cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.aka5ys
title: Occurrence Download

description: A dataset containing 314 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Boehmeria grandis",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 }
 ]
}

 The dataset includes 314 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014540-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18628713
title: 20260211_carmen
DOI: 10.5281/zenodo.18628714
title: 20260211_carmen
DOI: 10.17044/scilifelab.28673273
title: DNA-based monitoring of bacterial and protist diversity in the Baltic Sea

description: <pre>Here we share the code, the sequencing processing output, and the intermediate data files for the work on bacterial and protist diversity patterns in the Baltic Sea area based on 16S and 18S metabarcoding as implemented two times for a year alongside the Swedish coastline monitoring programme. This work is available as a preprint:<br><br>Distinct bacterial and protist plankton diversity dynamics uncovered through DNA-based monitoring in the Baltic Sea area, Krzysztof T Jurdzinski, Meike AC Latz, Anders Torstensson, Sonia Brugel, Mikael Hedblom, Yue O O Hu, Markus Lindh, Agneta Andersson, Bengt Karlson, Anders F Andersson, bioRxiv 2024.08.14.607742; doi: https://doi.org/10.1101/2024.08.14.607742 <br><br>Documentation files:<br><br>README.md - description of the files, including all the files within the zipped folders.<br>environment.yml - conda environment with software/packages needed to run all the included scripts.<br>workflow.sh - a bash script defining the workflow.<br><br>Zipped folders with data processing documentation and intermediate files<br><br>ampliseq_16S.zip - this directory includes the scripts used to run the nf-core/ampliseq pipeline on the V3-V4 16S metabarcoding samples, as well as output files needed for downstream analysis.<br><br>ampliseq_18S.zip - same as ampliseq_16S.zip, but for the the V4 18S metabarcoding.<br><br>taxa_reannotation.zip - each subdirectory contains results of taxonomic re-annotation of the metabarcoding results and the scripts to obtain them. Both 2015-2017 and 2019-2020 datasets were re-annotated with the GTDB corrected for mislabled sequences using SATIVA and with PR2 version 5.0.0 for 16S and 18S respectively. Both 16S datasets were re-annotated using the SILVA database (version 138.1). <br><br>data_2015_2017.zip -these files correspond to the data for the samples from 2015 to 2017 (+ storage test for some 2019 samples). This is new data, later down the pipeline merged with the 2019-2020 dataset.<br><br>merged_data.zip - this folder contains merged across the 2015-2017 and the 2019-2020 datasets, based on the files from folders data_2015_2017 and data_2019_2020-<br><br>GSHHG.zip - Global Self-consistent, Hierarchical, High-resolution Geography Database (GSHHG) version 2.3.7 file needed to plot maps, as downloaded from the NOAA website.<br><br>Herlemann_et_al_2016.zip - data from the transect-based study by Herlemann et al., 2016.<br><br>read_downsampling.zip - This folder includes the scripts used to rarefy raw reads and the key output files. It is all based on 16S data.<br><br>freshwater_marine_matching.zip - this folder includes files and code used for matching the ASVs from this study to database freshwater and marine sequences<br><br><br>Zipped folders with key R scripts<br><br>processing_code.zip - R scripts used for multiple steps of intermediate data table processing.<br><br>analysis_figures_code.zip - R scripts used to analyze the data and generate the figures.</pre><br>
DOI: 10.17044/scilifelab.28673273.v1
title: DNA-based monitoring of bacterial and protist diversity in the Baltic Sea

