cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.13352203
title: Whole-Genome Resequencing identifies SNPs in Sucrose Synthase and Sugar Transporter Genes Associated with Sweetness in Coconut

description: This vcf file constitute underlying raw data material for the manuscript "Whole-Genome Resequencing identifies SNPs in Sucrose Synthase and Sugar Transporter Genes Associated with Sweetness in Coconut". The SNP genotype data came from a whole-genome resequencing and were called using an unpublished coconut reference genome. SNPs with a non-missing and minor allele frequency (MAF) less than 5% were removed.  Finally, 19,149,289 SNPs were selected and used in the population study and gene mining.
DOI: 10.5281/zenodo.13352204
title: Whole-Genome Resequencing identifies SNPs in Sucrose Synthase and Sugar Transporter Genes Associated with Sweetness in Coconut

description: This vcf file constitute underlying raw data material for the manuscript "Whole-Genome Resequencing identifies SNPs in Sucrose Synthase and Sugar Transporter Genes Associated with Sweetness in Coconut". The SNP genotype data came from a whole-genome resequencing and were called using an unpublished coconut reference genome. SNPs with a non-missing and minor allele frequency (MAF) less than 5% were removed.  Finally, 19,149,289 SNPs were selected and used in the population study and gene mining.
DOI: 10.15468/dl.sha77d
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "TaxonKey is Nicholsina usta (Valenciennes, 1840)"
 ]
}

 The dataset includes 16 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0076705-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15485/1828377
title: Optode Images, and Dissolved Oxygen Data from Sand and Sediment Flow-through Column Experiments associated with: "2-D Imaging of Dissolved Oxygen Concentration in Flow-Through Sediment Columns"

description: This data package is associated with the publication "2-D Imaging of Dissolved Oxygen Concentration in Flow-Through Sediment Columns" submitted to Frontiers in Water (Garayburu-Caruso et al., 2022). This work presents a novel application of planar optode technology to sediment columns that allows the study of well-constrained flow fields without the need to assume completely homogeneous flow. We introduce a flow-through column with the interior coated in an oxygen sensing film and a series of sampling ports as a unique tool capable of capturing changes in dissolved oxygen (DO) at high frequency (10 s) and spatial (&lt; 1 mm) resolution across the length of a column. In addition, we provide custom scripts that allows image processing steps to be automated and consistently reproduced over a variety of experimental conditions. This dataset is comprised of four folders (1) 01_Riverbed_Sediment_Experiment, (2) 02_Sand_Experiment, (3) 01_Riverbed_Sediment_Raw_Images, and (4) 02_Sand_Experiment_Raw_Images. 01_Riverbed_Sediment_Experiment contains (1) a subfolder with csv files that contain statistical parameters from the linear regressions applied to each optode image, (2) a subfolder with csv files from DO data measured by in-line sensors, (3) a subfolder with csv files containing column and injection specific input parameters for the image processing script, and (4) a subfolder with scripts used to process the images and create associated figures. 02_Sand_Experiment contains (1) a subfolder with csv files containing column and injection-specific input parameters for the image processing script, and (2) a subfolder with scripts used to process the images and create associated figures. 01_Riverbed_Sediment_Raw_Images (spited in 3 parts due to size) contains a subfolder with raw red, and green images from the optode system during the MilliQ Injection, Vanillin Injection or Vanillin + Sampling Injection respectively. 02_Sand_Experiment_Raw_Images contains a subfolder with raw red, and green images from the optode system. Outside of the main folders there is a csv containing file-level metadata and a csv data dictionary defining column headers for all csv files contained in the data package.
DOI: 10.15485/1839188
title: FTICR-MS and Biochemical Transformation Data from Global Inland River Water and Sediment Associated with: "Organic Matter Transformations are Disconnected Between Surface Water and the Hyporheic Zone"

