cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/4hmrzsz59c.1
title: Incidence, risk factors and complications of central venous catheter-related thrombosis in adult medical ward and intensive care unit: A prospective cohort study

description: This is the de-identified data of the research titled "Incidence, risk factors and complications of central venous catheter-related thrombosis in adult medical ward and intensive care unit: A prospective cohort study "
DOI: 10.17632/3d7h58d4k3.1
title: Burnout_Risks_Bangladeshi_Physicians_Survey_2019_2021

description: This dataset includes detailed burnout assessments and related factors for 1,434 Bangladeshi physicians, representing one of the largest studies of physician burnout in a lower-middle-income country. The breadth of variables (demographic, occupational, and personal factors alongside standardized burnout measures) offers a rich resource for understanding contributors to burnout in healthcare settings. Researchers can reuse these data to perform secondary analyses, such as cross-cultural comparisons of burnout prevalence and predictors, meta-analyses, or validation studies of burnout interventions. The data can also be leveraged to test new hypotheses (e.g. mediating factors or subgroup differences) beyond the scope of the initial analysis. Stakeholders in healthcare management and policy can utilize the aggregated insights from this dataset to identify critical risk factors for physician burnout in Bangladesh and similar contexts. By highlighting factors like workload, workplace conflicts, job satisfaction, and personal well-being, the data can guide targeted interventions (such as wellness programs or organizational policy changes) to mitigate burnout. The burnout levels in this dataset were measured using the validated Maslach Burnout Inventory (MBI-HSS), ensuring reliability and comparability with international burnout research. In addition, the dataset contains responses to Likert-scale items on job-related sentiments (e.g., feeling annoyed with patients, perceived job security), which can facilitate nuanced analysis of how these sentiments correlate with burnout. Data were collected from 62 hospitals across urban and rural settings, capturing a diverse physician population from various specialties and job ranks. The large sample size and multicenter design enhance the generalizability of findings and allow subgroup analysis (for example, comparing burnout between different hospital types or between male and female physicians). Such granular analysis could help tailor interventions to specific groups of physicians most at risk.
DOI: 10.6084/m9.figshare.30070036
title: <b>Significant diversity of human anelloviruses revealed by novel viral sequences identified in human metagenomic data</b>

description: This Figshare item contains all supplementary materials for the article:"Significant diversity of human anelloviruses revealed by novel viral sequences identified in human metagenomic data" (Journal of General Virology, 2025, https://doi.org/10.1099/jgv.0.002199).<br>Contents:• Supplementary_Information.pdf – Legends for Supplementary Figures S1–Sx; any Supplementary Methods/References.• Supplementary_Figures.pdf – Figures S1–Sx (multi-page).• Supplementary_Tables.xlsx – Tables S1–Sy.• Supplementary_File_1.fasta – Assembled viral sequences.• AlphaFold_models/ – CIF (PDBx/mmCIF) models (model_0), confidence outputs, PAE (if available), README, manifest.This dataset is associated with the published article in Journal of General Virology (https://doi.org/10.1099/jgv.0.002199).
DOI: 10.6084/m9.figshare.30070036.v1
title: <b>Significant diversity of human anelloviruses revealed by novel viral sequences identified in human metagenomic data</b>

description: This Figshare item contains all supplementary materials for the article:"Significant diversity of human anelloviruses revealed by novel viral sequences identified in human metagenomic data" (Journal of General Virology, 2025, https://doi.org/10.1099/jgv.0.002199).<br>Contents:• Supplementary_Information.pdf – Legends for Supplementary Figures S1–Sx; any Supplementary Methods/References.• Supplementary_Figures.pdf – Figures S1–Sx (multi-page).• Supplementary_Tables.xlsx – Tables S1–Sy.• Supplementary_File_1.fasta – Assembled viral sequences.• AlphaFold_models/ – CIF (PDBx/mmCIF) models (model_0), confidence outputs, PAE (if available), README, manifest.This dataset is associated with the published article in Journal of General Virology (https://doi.org/10.1099/jgv.0.002199).
DOI: 10.5281/zenodo.18026101
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Philip Hunter Timberlake, http://www.wikidata.org/entity/Q7183790. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q7183790
DOI: 10.5281/zenodo.18026160
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Evan Waite, https://orcid.org/0000-0001-6877-3964. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
DOI: 10.5281/zenodo.6774592
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Evan Waite, https://orcid.org/0000-0001-6877-3964. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
DOI: 10.5281/zenodo.18026084
title: Privacy and Surveillance in Digital Life 2025 (Dataset, n = 271)

description: This dataset is part of the Human Clarity Institute’s AI–Human Experience 2025 data series. It examines how digitally active adults experience privacy erosion and surveillance in modern digital and AI-enabled environments, including perceived monitoring and tracking, behavioural self-regulation, power imbalance in data collection, and the emotional and autonomy-related impacts of surveillance.

