cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.vhdtxn
title: Occurrence Download

description: A dataset containing 1576 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Penelope pileata",
 "DecimalLongitude is not null",
 "DecimalLatitude is not null"
 ]
}

 The dataset includes 1576 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063439-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7gkq8c
title: Occurrence Download

description: A dataset containing 12500 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Percnostola",
 "DecimalLongitude is not null",
 "DecimalLatitude is not null"
 ]
}

 The dataset includes 12500 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063440-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/zh2jsn
title: Replication Data for: Toward an Understanding of the Returns to Cognitive Skill Across Cohorts

description: This is the replication package for "Toward an Understanding of the Returns to Cognitive Skill Across Cohorts," accepted in 2025 by the Journal of Political Economy: Microeconomics.
DOI: 10.6084/m9.figshare.30937373
title: AI Companionship & Human Connection 2025 (Dataset, n = 501)

description: This dataset is part of the Human Clarity Institute’s <b>AI–Human Experience 2025</b> data series. It examines how people experience emotional connection, companionship, and relational boundaries in interactions with AI tools, including perceived emotional support, values alignment, and concerns around emotional dependence.The dataset includes:<br>• validated 1–7 Likert-scale items<br>• measures of AI companionship, emotional support, trust, and perceived meaning<br>• behavioural indicators related to AI reliance, decision confidence, and boundary-setting<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 frequencyData were collected on 19 December 2025 via Prolific from adults in the<b> </b>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:• 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 filesThis dataset contributes to understanding how humans form emotional and cognitive relationships with AI tools, supporting longitudinal tracking of companionship dynamics, trust, and values alignment as the role of AI in everyday life continues to evolve.
DOI: 10.6084/m9.figshare.30937373.v1
title: AI Companionship & Human Connection 2025 (Dataset, n = 501)

description: This dataset is part of the Human Clarity Institute’s <b>AI–Human Experience 2025</b> data series. It examines how people experience emotional connection, companionship, and relational boundaries in interactions with AI tools, including perceived emotional support, values alignment, and concerns around emotional dependence.The dataset includes:<br>• validated 1–7 Likert-scale items<br>• measures of AI companionship, emotional support, trust, and perceived meaning<br>• behavioural indicators related to AI reliance, decision confidence, and boundary-setting<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 frequencyData were collected on 19 December 2025 via Prolific from adults in the<b> </b>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:• 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 filesThis dataset contributes to understanding how humans form emotional and cognitive relationships with AI tools, supporting longitudinal tracking of companionship dynamics, trust, and values alignment as the role of AI in everyday life continues to evolve.
DOI: 10.15468/dl.839cc6
title: Occurrence Download

description: A dataset containing 811 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Phaethornis aethopygus",
 "DecimalLongitude is not null",
 "DecimalLatitude is not null"
 ]
}

 The dataset includes 811 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063441-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n6dh23
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Phaethornis major",
 "DecimalLongitude is not null",
 "DecimalLatitude is not null"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063442-251120083545085/datasets/export for details.
DOI: 10.60493/qf8nd-y4611
title: São Luís, Brazil by Celso H. L. Silva-Junior - part of deadtrees.earth

description: This dataset was supported by funding from the National Council for Scientific and Technological Development (CNPq) under the project YBYRÁ-BR: Space-Time Quantification of CO2 Emissions and Removals by Brazilian Forests (CNPq Process 401741/2023-0). We also welcome users to invite us for collaboration.
DOI: 10.15468/dl.edt28t
title: Occurrence Download

description: A dataset containing 39 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Occurrence evidence)",
 "Continent is Asia",
 "Country is Philippines",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Dillenia philippinensis",
 "Year 2000-2025"
 ]
}

 The dataset includes 39 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063444-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8wbjmj
title: Occurrence Download

description: A dataset containing 204 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Phlegopsis borbae",
 "DecimalLongitude is not null",
 "DecimalLatitude is not null"
 ]
}

 The dataset includes 204 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063443-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18025816
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Jiří Danihelka, https://orcid.org/0000-0002-2640-7867. 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.18025747
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Mont A. Cazier, http://www.wikidata.org/entity/Q21392418. 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/Q21392418
DOI: 10.5281/zenodo.18026086
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Fridolin Krasser, http://www.wikidata.org/entity/Q88768. 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/Q88768
DOI: 10.5281/zenodo.18010339
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Fridolin Krasser, http://www.wikidata.org/entity/Q88768. 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/Q88768
DOI: 10.5281/zenodo.18026089
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Charles Francis Laseron, http://www.wikidata.org/entity/Q5077778. 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/Q5077778
DOI: 10.5281/zenodo.8148897
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Charles Francis Laseron, http://www.wikidata.org/entity/Q5077778. 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/Q5077778
DOI: 10.5281/zenodo.18026022
title: Metadata package supporting DOI:10.1093/mnras/stab3524 (COLAB, NCN OPUS)

description: This record provides a metadata package supporting DOI: 10.1093/mnras/stab3524. It documents dataset provenance, access conditions, and high-level reproducibility notes.

