cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/mb9zc8j7jg
title: Nursing Leadership and Governance in Health Systems (2010–2025): Meta-Analytic and Policy Evidence Dataset

description: This dataset accompanies the mixed-methods meta-analysis “Nursing Leadership and Governance in Health Systems (2010–2025).”

It consolidates data from 100 global studies examining the influence of nursing leadership and governance interventions on policy participation, accountability, and organizational reform within health systems.

The quantitative component includes standardized mean differences (SMDs), odds ratios (ORs), confidence intervals, heterogeneity (I²) statistics, and study-level quality scores derived from randomized and non-randomized designs.

The qualitative component provides NVivo-based thematic codes structured around the Walt & Gilson Policy Triangle Framework (context, content, process, actors), capturing leadership practices, decision-making pathways, and stakeholder engagement.

All information was extracted from peer-reviewed publications between 2010 and 2025. No identifiable participant data are included.

Ethics approval: Discaya Research Ethics Committee (Ref. No. DREC-NURS-2025-01).
DOI: 10.17632/mb9zc8j7jg.1
title: Nursing Leadership and Governance in Health Systems (2010–2025): Meta-Analytic and Policy Evidence Dataset

description: This dataset accompanies the mixed-methods meta-analysis “Nursing Leadership and Governance in Health Systems (2010–2025).”

It consolidates data from 100 global studies examining the influence of nursing leadership and governance interventions on policy participation, accountability, and organizational reform within health systems.

The quantitative component includes standardized mean differences (SMDs), odds ratios (ORs), confidence intervals, heterogeneity (I²) statistics, and study-level quality scores derived from randomized and non-randomized designs.

The qualitative component provides NVivo-based thematic codes structured around the Walt & Gilson Policy Triangle Framework (context, content, process, actors), capturing leadership practices, decision-making pathways, and stakeholder engagement.

All information was extracted from peer-reviewed publications between 2010 and 2025. No identifiable participant data are included.

Ethics approval: Discaya Research Ethics Committee (Ref. No. DREC-NURS-2025-01).
DOI: 10.15468/dl.czr4dv
title: Occurrence Download

description: A dataset containing 24441 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Loxodonta africana"
 ]
}

 The dataset includes 24441 records from 161 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057785-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8uv2bc
title: Occurrence Download

description: A dataset containing 196 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tragopogon porrifolius",
 "Country is Sweden",
 "HasCoordinate is true"
 ]
}

 The dataset includes 196 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057787-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/hrswr6vh5t
title: ‘Native’ English teachers navigating native-speakerism: Investigating the intersection of identity, beliefs, and emotions through narrative inquiry

description: This database contains the data collection methods used in the project (Appendices A to D), the participants' integral narratives published with their informed consent (Appendices E and F), and the authors' narratives (Appendices G and H). The latter are included to enhance the transparency of study by showcasing the stories and identities of the authors, and we hope that this would also be a fair way to repay our participants for allowing us to probe into their personal lives.

Appendix A contains the guidelines that helped the participants structure their narratives in a way that would address the research questions of the study.

Appendix B contains the interview guides for both participants. Although the two guides follow the same structure and order, some questions were tailored specifically for either Clara or Grace. This was because one narrative contained ideas not found in the other, or because the narrative contained ambiguous terms or statements which required further clarification.

Appendices C and D are PowerPoint Slides which were used during the interviews with Clara and Grace respectively. The slides acted as visual stimuli or aids on which to ground questions on specific parts of the participants' narratives.

Appendices E and F contain the participants' narratives (respectively pseudonymized as Clara and Grace). These were the main data sources for the project, and we include them in their entirety because we believe in their emotional value as stand-alone works, which could resonate with other 'native' English teachers around the world. We also hope that this inclusion may enhance the transparency of our research. The interview transcripts are not included in this dataset.

Appendices G and H respectively contain Zhewei and Paolo's narratives. We included them as a token of our gratitude for Clara and Grace, who have willingly confided in us, allowing us to investigate their past experiences and emotional lives, and consented to make their narratives available to a wide audience. We also hope that this inclusion will enhance the transparency of the project by allowing readers to understand the human beings involved in the research project.
DOI: 10.17632/hrswr6vh5t.1
title: ‘Native’ English teachers navigating native-speakerism: Investigating the intersection of identity, beliefs, and emotions through narrative inquiry

description: This database contains the data collection methods used in the project (Appendices A to D), the participants' integral narratives published with their informed consent (Appendices E and F), and the authors' narratives (Appendices G and H). The latter are included to enhance the transparency of study by showcasing the stories and identities of the authors, and we hope that this would also be a fair way to repay our participants for allowing us to probe into their personal lives.

Appendix A contains the guidelines that helped the participants structure their narratives in a way that would address the research questions of the study.