description: <pre>Here we share the code, the sequencing processing output, and the intermediate data files for the work on bacterial and protist diversity patterns in the Baltic Sea area based on 16S and 18S metabarcoding as implemented two times for a year alongside the Swedish coastline monitoring programme. This work is available as a preprint:<br><br>Distinct bacterial and protist plankton diversity dynamics uncovered through DNA-based monitoring in the Baltic Sea area, Krzysztof T Jurdzinski, Meike AC Latz, Anders Torstensson, Sonia Brugel, Mikael Hedblom, Yue O O Hu, Markus Lindh, Agneta Andersson, Bengt Karlson, Anders F Andersson, bioRxiv 2024.08.14.607742; doi: https://doi.org/10.1101/2024.08.14.607742 <br><br>Documentation files:<br><br>README.md - description of the files, including all the files within the zipped folders.<br>environment.yml - conda environment with software/packages needed to run all the included scripts.<br>workflow.sh - a bash script defining the workflow.<br><br>Zipped folders with data processing documentation and intermediate files<br><br>ampliseq_16S.zip - this directory includes the scripts used to run the nf-core/ampliseq pipeline on the V3-V4 16S metabarcoding samples, as well as output files needed for downstream analysis.<br><br>ampliseq_18S.zip - same as ampliseq_16S.zip, but for the the V4 18S metabarcoding.<br><br>taxa_reannotation.zip - each subdirectory contains results of taxonomic re-annotation of the metabarcoding results and the scripts to obtain them. Both 2015-2017 and 2019-2020 datasets were re-annotated with the GTDB corrected for mislabled sequences using SATIVA and with PR2 version 5.0.0 for 16S and 18S respectively. Both 16S datasets were re-annotated using the SILVA database (version 138.1). <br><br>data_2015_2017.zip -these files correspond to the data for the samples from 2015 to 2017 (+ storage test for some 2019 samples). This is new data, later down the pipeline merged with the 2019-2020 dataset.<br><br>merged_data.zip - this folder contains merged across the 2015-2017 and the 2019-2020 datasets, based on the files from folders data_2015_2017 and data_2019_2020-<br><br>GSHHG.zip - Global Self-consistent, Hierarchical, High-resolution Geography Database (GSHHG) version 2.3.7 file needed to plot maps, as downloaded from the NOAA website.<br><br><br>Herlemann_et_al_2016.zip - data from the transect-based study by Herlemann et al., 2016.<br><br>read_downsampling.zip - This folder includes the scripts used to rarefy raw reads and the key output files. It is all based on 16S data.<br><br>Zipped folders with key R scripts<br><br>processing_code.zip - R scripts used for multiple steps of intermediate data table processing.<br>analysis_figures_code.zip - R scripts used to analyze the data and generate the figures.</pre>
DOI: 10.17044/scilifelab.28673273.v2
title: DNA-based monitoring of bacterial and protist diversity in the Baltic Sea

description: <pre>Here we share the code, the sequencing processing output, and the intermediate data files for the work on bacterial and protist diversity patterns in the Baltic Sea area based on 16S and 18S metabarcoding as implemented two times for a year alongside the Swedish coastline monitoring programme. This work is available as a preprint:<br><br>Distinct bacterial and protist plankton diversity dynamics uncovered through DNA-based monitoring in the Baltic Sea area, Krzysztof T Jurdzinski, Meike AC Latz, Anders Torstensson, Sonia Brugel, Mikael Hedblom, Yue O O Hu, Markus Lindh, Agneta Andersson, Bengt Karlson, Anders F Andersson, bioRxiv 2024.08.14.607742; doi: https://doi.org/10.1101/2024.08.14.607742 <br><br>Documentation files:<br><br>README.md - description of the files, including all the files within the zipped folders.<br>environment.yml - conda environment with software/packages needed to run all the included scripts.<br>workflow.sh - a bash script defining the workflow.<br><br>Zipped folders with data processing documentation and intermediate files<br><br>ampliseq_16S.zip - this directory includes the scripts used to run the nf-core/ampliseq pipeline on the V3-V4 16S metabarcoding samples, as well as output files needed for downstream analysis.<br><br>ampliseq_18S.zip - same as ampliseq_16S.zip, but for the the V4 18S metabarcoding.<br><br>taxa_reannotation.zip - each subdirectory contains results of taxonomic re-annotation of the metabarcoding results and the scripts to obtain them. Both 2015-2017 and 2019-2020 datasets were re-annotated with the GTDB corrected for mislabled sequences using SATIVA and with PR2 version 5.0.0 for 16S and 18S respectively. Both 16S datasets were re-annotated using the SILVA database (version 138.1). <br><br>data_2015_2017.zip -these files correspond to the data for the samples from 2015 to 2017 (+ storage test for some 2019 samples). This is new data, later down the pipeline merged with the 2019-2020 dataset.<br><br>merged_data.zip - this folder contains merged across the 2015-2017 and the 2019-2020 datasets, based on the files from folders data_2015_2017 and data_2019_2020-<br><br>GSHHG.zip - Global Self-consistent, Hierarchical, High-resolution Geography Database (GSHHG) version 2.3.7 file needed to plot maps, as downloaded from the NOAA website.<br><br>Herlemann_et_al_2016.zip - data from the transect-based study by Herlemann et al., 2016.<br><br>read_downsampling.zip - This folder includes the scripts used to rarefy raw reads and the key output files. It is all based on 16S data.<br><br>freshwater_marine_matching.zip - this folder includes files and code used for matching the ASVs from this study to database freshwater and marine sequences<br><br><br>Zipped folders with key R scripts<br><br>processing_code.zip - R scripts used for multiple steps of intermediate data table processing.<br><br>analysis_figures_code.zip - R scripts used to analyze the data and generate the figures.</pre><br>
DOI: 10.15468/dl.m8vgde
title: Occurrence Download

description: A dataset containing 4052 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Agrilus planipennis)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Year is not null",
 "BasisOfRecord is one of (Human Observation, Occurrence evidence)",
 "Year is greater than or equal to 2010",
 "Year is less than or equal to 2026"
 ]
}

