36,000,000–54,000,000.




GIAB_40X.yaml: The configuration file containing parameters required to launch TriosCompass for the GIAB 40X test case.




input/: A directory containing the specific input files required by the workflow.




launch_40X.sh: A wrapper script designed to submit the TriosCompass Snakemake workflow to a Slurm workload manager.




ref/: The hg38 resource bundle/reference files required for TriosCompass execution.




TriosCompass_v2/: A clone of the TriosCompass repository (Main branch, commit: 55605b1).




expected_output/: A reference directory containing the results generated by a successful run of this test case for validation purposes.



 

Getting Started

 

To use this dataset, simply download and uncompress the TriosCompass_test_case.zip file. The uncompressed directory will contain all the necessary files to launch a test run. You will need to install the required dependencies: Singularity, Conda or Mamba, and the conda environment TriosCompassV2.

For detailed instructions on how to install the dependencies and configure the workflow for your computing environment, please refer to the TriosCompass v2 documentation.

By running this test case, users can quickly verify their setup and ensure that the workflow is ready for production use.
DOI: 10.5281/zenodo.7084147
title: TriosCompass Test Dataset

description: Here is a drafted description for the dataset to be uploaded to Zenodo.

 

TriosCompass Workflow Test Dataset

 

This dataset provides a complete test case for the TriosCompass workflow, a powerful tool designed for human whole-genome sequencing (WGS) analysis. The dataset is optimized for a quick and comprehensive test run, ensuring the workflow is set up correctly and produces the expected results.

 

Dataset Contents

 

The TriosCompass_test_case.zip archive includes all necessary components to run the test case. Below is a description of the directory structure and files:





bam/: Mini-BAM files extracted from the GIAB 40X dataset, covering the genomic region chr17:36,000,000–54,000,000.




GIAB_40X.yaml: The configuration file containing parameters required to launch TriosCompass for the GIAB 40X test case.




input/: A directory containing the specific input files required by the workflow.




launch_40X.sh: A wrapper script designed to submit the TriosCompass Snakemake workflow to a Slurm workload manager.




ref/: The hg38 resource bundle/reference files required for TriosCompass execution.




TriosCompass_v2/: A clone of the TriosCompass repository (Main branch, commit: 55605b1).




expected_output/: A reference directory containing the results generated by a successful run of this test case for validation purposes.



 

Getting Started

 

To use this dataset, simply download and uncompress the TriosCompass_test_case.zip file. The uncompressed directory will contain all the necessary files to launch a test run. You will need to install the required dependencies: Singularity, Conda or Mamba, and the conda environment TriosCompassV2.

For detailed instructions on how to install the dependencies and configure the workflow for your computing environment, please refer to the TriosCompass v2 documentation.

By running this test case, users can quickly verify their setup and ensure that the workflow is ready for production use.
DOI: 10.23642/usn.13034387
title: Data set for "Exploring pupils' and teachers' perspectives on face-to-face promotive interaction"

description: DATASET MIGRATED FROM FIGSHARE: &lt;div&gt;This study reports on pupils’ and teachers’ perceptions of face-to-face promotive interaction (FtFPI) in cooperative learning (CL) at two primary schools in post-war Bosnia and Herzegovina (BiH). Using mixed methods, the study asks (1) ‘To what extent are the aspects of FtFPI most likely to influence pupils’ CL group work?’ (2) ‘What are the challenges in applying pupils’ FtFPI in small CL groups?’ The findings reveal mostly positive beliefs of FtFPI influence on small CL group work. However, when it comes to pupils’ and teachers’ experiences, several challenges have been identified: (1) organisation of FtFPI, (2) planning and balancing between working on a group task and supporting peers, (3) interpersonal behaviours, and (4) supportive communication. The findings suggest that more classroom research related to peers’ promotive interpersonal behaviour and supportive communication is needed.&lt;/div&gt;&lt;div&gt;The article is accepted. &lt;br&gt;&lt;/div&gt;&lt;br&gt;&lt;br&gt;
DOI: 10.23642/usn.13034387/qhvjbf
title: Coded interview data.pdf

description: Coded interview data.pdf
DOI: 10.23642/usn.13034387/pqsrs7
title: Example of Interview - teacher 4th grade EngSA-T1.pdf

description: Example of Interview - teacher 4th grade EngSA-T1.pdf
DOI: 10.23642/usn.13034387/umaygl
title: Example of interview with high achievement student.pdf

description: Example of interview with high achievement student.pdf
DOI: 10.23642/usn.13034387/xs59cd
title: Example of interview with high achievement student_1.pdf