The dataset includes:• validated 1–7 Likert-scale items• perceived surveillance intensity, privacy understanding, and loss of control over personal data• behavioural indicators such as self-censorship, platform avoidance, and behaviour modification due to surveillance concerns• multi-select variables stored as canonical semicolon-delimited snake_case tokens• open-text reflections with minimal safe cleaning (trim + newline removal only)• demographic variables across six English-speaking countries• digital life exposure (daily hours online) and AI-tool usage frequency

Data were collected on 19 December 2025 via Prolific from adults in the UK, US, Australia, Canada, New Zealand, and Ireland.All data were cleaned, anonymised, and processed under the Human Clarity Institute’s machine-readable dataset protocol, which includes:

• canonical snake_case variable naming• validated numeric ranges• standardised multi-select formats• minimal safe text cleaning• full alignment with the accompanying data dictionary• removal of Prolific IDs and timestamps• SHA-256 checksums for all files

This dataset contributes to understanding how people cognitively and behaviourally adapt to perceived surveillance and data collection in AI-mediated digital life, supporting longitudinal tracking of autonomy, trust, behavioural self-regulation, and human–AI boundary negotiation as these dynamics evolve over time.
DOI: 10.5281/zenodo.18026085
title: Privacy and Surveillance in Digital Life 2025 (Dataset, n = 271)

description: This dataset is part of the Human Clarity Institute’s AI–Human Experience 2025 data series. It examines how digitally active adults experience privacy erosion and surveillance in modern digital and AI-enabled environments, including perceived monitoring and tracking, behavioural self-regulation, power imbalance in data collection, and the emotional and autonomy-related impacts of surveillance.

The dataset includes:• validated 1–7 Likert-scale items• perceived surveillance intensity, privacy understanding, and loss of control over personal data• behavioural indicators such as self-censorship, platform avoidance, and behaviour modification due to surveillance concerns• multi-select variables stored as canonical semicolon-delimited snake_case tokens• open-text reflections with minimal safe cleaning (trim + newline removal only)• demographic variables across six English-speaking countries• digital life exposure (daily hours online) and AI-tool usage frequency

Data were collected on 19 December 2025 via Prolific from adults in the UK, US, Australia, Canada, New Zealand, and Ireland.All data were cleaned, anonymised, and processed under the Human Clarity Institute’s machine-readable dataset protocol, which includes:

• canonical snake_case variable naming• validated numeric ranges• standardised multi-select formats• minimal safe text cleaning• full alignment with the accompanying data dictionary• removal of Prolific IDs and timestamps• SHA-256 checksums for all files

This dataset contributes to understanding how people cognitively and behaviourally adapt to perceived surveillance and data collection in AI-mediated digital life, supporting longitudinal tracking of autonomy, trust, behavioural self-regulation, and human–AI boundary negotiation as these dynamics evolve over time.
DOI: 10.5281/zenodo.18026168
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Robert Willard Alrutz, http://www.wikidata.org/entity/Q91800184. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q91800184
DOI: 10.5281/zenodo.8049522
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Robert Willard Alrutz, http://www.wikidata.org/entity/Q91800184. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q91800184
DOI: 10.15468/dl.szkjxv
title: Occurrence Download

description: A dataset containing 130 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Living Specimen, Occurrence evidence)",
 "Continent is Asia",
 "Country is Philippines",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Pterocarpus indicus",
 "Year 2000-2025"
 ]
}

 The dataset includes 130 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063449-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18026119
title: Metadata package supporting DOI:10.1093/mnras/stac1382 (COLAB, NCN OPUS)

description: This record provides a metadata package supporting DOI: 10.1093/mnras/stac1382. It documents dataset provenance, access conditions, and high-level reproducibility notes.

Primary input data: BAHAMAs suite of cosmological simulations (restricted external; not owned by COLAB). The simulation products are not redistributed here. Access information: https://www.astro.ljmu.ac.uk/~igm/BAHAMAS/ ; custodian contact: Ian McCarthy (i.g.mccarthy@ljmu.ac.uk), Liverpool John Moores University.

Core simulation references: McCarthy et al. 2017 (DOI: 10.1093/mnras/stw2792) and Pfeifer et al. 2020 (DOI: 10.1093/mnras/staa2240).

Public software pointer (not owned by COLAB): cows implementation and documentation at https://github.com/SimonPfeifer/cows and https://python-cows.readthedocs.io/en/latest/index.html .

