cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17511997
title: Litigating greenwashing: allegation-level dataset on environmental advertising disputes (2009–2025)

description: This is a single Excel workbook containing allegation-level records as rows with harmonised variable names and code lists as columns. A dedicated codebook sheet defines each variable, permissible values, and examples. Pivot sheets illustrate standard groupings by advertising format, message level, allegation framing, allegation subtype, and outcome; these are convenience views only.

The dataset captures environmental advertising and labelling disputes involving firms, coded at the level of the allegation instance. Each record identifies the advertising format, whether the message is product- or firm-level, how the allegation is framed (misrepresentation, omission, or both), the allegation subtype (lack of substantiation, hidden trade-off, vagueness or ambiguity, implied or false label), procedure and outcome. Allegations are nested within cases, so a single dispute can contribute multiple allegation records.

Records cover disputes filed or decided 1 January 2009 to 30 October 2025 across 13 countries. Earlier disputes present in the source repositories (back to 2009) are out of scope for this release. Coding reflects the most recent disposition available as of 30 October 2025.

Primary inputs were official decisions and public case summaries collected from The Climate Litigation Database maintaned by the SABIN CENTER FOR CLIMATE CHANGE LAW (https://www.climatecasechart.com/). Where summaries lacked material detail, the referenced filing or judgment was consulted to resolve ambiguity; non-English materials were translated to ensure accurate coding. Data were coded to a consistent schema; all coding decisions follow the codebook embedded in the file.

ncluded: court actions, advertising-standards rulings, and analogous complaint processes targeting environmental advertising or labelling by firms. Excluded: disputes solely about corporate reporting unconnected to advertising; academic or advocacy critiques without forum action; duplicate entries.

Counts and shares should be computed at the allegation level. A single case may contain one to three allegation subtypes, so subtype counts can exceed the number of disputes.
DOI: 10.5281/zenodo.17511998
title: Litigating greenwashing: allegation-level dataset on environmental advertising disputes (2009–2025)

description: This is a single Excel workbook containing allegation-level records as rows with harmonised variable names and code lists as columns. A dedicated codebook sheet defines each variable, permissible values, and examples. Pivot sheets illustrate standard groupings by advertising format, message level, allegation framing, allegation subtype, and outcome; these are convenience views only.

The dataset captures environmental advertising and labelling disputes involving firms, coded at the level of the allegation instance. Each record identifies the advertising format, whether the message is product- or firm-level, how the allegation is framed (misrepresentation, omission, or both), the allegation subtype (lack of substantiation, hidden trade-off, vagueness or ambiguity, implied or false label), procedure and outcome. Allegations are nested within cases, so a single dispute can contribute multiple allegation records.

Records cover disputes filed or decided 1 January 2009 to 30 October 2025 across 13 countries. Earlier disputes present in the source repositories (back to 2009) are out of scope for this release. Coding reflects the most recent disposition available as of 30 October 2025.

Primary inputs were official decisions and public case summaries collected from The Climate Litigation Database maintaned by the SABIN CENTER FOR CLIMATE CHANGE LAW (https://www.climatecasechart.com/). Where summaries lacked material detail, the referenced filing or judgment was consulted to resolve ambiguity; non-English materials were translated to ensure accurate coding. Data were coded to a consistent schema; all coding decisions follow the codebook embedded in the file.

ncluded: court actions, advertising-standards rulings, and analogous complaint processes targeting environmental advertising or labelling by firms. Excluded: disputes solely about corporate reporting unconnected to advertising; academic or advocacy critiques without forum action; duplicate entries.