Primary input data: Copernicus Complexio (COCO) simulations (CDM and WDM flavours). Access is consortium-only at the time of this deposit, and the simulation products are not redistributed here. Access contacts: Wojciech A. Hellwing (hellwing@cft.edu.pl, CFT PAN, Warsaw) and Sownak Bose (sownak.bose@durham.ac.uk, ICC Durham University).

Core simulation references: Hellwing et al. 2016 (COCO CDM, DOI: 10.1093/mnras/stw214) and Bose et al. 2016 (COCO WDM, DOI: 10.1093/mnras/stv2294).

Funding: NCN OPUS COLAB (UMO-2020/39/B/ST9/03494).
DOI: 10.5281/zenodo.18026023
title: Metadata package supporting DOI:10.1093/mnras/stab3524 (COLAB, NCN OPUS)

description: This record provides a metadata package supporting DOI: 10.1093/mnras/stab3524. It documents dataset provenance, access conditions, and high-level reproducibility notes.

Primary input data: Copernicus Complexio (COCO) simulations (CDM and WDM flavours). Access is consortium-only at the time of this deposit, and the simulation products are not redistributed here. Access contacts: Wojciech A. Hellwing (hellwing@cft.edu.pl, CFT PAN, Warsaw) and Sownak Bose (sownak.bose@durham.ac.uk, ICC Durham University).

Core simulation references: Hellwing et al. 2016 (COCO CDM, DOI: 10.1093/mnras/stw214) and Bose et al. 2016 (COCO WDM, DOI: 10.1093/mnras/stv2294).

Funding: NCN OPUS COLAB (UMO-2020/39/B/ST9/03494).
DOI: 10.13140/rg.2.2.32434.06086
title: Scientific Transliteration of the Quran
DOI: 10.5281/zenodo.18026090
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Wendell L. Minckley, http://www.wikidata.org/entity/Q7982444. 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/Q7982444
DOI: 10.6084/m9.figshare.30937391
title: ­SUPPLEMENTAL INFORMATION

description: ­SUPPLEMENTAL INFORMATION<b>Table S1</b><b>: </b>Differentially expressed genes between <i>IDICD</i> and <i>S2FCD</i> molecular subtypes of CD.<b>Table S2: </b>Excel datasheet with CD clinical parameters used for univariate and multivariate analyses in this current study.
DOI: 10.6084/m9.figshare.30937391.v1
title: ­SUPPLEMENTAL INFORMATION

description: ­SUPPLEMENTAL INFORMATION<b>Table S1</b><b>: </b>Differentially expressed genes between <i>IDICD</i> and <i>S2FCD</i> molecular subtypes of CD.<b>Table S2: </b>Excel datasheet with CD clinical parameters used for univariate and multivariate analyses in this current study.
DOI: 10.15468/dl.c3csvn
title: Occurrence Download

description: A dataset containing 418 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Hedleya macleayi, Notopala sublineata, Notopala hanleyi, Suavocallia splendens)"
 ]
}

 The dataset includes 418 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063446-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26030/4tsr-7518
title: Microbiological and Nutritional Analysis of Lettuce Crops Grown on the International Space Station (Anthocyanin Content, Phenolic Content, Elemental Analysis, ORAC)

description: The ability to grow safe, fresh food to supplement packaged foods of astronauts in space has been an important goal for NASA. Food crops grown in space experience different environmental conditions than plants grown on Earth (e.g., reduced gravity, elevated radiation levels). To study the effects of space conditions, red romaine lettuce, Lactuca sativa cv ‘Outredgeous,’ plants were grown in Veggie plant growth chambers on the International Space Station (ISS) and compared with ground-grown plants. Multiple plantings were grown on ISS and harvested using either a single, final harvest, or sequential harvests in which several mature leaves were removed from the plants at weekly intervals. Ground controls were grown simultaneously with a 24–72 h delay using ISS environmental data. Food safety of the plants was determined by heterotrophic plate counts for bacteria and fungi, as well as isolate identification using samples taken from the leaves and roots. Molecular characterization was conducted using Next Generation Sequencing (NGS) to provide taxonomic composition and phylogenetic structure of the community. Leaves were also analyzed for elemental composition, as well as levels of phenolics, anthocyanins, and Oxygen Radical Absorbance Capacity (ORAC). Comparison of flight and ground tissues showed some differences in total counts for bacteria and yeast/molds (2.14 – 4.86 log10 CFU/g), while screening for select human pathogens yielded negative results. Bacterial and fungal isolate identification and community characterization indicated variation in the diversity of genera between leaf and root tissue with diversity being higher in root tissue, and included differences in the dominant genera. The only difference between ground and flight experiments was seen in the third experiment, VEG-03A, with significant differences in the genera from leaf tissue. Flight and ground tissue showed differences in Fe, K, Na, P, S, and Zn content and total phenolic levels, but no differences in anthocyanin and ORAC levels. This study indicated that leafy vegetable crops can produce safe, edible, fresh food to supplement to the astronauts’ diet, and provide baseline data for continual operation of the Veggie plant growth units on ISS. This study derives results from the Anthocyanin Content, Phenolic Content, Elemental Analysis, and ORAC assays using leaf samples.
DOI: 10.26030/k1f5-1p32
title: Pick-and-eat space crop production flight testing on the International Space Station (Elemental Analysis, ORAC, Phenolic Content)

