cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.34740/kaggle/dsv/13279504
title: Predicting Road Accident Risk | Vault
DOI: 10.15468/dl.rktznb
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cambarincola mesochoreus",
 "Country is Italy",
 "HasCoordinate is true"
 ]
}

 The dataset includes 4 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053859-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ewfx2m
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cambarincola mesochoreus",
 "Country is Germany",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053858-250920141307145/datasets/export for details.
DOI: 10.26165/juelich-data/yvx4yp
title: Annual groundwater recharge (1971-2100) in Germany (200 m grid) with the identifier R26-MP1-RCA_mGROWA20210515

description: Annual groundwater recharge (1971-2100) in Germany (200 m grid) with the identifier R26-MP1-RCA_mGROWA20210515
DOI: 10.6084/m9.figshare.29371610.v2
title: Local Resilience from Rust Belt America to Jammu’s Forgotten Districts.docx

description: Deglobalisation offers a path to local resilience, mental health recovery, and ethical renewal.<br>From Rust Belt America to Jammu’s forgotten districts, it signals a return to dignity and self-determination.
DOI: 10.5517/ccdc.csd.cc2pd149
title: CCDC 2484220: Experimental Crystal Structure Determination

description: Related Article: Constantin G. Daniliuc, Jun Li, Gerhard Erker|2025|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2pdc3l
title: CCDC 2484529: Experimental Crystal Structure Determination

description: Related Article: Constantin G. Daniliuc, Kohei Watanabe, Gerhard Erker|2025|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2pdg7t
title: CCDC 2484626: Experimental Crystal Structure Determination

description: Related Article: Constantin G. Daniliuc, Atsushi Ueno, Gerhard Erker|2025|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2pdg8v
title: CCDC 2484627: Experimental Crystal Structure Determination

description: Related Article: Constantin G. Daniliuc, Atsushi Ueno, Gerhard Erker|2025|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2pdgm6
title: CCDC 2484638: Experimental Crystal Structure Determination

description: Related Article: Constantin G. Daniliuc, Atsushi Ueno, Gerhard Erker|2025|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2pdgp8
title: CCDC 2484640: Experimental Crystal Structure Determination

description: Related Article: Constantin G. Daniliuc, Jun Li, Gerhard Erker|2025|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.26023/jvc3-2a0q-k310
title: DC3: NASA DC-8 In-situ Submicron Particle Size Distributions from the DMT UHSAS Data. Version 2.0

description: This data set contains NASA DC-8 Langley Aerosol Research Group Experiment (LARGE) Ammonium Sulfate (AmmSO4) size distribution data from the DMT Ultra-High Sensitivity Aerosol Spectrometer (UHSAS) collected during the Deep Convective Clouds and Chemistry Experiment (DC3) from 18 May 2012 through 22 June 2012. This data set is in ICARTT format. Please see the header portion of the data files for details on instruments, parameters, quality assurance, quality control, contact information, and data set comments.
DOI: 10.15468/dl.cjf2sf
title: Occurrence Download

description: A dataset containing 9984 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Iran (Islamic Republic of)",
 "OccurrenceStatus is Present",
 "TaxonKey is Pycnonotus leucotis",
 "Year 2014-2025"
 ]
}

 The dataset includes 9984 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053860-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.c7rm9m
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Xironogiton victoriensis",
 "Country is Germany",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053861-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r9xwmb
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Xironogiton victoriensis",
 "Country is Italy",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053862-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57755/maj2-s226
title: Synbiotic amplification of Melissa officinalis phenolic acids: bacterial transformation, matrix interactions, and in vitro digestion data

description: <p>This dataset includes (I) UPLC-PDA chromatographic data of <em>Melissa officinalis</em> phenolic compounds after incubation with <em>Lactobacillus</em> and <em>Bifidobacterium</em> strains; (II) digestion data for <em>L. acidophilus</em>-transformed extract with and without non-starch polysaccharide matrices; (III) phenolic contents and digestion indices (BI%, RI%, RID%); (IV) spectrophotometric antioxidant and antidiabetic activities; and (V) statistical analyses (ANOVA, AHC, PCA, correlations, heat maps).<br /></p>
DOI: 10.15468/dl.42rwwf
title: Occurrence Download

description: A dataset containing 53 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Cottus gobio Linnaeus, 1758",
 "Country is Norway",
 "Year is greater than or equal to 2000",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 53 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053811-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g37yp6
title: Occurrence Download

description: A dataset containing 9968 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "Country is Uruguay"
 ]
 },
 "Geometry POLYGON((-55.83681 -34.74529,-55.83315 -34.76403,-55.80175 -34.76038,-55.81173 -34.73701,-55.82634 -34.73847,-55.83681 -34.74529))"
 ]
}

