cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14975367
title: MathWriting+

description: Overview

MathWriting+ extends the original MathWriting dataset with detailed structural annotations for handwritten equations. It includes labeled symbols, relation graphs in MathML, and refined trace group data across multiple subsets (train, validation, test, synthetic). This enables handwriting recognition approaches that leverage structural information. For more details, see "The Return of Structural Approaches in Handwriting Recognition".

Dataset Breakdown

The table below summarizes the labeled data versus the total available for each subset. (All numbers are rounded for simplicity.)




Subset
Annotated Count
Total Count




Symbols
~6.3K
~6.4K


Train
~143K
~230K


Validation
~9K
~16K


Test
~6K
~7.6K


Synthetic
~86K
~121K






Symbols: Isolated handwritten mathematical symbols

Train, Validation, Test: Handwritten mathematical expressions collected from various sources.

Synthetic: Artificially generated mathematical expressions.


The dataset includes only those samples that have been enhanced with additional structural annotations (trace groups and MathML).

Limitations and Quality Assurance

We have not yet labeled more complex constructs such as matrices, vectors, or symbols with overlines/arrow notations.

The annotations have been cross-checked using a state-of-the-art symbol classification model further described in the corresponding paper. While most of the data is highly accurate, there might be a few errors, especially for symbols not included in the CROHME dataset, so users should take these into account during their research.

Usage and Citation

If you use the MathWriting+ Dataset in your work, please cite this dataset or our paper:



"The Return of Structural Approaches in Handwriting Recognition"


Your citation helps acknowledge the effort behind the dataset and supports further advancements in interpretable handwritten mathematical expression recognition.
DOI: 10.5281/zenodo.15091575
title: MathWriting+

description: Overview

MathWriting+ extends the original MathWriting dataset with detailed structural annotations for handwritten equations. It includes labeled symbols, relation graphs in MathML, and refined trace group data across multiple subsets (train, validation, test, synthetic). This enables handwriting recognition approaches that leverage structural information. For more details, see "The Return of Structural Approaches in Handwriting Recognition".

Dataset Breakdown

The table below summarizes the labeled data versus the total available for each subset. (All numbers are rounded for simplicity.)




Subset
Annotated Count
Total Count




Symbols
~6.3K
~6.4K


Train
~143K
~230K


Validation
~9K
~16K


Test
~6K
~7.6K


Synthetic
~86K
~121K






Symbols: Isolated handwritten mathematical symbols

Train, Validation, Test: Handwritten mathematical expressions collected from various sources.

Synthetic: Artificially generated mathematical expressions.


The dataset includes only those samples that have been enhanced with additional structural annotations (trace groups and MathML).

Limitations and Quality Assurance

We have not yet labeled more complex constructs such as matrices, vectors, or symbols with overlines/arrow notations.

The annotations have been cross-checked using a state-of-the-art symbol classification model further described in the corresponding paper. While most of the data is highly accurate, there might be a few errors, especially for symbols not included in the CROHME dataset, so users should take these into account during their research.

Usage and Citation

If you use the MathWriting+ Dataset in your work, please cite this dataset or our paper:



"The Return of Structural Approaches in Handwriting Recognition"


Your citation helps acknowledge the effort behind the dataset and supports further advancements in interpretable handwritten mathematical expression recognition.
DOI: 10.5281/zenodo.14968569
title: CROHME+

description: Overview

This dataset, introduced in the paper "The Return of Structural Approaches in Handwriting Recognition", builds upon the original CROHME dataset by automatically generating detailed structural annotations that map handwritten traces to their corresponding symbols. For files where trace group information was missing or incorrect, we have added or corrected these details to enable precise symbol classification and segmentation. In addition, for files lacking MathML annotations, we incorporated the necessary relational information to accurately represent the structure of the mathematical expressions. These enhancements not only improve error analysis and interpretability but also support more effective spatially aware applications.

Dataset Breakdown

This dataset extends the CROHME 2023 dataset by adding structural annotations to the syntactical and artificial training data - most real data was already manually labeled (with only minor issues in a few real train, validation, and test files).



Syntactical Data: Generated by extracting and recombining valid sub-expressions from handwritten expressions to ensure syntactic correctness (trace groups were already annotated, but MathML annotation was missing).