Appendix B contains the interview guides for both participants. Although the two guides follow the same structure and order, some questions were tailored specifically for either Clara or Grace. This was because one narrative contained ideas not found in the other, or because the narrative contained ambiguous terms or statements which required further clarification.

Appendices C and D are PowerPoint Slides which were used during the interviews with Clara and Grace respectively. The slides acted as visual stimuli or aids on which to ground questions on specific parts of the participants' narratives.

Appendices E and F contain the participants' narratives (respectively pseudonymized as Clara and Grace). These were the main data sources for the project, and we include them in their entirety because we believe in their emotional value as stand-alone works, which could resonate with other 'native' English teachers around the world. We also hope that this inclusion may enhance the transparency of our research. The interview transcripts are not included in this dataset.

Appendices G and H respectively contain Zhewei and Paolo's narratives. We included them as a token of our gratitude for Clara and Grace, who have willingly confided in us, allowing us to investigate their past experiences and emotional lives, and consented to make their narratives available to a wide audience. We also hope that this inclusion will enhance the transparency of the project by allowing readers to understand the human beings involved in the research project.
DOI: 10.17632/ts4brdbx2h
title: Accompanying data to "Are springtime Arctic ozone columns predictable from wintertime conditions?"

description: These datasets represent already postprocessed reanalysis outputs to reproduce figures in the manuscript.
DOI: 10.17632/ts4brdbx2h.1
title: Accompanying data to "Are springtime Arctic ozone columns predictable from wintertime conditions?"

description: These datasets represent already postprocessed reanalysis outputs to reproduce figures in the manuscript.
DOI: 10.15468/dl.ypq7p9
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Galliformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((-150 -90,-120 -90,-120 -60,-150 -60,-150 -90))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057786-250920141307145/datasets/export for details.
DOI: 10.17632/v3tbnxpgm8
title: Imagined Speech eeg data

description: • Raw EEG files (.edf): Continuous 64-channel recordings with event markers.
• Processed data (.mat): Trial-level epoched data (2.5 s segments), formatted for MATLAB/MNE analysis.
• Event logs (.csv): Trial-by-trial metadata, including word label, cue type (visual, auditory, combined, or self-generated), condition, and session number.

• All data files, including the raw recordings, can be accessed at the Mendeley Data repository. All files are contained in a main folder called “Imagined Speech eeg data”, organized and named. The final dataset folder is composed of 9 subfolders containing the session raw data, each one corresponding to a different participant. There is an additional folder, containing files obtained after the proposed processing: EEG data in a mat file format. We now proceed to describe the contents of each one of these five files along with the raw data. 
• Raw data. The raw data file contains the continuous recording of the entire session for all 64 channels. The .edf file contains all the EEG data and the evens with further information about the recording sampling rate, the names of the channels and the recording filters, among other information. The raw events are obtained from the raw data file and contain the tags sent by PC1, synchronized with the recorded signals The raw events are stored in a csv file, where the first column contains the word information, the second has the cue type information, the third column contains the trigger number.
DOI: 10.17632/v3tbnxpgm8.1
title: Imagined Speech eeg data

description: • Raw EEG files (.edf): Continuous 64-channel recordings with event markers.
• Processed data (.mat): Trial-level epoched data (2.5 s segments), formatted for MATLAB/MNE analysis.
• Event logs (.csv): Trial-by-trial metadata, including word label, cue type (visual, auditory, combined, or self-generated), condition, and session number.

• All data files, including the raw recordings, can be accessed at the Mendeley Data repository. All files are contained in a main folder called “Imagined Speech eeg data”, organized and named. The final dataset folder is composed of 9 subfolders containing the session raw data, each one corresponding to a different participant. There is an additional folder, containing files obtained after the proposed processing: EEG data in a mat file format. We now proceed to describe the contents of each one of these five files along with the raw data. 
• Raw data. The raw data file contains the continuous recording of the entire session for all 64 channels. The .edf file contains all the EEG data and the evens with further information about the recording sampling rate, the names of the channels and the recording filters, among other information. The raw events are obtained from the raw data file and contain the tags sent by PC1, synchronized with the recorded signals The raw events are stored in a csv file, where the first column contains the word information, the second has the cue type information, the third column contains the trigger number.
DOI: 10.17632/mkt2zjb7pr
title: IDO in respiratory distress patients

description: Data linked to the proposed publication: Diagnostic accuracy of Kynurenine to tryptophan ratio in peripheral blood to distinguish Tuberculosis from COVID-19, PCP or CAP.