 The dataset includes 9968 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053863-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17028/rd.lboro.28920461
title: Supplementary information files for "Insights Into Lithium‐Ion Battery Cell Temperature and State of Charge Using Dynamic Electrochemical Impedance Spectroscopy"

description: Supplementary files for article "Insights into lithium‐ion battery cell temperature and state of charge using dynamic electrochemical impedance spectroscopy"<br><br>Understanding and accurately determining battery cell properties is crucial for assessing battery capabilities. Electrochemical impedance spectroscopy (EIS) is commonly employed to evaluate these properties, typically under controlled laboratory conditions with steady‐state measurements. Traditional steady‐state EIS (SSEIS) requires the battery to be at rest to ensure a linear response. However, real‐world applications, such as electric vehicles (EVs), expose batteries to varying states of charge (SOC) and temperature fluctuations, often occurring simultaneously. This study investigates the impact of SOC and temperature on EIS in terms of battery properties and impedance. Initially, SSEIS results were compared with dynamic EIS (DEIS) outcomes after a full charge under changing temperatures. Subsequently, DEIS was analysed using combined SOC and temperature variations during active charging. The study employed a commercial 450 mAh lithium‐ion (Li‐ion) cobalt oxide (LCO) graphite pouch cell, subject to a 1C constant current (CC)–constant voltage (CCCV) charge for SSEIS and CC charge for DEIS, with SOC ranging from 50% to 100% and cell temperatures from 10 to 35°C. The research developed models to interpolate battery impedance data, demonstrating accurate impedance predictions across operating conditions. Findings revealed significant differences between dynamic data and steady‐state results, with DEIS more accurately reflecting real‐use scenarios where the battery is not at equilibrium and exhibits concentration gradients. These models have potential applications in battery management systems (BMSs) for EVs, enabling health assessments by predicting resistance and capacitance changes, thereby ensuring battery cells’ longevity and optimal performance.<br><br>© The Author(s), CC BY-4.0
DOI: 10.17028/rd.lboro.28920461.v1
title: Supplementary information files for "Insights Into Lithium‐Ion Battery Cell Temperature and State of Charge Using Dynamic Electrochemical Impedance Spectroscopy"

description: Supplementary files for article "Insights into lithium‐ion battery cell temperature and state of charge using dynamic electrochemical impedance spectroscopy"<br><br>Understanding and accurately determining battery cell properties is crucial for assessing battery capabilities. Electrochemical impedance spectroscopy (EIS) is commonly employed to evaluate these properties, typically under controlled laboratory conditions with steady‐state measurements. Traditional steady‐state EIS (SSEIS) requires the battery to be at rest to ensure a linear response. However, real‐world applications, such as electric vehicles (EVs), expose batteries to varying states of charge (SOC) and temperature fluctuations, often occurring simultaneously. This study investigates the impact of SOC and temperature on EIS in terms of battery properties and impedance. Initially, SSEIS results were compared with dynamic EIS (DEIS) outcomes after a full charge under changing temperatures. Subsequently, DEIS was analysed using combined SOC and temperature variations during active charging. The study employed a commercial 450 mAh lithium‐ion (Li‐ion) cobalt oxide (LCO) graphite pouch cell, subject to a 1C constant current (CC)–constant voltage (CCCV) charge for SSEIS and CC charge for DEIS, with SOC ranging from 50% to 100% and cell temperatures from 10 to 35°C. The research developed models to interpolate battery impedance data, demonstrating accurate impedance predictions across operating conditions. Findings revealed significant differences between dynamic data and steady‐state results, with DEIS more accurately reflecting real‐use scenarios where the battery is not at equilibrium and exhibits concentration gradients. These models have potential applications in battery management systems (BMSs) for EVs, enabling health assessments by predicting resistance and capacitance changes, thereby ensuring battery cells’ longevity and optimal performance.<br><br>© The Author(s), CC BY-4.0
DOI: 10.5281/zenodo.15057027
title: Data for raxtax: A k-mer-based non-Bayesian Taxonomic Classifier

description: This repository contains the input databases and summarized results for evaluating our preprint:

 raxtax: A k-mer-based non-Bayesian Taxonomic Classifier (BioRxiv)