Artificial Data: Computationally produced from LaTeX sequences, these samples often had wrong trace group annotations and were lacking MathML annotations.





Dataset Type
Annotated Count
Total Count


Syntactical
~69,000
~76,000


Artificial
~55,000
~72,300




⚠️ Note: The provided dataset only includes the correctly annotated expressions. It is intended to complement the original CROHME dataset, which already contains manually labelled annotations.

Additional Resources

A similar structural annotation approach was applied to the original MathWriting dataset, resulting in the enhanced MathWriting+ dataset with annotated equations.

Usage and Citation

If you utilize this dataset for your research or development work, please cite the paper:



"The Return of Structural Approaches in Handwriting Recognition"


Citing the work not only acknowledges the effort behind creating these annotations but also supports further research into interpretable HMER systems.

Disclaimer

While extensive validation and cross-checking have been performed, the dataset might contain a few minor mistakes. Nonetheless, the vast majority of the data is highly accurate and is expected to be a valuable resource for advancing recognition dependent on detailed annotation in handwritten mathematical expressions.
DOI: 10.5281/zenodo.14968570
title: CROHME+

description: Overview

This dataset, introduced in the paper "The Return of Structural Approaches in Handwriting Recognition", builds upon the original CROHME dataset by automatically generating detailed structural annotations that map handwritten traces to their corresponding symbols. For files where trace group information was missing or incorrect, we have added or corrected these details to enable precise symbol classification and segmentation. In addition, for files lacking MathML annotations, we incorporated the necessary relational information to accurately represent the structure of the mathematical expressions. These enhancements not only improve error analysis and interpretability but also support more effective spatially aware applications.

Dataset Breakdown

This dataset extends the CROHME 2023 dataset by adding structural annotations to the syntactical and artificial training data - most real data was already manually labeled (with only minor issues in a few real train, validation, and test files).



Syntactical Data: Generated by extracting and recombining valid sub-expressions from handwritten expressions to ensure syntactic correctness (trace groups were already annotated, but MathML annotation was missing).

Artificial Data: Computationally produced from LaTeX sequences, these samples often had wrong trace group annotations and were lacking MathML annotations.





Dataset Type
Annotated Count
Total Count


Syntactical
~69,000
~76,000


Artificial
~55,000
~72,300




⚠️ Note: The provided dataset only includes the correctly annotated expressions. It is intended to complement the original CROHME dataset, which already contains manually labelled annotations.

Additional Resources

A similar structural annotation approach was applied to the original MathWriting dataset, resulting in the enhanced MathWriting+ dataset with annotated equations.

Usage and Citation

If you utilize this dataset for your research or development work, please cite the paper:



"The Return of Structural Approaches in Handwriting Recognition"


Citing the work not only acknowledges the effort behind creating these annotations but also supports further research into interpretable HMER systems.

Disclaimer

While extensive validation and cross-checking have been performed, the dataset might contain a few minor mistakes. Nonetheless, the vast majority of the data is highly accurate and is expected to be a valuable resource for advancing recognition dependent on detailed annotation in handwritten mathematical expressions.
DOI: 10.5281/zenodo.15752976
title: Enhanced Dynamic Performance of WPT Systems via PSO-based Stage-wise Optimization
DOI: 10.5281/zenodo.15752977
title: Enhanced Dynamic Performance of WPT Systems via PSO-based Stage-wise Optimization
DOI: 10.15468/dl.bwhr8q
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (India, China, Myanmar, Bhutan, Pakistan, Bangladesh, Nepal, Afghanistan)",
 "TaxonKey is Lethe moelleri (Elwes, 1887)"
 ]
}

 The dataset includes 8 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071324-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yqfevp
title: Occurrence Download

description: A dataset containing 41 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (India, China, Myanmar, Bhutan, Bangladesh, Afghanistan, Pakistan, Nepal)",
 "TaxonKey is Lethe jalaurida (de Nicéville, 1880)"
 ]
}

 The dataset includes 41 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071319-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qq6a4m
title: Occurrence Download

description: A dataset containing 68624 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Terrapene carolina (Linnaeus, 1758)"
 ]
}