Funding: NCN OPUS COLAB (UMO-2020/39/B/ST9/03494).
DOI: 10.5281/zenodo.18026120
title: Metadata package supporting DOI:10.1093/mnras/stac1382 (COLAB, NCN OPUS)

description: This record provides a metadata package supporting DOI: 10.1093/mnras/stac1382. It documents dataset provenance, access conditions, and high-level reproducibility notes.

Primary input data: BAHAMAs suite of cosmological simulations (restricted external; not owned by COLAB). The simulation products are not redistributed here. Access information: https://www.astro.ljmu.ac.uk/~igm/BAHAMAS/ ; custodian contact: Ian McCarthy (i.g.mccarthy@ljmu.ac.uk), Liverpool John Moores University.

Core simulation references: McCarthy et al. 2017 (DOI: 10.1093/mnras/stw2792) and Pfeifer et al. 2020 (DOI: 10.1093/mnras/staa2240).

Public software pointer (not owned by COLAB): cows implementation and documentation at https://github.com/SimonPfeifer/cows and https://python-cows.readthedocs.io/en/latest/index.html .

Funding: NCN OPUS COLAB (UMO-2020/39/B/ST9/03494).
DOI: 10.5281/zenodo.18026177
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Alfred Kolakovski, http://www.wikidata.org/entity/Q4227549. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q4227549
DOI: 10.5281/zenodo.8303643
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Alfred Kolakovski, http://www.wikidata.org/entity/Q4227549. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q4227549
DOI: 10.5683/sp3/00j4gh
title: St Georges Catholic Church

description: This is a dataset of information compiled for the CIVE3207 (ARCN4100) Historic Site Recording and Assessment course in 2025. Undergraduate students of the Architectural Conservation and Sustainability Program (engineering and architecture) at Carleton University will use these data to produce a Heritage Recording of this important site.
DOI: 10.5281/zenodo.18026189
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Johann Christian Breutel, http://www.wikidata.org/entity/Q21415674. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q21415674
DOI: 10.5281/zenodo.11044289
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Johann Christian Breutel, http://www.wikidata.org/entity/Q21415674. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q21415674
DOI: 10.5683/sp3/thsksu
title: Fairfields Heritage House

description: This is a dataset of information compiled for the CIVE3207 (ARCN4100) Historic Site Recording and Assessment course in 2025. Undergraduate students of the Architectural Conservation and Sustainability Program (engineering and architecture) at Carleton University will use these data to produce a Heritage Recording of this important site.
DOI: 10.5683/sp3/zp2qqp
title: Billings Estate National Historic Site 2

description: This is a dataset of information compiled for the CIVE3207 (ARCN4100) Historic Site Recording and Assessment course in 2025. Undergraduate students of the Architectural Conservation and Sustainability Program (engineering and architecture) at Carleton University will use these data to produce a Heritage Recording of this important Site.
DOI: 10.5683/sp3/rybpbh
title: Flora Hall

description: This is a dataset of information compiled for the CIVE3207 (ARCN4100) Historic Site Recording and Assessment course in 2025. Undergraduate students of the Architectural Conservation and Sustainability Program (engineering and architecture) at Carleton University will use these data to produce a Heritage Recording of this important site.
DOI: 10.5281/zenodo.18026202
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by K. Samanta Orellana, https://orcid.org/0000-0002-4098-5823. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
DOI: 10.5281/zenodo.3942155
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by K. Samanta Orellana, https://orcid.org/0000-0002-4098-5823. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
DOI: 10.5683/sp3/2ct3zp
title: Windsor Arms

description: This is a dataset of information compiled for the CIVE3207 (ARCN4100) Historic Site Recording and Assessment course in 2025. Undergraduate students of the Architectural Conservation and Sustainability Program (engineering and architecture) at Carleton University will use these data to produce a Heritage Recording of this important site.
DOI: 10.6084/m9.figshare.30937415
title: Privacy and Surveillance in Digital Life 2025 (Dataset, n=271)

