cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.48472/deposita/orhokd
title: Dados de replicação para: métodos para superação da dormência de sementes da Palmeira Azul (Bismarckia nobilis)

description: Os dados apresentados são das sementes germinadas quando aplicados os tratamentos para a quebra da dormência. Esses tratamentos tiveram o objetivo de quebra da dormência da semente da palmeira azul.
DOI: 10.5281/zenodo.14783212
title: Data for: Managing Retractions and their Afterlife: A Tripartite Framework for Research Datasets

description: This deposit includes supplementary data files for the paper "Managing Retractions and Their Afterlife: A Tripartite Framework for Research Datasets," which has been accepted for presentation at the International Digital Curation Conference (IDCC) 2025 in The Hague, Amsterdam (https://dcc.ac.uk/events/idcc25)

The dataset consists of retraction records crawled via Google Dataset Search queries, along with the selected sample and annotated data resulting from the assessment of these records. A README file is included to provide further details on the CSV files and their structure.

Abstract: Retractions serve as a critical, albeit last-resort, post-publication correction mechanism in scholarly publishing, playing an important role in upholding the integrity of the scientific record. By formally retracting flawed or misleading research, the scientific community mitigates the harm caused by errors or misconduct that may have escaped detection during peer review. While retractions of research articles have been extensively discussed across scientific disciplines and are well-integrated into most publishers' workflows, the retraction of research datasets remains underexplored and rarely implemented. This paper seeks to address this gap by reviewing recent developments in this area, analyzing a sample of publicly available retracted dataset records considering existing recommendations and guidelines, and putting forward a few points for discussions—particularly for cases where datasets have been published and correction is no longer feasible, or when all efforts to amend the dataset have been exhausted. These considerations are framed into three main categories: (1) preventive actions and timely response, (2) purposeful damage control, and (3) community engagement and shared standards. Although still preliminary, this framework aims to help entertain future debates and inform actionable strategies for addressing the unique challenges of managing retracted datasets where scientific rigor has been compromised. By contributing to the discussion on dataset retractions, this work seeks to better equip data curators, repository managers, and other stakeholders with tools to enhance accountability and transparency throughout the data preservation process while also helping to mitigate the error cascade effect in science.
DOI: 10.5281/zenodo.14783213
title: Data for: Managing Retractions and their Afterlife: A Tripartite Framework for Research Datasets

description: This deposit includes supplementary data files for the paper "Managing Retractions and Their Afterlife: A Tripartite Framework for Research Datasets," which has been accepted for presentation at the International Digital Curation Conference (IDCC) 2025 in The Hague, Amsterdam (https://dcc.ac.uk/events/idcc25)

The dataset consists of retraction records crawled via Google Dataset Search queries, along with the selected sample and annotated data resulting from the assessment of these records. A README file is included to provide further details on the CSV files and their structure.

Abstract: Retractions serve as a critical, albeit last-resort, post-publication correction mechanism in scholarly publishing, playing an important role in upholding the integrity of the scientific record. By formally retracting flawed or misleading research, the scientific community mitigates the harm caused by errors or misconduct that may have escaped detection during peer review. While retractions of research articles have been extensively discussed across scientific disciplines and are well-integrated into most publishers' workflows, the retraction of research datasets remains underexplored and rarely implemented. This paper seeks to address this gap by reviewing recent developments in this area, analyzing a sample of publicly available retracted dataset records considering existing recommendations and guidelines, and putting forward a few points for discussions—particularly for cases where datasets have been published and correction is no longer feasible, or when all efforts to amend the dataset have been exhausted. These considerations are framed into three main categories: (1) preventive actions and timely response, (2) purposeful damage control, and (3) community engagement and shared standards. Although still preliminary, this framework aims to help entertain future debates and inform actionable strategies for addressing the unique challenges of managing retracted datasets where scientific rigor has been compromised. By contributing to the discussion on dataset retractions, this work seeks to better equip data curators, repository managers, and other stakeholders with tools to enhance accountability and transparency throughout the data preservation process while also helping to mitigate the error cascade effect in science.
DOI: 10.15468/dl.y2gr3a
title: Occurrence Download

description: A dataset containing 14830243 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 14830243 records from 2714 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014707-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gskrgh
title: Occurrence Download

description: A dataset containing 6624 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Fragaria chiloensis",
 "BasisOfRecord is one of (Specimen, Human Observation, Occurrence evidence, Material sample)",
 "HasCoordinate is true",
 "Country is one of (Canada, United States of America, Mexico)"
 ]
}

 The dataset includes 6624 records from 76 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008230-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eervgf
title: Occurrence Download

description: A dataset containing 15 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ailanthus altissima",
 "Country is Cyprus",
 "HasCoordinate is true"
 ]
}

 The dataset includes 15 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016795-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kwrbcp
title: Occurrence Download

description: A dataset containing 2055 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Culex vishnui"
 ]
}

