cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.29424152.v2
title: Employee Wellbeing as a Competitive Business Advantage

description: Employee wellbeing has become a strategic priority for organisations aiming to secure a competitive advantage in the post-pandemic business environment. This paper explores how investing in employee wellbeing—covering physical health, mental health, work-life balance, and an inclusive workplace culture—can deliver positive returns across key business areas such as performance, innovation, productivity, and talent management. Drawing on recent research and industry case studies, particularly from the marketing sector, the analysis shows that companies with strong wellbeing programmes often outperform competitors through higher profitability, enhanced creativity, greater productivity, and improved employee retention. Post-pandemic trends, including the growth of remote and hybrid work, increased emphasis on mental health support, flexible working arrangements, and diversity, equity, and inclusion (DEI) initiatives, are examined as critical components of modern employee wellbeing strategies. The findings highlight that a genuine commitment to employee wellbeing not only improves employees’ quality of work life but also strengthens organisational resilience, innovation capacity, and employer branding, ultimately serving as a sustainable source of competitive advantage.
DOI: 10.6084/m9.figshare.29424152.v1
title: Zena Zwayyed - Employee Wellbeing as a Competitive Business Advantage

description: Employee wellbeing has become a strategic priority for organisations aiming to secure a competitive advantage in the post-pandemic business environment. This paper explores how investing in employee wellbeing—covering physical health, mental health, work-life balance, and an inclusive workplace culture—can deliver positive returns across key business areas such as performance, innovation, productivity, and talent management. Drawing on recent research and industry case studies, particularly from the marketing sector, the analysis shows that companies with strong wellbeing programmes often outperform competitors through higher profitability, enhanced creativity, greater productivity, and improved employee retention. Post-pandemic trends, including the growth of remote and hybrid work, increased emphasis on mental health support, flexible working arrangements, and diversity, equity, and inclusion (DEI) initiatives, are examined as critical components of modern employee wellbeing strategies. The findings highlight that a genuine commitment to employee wellbeing not only improves employees’ quality of work life but also strengthens organisational resilience, innovation capacity, and employer branding, ultimately serving as a sustainable source of competitive advantage.
DOI: 10.15468/dl.23sp3p
title: Occurrence Download

description: A dataset containing 11714 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Galium saxatile L.",
 "Geometry POLYGON((-8.00174339329464 54.1998526673513, 0.202120938926891 54.1998526673513, 0.202120938926891 61.2628565887411, -8.00174339329464 61.2628565887411, -8.00174339329464 54.1998526673513))",
 "CoordinateUncertaintyInMeters is 0,101",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 11714 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071518-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zatntt
title: Occurrence Download

description: A dataset containing 41 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (China, India, Bangladesh, Nepal, Pakistan, Bhutan, Myanmar, Afghanistan)",
 "TaxonKey is Lethe sinorix (Hewitson, 1863)"
 ]
}

 The dataset includes 41 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071519-250525065834625/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.29424164
title: Visualscenes1_dataset_mjs

description: The beta images of the visual scenes 1 dataset used for validating the moral judgment signature (MJS). For details, see Hopp et al. 2025 BioRxiv.
DOI: 10.6084/m9.figshare.29424164.v1
title: Visualscenes1_dataset_mjs

description: The beta images of the visual scenes 1 dataset used for validating the moral judgment signature (MJS). For details, see Hopp et al. 2025 BioRxiv.
DOI: 10.15468/dl.zg8n9w
title: Occurrence Download

description: A dataset containing 21642 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Portugal",
 "TaxonKey is Testudines"
 ]
}

 The dataset includes 21642 records from 68 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071521-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11048418
title: A Melanoma Patient Minimal Dataset for Cancer
title: MDC Melanoma
DOI: 10.15468/dl.nrz7n5
title: Occurrence Download

description: A dataset containing 55 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Calochortus simulans (Hoover) Munz"
 ]
}

 The dataset includes 55 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071523-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2h27t4
title: Occurrence Download

description: A dataset containing 15 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Calochortus raichei Farwig & V.Girard"
 ]
}

 The dataset includes 15 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071522-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3kf8n3
title: Occurrence Download

description: A dataset containing 226 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "Geometry POLYGON((-8.77389 39.87085,-8.60344 39.87085,-8.60344 39.98537,-8.77389 39.98537,-8.77389 39.87085))",
 "HasGeospatialIssue is false",
 "IucnRedListCategory is one of (EX, EW, CR, EN, VU, NT, LC)",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 226 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071525-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a8tbet
title: Occurrence Download

description: A dataset containing 6777 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Hexaplex trunculus (Linnaeus, 1758), Indigofera tinctoria L.)"
 ]
}

