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

description: A dataset containing 486900 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mammalia",
 "Year is 2005"
 ]
}

 The dataset includes 486900 records from 1125 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003837-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/bfdzy968rg
title: TCM and TikTok

description: 2024 dissemination statistic of TCM on TikTok platform
DOI: 10.17632/bfdzy968rg.1
title: TCM and TikTok

description: 2024 dissemination statistic of TCM on TikTok platform
DOI: 10.15468/dl.q96q92
title: Occurrence Download

description: A dataset containing 166576 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "GadmGid is CHN.24_1",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 166576 records from 156 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009414-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u8mdum
title: Occurrence Download

description: A dataset containing 72922 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Lynx lynx)",
 "OccurrenceStatus is Present",
 "SpeciesKey is not null",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2026",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 },
 "BasisOfRecord is one of (Human Observation, Machine Observation, Observation)"
 ]
}

 The dataset includes 72922 records from 67 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002174-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t4k8y4
title: Occurrence Download

description: A dataset containing 94 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Russian Federation",
 "GadmGid is RUS.45_1",
 "Geometry POLYGON((25.08099 62.40559,52.48138 62.40559,52.48138 73.36105,25.08099 73.36105,25.08099 62.40559))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Heracleum sosnowskyi"
 ]
}

 The dataset includes 94 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002216-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18143958
title: RNAeval
DOI: 10.5281/zenodo.18143957
title: RNAeval
DOI: 10.15468/dl.bwudkr
title: Occurrence Download

description: A dataset containing 3824 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Centroscyllium granulatum"
 ]
}

 The dataset includes 3824 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002217-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18273151
title: Chemical composition and snow physical properties of 35 profiles in a snow trench at Dome C, East Antarctica (2019)

description: The data set provides the chemical composition and physical snow properties of a 50m long and 1.5m deep snow trench sampled at Concordia Station (Dome C) in December 2019. The chemistry data includes 35 profiles of concentration of anions (SO42− ,NO2^− , NO3− , MSA, Cl−, Br−, oxalate, F−, acetate and formate) and cations (Li+, Na+, NH4+ , K+, Mg2+, and Ca2+). 31 profiles where sampled at 3 cm resolution and 4 profiles are sampled at 1.5 cm resolution. The measurements were carried out at Institut des Geosciences de l’Environnement (IGE), Grenoble and Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven. Throughout the files, trench snow pits are labeled by the letter "P" followed by their horizontal distance in meters to the left-most profile of the trench, from P0 to P50.

The physical properties include 33 snow density and specific surface area (SSA) profiles and 201 Snow Micro Pen (SMP) measurements (Schneebeli et al., 1999) to estimate snow hardness. SSA was measured at 3 cm resolution using ASSSAP (Arnaud et al., 2011, Libois et al. (2014). Snow density was measured at 3 cm resolution using a scale and squared metal sampler tool with a known volume. SSA and density were measured along the same profiles as chemistry, except for P0.3 and P47.7 who share the same SSA and density profiles as P0 and P48, respectively. SMP measurements were realized every 25 cm along the trench (201 profiles). The vertical resolution is extremely fine (0.004 mm) but the measurements were averaged at 1 cm resolution to obtain a macroscopic significance. The snow hardness probe was set to penetrate up to 150 cm, but it stopped earlier for several profiles due to too hard layers, leaving a few incomplete profiles.
DOI: 10.15468/dl.6jnfjm
title: Occurrence Download

description: A dataset containing 4208233 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry MULTIPOLYGON (((-7.08105 50.77893, -7.2275 50.09474, -6.34878 49.36886, -4.83542 49.49588, -4.73778 50.40696, -7.08105 50.77893)))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 4208233 records from 542 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002150-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.58116/uek/bnszqz
title: Olfactory heritage research: capture, reconstruction and conservation of historic smells, p.2

description: Odotheka is the project for Olfactory heritage research: capture, reconstruction and conservation of historic smells
DOI: 10.15468/dl.m4mwpr
title: Occurrence Download