 The dataset includes 2055 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016796-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2xauh4
title: Occurrence Download

description: A dataset containing 187 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Synodontis schoutedeni"
 ]
}

 The dataset includes 187 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016797-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vnvfb3
title: Occurrence Download

description: A dataset containing 1199 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ailanthus altissima",
 "Country is Czechia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1199 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016798-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yn2jae
title: Occurrence Download

description: A dataset containing 1822 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (China, Chinese Taipei)",
 "TaxonKey is Ardisia japonica"
 ]
}

 The dataset includes 1822 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016799-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zmppxy
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is BOLD:ADC8456"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016800-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/469w-se21
title: "SEAR"

description: "We constructed and released a new dataset comprising both frontal and lateral views with varying degrees of blur. This dataset was used to validate the feasibility of extracting respiratory signals from blurred video."
DOI: 10.15468/dl.jpnkzn
title: Occurrence Download

description: A dataset containing 187 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ailanthus altissima",
 "Country is Denmark",
 "HasCoordinate is true"
 ]
}

 The dataset includes 187 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016801-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5hct8n
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hypophthalmichthys molitrix",
 "Country is Slovenia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016802-250717081556266/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.29587319.v1
title: tumor_immunotherapy

description: transciptome information of immunotherapy
DOI: 10.15468/dl.vgev65
title: Occurrence Download

description: A dataset containing 55 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Systomus pleurotaenia"
 ]
}

 The dataset includes 55 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016803-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bwu5vs
title: Occurrence Download

description: A dataset containing 90 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ailanthus altissima",
 "Country is Georgia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 90 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016805-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.86e5gm
title: Occurrence Download

description: A dataset containing 34378 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ailanthus altissima",
 "Country is France",
 "HasCoordinate is true"
 ]
}

 The dataset includes 34378 records from 742 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016804-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.y2sfbx
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Barbus pleurotaenia"
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016806-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16202410
title: Quantum Analogue of Dzhanibekov Effect in Spin Systems: Theory and Computational Framework

description: We establish a fundamental correspondence between the classical Dzhanibekov effect and quantum spin dynamics in anisotropic magnetic environments. The theory predicts spontaneous spin flips when: (1) the effective field has intermediate anisotropy, (2) initial spin orientation aligns with theunstable axis. Three extensions are developed: dissipative dynamics, collective synchronization, and quantum tunneling corrections. Numericalprotocols for supercomputer implementation are provided, enabling experimental verification in quantum materials and spintronic devices.
DOI: 10.5281/zenodo.16202411
title: Quantum Analogue of Dzhanibekov Effect in Spin Systems: Theory and Computational Framework

description: We establish a fundamental correspondence between the classical Dzhanibekov effect and quantum spin dynamics in anisotropic magnetic environments. The theory predicts spontaneous spin flips when: (1) the effective field has intermediate anisotropy, (2) initial spin orientation aligns with theunstable axis. Three extensions are developed: dissipative dynamics, collective synchronization, and quantum tunneling corrections. Numericalprotocols for supercomputer implementation are provided, enabling experimental verification in quantum materials and spintronic devices.
DOI: 10.5281/zenodo.16202322
title: Unified FLUXes (UFLUX) emulator

description: Process-based biosphere models, which formulate biophysical ecosystem processes, provide a mechanistic framework for understanding terrestrial carbon dynamics. In contrast, data-driven approaches—e.g., upscaling eddy covariance (EC) fluxes using satellite observations and machine learning—offer empirical estimates. These complementary methods often diverge significantly, particularly in estimating global photosynthetic uptake and ecosystem respiration, with discrepancies exceeding 50 PgC and highlighting persistent uncertainties.To bridge this gap, we adopt a hybrid strategy that embeds physiological understanding via semi-empirical models, refines it with EC fluxes constrained by machine learning, and integrates process-based allocation to resolve component fluxes. This process-informed hybrid approach links ecological knowledge with predictive models, enabling generalisation beyond flux tower sites and supporting the development of new insights.We assess global carbon dynamics over the past two decades, applying Bayesian inference to evaluate climate impacts on land carbon processes. Using the Unified FLUXes (UFLUX) emulating the carbon allocations of process-based models, our study delivers the first observational and process-informed hybrid assessment of global carbon flux and stock changes. Notably, while gross carbon uptake is consistent across methods (~130 PgC in 2022, increasing by 0.4 annually), respiration estimates diverge—from 6 PgC in process-based models to 26 in conventional upscaling, and 16 in our hybrid model—revealing structural limitations in respiration parameterisation.Improved representation of respiratory processes is essential to capture the competing roles of photosynthesis and respiration under climate change. Despite rising global carbon fluxes and biomass stocks, tipping point risks remain: in tropical regions, increased photosynthesis (0.1 PgC) is offset by rising respiration (0.05 PgC).
DOI: 10.5281/zenodo.16202323
title: Unified FLUXes (UFLUX) emulator