description: Example of interview with high achievement student_1.pdf
DOI: 10.23642/usn.13034387/uikxx2
title: frequency tables for items.pdf

description: frequency tables for items.pdf
DOI: 10.23642/usn.13034387/ykgmy4
title: Figures.xlsx

description: Figures.xlsx
DOI: 10.23642/usn.13034387/aewiga
title: items 1.jpg

description: items 1.jpg
DOI: 10.23642/usn.13034387/gews5k
title: Interview guide -students.pdf

description: Interview guide -students.pdf
DOI: 10.23642/usn.13034387/tathwb
title: items 2.jpg

description: items 2.jpg
DOI: 10.23642/usn.13034387/3jrgbu
title: readme.txt

description: readme.txt
DOI: 10.23642/usn.13034387/b46wel
title: items 3.jpg

description: items 3.jpg
DOI: 10.23642/usn.13034387/ci8auc
title: statistical data_1.xlsx

description: statistical data_1.xlsx
DOI: 10.23642/usn.13034387/mrs6rc
title: Reliability Statistics cron.docx

description: Reliability Statistics cron.docx
DOI: 10.23642/usn.13034387/u05zhm
title: Students questionnaire -.pdf

description: Students questionnaire -.pdf
DOI: 10.23642/usn.13034387/rbkess
title: tables.pdf

description: tables.pdf
DOI: 10.23642/usn.12925085
title: 20200707_Traumer_barnehage_Norden.docx

description: DATASET MIGRATED FROM FIGSHARE: These files comprises the search strategies for a review article about characteristics for psychosocial support for children with trauma in the Nordic countries.&lt;br&gt;The searches were performed by a trained librarian in the databases ERIC, PsycInfo, Web of Science, Social premium collection, Academic
Search Premier and Scopus in July 2020.
DOI: 10.23642/usn.12925085/9hn3bb
title: 20200707_Traumer_barnehage_Norden_til_RDA.docx

description: 20200707_Traumer_barnehage_Norden_til_RDA.docx
DOI: 10.23642/usn.12925085/shnisq
title: 20200707_Traumer_barnehage_Norden_til_RDA.pdf

description: 20200707_Traumer_barnehage_Norden_til_RDA.pdf
DOI: 10.23642/usn.12925085/cdffox
title: Narrative.docx

description: Narrative.docx
DOI: 10.23642/usn.12925085/hkh9vj
title: ReadMe.txt

description: ReadMe.txt
DOI: 10.23642/usn.12925085/wqh0kf
title: Narrative.pdf

description: Narrative.pdf
DOI: 10.5281/zenodo.17975888
title: A Ground-Truth Dataset for Article Separation in Historical Newspapers: A ProQuest corpus centered on the China Foundation for the Promotion of Education and Culture (1925-1950)

description: Overview

This ground-truth dataset contains manually segmented documents, with partial post-OCR correction, derived from an original corpus of news articles focused on the China Foundation for the Promotion of Education and Culture (established in 1924 to manage the Second remission of the U.S. Boxer Indemnity. The dataset includes 378 articles published between 1925 and 1950 drawn from the ProQuest collection of Chinese Historical newspapers.

The ground-truth data contains the following fields:



DocId: Unique identifier as stored in the Modern China Textual Database (MCTB).

Date: Original date of publication

Title: Article title as provided by ProQuest.

Source: Periodical in which the article was published (principally China Press, China Weekly Review, North-China Herald) 

Text: Original, unsegmented text

text_seg: Historian-curated segmented text, produced using GPT + close reading

length: Character/word length of the original text

length_seg: Character/word length after re-segmentation

diff: length difference between original and segmented text


The segmentation process uses a hybrid human–AI workflow: an automated step with a GPT-based “Historical Text Segmenter,” followed by detailed historian-guided verification and correction. The result is a high-quality ground-truth dataset suitable for OCR benchmarking, segmentation modeling, historical text analysis, and digital humanities research. Additional documentation on the configuration of the GPT “Historical Text Segmenter” is available here.

Use Cases

This dataset is intended for:



Historical research on Sino-American cultural institutions

Media and discourse analysis of English-language periodicals in China. 

Training/evaluating segmentation and OCR models

Digital humanities projects requiring high-quality ground truth corpora

Studies of textual reuse and viral news circulation in Republican-era newspapers
DOI: 10.5281/zenodo.17975887
title: A Ground-Truth Dataset for Article Separation in Historical Newspapers: A ProQuest corpus centered on the China Foundation for the Promotion of Education and Culture (1925-1950)

description: Overview

This ground-truth dataset contains manually segmented documents, with partial post-OCR correction, derived from an original corpus of news articles focused on the China Foundation for the Promotion of Education and Culture (established in 1924 to manage the Second remission of the U.S. Boxer Indemnity. The dataset includes 378 articles published between 1925 and 1950 drawn from the ProQuest collection of Chinese Historical newspapers.