 The dataset includes 6777 records from 251 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071526-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9meaq5
title: Occurrence Download

description: A dataset containing 1620 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is NZL",
 "TaxonKey is Mus musculus Linnaeus, 1758"
 ]
}

 The dataset includes 1620 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071527-250525065834625/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.29424176
title: Visualscenes2_dataset_mjs

description: The beta images of the visual scenes 2 dataset used for validating the moral judgment signature (MJS). For details, see Hopp et al. 2025 BioRxiv.
DOI: 10.6084/m9.figshare.29424176.v1
title: Visualscenes2_dataset_mjs

description: The beta images of the visual scenes 2 dataset used for validating the moral judgment signature (MJS). For details, see Hopp et al. 2025 BioRxiv.
DOI: 10.34810/data311
title: Apertium Monolingual Lexicon to LMF converter

description: This tool generates the LMF version of Apertium monolingual lexicons. The script takes as input an expanded monolingual Apertium lexicon (generated using: lt-expand apertium.dix &gt; apertium.expanded) and generates the corresponding LMF version. In the Apertium expended lexicons, the first tag corresponds to the part of speech. The rest of tags (all enclosed in angle brackets) encode additional information depending on the lemma and PoS tag. Run "perl ApertiumMonolingual2LMF.pl --help" to get more information.
DOI: 10.5522/04/29356586
title: Datasets for <i>Personalizing Federated Instrument Segmentation With Visual Trait Priors in Robotic Surgery</i>

description: Preprocessed EndoVis 2017 [1], EndoVis 2018 [2], and SAR-RARP [3] datasets for federated instrument segmentation.<br>[1] M. Allan, “2017 robotic instrument segmentation challenge,” 2019, arXiv:1902.06426.[2] M. Allan, “2018 robotic scene segmentation challenge,” 2020, arXiv:2001.11190.[3] B. Van Amsterdam, “Gesture recognition in robotic surgery with multimodal attention,” <i>IEEE Trans. Med. Imag.</i>, vol. 41, no. 7, pp. 1677–1687, Jul. 2022.
DOI: 10.5522/04/29356586.v1
title: Datasets for <i>Personalizing Federated Instrument Segmentation With Visual Trait Priors in Robotic Surgery</i>

description: Preprocessed EndoVis 2017 [1], EndoVis 2018 [2], and SAR-RARP [3] datasets for federated instrument segmentation.<br>[1] M. Allan, “2017 robotic instrument segmentation challenge,” 2019, arXiv:1902.06426.[2] M. Allan, “2018 robotic scene segmentation challenge,” 2020, arXiv:2001.11190.[3] B. Van Amsterdam, “Gesture recognition in robotic surgery with multimodal attention,” <i>IEEE Trans. Med. Imag.</i>, vol. 41, no. 7, pp. 1677–1687, Jul. 2022.
DOI: 10.15468/dl.jgq6ae
title: Occurrence Download

description: A dataset containing 107 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is NZL",
 "OccurrenceStatus is Present",
 "TaxonKey is Ovis aries Linnaeus, 1758"
 ]
}

 The dataset includes 107 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071528-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vdpp93
title: Occurrence Download

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

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071531-250525065834625/datasets/export for details.
DOI: 10.15468/dl.u4vmvs
title: Occurrence Download

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

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071532-250525065834625/datasets/export for details.
DOI: 10.5281/zenodo.15538314
title: ToxHabits-NER: A Gold-Standard annotated Dataset for Named Entity Recognition in Toxic Habits context.

description: ToxHabits-NER stands for Toxic Habits Named Entity Recognition. It is a gold-standard annotated dataset focused on the detection and classification of toxic habit mentions — such as tobacco use, alcohol consumption, and illicit drug use — within clinical texts written in Spanish.

This repository includes the corpus' train and test sets in multiple formats. The annotations cover mentions of toxic habits, associated behaviors, and contextual cues relevant for clinical and epidemiological studies. For more information, please check the attached README file.

ToxHabits-NER was developed by the Barcelona Supercomputing Center's NLP for Biomedical Information Analysis team. It is intended as a resource to advance research on toxic habit extraction and normalization tasks from medical documents.

This dataset is part of the ToxHabits Shared Task of BioCreative IX. 

For more information on the corpus, annotation scheme, and usage instructions, please visit: [link to your project page if you have one, or Zenodo landing page].

Please cite if you use this resource:



Salvador Lima-López, Wesam Alnabki, Gabriel Vayá-Abad, and Martin Krallinger.ToxHabits-NER: A Gold-Standard Annotated Dataset for Named Entity Recognition in Toxic Habits Context.Zenodo. 2025.DOI: 10.5281/zenodo.15304758.