description: A dataset containing 36 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((119.097 5.824142, 119.026376 5.818571, 118.957494 5.801996, 118.892055 5.774826, 118.831673 5.737732, 118.777836 5.691628, 118.731871 5.637652, 118.694908 5.577135, 118.667855 5.511568, 118.651377 5.442568, 118.645874 5.371833, 118.651479 5.301107, 118.668051 5.23213, 118.695177 5.166599, 118.732187 5.106128, 118.778169 5.052202, 118.831989 5.006149, 118.892324 4.9691, 118.95769 4.941966, 119.026478 4.925415, 119.097 4.919852, 119.167522 4.925415, 119.23631 4.941966, 119.301676 4.9691, 119.362011 5.006149, 119.415831 5.052202, 119.461813 5.106128, 119.498823 5.166599, 119.525949 5.23213, 119.542521 5.301107, 119.548126 5.371833, 119.542623 5.442568, 119.526145 5.511568, 119.499092 5.577135, 119.462129 5.637652, 119.416164 5.691628, 119.362327 5.737732, 119.301945 5.774826, 119.236506 5.801996, 119.167624 5.818571, 119.097 5.824142))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 36 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002219-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17633/rd.brunel.30157126
title: Zn ion capacitors in aprotic ionic liquids

description: This research shows the synergic effect of using aprotic ionic liquid and a redox molecule as electrolytes for Zn-ion capacitor. The studies show that the combination of the ionic liquid results in an improve Zn-ion capacitor.
DOI: 10.17633/rd.brunel.30157126.v1
title: Zn ion capacitors in aprotic ionic liquids

description: This research shows the synergic effect of using aprotic ionic liquid and a redox molecule as electrolytes for Zn-ion capacitor. The studies show that the combination of the ionic liquid results in an improve Zn-ion capacitor.
DOI: 10.34740/kaggle/dsv/14569037
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.5281/zenodo.18324959
title: Sensorimotor Integration and Functional Mobility in Early-Stage Parkinson's Disease: A Cross-Sectional Study Using Clinically Feasible Assessments

description: Sensorimotor Integration and Functional Mobility in Early-Stage Parkinson’s Disease: A Cross-Sectional Study Using Clinically Feasible Assessments
DOI: 10.5281/zenodo.18324960
title: Sensorimotor Integration and Functional Mobility in Early-Stage Parkinson's Disease: A Cross-Sectional Study Using Clinically Feasible Assessments

description: Sensorimotor Integration and Functional Mobility in Early-Stage Parkinson’s Disease: A Cross-Sectional Study Using Clinically Feasible Assessments
DOI: 10.5517/ccdc.csd.cc2pdytw
title: CSD 2485109: Experimental Crystal Structure Determination

description: Related Article: Xiangcong Ma, Jia Wang, Xiaona Li, Yabo Wu, Zhihua Yang, Fangfang Zhang, Shujuan Han, Shilie Pan|2025|J.Mater.Chem.C|14|572|doi:10.1039/d5tc04194e
description: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2pdyvx
title: CSD 2485110: Experimental Crystal Structure Determination

description: Related Article: Xiangcong Ma, Jia Wang, Xiaona Li, Yabo Wu, Zhihua Yang, Fangfang Zhang, Shujuan Han, Shilie Pan|2025|J.Mater.Chem.C|14|572|doi:10.1039/d5tc04194e
description: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2pdysv
title: CSD 2485108: Experimental Crystal Structure Determination

description: Related Article: Xiangcong Ma, Jia Wang, Xiaona Li, Yabo Wu, Zhihua Yang, Fangfang Zhang, Shujuan Han, Shilie Pan|2025|J.Mater.Chem.C|14|572|doi:10.1039/d5tc04194e
description: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.18322583
title: A Quality-Filtered SNP Genotype Dataset of Frieswal Cattle Developed in India

description: This quality-controlled SNP genotype dataset was generated using PLINK and includes 14 Frieswal animals genotyped at 52944 SNP loci. Quality control removed markers and individuals with high missingness, resulting in a genotyping rate of 0.999052 and high data completeness. Phenotype and pedigree data are not included. This dataset is intended for methodological development, teaching, software testing, and pilot-scale genomic analyses. Genotypes are provided in PLINK PED/MAP format to support broad reuse in various genomic analysis pipelines. Due to the small sample size, this dataset should not be used for population-level inference or breed-wide conclusions without caution.

 

The authors gratefully acknowledge the support and research environment provided by the Indian Council of Agricultural Research – Indian Veterinary Research Institute (ICAR-IVRI), India. Data processing and computational analyses were conducted as part of research and capacity-building activities led by Dr. Manjit Panigrahi, Senior Scientist, IVRI.
DOI: 10.5281/zenodo.18322582
title: A Quality-Filtered SNP Genotype Dataset of Frieswal Cattle Developed in India

description: This quality-controlled SNP genotype dataset was generated using PLINK and includes 14 Frieswal animals genotyped at 52944 SNP loci. Quality control removed markers and individuals with high missingness, resulting in a genotyping rate of 0.999052 and high data completeness. Phenotype and pedigree data are not included. This dataset is intended for methodological development, teaching, software testing, and pilot-scale genomic analyses. Genotypes are provided in PLINK PED/MAP format to support broad reuse in various genomic analysis pipelines. Due to the small sample size, this dataset should not be used for population-level inference or breed-wide conclusions without caution.