The ground-truth data contains the following fields:



DocId: Unique identifier as stored in the Modern China Textual Database (MCTB).

Date: Original date of publication

Title: Article title as provided by ProQuest.

Source: Periodical in which the article was published (principally China Press, China Weekly Review, North-China Herald) 

Text: Original, unsegmented text

text_seg: Historian-curated segmented text, produced using GPT + close reading

length: Character/word length of the original text

length_seg: Character/word length after re-segmentation

diff: length difference between original and segmented text


The segmentation process uses a hybrid human–AI workflow: an automated step with a GPT-based “Historical Text Segmenter,” followed by detailed historian-guided verification and correction. The result is a high-quality ground-truth dataset suitable for OCR benchmarking, segmentation modeling, historical text analysis, and digital humanities research. Additional documentation on the configuration of the GPT “Historical Text Segmenter” is available here.

Use Cases

This dataset is intended for:



Historical research on Sino-American cultural institutions

Media and discourse analysis of English-language periodicals in China. 

Training/evaluating segmentation and OCR models

Digital humanities projects requiring high-quality ground truth corpora

Studies of textual reuse and viral news circulation in Republican-era newspapers
DOI: 10.5281/zenodo.17940187
title: A 500-m Agricultural Drought Impact Dataset in China's Main Grain Region

description:  This study generated a 500 m-gridded agricultural drought-impacted area dataset in China’s main grain region (ADIA-CMGR) during 2006-2020. The dataset constitutes various information, including drought-covered area, drought-damaged area, and crop failure area. Validation with the text-based qualitative records of agricultural drought-impacted areas shows that ADIA-CMGR offers accurate temporal variability and reasonable spatial distribution. The developed dataset satisfactorily revealed the spatial and inter-annual dynamics of agricultural drought-impacted areas across various crop-growing seasons, providing a solid foundation for managing drought impacts and improving agricultural practices. Cresponding code can be achieved at: https://github.com/SJL-UCAS/ADAD_generate
DOI: 10.5281/zenodo.15201952
title: A 500-m Agricultural Drought Impact Dataset in China's Main Grain Region

description:  This study generated a 500 m-gridded agricultural drought-impacted area dataset in China’s main grain region (ADIA-CMGR) during 2006-2020. The dataset constitutes various information, including drought-covered area, drought-damaged area, and crop failure area. Validation with the text-based qualitative records of agricultural drought-impacted areas shows that ADIA-CMGR offers accurate temporal variability and reasonable spatial distribution. The developed dataset satisfactorily revealed the spatial and inter-annual dynamics of agricultural drought-impacted areas across various crop-growing seasons, providing a solid foundation for managing drought impacts and improving agricultural practices. Cresponding code can be achieved at: https://github.com/SJL-UCAS/ADAD_generate
DOI: 10.15468/dl.hx4fr9
title: Occurrence Download

description: A dataset containing 21314 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Geometry POLYGON((3.73975 43.69752,3.75077 43.68427,3.77928 43.68405,3.79731 43.70498,3.80477 43.72402,3.80689 43.74028,3.79241 43.74896,3.77527 43.74818,3.74565 43.72736,3.73975 43.69752))",
 "Geometry POLYGON((4.45501 43.80061,4.45559 43.78039,4.4759 43.7762,4.5006 43.79059,4.53025 43.81682,4.5251 43.83513,4.49878 43.83579,4.47103 43.81825,4.45501 43.80061))"
 ]
 },
 "OccurrenceStatus is Present",
 "TaxonKey is Aves"
 ]
}

 The dataset includes 21314 records from 201 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063010-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17952992
title: A Ground-Truth Dataset for Article Separation in Historical Newspapers: A Shenbao corpus centered on 中華教育文化基金會 (1924–1947)

description: This ground-truth dataset contains carefully curated and properly segmented documents derived from an original corpus of news articles focused on China Foundation for the Promotion of Education and Culture 中華教育文化基金會 (established in 1924 to manage the Second remission of the U.S. Boxer Indemnity. The dataset includes 379 articles published in the Shenbao 申報 newspaper between 1924 and 1947.

The ground-truth data contains the following fields:



DocId: Unique identifier as stored  in the Modern China Textual Database (MCTB).