Tuberculosis (TB) kills almost as many people annually as COVID-19 killed in 2020, yet remains challenging to diagnose. The kynurenine (kyn)/tryptophan (trp) ratio, an indicator of indoleamine 2,3-dioxygenase activity, is of interest as a host biomarker of respiratory distress. We calculated the diagnostic potential of the kyn/trp ratio to distinguish TB from COVID-19, community-acquired pneumonia (CAP), Pneumocystis pneumonia (PCP) and non-communicable lung disease. We measured the kyn/trp ratio by ELISA on peripheral blood along with C-reactive protein (CRP) values as a comparator assay of the host immune response. An elevated kyn/trp ratio was seen in individuals with TB, COVID-19, CAP and PCP but not in those with non-communicable diseases. Individuals with TB had the highest kyn/trp ratio. At a cut-off value of 0.165, the kyn/trp ratio was able to differentiate individuals with TB disease from healthy control subjects with a sensitivity of 72.5%, specificity of 100.0%, positive predictive value (PPV) of 100.0% and negative predictive value (NPV) of 93.9%, and from patients with other aetiologies of respiratory distress with a sensitivity of 72.5%, specificity of 74.8%, PPV of 40.5% and NPV of 92.0%. The kyn/trp ratio performed better than CRP for distinguishing TB disease from other respiratory illnesses with the area under the receiver operating curve of 0.76 compared with 0.61. The kyn/trp ratio can be used as an adjunctive blood-based diagnostic test for TB.
DOI: 10.17632/mkt2zjb7pr.2
title: IDO in respiratory distress patients

description: Data linked to the proposed publication: Diagnostic accuracy of Kynurenine to tryptophan ratio in peripheral blood to distinguish Tuberculosis from COVID-19, PCP or CAP.

Tuberculosis (TB) kills almost as many people annually as COVID-19 killed in 2020, yet remains challenging to diagnose. The kynurenine (kyn)/tryptophan (trp) ratio, an indicator of indoleamine 2,3-dioxygenase activity, is of interest as a host biomarker of respiratory distress. We calculated the diagnostic potential of the kyn/trp ratio to distinguish TB from COVID-19, community-acquired pneumonia (CAP), Pneumocystis pneumonia (PCP) and non-communicable lung disease. We measured the kyn/trp ratio by ELISA on peripheral blood along with C-reactive protein (CRP) values as a comparator assay of the host immune response. An elevated kyn/trp ratio was seen in individuals with TB, COVID-19, CAP and PCP but not in those with non-communicable diseases. Individuals with TB had the highest kyn/trp ratio. At a cut-off value of 0.165, the kyn/trp ratio was able to differentiate individuals with TB disease from healthy control subjects with a sensitivity of 72.5%, specificity of 100.0%, positive predictive value (PPV) of 100.0% and negative predictive value (NPV) of 93.9%, and from patients with other aetiologies of respiratory distress with a sensitivity of 72.5%, specificity of 74.8%, PPV of 40.5% and NPV of 92.0%. The kyn/trp ratio performed better than CRP for distinguishing TB disease from other respiratory illnesses with the area under the receiver operating curve of 0.76 compared with 0.61. The kyn/trp ratio can be used as an adjunctive blood-based diagnostic test for TB.
DOI: 10.15468/dl.kntrtx
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Caprimulgiformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((30 -90,60 -90,60 -60,30 -60,30 -90))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057788-250920141307145/datasets/export for details.
DOI: 10.15468/dl.gz52pq
title: Occurrence Download

description: A dataset containing 3707 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Ilex macropoda)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 3707 records from 89 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057789-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/9ynwrjw3rk
title: Puberty as a Superspreader of Mutations Elevating Tumor Long-term Risk in Breast Tissue

description: This repository includes the VCF-level data needed to reproduce the figure(s) from the paper "Puberty as a Superspreader of Mutations Elevating Tumor Long-term Risk in Breast Tissue", including downstream PTA samples analysis (downstream_PTA_analysis.sh in Github repo) and downstream WGS samples analysis (downstream_WGS_analysis.sh in Github repo). To reproduce the analysis, download the Breast_1 and Breast_2 folders and move them to the /home_dir/3_Output directory on your machine.
DOI: 10.17632/9ynwrjw3rk.1
title: Puberty as a Superspreader of Mutations Elevating Tumor Long-term Risk in Breast Tissue

description: This repository includes the VCF-level data needed to reproduce the figure(s) from the paper "Puberty as a Superspreader of Mutations Elevating Tumor Long-term Risk in Breast Tissue", including downstream PTA samples analysis (downstream_PTA_analysis.sh in Github repo) and downstream WGS samples analysis (downstream_WGS_analysis.sh in Github repo). To reproduce the analysis, download the Breast_1 and Breast_2 folders and move them to the /home_dir/3_Output directory on your machine.
DOI: 10.5281/zenodo.15555144
title: DATASET: Proyectos de investigación Generación de Conocimiento del Plan Nacional I+D+i de España
title: DATASET: Research projects National R&D&I Plan Spain

description: Este repositorio contiene un dataset de proyectos de investigación presentados en el marco del Plan Nacional de I+D desde 2004 hasta 2023. El dataset aglutina y harmoniza la información presente en las diferentes resoluciones de convocatorias publicadas en la web de la Agencia Estatal de Investigación. El dataset se presenta en profundidad en el artículo el artículo "Dos décadas de financiación competitiva en España: un análisis longitudinal del instrumento de financiación de proyectos de investigación del Plan Nacional de I+D+i (2004-2023)".