description: This data package is associated with the publication "Organic Matter Transformations are Disconnected Between Surface Water and the Hyporheic Zone" submitted to Biogeosciences (Stegen et al., 2022). The study aims to understand how the diversity of OM transformations varies across surface and subsurface components of river corridors using inland surface water and sediments collected along river corridors across the contiguous United States. Sediment extracts and water samples were analyzed using ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). This dataset is comprised of one folder (WHONDR_S19S) which contains (1) a subfolder with R scripts used to process the data and to calculate biochemical transformations, (2) processed FTICR-MS data as csv files, sample collection metadata and climate data as csv files, (3) biochemical transformations profile, classifications and database as csv files, and (4) a readme file with more information regarding WHONDRS raw FTICR-MS data and processing scripts. Outside of the main folders there is a csv containing file-level metadata and a csv data dictionary defining column headers for all csv files contained in the data package. The samples were part of a WHONDRS (https://whondrs.pnnl.gov) study. The raw, unprocessed FTICR-MS data with additional data can be found at doi:10.15485/1729719 for sediments and doi:10.15485/1603775 for water. This data package contains the processed data used in the associated manuscript.
DOI: 10.15485/1869708
title: FTICR-MS, Sensor, and Environmental Data from 5 Streams Impacted by the 2020 Holiday Farm Fire Associated with: "Spatiotemporal controls on the delivery of dissolved organic matter to streams following a wildfire"

description: This data package is associated with the publication "Spatiotemporal Controls on the Delivery of Dissolved Organic Matter to Streams Following a Wildfire" submitted to Geophysical Research Letters (Roebuck et al., 2022). The study aims to understand storm induced transport of pyrogenic materials to streams impacted by varying degrees of burn severity. Time series samples (24 samples in 1-hour intervals) were collected at 5 sites within the McKenzie River Watershed (Oregon, USA) whose catchment were each completely engulfed by the 2020 Holiday Farm Fire. The samples were collected in November 2020 during the first major storm pulse following the conclusion of the wildfire. Samples were characterized for dissolved organic carbon, total dissolved nitrogen, and by ultra-high resolution mass spectrometry. In situ turbidity data also collected.This data package contains 4 primary folders that include the following: 1) Metadata, 2) EnvData (Environmental Data), 3) SensorData, and 4) FTICR_SupportingData. The package contains a single file-level metadata (flmd) file. Each primary folder also contains individual data dictionaries (dd) to define and provide descriptors of column/row headers and data flags. The FTICR_SupportingData, folder 4, contains raw, unprocessed FTICR-MS Data files in addition to a csv containing processed FTICR-MS data. This package contains the following file types: csv, xml, pdf.
DOI: 10.15485/1962818
title: Model Inputs, Outputs, and Scripts associated with: “Spatial microbial respiration variations in the hyporheic zones within the Columbia River Basin”