description: Process-based biosphere models, which formulate biophysical ecosystem processes, provide a mechanistic framework for understanding terrestrial carbon dynamics. In contrast, data-driven approaches—e.g., upscaling eddy covariance (EC) fluxes using satellite observations and machine learning—offer empirical estimates. These complementary methods often diverge significantly, particularly in estimating global photosynthetic uptake and ecosystem respiration, with discrepancies exceeding 50 PgC and highlighting persistent uncertainties.To bridge this gap, we adopt a hybrid strategy that embeds physiological understanding via semi-empirical models, refines it with EC fluxes constrained by machine learning, and integrates process-based allocation to resolve component fluxes. This process-informed hybrid approach links ecological knowledge with predictive models, enabling generalisation beyond flux tower sites and supporting the development of new insights.We assess global carbon dynamics over the past two decades, applying Bayesian inference to evaluate climate impacts on land carbon processes. Using the Unified FLUXes (UFLUX) emulating the carbon allocations of process-based models, our study delivers the first observational and process-informed hybrid assessment of global carbon flux and stock changes. Notably, while gross carbon uptake is consistent across methods (~130 PgC in 2022, increasing by 0.4 annually), respiration estimates diverge—from 6 PgC in process-based models to 26 in conventional upscaling, and 16 in our hybrid model—revealing structural limitations in respiration parameterisation.Improved representation of respiratory processes is essential to capture the competing roles of photosynthesis and respiration under climate change. Despite rising global carbon fluxes and biomass stocks, tipping point risks remain: in tropical regions, increased photosynthesis (0.1 PgC) is offset by rising respiration (0.05 PgC).
DOI: 10.15468/dl.peee7u
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Puntius pleurotaenia"
 ]
}

 The dataset includes 5 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016808-250717081556266/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.29587319.v2
title: tumor_immunotherapy

description: transciptome information of immunotherapy
DOI: 10.15468/dl.w967ek
title: Occurrence Download

description: A dataset containing 67 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mimosa diplotricha",
 "Country is Australia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 67 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016810-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gnsy92
title: Occurrence Download

description: A dataset containing 11233 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ailanthus altissima",
 "Country is Germany",
 "HasCoordinate is true"
 ]
}

 The dataset includes 11233 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016809-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fhjwq6
title: Occurrence Download

description: A dataset containing 145 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Guamatela"
 ]
}

 The dataset includes 145 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016811-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uvu3jj
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is BOLD:AEG6088"
 ]
}

 The dataset includes 10 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016813-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e4qjr6
title: Occurrence Download

description: A dataset containing 26245 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mimosa pigra",
 "Country is Australia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 26245 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016814-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mp2rnw
title: Occurrence Download

description: A dataset containing 508 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ailanthus altissima",
 "Country is Greece",
 "HasCoordinate is true"
 ]
}

 The dataset includes 508 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016815-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15601930
title: IMC data for PDAC Rapid Autopsy Samples - Cho Y et al. (Raw MCD)

description: Raw (.MCD) files associated with Cho Y et al. manuscript entitled, "Modeling cellular influence delineates functionally relevant cellular neighborhoods in primary and metastatic pancreatic ductal adenocarcinoma".

Processed and annotated single-cell data (.RDS) are located: https://doi.org/10.5281/zenodo.15596960

Code for analysis is located: https://github.com/DeshpandeLab/Spatial_Influence
DOI: 10.5281/zenodo.15601931
title: IMC data for PDAC Rapid Autopsy Samples - Cho Y et al. (Raw MCD)

description: Raw (.MCD) files associated with Cho Y et al. manuscript entitled, "Modeling cellular influence delineates functionally relevant cellular neighborhoods in primary and metastatic pancreatic ductal adenocarcinoma".

Processed and annotated single-cell data (.RDS) are located: https://doi.org/10.5281/zenodo.15596960

Code for analysis is located: https://github.com/DeshpandeLab/Spatial_Influence
DOI: 10.5281/zenodo.15596960
title: IMC data for PDAC Rapid Autopsy Samples - Cho Y et al. (Processed)

description: Processed and annotated single-cell data (.RDS) associated with Cho Y et al. manuscript entitled, "Modeling cellular influence delineates functionally relevant cellular neighborhoods in primary and metastatic pancreatic ductal adenocarcinoma".

Raw (.MCD) files are located: https://doi.org/10.5281/zenodo.15601931

Code for analysis is located: https://github.com/DeshpandeLab/Spatial_Influence
DOI: 10.5281/zenodo.15596959
title: IMC data for PDAC Rapid Autopsy Samples - Cho Y et al. (Processed)

description: Processed and annotated single-cell data (.RDS) associated with Cho Y et al. manuscript entitled, "Modeling cellular influence delineates functionally relevant cellular neighborhoods in primary and metastatic pancreatic ductal adenocarcinoma".

Raw (.MCD) files are located: https://doi.org/10.5281/zenodo.15601931

Code for analysis is located: https://github.com/DeshpandeLab/Spatial_Influence