cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.31115929.v1
title: Supplementary Tables

description: This study is a cross-sectional case–control analysis investigating the effect of e-cigarette use on the subgingival oral mycobiome. Subgingival plaque samples from 123 systemically and periodontally healthy adults, including e-cigarette users, smokers, dual users, former smokers who vape, and never-smokers, were analyzed using whole-genome shotgun sequencing, with fungal taxa identified by Kraken2 and functional pathways annotated using KEGG, alongside bacterial–fungal correlation network analyses. The study concludes that e-cigarette use, irrespective of smoking history, is associated with distinct remodeling of the oral mycobiome characterized by increased fungal diversity, enrichment of stress-tolerant and metabolically adaptable fungi, and markedly enhanced cross-kingdom microbial interactions, indicating that vaping exerts a dominant ecological impact on the oral microbial environment rather than representing a biologically neutral alternative to smoking.
DOI: 10.15468/dl.kam6as
title: Occurrence Download

description: A dataset containing 4434 records in GBIF matching the query:
SELECT
 '27' AS fish_cell,
 GBIF_MGRSCode(1000, decimalLatitude, decimalLongitude, 0) AS cell, -- NO randomization
 COUNT(DISTINCT speciesKey) AS species_richness
 FROM occurrence
 WHERE hasCoordinate = TRUE
 AND speciesKey IS NOT NULL
 AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID')
 AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH')
 AND decimalLatitude &gt;= -33.06103686093294
 AND decimalLatitude &lt;= -28.773895969281842
 AND decimalLongitude &gt;= 119.08601953811215
 AND decimalLongitude &lt;= 128.0206804974514
 AND "year" &gt;= 2015
 AND "year" &lt;= 2026
 AND (coordinateUncertaintyInMeters &lt;= 100 OR coordinateUncertaintyInMeters IS NULL)
 GROUP BY fish_cell, cell

 The dataset's 4434 records were derived from 54 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003135-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18330213
title: 7-Tage-Inzidenz der COVID-19-Fälle in Deutschland

description: Im Datensatz "7-Tage-Inzidenz der COVID-19-Fälle in Deutschland" des Robert Koch-Instituts werden die täglich aktualisierten COVID-19-Inzidenzen auf Bundes-, Landes- und Landkreisebene basierend auf den Meldungen nach dem Infektionsschutzgesetz (IfSG) bereitgestellt. Die 7-Tage-Inzidenz wird definiert als Anzahl gemeldeter Fälle der letzten sieben Tage pro 100.000 Einwohner:innen und differenziert nach Altersgruppen und Regionen. Die Datenverarbeitung erfolgt vollständig elektronisch über das Deutsche Elektronische Melde- und Informationssystem (DEMIS).
DOI: 10.1594/pangaea.988237
title: Downcore benthic and planktic foraminiferal δ¹⁸O records from the North Atlantic over the past 25 ka

description: Depending on sample size, stable oxygen and carbon isotope measurements were performed using a VG Isogas SIRA mass spectrometer with Multicarb preparation system (&gt;80 μg) and a Thermo MAT253 isotope ratio mass spectrometer with Kiel IV carbonate preparation device (&lt;80 μg) at the Godwin Laboratory, University of Cambridge. δ18O and δ13C is reported relative to the Vienna Peedee belemnite (VPDB) standard, and for both instruments analytical precision is estimated to be better than ±0.07 ‰ and ±0.04 ‰ respectively.
DOI: 10.1594/pangaea.988217
title: Individual benthic foraminiferal Δ47 and δ¹⁸O data, and derived temperature estimates, from the Northwest Atlantic during the mid-to-late Holocene (2-6 ka BP) and the Last Glacial Maximum (19-23 ka BP)

description: Depending on sample size, stable oxygen and carbon isotope measurements were performed using a VG Isogas SIRA mass spectrometer with Multicarb preparation system (&gt;80 μg) and a Thermo MAT253 isotope ratio mass spectrometer with Kiel IV carbonate preparation device (&lt;80 μg) at the Godwin Laboratory, University of Cambridge. δ18O and δ13C is reported relative to the Vienna Peedee belemnite (VPDB) standard, and for both instruments analytical precision is estimated to be better than ±0.07 ‰ and ±0.04 ‰ respectively.
DOI: 10.1594/pangaea.988214
title: Vertical temperature and seawater δ¹⁸O profiles from the North Atlantic during the mid-Holocene (2-6 ka BP) and the Last Glacial Maximum (19-23 ka BP)
DOI: 10.1594/pangaea.988193
title: Monospecific benthic foraminiferal trace metal and δ¹⁸O data from the North Atlantic during the mid-to-late Holocene (2-6 ka BP) and the Last Glacial Maximum (19-23 ka BP)
DOI: 10.15468/dl.dy7zrg
title: Occurrence Download