 The dataset includes 4052 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014541-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18257787
title: Dataset of "A Comparative Study of Physical blending and hydrogel-derived approaches for Si-based anode materials in Li-ion batteries"

description: Silicon nanomaterials are promising anode materials for lithium-ion batteries (LIB) due to their high theoretical capacity. However, their practical application is hindered by poor electrical conductivity and large volume expansion during cycling. Among these nanomaterials, silicon nanocrystals (SiNC) offer tunable particle size and surface properties that strongly influence electrochemical performance. This study investigates how anode fabrication method and SiNC structural characteristics, including particle size and surface oxidation, affect LIB behavior. Two widely used preparation strategies were compared: (i) physical blending of SiNC with a polyacrylic acid binder and Super P conductive carbon, and (ii) hydrogel-assisted synthesis via in situ polymerization of polypyrrole (PPy) in the presence of phytic acid and SiNC, forming a three-dimensional, flexible, and conductive network. Microstructural analysis, galvanostatic cycling, cyclic voltammetry, electrochemical impedance spectroscopy, and post-mortem characterization revealed complementary strengths and limitations  of each preparation method. Smaller SiNC improved capacity retention in both systems, with a more pronounced effect in hydrogel-derived anodes (44% retention after 500 cycles) due to enhanced dispersion and mechanical support. Super P/SiNC anodes exhibited higher initial discharge capacity (2581 mAh/g) and faster lithiation kinetics, whereas PPy/SiNC anodes demonstrated superior long-term cycling stability by mitigating anode degradation. These results highlight the critical interplay between nanomaterial design and electrode architecture and provide mechanistic insight and guidance for the development of next-generation high-performance Si-based anodes.
DOI: 10.5281/zenodo.18257786
title: Dataset of "A Comparative Study of Physical blending and hydrogel-derived approaches for Si-based anode materials in Li-ion batteries"

description: Silicon nanomaterials are promising anode materials for lithium-ion batteries (LIB) due to their high theoretical capacity. However, their practical application is hindered by poor electrical conductivity and large volume expansion during cycling. Among these nanomaterials, silicon nanocrystals (SiNC) offer tunable particle size and surface properties that strongly influence electrochemical performance. This study investigates how anode fabrication method and SiNC structural characteristics, including particle size and surface oxidation, affect LIB behavior. Two widely used preparation strategies were compared: (i) physical blending of SiNC with a polyacrylic acid binder and Super P conductive carbon, and (ii) hydrogel-assisted synthesis via in situ polymerization of polypyrrole (PPy) in the presence of phytic acid and SiNC, forming a three-dimensional, flexible, and conductive network. Microstructural analysis, galvanostatic cycling, cyclic voltammetry, electrochemical impedance spectroscopy, and post-mortem characterization revealed complementary strengths and limitations  of each preparation method. Smaller SiNC improved capacity retention in both systems, with a more pronounced effect in hydrogel-derived anodes (44% retention after 500 cycles) due to enhanced dispersion and mechanical support. Super P/SiNC anodes exhibited higher initial discharge capacity (2581 mAh/g) and faster lithiation kinetics, whereas PPy/SiNC anodes demonstrated superior long-term cycling stability by mitigating anode degradation. These results highlight the critical interplay between nanomaterial design and electrode architecture and provide mechanistic insight and guidance for the development of next-generation high-performance Si-based anodes.
DOI: 10.34894/ytqrm8
title: GO TEST Overture – Pragmatic RCT dataset: Treat-to-Target vs Treat-to-Avoid-Symptoms in early gout (Netherlands, 2021–2025)

description: Pragmatic multicentre open-label randomized controlled trial conducted in seven centres in the Netherlands (n=308), comparing Treat-to-Target (T2T) versus Treat-to-Avoid-Symptoms (T2S) strategies in patients with early gout. Participants were followed for 24 months. Data include baseline characteristics, laboratory measurements (including serum urate and eGFR), medication use, gout flares, adverse events, and patient-reported outcome measures collected every three months. Data were captured using Castor EDC. Access to the data is subject to consent and approval by VieCuri Medical Center.
description: The data are sensitive since they involve personal information of patients. There are restrictions on use by commercial parties and on sharing openly, based on (inter)national laws and regulations and written informed consent. Therefore these data (and additional clinical data) are only available upon signing a Data Transfer Agreement (see Terms of Access).
DOI: 10.15468/dl.ehzfeg
title: Occurrence Download

description: A dataset containing 1739 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Peltigera collina",
 "Country is one of (Norway)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "CoordinateUncertaintyInMeters is less than or equal to 1000",
 "Year is greater than or equal to 1986",
 "Year is less than or equal to 2025",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 },
 {
 "not" : {
 "BasisOfRecord" : [
 "is Machine Observation"
 ]
 }
 }
 ]
}