Date: Original date of publication

Section, section2: Newspaper section in which the article appeared (automatically retrieved from the Title or full text)

Title: Title as provided by the data supplier

Source: Shenbao

Text: Original, unsegmented text

text_seg: Historian-curated segmented text, produced using GPT + close reading

length: Character/word length of the original text

length_seg: Character/word length after re-segmentation

diff: length difference between original and segmented text


The segmentation process uses a hybrid human–AI workflow: an automated step with a GPT-based “Historical Text Segmenter,” followed by detailed historian-guided verification and correction. The result is a high-quality ground-truth dataset suitable for OCR benchmarking, segmentation modeling, historical text analysis, and digital humanities research. Additional documentation on the configuration of the GPT “Historical Text Segmenter” is available here.

Use Cases

This dataset is intended for:



Historical research on academic institutions and Sino-American cultural relations

Media and discourse analysis of Shenbao

Training/evaluating segmentation models

Digital humanities projects requiring high-quality ground truth corpora

Studies of textual reuse and viral news circulation in Republican-era newspapers
DOI: 10.5281/zenodo.17952993
title: A Ground-Truth Dataset for Article Separation in Historical Newspapers: A Shenbao corpus centered on 中華教育文化基金會 (1924–1947)

description: This ground-truth dataset contains carefully curated and properly segmented documents derived from an original corpus of news articles focused on China Foundation for the Promotion of Education and Culture 中華教育文化基金會 (established in 1924 to manage the Second remission of the U.S. Boxer Indemnity. The dataset includes 379 articles published in the Shenbao 申報 newspaper between 1924 and 1947.

The ground-truth data contains the following fields:



DocId: Unique identifier as stored  in the Modern China Textual Database (MCTB).

Date: Original date of publication

Section, section2: Newspaper section in which the article appeared (automatically retrieved from the Title or full text)

Title: Title as provided by the data supplier

Source: Shenbao

Text: Original, unsegmented text

text_seg: Historian-curated segmented text, produced using GPT + close reading

length: Character/word length of the original text

length_seg: Character/word length after re-segmentation

diff: length difference between original and segmented text


The segmentation process uses a hybrid human–AI workflow: an automated step with a GPT-based “Historical Text Segmenter,” followed by detailed historian-guided verification and correction. The result is a high-quality ground-truth dataset suitable for OCR benchmarking, segmentation modeling, historical text analysis, and digital humanities research. Additional documentation on the configuration of the GPT “Historical Text Segmenter” is available here.

Use Cases

This dataset is intended for:



Historical research on academic institutions and Sino-American cultural relations

Media and discourse analysis of Shenbao

Training/evaluating segmentation models

Digital humanities projects requiring high-quality ground truth corpora

Studies of textual reuse and viral news circulation in Republican-era newspapers
DOI: 10.5281/zenodo.18018245
title: Risk Models for Ventotene pilot site of TRIQUETRA

description: The list of risk quantification models produced for the pilot site of Ventotene in the context of TRIQUETRA, including: 



sea-level rise

periodic waves vertical cliff

solitary wave on-nothed cliff

solitary waves inclined cliff

geomorphological maps

local seismic response analysis

projected changes

solitary waves vertical cliff.
DOI: 10.5281/zenodo.18018246
title: Risk Models for Ventotene pilot site of TRIQUETRA

description: The list of risk quantification models produced for the pilot site of Ventotene in the context of TRIQUETRA, including: 



sea-level rise

periodic waves vertical cliff

solitary wave on-nothed cliff

solitary waves inclined cliff

geomorphological maps

local seismic response analysis

projected changes

solitary waves vertical cliff.
DOI: 10.34740/kaggle/dsv/14257438
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.4ubq54
title: Occurrence Download

description: A dataset containing 330 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Aneides klamathensis"
 ]
}

 The dataset includes 330 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063014-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nk5k7n
title: Occurrence Download

description: A dataset containing 7502677 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Regulus calendula",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON((-180 -90, 180 -90, 180 90, -180 90, -180 -90))"
 ]
}

 The dataset includes 7502677 records from 152 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0062991-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.30911042
title: <b>完整的叶绿体基因组序列</b>

description: Maesa cavinervis is a species of the genus Maesa in the Primulaceae family (Primulaceae s.l). In this study, we sequenced and assembled the complete chloroplast genome of M. cavinervis using Illumina sequencing technology. This study aims to address the scarcity of chloroplast genomic data in this genus and provide new molecular insights into the phylogeny and conservation biology of the primrose family.