Counts and shares should be computed at the allegation level. A single case may contain one to three allegation subtypes, so subtype counts can exceed the number of disputes.
DOI: 10.15468/dl.h9jhme
title: Occurrence Download

description: A dataset containing 2139 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is Asia",
 "OccurrenceStatus is Present",
 "TaxonKey is Sparganium",
 "Year 1000-2025"
 ]
}

 The dataset includes 2139 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012615-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/vr9bso
title: PAN-00179949 - brooch

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00179949&lt;/p&gt;
description: Modified: 2025-09-26T13:28:00Z
DOI: 10.15468/dl.zndk4m
title: Occurrence Download

description: A dataset containing 93 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is Asia",
 "OccurrenceStatus is Present",
 "TaxonKey is Taxodium",
 "Year 1000-2025"
 ]
}

 The dataset includes 93 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012616-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57745/po5fdp
title: WR_Phenotypic_Barley_raw_Historical.tab

description: :unav
DOI: 10.57745/f8tugo
title: ICARDA_outlier_corrected.tab

description: :unav
DOI: 10.57745/szxgpb
title: NPPC_Phenotypic_Winter_Barley_raw_Historical.tab

description: :unav
DOI: 10.57745/ilwukl
title: NPPC_Phenotypic_Spring_Barley_raw_Historical.tab

description: :unav
DOI: 10.57745/c8v2o2
title: IHAR_Phenotypic_winter_barley_raw_Historical.tab

description: :unav
DOI: 10.57745/avxngu
title: NARDI_Spring_outlier_corrected.tab

description: :unav
DOI: 10.57745/tbwkrx
title: NPPC_Spring_outlier_corrected.tab

description: :unav
DOI: 10.57745/7yvjym
title: WR_outlier_corrected.tab

description: :unav
DOI: 10.57745/ezwvj6
title: CARC_Phenotypic_Winter_Barley_raw_Historical.tab

description: :unav
DOI: 10.57745/oljks4
title: NARDI_Phenotypic_Winter_Barley_raw_Historical.tab

description: :unav
DOI: 10.57745/g2uajt
title: IPGR-Sadovo_Phenotypic_Barley_raw_Historical.tab

description: :unav
DOI: 10.57745/yyk3i4
title: CARC_Winter_oulier_corrected.tab

description: :unav
DOI: 10.57745/5f95xt
title: IHAR_Winter_outlier_corrected.tab

description: :unav
DOI: 10.57745/8wsgxr
title: IHAR_Phenotypic_spring_barley_raw_Historical.tab

description: :unav
DOI: 10.57745/y3zbao
title: CARC_Phenotypic_Spring_Barley_raw_Historical.tab

description: :unav
DOI: 10.57745/uq2ngx
title: BLUEs_historical_Barley.tab

description: :unav
DOI: 10.57745/5tabkw
title: NPPC_Winter_outlier_corrected.tab

description: :unav
DOI: 10.57745/kfab8h
title: Phenotypic_historical_template - SPRING-BARLEY_v7.tab

description: :unav
DOI: 10.57745/vutpsg
title: NARDI_Phenotypic_Spring_Barley_raw_Historical.tab

description: :unav
DOI: 10.57745/7qxfzs
title: CARC_Spring_outlier_corrected.tab

description: :unav
DOI: 10.57745/ca2svj
title: IHAR_Spring_outlier_corrected.tab

description: :unav
DOI: 10.57745/nplm6d
title: IPGR_outlier_corrected.tab

description: :unav
DOI: 10.57745/gawdet
title: NARDI_Winter_outlier_corrected.tab

description: :unav
DOI: 10.57745/8knpgy
title: R_script_BLUEs_estimation.R

description: :unav
DOI: 10.57745/huygjv
title: R_script_outleirs_correction.R

description: :unav
DOI: 10.57745/g0evbv
title: README_OCD.txt

description: :unav
DOI: 10.57745/bqkz8q
title: README_RAW_DATA.txt

description: :unav
DOI: 10.57745/ggcfdx
title: README_BLUES.txt

description: :unav
DOI: 10.57745/cj5swj
title: ICARDA_Phenotypic_Spring_Barley_raw_Historical.tab

description: :unav
DOI: 10.15468/dl.aantj8
title: Occurrence Download

description: A dataset containing 930829 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "DatasetKey is EOD – eBird Observation Dataset",
 "Geometry POLYGON((-110 -60,-20 -60,-20 25,-110 25,-110 -60))",
 "Issue is Continent derived from coordinates",
 "OccurrenceStatus is Present",
 "TaxonKey is Pipridae",
 "Year 1900-2025"
 ]
}