description: Fresh, nutritious, palatable produce for crew consumption on long-duration spaceflight missions may provide health-promoting, bioavailable nutrients and enhance the dietary experience. VEG-04A and VEG-04B explored growing leafy greens on the International Space Station using the Veggie Vegetable Production System. Two flight tests with ground controls were conducted in 2019 growing mizuna mustard, where Veggie chambers were set to different red-to-blue-to-green light formulations. Light quality affects plant growth, nutrition, microbiology, and organoleptic characteristics on Earth, and we examined how these vary in microgravity and under different harvest scenarios. Astronauts harvested and weighed mizuna and completed organoleptic evaluations. Flight samples were returned to Earth for nutritional quality and microbial food safety analyses. Yield and chemistry differed between ground and flight samples and light treatments, and bacterial and fungal counts were lower in ground than in flight samples. This research helps increase our understanding of the requirements for growing high-quality crops in spaceflight. This study derives results from the Phenolic Content, Elemental Analysis, and ORAC assays using leaf samples.
DOI: 10.60493/dcwx5-p2v74
title: São Luís, Brazil by Celso H. L. Silva-Junior - part of deadtrees.earth

description: This dataset was supported by funding from the National Council for Scientific and Technological Development (CNPq) under the project YBYRÁ-BR: Space-Time Quantification of CO2 Emissions and Removals by Brazilian Forests (CNPq Process 401741/2023-0). We also welcome users to invite us for collaboration.
DOI: 10.15468/dl.tg348c
title: Occurrence Download

description: A dataset containing 658276 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Clupea harengus",
 "Year 2000-2025"
 ]
}

 The dataset includes 658276 records from 172 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063438-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.56btxx
title: Occurrence Download

description: A dataset containing 476 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "DatasetKey is one of (Insect Species Occurrence Data from Multiple Projects Worldwide with Focus on Bees and Wasps in North America, Bee Fauna of National Wildlife Refuges in the Pacific Northwest, 2010-2016, hymenoptera, International Barcode of Life project (iBOL), Illinois Natural History Survey Insect Collection, Snow Entomological Museum Collection, Bee Biology and Systematics Laboratory, Oregon Bee Atlas Survey Data: 2018, Oregon Bee Atlas Survey Data: 2019)",
 "StateProvince is Idaho",
 "TaxonKey is one of (, Melissodes)"
 ]
}

 The dataset includes 476 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0063447-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16895887
title: Data from: Spider web architecture and rainfall damage: observational and manipulative studies along a precipitation gradient on the tropical Andes

description: Code and data associated with the manuscript: Spider web architecture and rainfall damage: observational and manipulative studies along a precipitation gradient on the tropical Andes
DOI: 10.5281/zenodo.18026096
title: Metadata package supporting DOI:10.1103/PhysRevD.106.023521 (COLAB, NCN OPUS)

description: This record provides a metadata package supporting DOI: 10.1103/PhysRevD.106.023521. It documents dataset provenance, access conditions, and high-level reproducibility notes.

Primary input data: Copernicus Complexio (COCO) simulations (CDM and WDM flavours). Access is consortium-only at the time of this deposit, and the simulation products are not redistributed here. Access contacts: Wojciech A. Hellwing (hellwing@cft.edu.pl, CFT PAN, Warsaw) and Sownak Bose (sownak.bose@durham.ac.uk, ICC Durham University).

Core simulation references: Hellwing et al. 2016 (COCO CDM, DOI: 10.1093/mnras/stw214) and Bose et al. 2016 (COCO WDM, DOI: 10.1093/mnras/stv2294).

Funding: NCN OPUS COLAB (UMO-2020/39/B/ST9/03494).
DOI: 10.5281/zenodo.18026097
title: Metadata package supporting DOI:10.1103/PhysRevD.106.023521 (COLAB, NCN OPUS)

description: This record provides a metadata package supporting DOI: 10.1103/PhysRevD.106.023521. It documents dataset provenance, access conditions, and high-level reproducibility notes.

Primary input data: Copernicus Complexio (COCO) simulations (CDM and WDM flavours). Access is consortium-only at the time of this deposit, and the simulation products are not redistributed here. Access contacts: Wojciech A. Hellwing (hellwing@cft.edu.pl, CFT PAN, Warsaw) and Sownak Bose (sownak.bose@durham.ac.uk, ICC Durham University).

Core simulation references: Hellwing et al. 2016 (COCO CDM, DOI: 10.1093/mnras/stw214) and Bose et al. 2016 (COCO WDM, DOI: 10.1093/mnras/stv2294).

Funding: NCN OPUS COLAB (UMO-2020/39/B/ST9/03494).
DOI: 10.17632/4hmrzsz59c
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
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.