description: A dataset containing 6341125 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Salmo trutta, Gadus morhua, Gadus morhua)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 6341125 records from 904 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003110-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/11534293
title: Balochi Language to English Translation Dataset
DOI: 10.5281/zenodo.11166938
title: Representative Counties of Germany and Their Structural Data

description: Content

A dataset of counties that are representative for Germany with regard to



the average disposable income,

the quota of divorces,

the respective quotas of employees working in the services (excluding logistics, security, and cleaning) and the MINT sectors,

the proportions of age groups in the total proportion of the respective population, with age groups in five-year strata for the population aged between 30 and 65 and the population in the age range between 65 and 75 each considered separately for the calculation of representativeness.

population density, if the benchmark is defined as the national average density weighted by county population. This value is calculated by averaging the population-per-square-kilometer figures of all German counties, weighted by the population size of each county. In contrast to a simple arithmetic mean of county-level densities, which would disproportionately reflect sparsely populated areas, this method reflects the actual density of the environments where people live. The resulting value for the selected counties falls within the 95% confidence interval of the national weighted average.


In addition, data from the four big cities Berlin, München (Munich), Hamburg, and Köln (Cologne) were collected and reflected in the dataset.

The dataset is based on the most recent data available at the time of the creation of the dataset, mainly deriving from 2022, as set out in detail in the readme.md file.

Method applied

The selection of the representative counties, as reflected in the dataset, was performed on the basis of official statistics with the aim of obtaining a confidence rate of 95%. The selection was based on a principal component analysis of the statistical data available for Germany and the addition of the regions with the lowest population density and the highest and lowest per capita disposable income. A check of the representativity of the selected counties was performed.

In the case of Leipzig, the city and the district had to be treated together, in deviation from the official territorial division, with respect to a specific use case of the data.
DOI: 10.5281/zenodo.11166939
title: Representative Counties of Germany and Their Structural Data

description: Content

A dataset of counties that are representative for Germany with regard to



the average disposable income,

the quota of divorces,

the respective quotas of employees working in the services (excluding logistics, security, and cleaning) and the MINT sectors,

the proportions of age groups in the total proportion of the respective population, with age groups in five-year strata for the population aged between 30 and 65 and the population in the age range between 65 and 75 each considered separately for the calculation of representativeness.


In addition, data from the four big cities Berlin, München (Munich), Hamburg, and Köln (Cologne) were collected and reflected in the dataset.

The dataset is based on the most recent data available at the time of the creation of the dataset, mainly deriving from 2022, as set out in detail in the readme.md file.

Method applied

The selection of the representative counties, as reflected in the dataset, was performed on the basis of official statistics with the aim of obtaining a confidence rate of 95%. The selection was based on a principal component analysis of the statistical data available for Germany and the addition of the regions with the lowest population density and the highest and lowest per capita disposable income. A check of the representativity of the selected counties was performed.

In the case of Leipzig, the city and the district had to be treated together, in deviation from the official territorial division, with respect to a specific use case of the data.
DOI: 10.5281/zenodo.11167333
title: Representative Counties of Germany and Their Structural Data

description: Content

A dataset of counties that are representative for Germany with regard to



the average disposable income,

the quota of divorces,

the respective quotas of employees working in the services (excluding logistics, security, and cleaning) and the MINT sectors,

the proportions of age groups in the total proportion of the respective population, with age groups in five-year strata for the population aged between 30 and 65 and the population in the age range between 65 and 75 each considered separately for the calculation of representativeness.


In addition, data from the four big cities Berlin, München (Munich), Hamburg, and Köln (Cologne) were collected and reflected in the dataset.

The dataset is based on the most recent data available at the time of the creation of the dataset, mainly deriving from 2022, as set out in detail in the readme.md file.

Method applied

The selection of the representative counties, as reflected in the dataset, was performed on the basis of official statistics with the aim of obtaining a confidence rate of 95%. The selection was based on a principal component analysis of the statistical data available for Germany and the addition of the regions with the lowest population density and the highest and lowest per capita disposable income. A check of the representativity of the selected counties was performed.

In the case of Leipzig, the city and the district had to be treated together, in deviation from the official territorial division, with respect to a specific use case of the data.
DOI: 10.5281/zenodo.11265139
title: Representative Counties of Germany and Their Structural Data

description: Content

A dataset of counties that are representative for Germany with regard to



the average disposable income,

the quota of divorces,

the respective quotas of employees working in the services (excluding logistics, security, and cleaning) and the MINT sectors,

the proportions of age groups in the total proportion of the respective population, with age groups in five-year strata for the population aged between 30 and 65 and the population in the age range between 65 and 75 each considered separately for the calculation of representativeness.