 

The authors gratefully acknowledge the support and research environment provided by the Indian Council of Agricultural Research – Indian Veterinary Research Institute (ICAR-IVRI), India. Data processing and computational analyses were conducted as part of research and capacity-building activities led by Dr. Manjit Panigrahi, Senior Scientist, IVRI.
DOI: 10.5281/zenodo.18322233
title: SuperDARN data in netCDF format (2002-May)

description: 2002-May SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6787926
title: SuperDARN data in netCDF format (2002-May)

description: 2002-May SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.18324956
title: Heart Rate Variability in Adolescents Following Surgical Correction of Aortic Coarctation: Dataset

description: This dataset contains anonymized raw heart rate variability (HRV) data from adolescents aged 12–17 years during the long-term period after surgical correction of aortic coarctation (CoA) and from age- and sex-matched healthy peers.

The dataset includes results of a 5-minute resting ECG analysis with HRV calculated in time-domain, frequency-domain, and nonlinear measures.

Dataset structure (Excel file):





Sheet 1: CoA group — demographic and anthropometric parameters, HRV indices (time domain, spectral, nonlinear measures)




Sheet 2: Healthy control group — same parameters as above

Description of HRV variables:





Time-domain indices:





SDNN, ms Standard deviation of normal RR-intervals




RMSSD, ms Square root of the mean square of the mean square of the differences of consecutive RR-intervals




pNN50, % Percentage of consecutive RR-intervals differing by more than 50 ms






Frequency-domain indices:





VLF, % Very low-frequency component of the heart rate spectrum




LF, % Low-frequency component of the heart rate spectrum




HF, % High-frequency component of the heart rate spectrum




LF/HF low- to high-frequency components ratio




Total power, ms2 Total power of the heart rate spectrum






Nonlinear indices:





SD1, ms Poincaré plot width, dispersion of point projections on a straight line perpendicular to the line of identity




SD2, ms Poincaré plot length, dispersion of point projections on the line of identitySD2/SD1 SD2 to SD1 ratio




ApEn Approximate entropy, an index of heart rate complexity and irregularity




SampEn Sample entropy, index of heart rate complexity and irregularity




Alpha DFA fractal dimension index of cardiac intervals time series





Important note:Some cells contain empty values. These represent outliers identified and removed during statistical analysis to ensure data quality.
DOI: 10.5281/zenodo.18196716
title: Clinical Performance of Contrast-Enhanced Mammography versus Breast MRI in Women at Increased Breast Cancer Risk

description: This dataset contains the multireader, multicase (MRMC) raw data from a retrospective study comparing the diagnostic performance of contrast-enhanced mammography (CEM), low-energy CEM (LE-CEM), and breast MRI in women at intermediate or high risk for breast cancer. The study included 461 women (mean age 50 ± 9 years) enrolled who underwent both CEM and breast MRI between March 2019 and October 2022.

The provided CSV file contains the individual reader assessments used to evaluate sensitivity, specificity, and Area Under the ROC Curve (AUC) for three imaging modalities.

Column Description:



readerID: Identifier for the eight breast radiologists involved in the study.



R1, R2, R3, R4: Group 1 readers, who are experienced in CEM (2–5 years) and interpreted both LE-CEM and CEM datasets

R5, R6, R7, R8: Group 2 readers, who are experts in breast MRI (8–15 years)



modality: The imaging technique used for the assessment.





LE-CEM: Low-energy images considered equivalent to standard digital mammography




CEM: Contrast-enhanced images generated through dual-energy subtraction (DES)




MRI: Standardized dynamic contrast-enhanced breast MRI




caseID: Unique anonymized identifier for each of the 461 participants.

truth: The established ground truth for each case.





For positive cases, truth was determined by histopathology from biopsy or surgery




For negative or benign cases, truth was verified by at least 24 months of stable imaging follow-up




score: The BI-RADS assessment score assigned by the reader for each case and modality.