 The dataset includes 68624 records from 145 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071329-250525065834625/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.29422649
title: From Fuzzballs to Fractals: Pioneering QuantumDynamics

description: This work synthesizes transformative insights with algorithmic refinements, focusing on physics-only models that demonstrate novel approaches to quantum gravity and spacetime dynamics. The research leverages holographic data storage principles, self-organizing quantum states, and a 6-dimensional Calabi-Yau manifold model, with comprehensive validation through 90+ simulation runs achieving 93.2% accuracy. The AI-assisted computational methodologies demonstrate the potential for breakthrough discoveries through interdisciplinary approaches in theoretical physics research.
DOI: 10.6084/m9.figshare.29422649.v1
title: From Fuzzballs to Fractals: Pioneering QuantumDynamics

description: This work synthesizes transformative insights with algorithmic refinements, focusing on physics-only models that demonstrate novel approaches to quantum gravity and spacetime dynamics. The research leverages holographic data storage principles, self-organizing quantum states, and a 6-dimensional Calabi-Yau manifold model, with comprehensive validation through 90+ simulation runs achieving 93.2% accuracy. The AI-assisted computational methodologies demonstrate the potential for breakthrough discoveries through interdisciplinary approaches in theoretical physics research.
DOI: 10.6084/m9.figshare.29422649.v2
title: From Fuzzballs to Fractals: Pioneering QuantumDynamics

description: This work synthesizes transformative insights with algorithmic refinements, focusing on physics-only models that demonstrate novel approaches to quantum gravity and spacetime dynamics. The research leverages holographic data storage principles, self-organizing quantum states, and a 6-dimensional Calabi-Yau manifold model, with comprehensive validation through 90+ simulation runs achieving 93.2% accuracy. The AI-assisted computational methodologies demonstrate the potential for breakthrough discoveries through interdisciplinary approaches in theoretical physics research.
DOI: 10.15468/dl.tzrnnw
title: Occurrence Download

description: A dataset containing 1565 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Gerrhonotus infernalis Baird, 1859"
 ]
}

 The dataset includes 1565 records from 56 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071326-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8mjytm
title: Occurrence Download

description: A dataset containing 53964 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Quercus cerris L.)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Geometry POLYGON ((-20 20, 45 20, 45 75, -20 75, -20 20))"
 ]
}

 The dataset includes 53964 records from 309 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071332-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.av785v
title: Occurrence Download

description: A dataset containing 68 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 "year",
 IF(ISNULL(kingdomkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY kingdomkey, "year")) kingdomcount,
 IF(ISNULL(phylumkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY phylumkey, "year")) phylumcount,
 IF(ISNULL(classkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY classkey, "year")) classcount,
 IF(ISNULL(orderkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY orderkey, "year")) ordercount,
 IF(ISNULL(familykey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY familykey, "year")) familycount,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey, "year")) genuscount,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 occurrence.hascoordinate = TRUE
 AND occurrence.hasgeospatialissues = FALSE
 AND occurrence.occurrencestatus = 'PRESENT'
 AND (occurrence.taxonkey = 5109931 OR occurrence.acceptedtaxonkey = 5109931 OR occurrence.kingdomkey = 5109931 OR occurrence.phylumkey = 5109931 OR occurrence.classkey = 5109931 OR occurrence.orderkey = 5109931 OR occurrence.familykey = 5109931 OR occurrence.genuskey = 5109931 OR occurrence.specieskey = 5109931)
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND NOT occurrence.basisofrecord IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')
 AND (occurrence.specieskey IS NOT NULL AND occurrence."year" IS NOT NULL)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 occurrence."year"

 The dataset's 68 records were derived from 64 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071337-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pp7fkd
title: Occurrence Download

description: A dataset containing 27226 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Scincella lateralis (Say, 1822)"
 ]
}

 The dataset includes 27226 records from 104 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071330-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tjbtdz
title: Occurrence Download

description: A dataset containing 2822 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Spodoptera littoralis (Boisduval, 1833)"
 ]
}