In addition, data from the four big cities Berlin, München (Munich), Hamburg, and Köln (Cologne) were collected and reflected in the dataset.

The dataset is based on the most recent data available at the time of the creation of the dataset, mainly deriving from 2022, as set out in detail in the readme.md file.

Method applied

The selection of the representative counties, as reflected in the dataset, was performed on the basis of official statistics with the aim of obtaining a confidence rate of 95%. The selection was based on a principal component analysis of the statistical data available for Germany and the addition of the regions with the lowest population density and the highest and lowest per capita disposable income. A check of the representativity of the selected counties was performed.

In the case of Leipzig, the city and the district had to be treated together, in deviation from the official territorial division, with respect to a specific use case of the data.
DOI: 10.5281/zenodo.15271768
title: Representative Counties of Germany and Their Structural Data

description: Content

A dataset of counties that are representative for Germany with regard to



the average disposable income,

the quota of divorces,

the respective quotas of employees working in the services (excluding logistics, security, and cleaning) and the MINT sectors,

the proportions of age groups in the total proportion of the respective population, with age groups in five-year strata for the population aged between 30 and 65 and the population in the age range between 65 and 75 each considered separately for the calculation of representativeness.

population density, if the benchmark is defined as the national average density weighted by county population. This value is calculated by averaging the population-per-square-kilometer figures of all German counties, weighted by the population size of each county. In contrast to a simple arithmetic mean of county-level densities, which would disproportionately reflect sparsely populated areas, this method reflects the actual density of the environments where people live. The resulting value for the selected counties falls within the 95% confidence interval of the national weighted average.


In addition, data from the four big cities Berlin, München (Munich), Hamburg, and Köln (Cologne) were collected and reflected in the dataset.

The dataset is based on the most recent data available at the time of the creation of the dataset, mainly deriving from 2022, as set out in detail in the readme.md file.

Method applied

The selection of the representative counties, as reflected in the dataset, was performed on the basis of official statistics with the aim of obtaining a confidence rate of 95%. The selection was based on a principal component analysis of the statistical data available for Germany and the addition of the regions with the lowest population density and the highest and lowest per capita disposable income. A check of the representativity of the selected counties was performed.

In the case of Leipzig, the city and the district had to be treated together, in deviation from the official territorial division, with respect to a specific use case of the data.
DOI: 10.15468/dl.fghdpx
title: Occurrence Download

description: A dataset containing 15 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia melanoxylon",
 "Country is Tanzania, United Republic of",
 "HasCoordinate is true"
 ]
}

 The dataset includes 15 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024562-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5w8mv8
title: Occurrence Download

description: A dataset containing 43107 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Switzerland, France, Germany)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Lynx lynx (Linnaeus, 1758)"
 ]
}

 The dataset includes 43107 records from 120 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009474-250515123054153/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.28575032
title: May-July precipitation reconstruction in the northwestern Qinghai-Tibet Plateau from 845–2023 CE

description: This is a May–July precipitation reconstruction for the northeastern Qinghai-Tibetan Plateau using a well-replicated ensemble tree-ring-width chronology from 350 Qilian juniper samples, spanning 845–2023 CE. The sampling informatin can be obtained from the paper entitled 'Recent and future climate extremes in the northwestern Qinghai-Tibet Plateau under anthropogenic forcing' submitted to Gephysical Research Letters.
DOI: 10.6084/m9.figshare.28575032.v1
title: May-July precipitation reconstruction in the northwestern Qinghai-Tibet Plateau from 845–2023 CE

description: This is a May–July precipitation reconstruction for the northeastern Qinghai-Tibetan Plateau using a well-replicated ensemble tree-ring-width chronology from 350 Qilian juniper samples, spanning 845–2023 CE. The sampling informatin can be obtained from the paper entitled 'Recent and future climate extremes in the northwestern Qinghai-Tibet Plateau under anthropogenic forcing' submitted to Gephysical Research Letters.
DOI: 10.15468/dl.9r8f6a
title: Occurrence Download