 In the study’s analysis, a score >3 (BI-RADS 4 or 5) was considered positive for malignancy, while scores ≤3 were considered negative
DOI: 10.5281/zenodo.18196715
title: Clinical Performance of Contrast-Enhanced Mammography versus Breast MRI in Women at Increased Breast Cancer Risk

description: This dataset contains the multireader, multicase (MRMC) raw data from a retrospective study comparing the diagnostic performance of contrast-enhanced mammography (CEM), low-energy CEM (LE-CEM), and breast MRI in women at intermediate or high risk for breast cancer. The study included 461 women (mean age 50 ± 9 years) enrolled who underwent both CEM and breast MRI between March 2019 and October 2022.

The provided CSV file contains the individual reader assessments used to evaluate sensitivity, specificity, and Area Under the ROC Curve (AUC) for three imaging modalities.

Column Description:



readerID: Identifier for the eight breast radiologists involved in the study.



R1, R2, R3, R4: Group 1 readers, who are experienced in CEM (2–5 years) and interpreted both LE-CEM and CEM datasets

R5, R6, R7, R8: Group 2 readers, who are experts in breast MRI (8–15 years)



modality: The imaging technique used for the assessment.





LE-CEM: Low-energy images considered equivalent to standard digital mammography




CEM: Contrast-enhanced images generated through dual-energy subtraction (DES)




MRI: Standardized dynamic contrast-enhanced breast MRI




caseID: Unique anonymized identifier for each of the 461 participants.

truth: The established ground truth for each case.





For positive cases, truth was determined by histopathology from biopsy or surgery




For negative or benign cases, truth was verified by at least 24 months of stable imaging follow-up




score: The BI-RADS assessment score assigned by the reader for each case and modality.



 In the study’s analysis, a score >3 (BI-RADS 4 or 5) was considered positive for malignancy, while scores ≤3 were considered negative
DOI: 10.5281/zenodo.18324597
title: peer review
DOI: 10.5281/zenodo.18320903
title: peer review
DOI: 10.14272/xkynuwxcddwjfk-uhfffaoysa-n/chmo0000599
title: correlation spectroscopy (COSY) (2-bromo-1-(4-fluoro-3-hydroxyphenyl)ethanone)
title: InChI=1S/C8H6BrFO2/c9-4-8(12)5-1-2-6(10)7(11)3-5/h1-3,11H,4H2

description: dataset for correlation spectroscopy (COSY)
DOI: 10.14272/xkynuwxcddwjfk-uhfffaoysa-n/chmo0002337
title: electrospray ionisation quadrupole detection (ESI Q Trap) (2-bromo-1-(4-fluoro-3-hydroxyphenyl)ethanone)
title: InChI=1S/C8H6BrFO2/c9-4-8(12)5-1-2-6(10)7(11)3-5/h1-3,11H,4H2

description: dataset for electrospray ionisation quadrupole detection (ESI Q Trap)
DOI: 10.14272/xkynuwxcddwjfk-uhfffaoysa-n/chmo0000596.1
title: distortionless enhancement with polarization transfer (DEPT) (2-bromo-1-(4-fluoro-3-hydroxyphenyl)ethanone)
title: InChI=1S/C8H6BrFO2/c9-4-8(12)5-1-2-6(10)7(11)3-5/h1-3,11H,4H2

description: dataset for distortionless enhancement with polarization transfer (DEPT)
DOI: 10.14272/xkynuwxcddwjfk-uhfffaoysa-n/chmo0000604
title: heteronuclear single quantum coherence (HSQC) (2-bromo-1-(4-fluoro-3-hydroxyphenyl)ethanone)
title: InChI=1S/C8H6BrFO2/c9-4-8(12)5-1-2-6(10)7(11)3-5/h1-3,11H,4H2

description: dataset for heteronuclear single quantum coherence (HSQC)
DOI: 10.14272/xkynuwxcddwjfk-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (2-bromo-1-(4-fluoro-3-hydroxyphenyl)ethanone)
title: InChI=1S/C8H6BrFO2/c9-4-8(12)5-1-2-6(10)7(11)3-5/h1-3,11H,4H2

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR)
DOI: 10.14272/xkynuwxcddwjfk-uhfffaoysa-n/chmo0000597
title: 19F nuclear magnetic resonance spectroscopy (19F NMR) (2-bromo-1-(4-fluoro-3-hydroxyphenyl)ethanone)
title: InChI=1S/C8H6BrFO2/c9-4-8(12)5-1-2-6(10)7(11)3-5/h1-3,11H,4H2

description: dataset for 19F nuclear magnetic resonance spectroscopy (19F NMR)