Abstract

Motivation: Taxonomic classification in biodiversity studies is the process of assigning the anonymous sequences of amarker gene (barcode) or whole genomes (metagenomics) to a specific lineage using a reference database that containsnamed sequences in a known taxonomy. This classification is important for assessing the diversity of biological systems.Taxonomic classification faces two main challenges: first, accuracy is critical as errors can propagate to downstreamanalysis results; and second, the classification time requirements can limit study size and study design, in particularwhen considering the constantly growing reference databases. To address these two challenges, we introduce raxtax,an efficient, novel taxonomic classification tool for barcodes that uses common k-mers between all pairs of query andreference sequences. We also introduce two novel uncertainty scores which take into account the fundamental biases ofreference databases.Results: We validate raxtax on three widely used empirical reference databases and show that it is 2.7-100 times fasterthan competing state-of-the-art tools on the largest database while being equally accurate. In particular, raxtax exhibitsincreasing speedups with growing query and reference sequence numbers compared to existing tools (for 100,000 and1,000,000 query and reference sequences overall, it is 1.3 and 2.9 times faster, respectively), and therefore alleviates thetaxonomic classification scalability challenge.Availability and Implementation: raxtax is available at https://github.com/noahares/raxtax under a CC-NC-BY-SA license. The raxtax source code, scripts and summary metrics used in our analyses are available at https://github.com/noahares/raxtax_paper_scripts.

Original Data Sources

UNITE: https://doi.plutof.ut.ee/doi/10.15156/BIO/2959332

Greengenes: http://ftp.microbio.me/greengenes_release/gg_13_5/

BOLD: https://boldsystems.org/ (exact database version no longer available)

Empirical Insect OTUs: https://www.ebi.ac.uk/ena/browser/view/PRJEB71324
DOI: 10.5281/zenodo.17277436
title: Data for raxtax: A k-mer-based non-Bayesian Taxonomic Classifier

description: This repository contains the input databases and summarized results for evaluating our preprint:

 raxtax: A k-mer-based non-Bayesian Taxonomic Classifier (BioRxiv)

Abstract

Motivation: Taxonomic classification in biodiversity studies is the process of assigning the anonymous sequences of amarker gene (barcode) or whole genomes (metagenomics) to a specific lineage using a reference database that containsnamed sequences in a known taxonomy. This classification is important for assessing the diversity of biological systems.Taxonomic classification faces two main challenges: first, accuracy is critical as errors can propagate to downstreamanalysis results; and second, the classification time requirements can limit study size and study design, in particularwhen considering the constantly growing reference databases. To address these two challenges, we introduce raxtax,an efficient, novel taxonomic classification tool for barcodes that uses common k-mers between all pairs of query andreference sequences. We also introduce two novel uncertainty scores which take into account the fundamental biases ofreference databases.Results: We validate raxtax on three widely used empirical reference databases and show that it is 2.7-100 times fasterthan competing state-of-the-art tools on the largest database while being equally accurate. In particular, raxtax exhibitsincreasing speedups with growing query and reference sequence numbers compared to existing tools (for 100,000 and1,000,000 query and reference sequences overall, it is 1.3 and 2.9 times faster, respectively), and therefore alleviates thetaxonomic classification scalability challenge.Availability and Implementation: raxtax is available at https://github.com/noahares/raxtax under a CC-NC-BY-SA license. The raxtax source code, scripts and summary metrics used in our analyses are available at https://github.com/noahares/raxtax_paper_scripts.

Original Data Sources

UNITE: https://doi.plutof.ut.ee/doi/10.15156/BIO/2959332

Greengenes: http://ftp.microbio.me/greengenes_release/gg_13_5/

BOLD: https://boldsystems.org/ (exact database version no longer available)

Empirical Insect OTUs: https://www.ebi.ac.uk/ena/browser/view/PRJEB71324
DOI: 10.5281/zenodo.17279009
title: Data set Le boulch et al.
DOI: 10.5281/zenodo.17279010
title: Data set Le boulch et al.
DOI: 10.5281/zenodo.17277443
title: A robust phenology-based algorithm for sugar beet mapping with time-series Sentinel-2 and MODIS LST data

description: This dataset provides yearly maps of sugar beet cultivation areas in Inner Mongolia, China.