description: This dataset is part of the Human Clarity Institute’s <b>AI–Human Experience 2025</b> data series. It examines how digitally active adults experience privacy erosion and surveillance in modern digital and AI-enabled environments, including perceived monitoring and tracking, behavioural self-regulation, power imbalance in data collection, and the emotional and autonomy-related impacts of surveillance.The dataset includes:<br>• validated 1–7 Likert-scale items<br>• perceived surveillance intensity, privacy understanding, and loss of control over personal data<br>• behavioural indicators such as self-censorship, platform avoidance, and behaviour modification due to surveillance concerns<br>• multi-select variables stored as canonical semicolon-delimited snake_case tokens<br>• open-text reflections with minimal safe cleaning (trim + newline removal only)<br>• demographic variables across six English-speaking countries<br>• digital life exposure (daily hours online) and AI-tool usage frequency<br>Data were collected on 19 December 2025 via Prolific from adults in the UK, US, Australia, Canada, New Zealand, and Ireland.<br>All data were cleaned, anonymised, and processed under the Human Clarity Institute’s machine-readable dataset protocol, which includes:<br>• canonical snake_case variable naming<br>• validated numeric ranges<br>• standardised multi-select formats<br>• minimal safe text cleaning<br>• full alignment with the accompanying data dictionary<br>• removal of Prolific IDs and timestamps<br>• SHA-256 checksums for all files<br>This dataset contributes to understanding how people cognitively and behaviourally adapt to perceived surveillance and data collection in AI-mediated digital life, supporting longitudinal tracking of autonomy, trust, behavioural self-regulation, and human–AI boundary negotiation as these dynamics evolve over time.
DOI: 10.6084/m9.figshare.30937415.v1
title: Privacy and Surveillance in Digital Life 2025 (Dataset, n=271)

description: This dataset is part of the Human Clarity Institute’s <b>AI–Human Experience 2025</b> data series. It examines how digitally active adults experience privacy erosion and surveillance in modern digital and AI-enabled environments, including perceived monitoring and tracking, behavioural self-regulation, power imbalance in data collection, and the emotional and autonomy-related impacts of surveillance.The dataset includes:<br>• validated 1–7 Likert-scale items<br>• perceived surveillance intensity, privacy understanding, and loss of control over personal data<br>• behavioural indicators such as self-censorship, platform avoidance, and behaviour modification due to surveillance concerns<br>• multi-select variables stored as canonical semicolon-delimited snake_case tokens<br>• open-text reflections with minimal safe cleaning (trim + newline removal only)<br>• demographic variables across six English-speaking countries<br>• digital life exposure (daily hours online) and AI-tool usage frequency<br>Data were collected on 19 December 2025 via Prolific from adults in the UK, US, Australia, Canada, New Zealand, and Ireland.<br>All data were cleaned, anonymised, and processed under the Human Clarity Institute’s machine-readable dataset protocol, which includes:<br>• canonical snake_case variable naming<br>• validated numeric ranges<br>• standardised multi-select formats<br>• minimal safe text cleaning<br>• full alignment with the accompanying data dictionary<br>• removal of Prolific IDs and timestamps<br>• SHA-256 checksums for all files<br>This dataset contributes to understanding how people cognitively and behaviourally adapt to perceived surveillance and data collection in AI-mediated digital life, supporting longitudinal tracking of autonomy, trust, behavioural self-regulation, and human–AI boundary negotiation as these dynamics evolve over time.
DOI: 10.5683/sp3/mlcwth
title: St. Mark & St. Mary of Egypt Coptic Orthodox Church

description: This is a dataset of information compiled for the CIVE3207 (ARCN4100) Historic Site Recording and Assessment course in 2025. Undergraduate students of the Architectural Conservation and Sustainability Program (engineering and architecture) at Carleton University will use these data to produce a Heritage Recording of this important site.
DOI: 10.5281/zenodo.18026221
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Enio B. Cano, http://www.wikidata.org/entity/Q42335752. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q42335752
DOI: 10.5281/zenodo.8023533
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Enio B. Cano, http://www.wikidata.org/entity/Q42335752. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q42335752
DOI: 10.5683/sp3/6wixxp
title: Billings Estate National Historic Site 1

description: This is a dataset of information compiled for the CIVE3207 (ARCN4100) Historic Site Recording and Assessment course in 2025. Undergraduate students of the Architectural Conservation and Sustainability Program (engineering and architecture) at Carleton University will use these data to produce a Heritage Recording of this important Site.
DOI: 10.5683/sp3/3h6mbw
title: The Bronson Centre

description: This is a dataset of information compiled for the CIVE3207 (ARCN4100) Historic Site Recording and Assessment course in 2025. Undergraduate students of the Architectural Conservation and Sustainability Program (engineering and architecture) at Carleton University will use these data to produce a Heritage Recording of this important site.
DOI: 10.5683/sp3/ww4j0e
title: The Gamman House

description: This is a dataset of information compiled for the CIVE3207 (ARCN4100) Historic Site Recording and Assessment course in 2025. Undergraduate students of the Architectural Conservation and Sustainability Program (engineering and architecture) at Carleton University will use these data to produce a Heritage Recording of this important site.