 The dataset includes 930829 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012604-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17511785
title: CITIC-MTMC dataset

description: This repository contains the CITIC-MTMC dataset. A multi-target multi-camera video dataset for indoor location and tracking of people.
The recordings were carried out inside the CITIC research center. Five cameras were deployed in four spaces of the building: an entrance hall with two cameras (HallWide, HallSeg), two passageways with one camera each (PF and PC), and a showroom with one camera (Showroom).
description: If you use this dataset, please cite the following paper: Á. Carro-Lagoa, V. Barral, M. González-López, C. J. Escudero, and L. Castedo, "Multicamera edge-computing system for persons indoor location and tracking," Elsevier Internet of Things, vol. 24, no. 100940, pp. 1-15, Sep 2023. DOI: https://doi.org/10.1016/j.iot.2023.100940
DOI: 10.5281/zenodo.17512043
title: CITIC-MTMC dataset

description: This repository contains the CITIC-MTMC dataset. A multi-target multi-camera video dataset for indoor location and tracking of people.
The recordings were carried out inside the CITIC research center. Five cameras were deployed in four spaces of the building: an entrance hall with two cameras (HallWide, HallSeg), two passageways with one camera each (PF and PC), and a showroom with one camera (Showroom).
description: If you use this dataset, please cite the following paper: Á. Carro-Lagoa, V. Barral, M. González-López, C. J. Escudero, and L. Castedo, "Multicamera edge-computing system for persons indoor location and tracking," Elsevier Internet of Things, vol. 24, no. 100940, pp. 1-15, Sep 2023. DOI: https://doi.org/10.1016/j.iot.2023.100940
DOI: 10.15468/dl.jqng6s
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-4.11725 40.28573,-3.94914 40.28573,-3.94914 40.40816,-4.11725 40.40816,-4.11725 40.28573))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Lanius meridionalis",
 "Year 2020-2025"
 ]
}

 The dataset includes 18 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012617-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.answxd
title: Occurrence Download

description: A dataset containing 431 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "OccurrenceStatus is Present",
 "TaxonKey is Glinus lotoides"
 ]
}

 The dataset includes 431 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012618-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mumx3a
title: Occurrence Download

description: A dataset containing 4633 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is Asia",
 "OccurrenceStatus is Present",
 "TaxonKey is Tilia",
 "Year 1000-2025"
 ]
}

 The dataset includes 4633 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012619-251025141854904/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.30518138
title: <b>Chemical Proteomics Revealed Global Occurrence of a Phytoplankton Lyase Capable of Reconverting the Progestogens</b>

description: Endocrine-disrupting chemicals (EDCs), such as progestogens, are generally recognized as environmental pollutants of global concern due to their pervasive and adverse effects on aquatic ecosystems and human health. Despite extensive research on their transformation by animals and bacteria (e.g., <i>Denitratisoma sp.</i>), the interactions between phytoplankton and progestogens remain poorly understood. In this study, we reveal a universal biotransformation of norethindrone acetate (NEA), a representative progestogen, across 18 phylogenetically diverse freshwater and marine phytoplankton species. All species demonstrated the ability to remove NEA from culture media (16.4–99.31% removal within 24 hours), primarily through enzymatic biodegradation. Notably, <i>Chlamydomonas reinhardtii</i> achieved complete NEA removal and further metabolized its main product, norethindrone (NET), a more potent neurosteroid, highlighting its biocatalytic efficiency. Further analysis using click chemistry-based chemical proteomics, combined with protein heterologous expression and purification, identified adenylosuccinate lyase has a binding affinity (K<sub>D</sub>) of 4.27 µM for NEA, acting as the key enzyme responsible for the deacetylation of NEA into NET in <i>C. reinhardtii</i>. This identified enzymatic role in phytoplankton is distinct from the β-elimination of fumarate seen in animal counterparts. Using metagenome and metatranscriptome database, we uncovered the global distribution and transcription of genes encoding this lyase across various eukaryotic phyla. Thus, the reconversion of NEA into NET by phytoplankton occurs in diverse Earth environments, which may exacerbate the risks of progestogens such as NEA to ecosystem health and human safety.
DOI: 10.6084/m9.figshare.30518138.v1
title: <b>Chemical Proteomics Revealed Global Occurrence of a Phytoplankton Lyase Capable of Reconverting the Progestogens</b>