Specifications:





Format: GeoTIFF




Temporal Resolution: Yearly (2020–2024)




Spatial Resolution: 10 m




Coordinate System: WGS 1984




Geographic Extent: Inner Mongolia, China



Data Content:Each file is a binary map where:





Value 1: Sugar beet pixels




Value 0: Other land cover types or no data



File Naming:Files are named as sugarbeetYYYY.tif, with YYYY representing the year (e.g., sugarbeet2020.tif).
DOI: 10.5281/zenodo.17277444
title: A robust phenology-based algorithm for sugar beet mapping with time-series Sentinel-2 and MODIS LST data

description: This dataset provides yearly maps of sugar beet cultivation areas in Inner Mongolia, China.

Specifications:





Format: GeoTIFF




Temporal Resolution: Yearly (2020–2024)




Spatial Resolution: 10 m




Coordinate System: WGS 1984




Geographic Extent: Inner Mongolia, China



Data Content:Each file is a binary map where:





Value 1: Sugar beet pixels




Value 0: Other land cover types or no data



File Naming:Files are named as sugarbeetYYYY.tif, with YYYY representing the year (e.g., sugarbeet2020.tif).
DOI: 10.15468/dl.je24y9
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Piscicola haranti",
 "Country is Germany",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053866-250920141307145/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.30286492
title: Data file 11 Mobile genetic element detection of <i>H. oleronia</i> EISK28

description: Data file 11 Mobile genetic element detection of <i>H. oleronia</i> EISK28
DOI: 10.6084/m9.figshare.30286492.v1
title: Data file 11 Mobile genetic element detection of <i>H. oleronia</i> EISK28

description: Data file 11 Mobile genetic element detection of <i>H. oleronia</i> EISK28
DOI: 10.25824/redu/zh2pij
title: Dados de replicação para: Simulação reativa de dispersão de poluentes em desfiladeiros urbanos

description: OpenFOAM files for generating CFD simulations of reactive pollutant dispersion.
DOI: 10.26023/5kwq-whgw-t80j
title: DC3: NASA DC-8 Diode Laser Spectrometer CO, CH4, and N2O Measurements. Version 2.0

description: This data set contains NASA DC-8 Diode Laser Spectrometer measurements of CO, CH4, and N2O collected during the Deep Convective Clouds and Chemistry Experiment (DC3) from 18 May 2012 through 22 June 2012. This data set is in ICARTT format. Please see the header portion of the data files for details on instruments, parameters, quality assurance, quality control, contact information, and data set comments. Latest Update: * Data time offset has been adjusted to provide maximum temporal registration with DLH water vapor data.
DOI: 10.15468/dl.ykfssh
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cicurina japonica",
 "Country is Germany",
 "HasCoordinate is true"
 ]
}

 The dataset includes 20 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053867-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17144220
title: DNA methylation and immune infiltration mediate the impact of tobacco exposure on pancreatic adenocarcinoma outcome: a high-dimensional mediation analysis - Datasets

description: All necessary files to reproduce the figures.
DOI: 10.5281/zenodo.17278960
title: DNA methylation and immune infiltration mediate the impact of tobacco exposure on pancreatic adenocarcinoma outcome: a high-dimensional mediation analysis - Datasets

description: All necessary files to reproduce the figures.
DOI: 10.25824/redu/zu616h
title: Dados relativos a aspectos demográficos, clínicos e parâmetros laboratoriais de anemia, hemólise, metabolismo do ferro e inflamação de pacientes internados por COVID-19

description: Tabela de dados coletados retrospectivamente relativos a aspectos demográficos, clínicos e parâmetros laboratoriais de anemia, hemólise, metabolismo do ferro e inflamação de pacientes não vacinados internados devido à COVID-19 no HC/Unicamp no período de abril/2020 a março/2021.
DOI: 10.57755/a75r-bp45
title: Green tea phenolic compounds: bacterial pre-transformation, in vitro digestion, LC-MS profiling and bioaccessibility

description: <p>This dataset contains raw data supporting chromatographic profiling and digestive behavior of green tea phenolic compounds in synbiotic systems. The package includes: (i) UPLC-PDA chromatographic data for phenolic compounds in synbiotics containing green tea extract (<em>Camellia sinensis</em> L.) with <em>Lactobacillus</em> and <em>Bifidobacterium</em> strains and corresponding controls; (ii) UPLC-PDA chromatographic data of fractions obtained after in vitro digestion of selected synbiotic with <em>L. acidophilus</em> DSM 20079, with and without food matrices; (iii) LC-PDA chromatographic datasets of selected synbiotic samples and controls; (iv) quantitative changes and digestive retention indices of phenolic compounds in synbiotic and matrix-enriched variants during simulated digestion; and (v) statistical outputs including PCA, hierarchical clustering (AHC), and heat map visualizations.</p>