 The dataset includes 2822 records from 85 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071331-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.75pzc9
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Abelmoschus moschatus",
 "Country is Cook Islands",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071333-250525065834625/datasets/export for details.
DOI: 10.5281/zenodo.15752080
title: Ethical Issues of Digital Marketing on Skincare Products

description: The rise of digital marketing in the skincare industry has raised concerns about the ethical implications of online promotional strategies. This study investigates ethical issues in the digital marketing of skin care products, focusing on how misleading advertising, exaggerated product claims, and perceived deception affect consumer perceptions and purchasing behaviour. 651 responses were collected in April 2025 through an online questionnaire distributed through social media and digital platforms. After removing outliers, 440 valid responses were retained for analysis. Respondents were individuals from various regions in Indonesia, including Greater Jakarta, Java, Sumatra, and other major urban areas, who had purchased a skin care product inconsistent with digital marketing. The sampling method was purposive, targeting consumers who directly encountered the claims. Using Structural Equation Modeling with Partial Least Squares (SEM-PLS), this study examined the effects of brand awareness, consumer trust, misleading advertising, perceived deception, and exaggerated product claims on purchase intention and perceived product risk. The results show that brand awareness and consumer trust are important in forming purchase intentions. At the same time, misleading and deceptive marketing elements indirectly influence consumer decisions by increasing risk perception and decreasing trust. These findings highlight the importance of honest brand communication in fostering consumer trust and promoting ethical marketing practices.
DOI: 10.15468/dl.bfqeau
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Abelmoschus moschatus",
 "Country is Fiji",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071335-250525065834625/datasets/export for details.
DOI: 10.15468/dl.nbr2vz
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Abelmoschus moschatus",
 "Country is Micronesia (Federated States of)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071334-250525065834625/datasets/export for details.
DOI: 10.6084/m9.figshare.28296344
title: Underlying data for "East Asian aerosol cleanup has likely contributed to the recent acceleration in global warming"

description: Data files used for producing the figures of the paper "East Asian aerosol cleanup has likely contributed to the recent acceleration in global warming".
DOI: 10.6084/m9.figshare.28296344.v1
title: Underlying data for "East Asian aerosol cleanup has likely contributed to the recent acceleration in global warming"

description: Data files used for producing the figures of the paper "East Asian aerosol cleanup has likely contributed to the recent acceleration in global warming".
DOI: 10.34810/data292
title: English-Galician LMF Apertium Bilingual dictionary

description: This is the LMF version of the Apertium bilingual dictionary for English and Galician languages. Apertium is a free/open-source machine translation platform, initially aimed at related-language pairs but recently expanded to deal with more divergent language pairs (such as English-Catalan). The platform provides: a language-independent machine translation engine; tools to manage the linguistic data necessary to build a machine translation system for a given language pair and linguistic data for a growing number of language pairs.
DOI: 10.15468/dl.6hxm2w
title: Occurrence Download

description: A dataset containing 26718 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is France",
 "GadmGid is FRA.7.1_1",
 "License is one of (CC0 1.0, CC-BY 4.0, CC-BY-NC 4.0, Pending, Incompatible)",
 "OccurrenceStatus is Present",
 "PublishingOrg is c8d737e0-2ff8-42e8-b8fc-6b805d26fc5f"
 ]
}

 The dataset includes 26718 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071338-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.thjq92
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ephemeroptera",
 "Geometry POLYGON ((15.4784 -23.4046, 15.4933 -24.0715, 20.509 -24.0715, 20.509 -24.0455, 20.0952 -23.5072, 19.9968 -23.017, 19.7843 -22.5405, 19.1988 -21.8785, 18.5972 -21.5447, 17.8859 -21.3993, 17.1626 -21.4805, 16.5332 -21.7596, 16.1257 -22.0882, 15.8234 -22.4662, 15.606 -22.8993, 15.4784 -23.4046))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is Human Observation"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071336-250525065834625/datasets/export for details.
DOI: 10.5519/qd.4hw3nmpb
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5281/zenodo.15753036
title: Helical instability of non-isothermal liquid jets
DOI: 10.5281/zenodo.15753037
title: Helical instability of non-isothermal liquid jets
DOI: 10.15468/dl.thdpw8
title: Occurrence Download

description: A dataset containing 24226 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((16.665268578288664 48.25197073307624, 16.900759257043696 48.23747308478536, 16.9225330323594 48.39589285418887, 16.686309942675752 48.41044311539586, 16.665268578288664 48.25197073307624))"
 ]
}

 The dataset includes 24226 records from 104 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071339-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.