Los principales archivos del repositorio son:



proyectos_plan_nacional_2004_2023.csv: este dataset contiene proyectos de investigación presentados en el marco del Plan Nacional de I+D desde 2004 hasta 2023.

proyectos_resoluciones_fuentes.csv: este dataset contiene las fuentes de las que se ha extraído la información para la construcción del dataset de proyectos de investigación.

diccionario_areas_tematicas.csv: este dataset contiene el diccionario de áreas temáticas en las que se clasifican los proyectos de investigación.


----------------------------------------------------------------------------------------------------------------------------------------------------

This repository contains a dataset of research projects submitted under the National R&D Plan from 2004 to 2023. The dataset brings together and harmonizes the information present in the different resolutions of calls published on the website of the State Research Agency. The dataset is presented in depth in the article “Two decades of competitive funding in Spain: a longitudinal analysis of the research project funding instrument of the National R&D&I Plan (2004-2023)”.

The main repository archives are:



proyectos_plan_nacional_2004_2023.csv: This dataset contains a list of research projects submitted under the National R&D Plan from 2004 to 2023. It contains both accepted proposals (2004-2023) and rejected proposals (2009-2023).

proyectos_resoluciones_fuentes.csv: This dataset contains the sources from which the information for the construction of the research projects dataset has been extracted.

diccionario_areas_tematicas.csv: This dataset contains the dictionary of thematic areas in which research projects are classified.
DOI: 10.5281/zenodo.15555143
title: DATASET: Proyectos de investigación Generación de Conocimiento del Plan Nacional I+D+i de España
title: DATASET: Research projects National R&D&I Plan Spain

description: Este repositorio contiene un dataset de proyectos de investigación presentados en el marco del Plan Nacional de I+D desde 2004 hasta 2023. El dataset aglutina y harmoniza la información presente en las diferentes resoluciones de convocatorias publicadas en la web de la Agencia Estatal de Investigación. El dataset se presenta en profundidad en el artículo el artículo "Dos décadas de financiación competitiva en España: un análisis longitudinal del instrumento de financiación de proyectos de investigación del Plan Nacional de I+D+i (2004-2023)".

Los principales archivos del repositorio son:



proyectos_plan_nacional_2004_2023.csv: este dataset contiene proyectos de investigación presentados en el marco del Plan Nacional de I+D desde 2004 hasta 2023.

proyectos_resoluciones_fuentes.csv: este dataset contiene las fuentes de las que se ha extraído la información para la construcción del dataset de proyectos de investigación.

diccionario_areas_tematicas.csv: este dataset contiene el diccionario de áreas temáticas en las que se clasifican los proyectos de investigación.


----------------------------------------------------------------------------------------------------------------------------------------------------

This repository contains a dataset of research projects submitted under the National R&D Plan from 2004 to 2023. The dataset brings together and harmonizes the information present in the different resolutions of calls published on the website of the State Research Agency. The dataset is presented in depth in the article “Two decades of competitive funding in Spain: a longitudinal analysis of the research project funding instrument of the National R&D&I Plan (2004-2023)”.

The main repository archives are:



proyectos_plan_nacional_2004_2023.csv: This dataset contains a list of research projects submitted under the National R&D Plan from 2004 to 2023. It contains both accepted proposals (2004-2023) and rejected proposals (2009-2023).

proyectos_resoluciones_fuentes.csv: This dataset contains the sources from which the information for the construction of the research projects dataset has been extracted.

diccionario_areas_tematicas.csv: This dataset contains the dictionary of thematic areas in which research projects are classified.
DOI: 10.17632/32zydvmzjd
title: Douglas-fir and Norway spruce tree-ring data from three sites in Slovenia

description: Data consists of two files:
1. TRW-chronologies-raw-std-res.xlsx - contains tree-ring widths in raw and standardised form
2. All-sites-dug-spru-pointer years.xlsx
In files DF stands for Douglas fir and NS for Norway spruce
DOI: 10.17632/32zydvmzjd.2
title: Douglas-fir and Norway spruce tree-ring data from three sites in Slovenia

description: Data consists of two files:
1. TRW-chronologies-raw-std-res.xlsx - contains tree-ring widths in raw and standardised form
2. All-sites-dug-spru-pointer years.xlsx
In files DF stands for Douglas fir and NS for Norway spruce