@misc{toxhabitsner,    title={ToxHabits-NER: A Gold-Standard Annotated Dataset for Named Entity Recognition in Toxic Habits Context},    author={Lima-López, Salvador and Alnabki, Wesam and Vayá-Abad, Gabriel and Krallinger, Martin},    year={2025},    publisher={Zenodo},    doi={YOUR_DOI_HERE},    url={https://doi.org/10.5281/zenodo.15304758}

Related Links:





Annotation Guidelines (Spanish): https://doi.org/10.5281/zenodo.15753952



License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Contact

If you have any questions or suggestions, please contact us at:

- Wesam Alnabki (<wesam [dot] alnabki [dot] bsc [at] gmail [dot] com>)

- Gabriel Vaya (<gvaya [dot] bsc [at] gmail [dot] com>)
DOI: 10.15468/dl.d4cesq
title: Occurrence Download

description: A dataset containing 4795 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Hexaplex trunculus (Linnaeus, 1758)"
 ]
}

 The dataset includes 4795 records from 87 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0071533-250525065834625/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.28796177
title: Data for manuscript: "Contrasting mechanisms dictate climate sensitivities in response to tropical versus extratropical forcings"

description: Climate sensitivity and radiative feedbacks across a variety of scenarios have been understood in recent years in terms of diverse surface warming patterns. The question of how these warming patterns arise, in response to different forcing patterns, has remained poorly understood. To improve our understanding in this regard, we performed a set of experiments with heating prescribed over tropical and extratropical oceans, in a pair of distinct climate models. Through these, we found contrasting mechanisms in both cases. There is low sensitivity to tropical heating, owing to rapid warm pool warming. By contrast, there is a high sensitivity to extratropical heating which involves deep ocean heat uptake that distributes warming homogeneously. Different resulting warming patterns drive shortwave cloud feedbacks of opposite signs, leading to contrasted sensitivities. We further find that these heatings do not combine linearly in their responses, highlighting a non-linearity in the climate response to combining forcing patterns.
DOI: 10.6084/m9.figshare.28796177.v1
title: Data for manuscript: "Contrasting mechanisms dictate climate sensitivities in response to tropical versus extratropical forcings"

description: Climate sensitivity and radiative feedbacks across a variety of scenarios have been understood in recent years in terms of diverse surface warming patterns. The question of how these warming patterns arise, in response to different forcing patterns, has remained poorly understood. To improve our understanding in this regard, we performed a set of experiments with heating prescribed over tropical and extratropical oceans, in a pair of distinct climate models. Through these, we found contrasting mechanisms in both cases. There is low sensitivity to tropical heating, owing to rapid warm pool warming. By contrast, there is a high sensitivity to extratropical heating which involves deep ocean heat uptake that distributes warming homogeneously. Different resulting warming patterns drive shortwave cloud feedbacks of opposite signs, leading to contrasted sensitivities. We further find that these heatings do not combine linearly in their responses, highlighting a non-linearity in the climate response to combining forcing patterns.
DOI: 10.25345/c5862bq68
title: MassIVE MSV000098349 - #3D_printer_waste_sample_Positive_NTS
title: Untargeted MS/MS data from dental implant 3D printer connector waste
DOI: 10.6084/m9.figshare.27011491
title: <b>GloUCP</b>: A global 1 km spatially continuous urban canopy parameters for the WRF model.