description: Endocrine-disrupting chemicals (EDCs), such as progestogens, are generally recognized as environmental pollutants of global concern due to their pervasive and adverse effects on aquatic ecosystems and human health. Despite extensive research on their transformation by animals and bacteria (e.g., <i>Denitratisoma sp.</i>), the interactions between phytoplankton and progestogens remain poorly understood. In this study, we reveal a universal biotransformation of norethindrone acetate (NEA), a representative progestogen, across 18 phylogenetically diverse freshwater and marine phytoplankton species. All species demonstrated the ability to remove NEA from culture media (16.4–99.31% removal within 24 hours), primarily through enzymatic biodegradation. Notably, <i>Chlamydomonas reinhardtii</i> achieved complete NEA removal and further metabolized its main product, norethindrone (NET), a more potent neurosteroid, highlighting its biocatalytic efficiency. Further analysis using click chemistry-based chemical proteomics, combined with protein heterologous expression and purification, identified adenylosuccinate lyase has a binding affinity (K<sub>D</sub>) of 4.27 µM for NEA, acting as the key enzyme responsible for the deacetylation of NEA into NET in <i>C. reinhardtii</i>. This identified enzymatic role in phytoplankton is distinct from the β-elimination of fumarate seen in animal counterparts. Using metagenome and metatranscriptome database, we uncovered the global distribution and transcription of genes encoding this lyase across various eukaryotic phyla. Thus, the reconversion of NEA into NET by phytoplankton occurs in diverse Earth environments, which may exacerbate the risks of progestogens such as NEA to ecosystem health and human safety.
DOI: 10.5281/zenodo.17482306
title: Inflammatory bowel diseases (IBD) gene expression data for the manuscript entitled "Supervised Ensemble Learning Identifies Minimal Consensus Gene Signatures for Crohn's Disease Classification"

description: RNA sequencing reads related to IBD intestinal biopsies were obtained from the Sequence Read Archive (SRA). All samples were uniformly processed using a standardized custom pipeline to ensure consistency across datasets. Quality control was performed with fastp (v1.0.1), followed by alignment to the human reference genome GRCh38.p14 (NCBI RefSeq assembly GCF_000001405.40) using STAR (v2.7.10) with default parameters. Read strandedness was assessed with RSeQC (v5.0.1), and transcript quantification was carried out using Rsubread (v2.22.1).

Publicly available datasets included in this repository: PRJNA248469, PRJNA565216, PRJNA702434, PRJNA728646, PRJNA985602.





ibd_counts.csv – contains gene expression count data from all included studies. To avoid non-interpretable results and reduce computation time, genes not annotated in GO or KEGG were filtered out from this table.




ibd_clin.csv – contains clinical metadata for all samples across all studies.


ibd_dataset.Rdata - contains both tables in a single .Rdata object.

TENTACLES_Workflow.html - contains a demonstration vignette that shows how to work with TENTACLES. ibd_dataset.Rdata is used for this demonstration.
DOI: 10.5281/zenodo.17482307
title: Inflammatory bowel diseases (IBD) gene expression data for the manuscript entitled "Supervised Ensemble Learning Identifies Minimal Consensus Gene Signatures for Crohn's Disease Classification"

description: RNA sequencing reads related to IBD intestinal biopsies were obtained from the Sequence Read Archive (SRA). All samples were uniformly processed using a standardized custom pipeline to ensure consistency across datasets. Quality control was performed with fastp (v1.0.1), followed by alignment to the human reference genome GRCh38.p14 (NCBI RefSeq assembly GCF_000001405.40) using STAR (v2.7.10) with default parameters. Read strandedness was assessed with RSeQC (v5.0.1), and transcript quantification was carried out using Rsubread (v2.22.1).