description: A dataset listing the 429 species recorded in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Colombia",
 "Geometry POLYGON((-73.77502 8.14115,-73.87592 7.99276,-73.77502 7.77314,-73.83437 7.72565,-73.78095 7.63661,-73.9056 7.48822,-73.92934 7.12614,-73.86999 7.0371,-74.41608 6.59786,-74.41608 6.4554,-74.35078 6.41979,-74.5526 6.25359,-74.61196 6.09926,-74.34255 6.03508,-74.29593 6.08836,-74.26041 6.06838,-74.26041 6.0151,-74.22933 5.95738,-74.24709 5.93518,-74.22045 5.91964,-74.27595 5.86858,-74.26485 5.83528,-74.20047 5.85304,-74.18271 5.9041,-74.12943 5.87968,-74.09835 5.87302,-74.07837 5.8264,-74.02731 5.80642,-74.00733 5.7598,-73.98291 5.7154,-73.94517 5.7376,-73.86747 5.73982,-73.88967 5.69542,-73.85415 5.70874,-73.82973 5.75092,-73.80974 5.73094,-73.7387 5.77756,-73.70096 5.76868,-73.6499 5.71984,-73.62326 5.76868,-73.62992 5.8042,-73.58774 5.87524,-73.62326 5.9152,-73.56776 6.01732,-73.5167 6.06838,-73.5056 6.11722,-73.4057 6.05284,-73.3724 6.01288,-73.40126 5.89078,-73.439 5.89522,-73.439 5.85082,-73.4723 5.84194,-73.4723 5.81308,-73.439 5.80864,-73.41902 5.75758,-73.39016 5.75314,-73.34576 5.86858,-73.27916 5.84194,-73.24808 5.81752,-73.18148 5.83084,-73.18592 5.85748,-73.2392 5.89966,-73.21922 5.95072,-73.21256 5.98846,-73.18814 6.00844,-73.15262 5.97514,-73.14152 6.03064,-73.12376 6.00178,-73.08824 5.99068,-73.03052 6.00844,-73.01498 5.96182,-72.93822 6.08968,-72.80075 6.20054,-72.7431 6.22715,-72.73423 6.36462,-72.7564 6.48435,-72.79188 6.56861,-72.72536 6.5553,-72.64111 6.41783,-72.56572 6.47105,-72.46816 6.67947,-72.4859 6.81251,-72.52581 6.88346,-72.55242 6.98989,-72.67658 6.98989,-72.73867 7.00763,-72.7564 7.05197,-72.84953 7.10519,-72.85397 7.18945,-72.87614 7.2604,-72.82292 7.33135,-72.99587 7.61073,-73.10673 7.60186,-73.24842 7.62302,-73.23505 7.53388,-73.36876 7.56953,-73.47573 7.5829,-73.56041 7.73444,-73.74315 7.75673,-73.73869 7.81912,-73.66292 7.90826,-73.77502 8.14115))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Bryophyta",
 "Year 1980-2025"
 ]
}

 The dataset's 429 records were derived from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003512-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u8ksnn
title: Occurrence Download

description: A dataset containing 8864 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Colombia",
 {
 "and" : [
 "Country is Colombia",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 }
 ]
 },
 {
 "and" : [
 "GadmGid is one of (COL.2_2)",
 "StateProvince is one of (Antioquia)",
 "Geometry POLYGON((-75.57003 6.42244,-75.56937 6.32084,-75.57003 6.2835,-75.57035 6.24454,-75.41945 6.24421,-75.41618 6.42147,-75.57003 6.42244))",
 "Issue is one of (Geodetic datum assumed WGS84, Coordinate reprojected, Country derived from coordinates)"
 ]
 }
 ]
}

 The dataset includes 8864 records from 63 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003514-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sa97w3
title: Occurrence Download

description: A dataset containing 114614 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sciurus niger"
 ]
}

 The dataset includes 114614 records from 143 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003498-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uw4zst
title: Occurrence Download

description: A dataset containing 21729 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tamias sibiricus"
 ]
}

 The dataset includes 21729 records from 219 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003516-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zmcrzz
title: Occurrence Download

description: A dataset containing 9931 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Panthera onca"
 ]
}

 The dataset includes 9931 records from 306 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003518-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m38dvt
title: Occurrence Download

description: A dataset containing 7178 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Chilocorus renipustulatus"
 ]
}

 The dataset includes 7178 records from 66 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003520-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/13830561
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.6vb9cz
title: Occurrence Download

description: A dataset containing 58348 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Geometry POLYGON((33.5 26.9,34.2 26.9,34.2 27.6,33.66352 27.6,33.5 27.6,33.5 26.9))",
 "Geometry POLYGON((33.65763 27.56829,33.53601 27.43605,33.84007 26.94574,34.17355 27.02964,33.65763 27.56829))"
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 58348 records from 120 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003487-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fqbtvm
title: Occurrence Download

description: A dataset containing 564869 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-71.35905 -0.17862,-71.39743 -0.86957,-71.58937 -1.79063,-71.05194 -2.82625,-70.47612 -3.66942,-70.16901 -4.32043,-69.13253 -4.12901,-68.05767 -4.09072,-65.17856 -3.78435,-64.4108 -3.09461,-64.52596 -2.21264,-65.3705 -1.48365,-65.90793 -1.29176,-66.67569 -0.98472,-67.32829 -0.7928,-68.47994 -0.67765,-70.24579 -0.33217,-71.35905 -0.17862))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 564869 records from 686 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003513-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.