description: <b>Version 3 </b><b>Global Urban Canopy Parameters Dataset</b>This dataset provides <b>Glo</b>bal <b>U</b>rban <b>C</b>anopy <b>P</b>arameters (<b>GloUCP</b>) at a 1-km resolution for approximately the year 2020, which is derived from the global three-dimensional building footprint (3D-GloBFP) dataset generated by Che et al. (2024). The data is divided into 288 tiles, each stored in a compressed file, covering 15°×15° geographic regions. The corresponding geographic area for each compressed file can be identified from its filename (e.g., GloUCP-X105_119.Y15_29.zip contains data for the region spanning 105°E-120°E and 15°N-30°N, while GloUCP-X-180_-166.Y-60_-46.zip corresponds to the region between 180°W-165°W and 60°S-45°S).Each compressed file includes 255 <b>geogrid binary format files</b>, with each file representing a 1°×1° region. The specific geographic coverage of each file can be determined by consulting the <b>index file</b> and the file names, as explained in the WRF (Weather Research and Forecasting) User Guide.(e.g., 35161-35280.14281-14400 contains data for the region spanning 113°E-114°E and 29°N-30°N).<b>Global 1km Resolution Impervious Surface Fraction Data</b>In addition, this dataset provides two forms of impervious surface data for the year 2020, both derived from the Global Artificial Impervious Area (GAIA) dataset developed by Gong et al. (2020). The first is the <b>impervious surface fraction data</b>, a continuous variable at 1 km spatial resolution, representing the proportion of impervious surfaces within each grid cell, with values ranging from 0 to 1. The second is the <b>impervious surface mask data</b>, a binary classification derived from the fraction data by applying a threshold of 0.01, where a value of 1 denotes impervious surfaces and 0 denotes non-impervious surfaces. These datasets are provided alongside the GloUCP dataset and can support consistent land cover/use classification in WRF simulations.<b>APP: GloUCP Processor</b>To streamline data retrieval and facilitate dataset download, we developed a dedicated GloUCP Data Application. Users may specify the latitude and longitude bounds of their study area (e.g., 110°E–115°E, 25°N–30°N), based on which the application will automatically identify, retrieve, and merge the corresponding tiles along with the index.<br><b>References:</b>Che, Y., Li, X., Liu, X.*, Wang, Y., Liao, W., Zheng, X., Zhang, X., Xu, X., Shi, Q., Zhu, J., Yuan, H., and Dai, Y. 2024: 3D-GloBFP: the first global three-dimensional building footprint dataset, Earth System Science Data, 16, 5357–5374. doi: 10.5194/essd-16-5357-2024.Gong, P.*, Li, X.C., Wang, J.*, Bai, Y., Chen, B., Hu, T.Y., Liu, X.P., Xu, B., Yang, J., Zhang, W., & Zhou, Y.Y. 2020. Annual maps of global artificial impervious areas (GAIA) between 1985 and 2018. Remote Sensing of Environment, 236, 111510. doi: 10.1016/j.rse.2019.111510.<br>
DOI: 10.6084/m9.figshare.27011491.v3
title: <b>GloUCP</b>: A global 1 km spatially continuous urban canopy parameters for the WRF model.

description: <b>Version 3 </b><b>Global Urban Canopy Parameters Dataset</b>This dataset provides <b>Glo</b>bal <b>U</b>rban <b>C</b>anopy <b>P</b>arameters (<b>GloUCP</b>) at a 1-km resolution for approximately the year 2020, which is derived from the global three-dimensional building footprint (3D-GloBFP) dataset generated by Che et al. (2024). The data is divided into 288 tiles, each stored in a compressed file, covering 15°×15° geographic regions. The corresponding geographic area for each compressed file can be identified from its filename (e.g., GloUCP-X105_119.Y15_29.zip contains data for the region spanning 105°E-120°E and 15°N-30°N, while GloUCP-X-180_-166.Y-60_-46.zip corresponds to the region between 180°W-165°W and 60°S-45°S).Each compressed file includes 255 <b>geogrid binary format files</b>, with each file representing a 1°×1° region. The specific geographic coverage of each file can be determined by consulting the <b>index file</b> and the file names, as explained in the WRF (Weather Research and Forecasting) User Guide.(e.g., 35161-35280.14281-14400 contains data for the region spanning 113°E-114°E and 29°N-30°N).<b>Global 1km Resolution Impervious Surface Fraction Data</b>In addition, this dataset provides two forms of impervious surface data for the year 2020, both derived from the Global Artificial Impervious Area (GAIA) dataset developed by Gong et al. (2020). The first is the <b>impervious surface fraction data</b>, a continuous variable at 1 km spatial resolution, representing the proportion of impervious surfaces within each grid cell, with values ranging from 0 to 1. The second is the <b>impervious surface mask data</b>, a binary classification derived from the fraction data by applying a threshold of 0.01, where a value of 1 denotes impervious surfaces and 0 denotes non-impervious surfaces. These datasets are provided alongside the GloUCP dataset and can support consistent land cover/use classification in WRF simulations.<b>APP: GloUCP Processor</b>To streamline data retrieval and facilitate dataset download, we developed a dedicated GloUCP Data Application. Users may specify the latitude and longitude bounds of their study area (e.g., 110°E–115°E, 25°N–30°N), based on which the application will automatically identify, retrieve, and merge the corresponding tiles along with the index.<br><b>References:</b>Che, Y., Li, X., Liu, X.*, Wang, Y., Liao, W., Zheng, X., Zhang, X., Xu, X., Shi, Q., Zhu, J., Yuan, H., and Dai, Y. 2024: 3D-GloBFP: the first global three-dimensional building footprint dataset, Earth System Science Data, 16, 5357–5374. doi: 10.5194/essd-16-5357-2024.Gong, P.*, Li, X.C., Wang, J.*, Bai, Y., Chen, B., Hu, T.Y., Liu, X.P., Xu, B., Yang, J., Zhang, W., & Zhou, Y.Y. 2020. Annual maps of global artificial impervious areas (GAIA) between 1985 and 2018. Remote Sensing of Environment, 236, 111510. doi: 10.1016/j.rse.2019.111510.<br>