Publicly available datasets included in this repository: PRJNA248469, PRJNA565216, PRJNA702434, PRJNA728646, PRJNA985602.





ibd_counts.csv – contains gene expression count data from all included studies. To avoid non-interpretable results and reduce computation time, genes not annotated in GO or KEGG were filtered out from this table.




ibd_clin.csv – contains clinical metadata for all samples across all studies.


ibd_dataset.Rdata - contains both tables in a single .Rdata object.

TENTACLES_Workflow.html - contains a demonstration vignette that shows how to work with TENTACLES. ibd_dataset.Rdata is used for this demonstration.
DOI: 10.15468/dl.nmrzrj
title: Occurrence Download

description: A dataset containing 582368 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is one of (Asia, Europe, North America)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is one of (Geodetic datum assumed WGS84, Coordinate rounded, Continent derived from coordinates, Occurrence status inferred from individual count)",
 "OccurrenceStatus is Present",
 "TaxonKey is Cygnus cygnus",
 "Year 1980-2020"
 ]
}

 The dataset includes 582368 records from 286 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012569-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17474181
title: Steam Games

description: El conjunto de datos steam_games contiene información obtenida de la sección Top Sellers de la plataforma Steam.

Incluye 3 567 registros y 11 variables relacionadas con los videojuegos más vendidos, como el título, plataformas disponibles, fecha de lanzamiento, precio original, descuento (%), precio final, imagen, valoración de los usuarios, porcentaje de votos positivos y fecha scraping 

Este dataset puede emplearse para análisis descriptivos o exploratorios sobre tendencias de precios, popularidad de géneros y comportamiento del mercado de videojuegos digitales.
DOI: 10.5281/zenodo.17512135
title: Steam Games

description: El conjunto de datos steam_games contiene información obtenida de la sección Top Sellers de la plataforma Steam.

Incluye 3 567 registros y 11 variables relacionadas con los videojuegos más vendidos, como el título, plataformas disponibles, fecha de lanzamiento, precio original, descuento (%), precio final, imagen, valoración de los usuarios, porcentaje de votos positivos y fecha scraping 

Este dataset puede emplearse para análisis descriptivos o exploratorios sobre tendencias de precios, popularidad de géneros y comportamiento del mercado de videojuegos digitales.
DOI: 10.25345/c5ht2gr2t
title: MassIVE MSV000099724 - Agentic AI Integrated with Scientific Knowledge: Laboratory Validation in Systems Biology
title: Contains intracellular metabolomics data for S. cerevisiae under several different conditions. Metabolomics data generated through a RapidFire+6560 combination.
DOI: 10.5281/zenodo.17512110
title: Pancreatic Cancer Dataset courtesy Angie G

description: Dataset Collected from 

Pancreatic Cancer Dataset
DOI: 10.5281/zenodo.17512111
title: Pancreatic Cancer Dataset courtesy Angie G

description: Dataset Collected from 

Pancreatic Cancer Dataset
DOI: 10.15468/dl.k3wthg
title: Occurrence Download

description: A dataset containing 60661 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Hong Kong",
 "Year is 2022",
 "InstitutionCode is iNaturalist"
 ]
}

 The dataset includes 60661 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012611-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.usc2bs
title: Occurrence Download

description: A dataset containing 4161 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is Asia",
 "OccurrenceStatus is Present",
 "TaxonKey is Tsuga",
 "Year 1000-2025"
 ]
}

 The dataset includes 4161 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012621-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.11583/dtu.30400081
title: Source data for "Tunable and low-noise WSe<sub>2</sub><b> </b>quantum emitters for quantum photonics"

description: Raw data set for the main figures in "Tunable and low-noise WSe<sub>2</sub> quantum emitters for quantum photonics".
DOI: 10.11583/dtu.30400081.v1
title: Source data for "Tunable and low-noise WSe<sub>2</sub><b> </b>quantum emitters for quantum photonics"

description: Raw data set for the main figures in "Tunable and low-noise WSe<sub>2</sub> quantum emitters for quantum photonics".
DOI: 10.15468/dl.ssc7s4
title: Occurrence Download

description: A dataset containing 41 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cassida unimaculata"
 ]
}

 The dataset includes 41 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012623-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.