 The dataset includes 1739 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014542-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fpzknh
title: Occurrence Download

description: A dataset containing 88053 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pseudopleuronectes",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 88053 records from 104 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014511-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.23668/psycharchives.15511
title: Dataset for: Deficits in or preservation of basic number processing in Parkinson's Disease
title: NumCogPD Basic number processing

description: Neurodegenerative diseases such as Parkinson’s Disease (PD) have a huge impact on patients, caregivers, and the health care system. Until now, diagnosis of mild cognitive impairments in PD has been established based on domain-general functions such as executive functions, attention or working memory. However, specific numerical deficits observed in clinical practice have not yet been systematically investigated. PD-immanent deterioration of domain-general functions and domain-specific numerical areas suggests mechanisms of both primary and secondary dyscalculia. The current study systematically investigated basic number processing performance in PD patients for the first time, targeting domain-specific cognitive representations of numerosity and the influence of domain-general factors. The overall sample consisted of patients with a diagnosis of PD, according to consensus guidelines, and healthy controls. PD patients were stratified into patients with normal cognition (PD-NC) or mild cognitive impairment (level I-PD-MCI based on cognitive screening). Basic number processing was assessed using transcoding, number line estimation, and (non-) symbolic number magnitude comparison tasks. Discriminant analysis was employed to assess whether basic number processing tasks can differentiate between a healthy control group and both PD groups. All participants were subjected to a comprehensive numerical and a neuropsychological test battery, as well as sociodemographic and clinical measures. Results indicate a profile of preserved (verbal representation) and impaired (magnitude representation, place × value activation) function in PD-MCI, hinting at basal ganglia dysfunction affecting numerical cognition in PD. Numerical deficits could not be explained by domain-general cognitive impairments, so that future research needs to incorporate domain-specific tasks of sufficient difficulty.
description: Dataset for: Loenneker, H.D., Artemenko, C., Willmes, K., Liepelt-Scarfone, I. and Nuerk, H.-C. (2024), Deficits in or Preservation of Basic Number Processing in Parkinson's Disease? A Registered Report. J Neurosci Res, 102: e25397. https://doi.org/10.1002/jnr.25397 [Stage 2 Registered Report]
DOI: 10.15468/dl.upw3jy
title: Occurrence Download

description: A dataset containing 24 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cyrtandra cordifolia",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 }
 ]
}

 The dataset includes 24 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014543-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9nxgmd
title: Occurrence Download

description: A dataset containing 541 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Peltigera rufescens",
 "Country is one of (Norway)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "CoordinateUncertaintyInMeters is less than or equal to 1000",
 "Year is greater than or equal to 1986",
 "Year is less than or equal to 2025",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 },
 {
 "not" : {
 "BasisOfRecord" : [
 "is Machine Observation"
 ]
 }
 }
 ]
}

 The dataset includes 541 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014544-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48580/dgwnj.v1
title: New records of semi-aquatic bugs (Hemiptera, Heteroptera, Gerromorpha) from the South Region of Brazil
DOI: 10.15468/dl.u2ftf3
title: Occurrence Download

description: A dataset containing 103 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cyrtandra longifolia",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 }
 ]
}

 The dataset includes 103 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014545-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4wrjmx
title: Occurrence Download

description: A dataset containing 3105 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Nephroma parile",
 "Country is one of (Norway)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "CoordinateUncertaintyInMeters is less than or equal to 1000",
 "Year is greater than or equal to 1986",
 "Year is less than or equal to 2025",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 },
 {
 "not" : {
 "BasisOfRecord" : [
 "is Machine Observation"
 ]
 }
 }
 ]
}

 The dataset includes 3105 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014546-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m6hcqb
title: Occurrence Download

description: A dataset containing 1535 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((3.01614 42.78598,3.01325 42.77751,3.01637 42.77033,3.02543 42.77045,3.03126 42.7768,3.02991 42.78275,3.02643 42.78775,3.01896 42.78916,3.01614 42.78598))",
 "PublishingOrg is 1928bdf0-f5d2-11dc-8c12-b8a03c50a862"
 ]
}

 The dataset includes 1535 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014548-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18628730
title: A curated list of computational tools, databases, and software for metabolomics research published between 2021-2025.

description: Methodology


We compiled this comprehensive list of computational tools and databases through a systematic approach. We began with manual curation of published metabolomics resources starting in 2021, building upon our prior review efforts (Misra, 2021; Misra and van der Hooft, 2015). To ensure complete coverage and minimize gaps, we subsequently employed three complementary strategies:



Computational screening: Used AI-assisted tools and Google Scholar to identify emerging metabolomics software and databases across the 2021–2025 period

Literature review: Systematically examined citations and references in recent comprehensive metabolomics reviews for each functional category

Field experts: Reviewed our compilation with domain experts across different metabolomics subdisciplines


Details at https://github.com/enveda/computational-metabolomics-review/