description: This data package is associated with the publication “Spatial microbial respiration variations in the hyporheic zones within the Columbia River Basin” published in the Journal of Geophysical Research: Biogeosciences (Son et al. 2022) available at doi: 10.1029/2021JG006654. This data package includes the key model inputs/outputs of the river corridor model for the Columbia River Basin (CRB) and the model source codes, which were used in the manuscript. The model is a carbon-nitrogen-coupled river corridor model (RCM), and the model is used to quantify hyporheic zone (HZ) aerobic and anaerobic respiration at the NHDPLUS stream reach scales. The RCM used in this study combines empirical substrate models derived from observations and three microbially driven reactions to compute respiration of the HZ for each National Hydrography Dataset (NHD) reach within the CRB. The reactions in HZs of each NHD reach include anaerobic respiration and two-step anaerobic respiration via denitrification. Our HZ respiration estimates are limited to the lotic (or flowing) stream/river systems, and do not account for the respiration process in water column. Note that the RCM only simulates the HZ’s contribution to the dissolved carbon dioxide (CO2) concentrations in the streams, and the CO2 emissions to the atmosphere are not modelled. The model computes at hourly timesteps because of the fast reaction rates. The key input data of the model are exchange flux, residence time, and stream solute (dissolved organic carbon (DOC), dissolved oxygen (DO), and nitrate concentrations). These inputs are constant over time and represent long-term averaged values.This modeling framework successfully quantified HZ respiration components over multiple scales. It revealed key mechanisms driving the spatial variation of HZ aerobic and anaerobic respiration in reaches with varying hydrologic and substrate conditions. Thus, this modeling study offers a testing hypothesis in different river system (e.g., climate and biomes) for the HZ respiration processes, and can be used as a sampling design tool for large-scale HZ experimental studies.This dataset contains five folders: (1) model_inputs, (2) model_outputs, (3) Rscripts, (4) figures, and (5) model_codes. It also contains a readme, file level metadata (FLMD), and data dictionary (dd). Please see the FLMD for a list of all the files contained in this data package and descriptions for each. The model_inputs folder contains the model inputs used to drive the model simulations. The model_outputs folder contains key model output files from the river corridor model. The Rscripts folder contains the Rscripts for pre- and post- processing model results. The figures folder contains the raw figures associated with the manuscript. The model_codes folder includes key model source codes/input files. All files are .jpg, .jpeg, .out, .e, .od, .dat, .sub, .F90, .0, .R, .sbx, .cpg, .sbn, .shx, .shp, .dbf, .prj, .tfw, .tif, .xml, .pdf, or .csv.
DOI: 10.15485/1969114
title: WHONDRS Surface Water Dissolved Organic Carbon and FTICR-MS across Glacial Features in Svalbard 2022

description: This dataset supports a broader study examining climatic forcing of terrestrial greenhouse gas emission through permafrost and glaciers in Svalbard. The dataset provides geochemistry and organic matter characterization data generated from surface water collected from 11 sites across central Svalbard. Data were also collected in 2021 and can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1888571. Additional related data were collected and will be published separately in collaboration with Yde and Kleber.This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) dissolved organic carbon (DOC; measured as non-purgeable organic carbon; NPOC); (5) surface water sampling protocol; (6) readme; (7) methods codes; (8) international geo-sample number (IGSN) mapping file; (9) a folder of field photos; and (10) folder of high resolution characterization of organic matter via 7 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). The FTICR folder contains two subfolders, one containing the .xml data files and the other containing instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .R, .ref, or .xml.
DOI: 10.15485/1969118
title: Surface Water Disinfection Byproducts and Organic Matter Characterization Data Associated with: “Disinfection byproducts formed during drinking water treatment reveal an export control point for dissolved organic matter in a subalpine headwater stream”

description: This dataset is associated with the publication “Disinfection byproducts formed during drinking water treatment reveal an export control point for dissolved organic matter in a subalpine headwater stream” published in Water Research X (Leonard et al. 2022; https://doi.org/10.1016/j.wroa.2022.100144). The associated study analyzed temporal trends from the Town of Crested Butte water treatment facility and synoptic sampling at Coal Creek in Crested Butte, Colorado, US. This work demonstrates how drinking water quality archives combined with synoptic sampling and targeted analyses can be used to identify and understand export control points for dissolved organic matter.This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) metadata and international geo-sample number (IGSN) mapping file; (4) dissolved organic carbon (DOC), ultraviolet absorbance at 254 nanometers (UV254), total nitrogen (TN), and specific ultraviolet absorbance (SUVA) data; (5) disinfection bioproduct formation potential (DBP-FP) data; (6) readme; (7) methods codes; (8) water collection protocol; (9) folder of high resolution characterization of organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory); and (10) folder of excitation emissions matrix (EEM) spectra. The FTICR folder contains a file of DOC (measured as non-purgeable organic carbon; NPOC) used for FTICR sample preparation. The FTICR folder also contains three subfolders: one subfolder containing the raw .xml data files, one containing the processed data, and the other containing instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .dat, .R, .ref, or .xml
DOI: 10.15468/dl.kh7gts
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Locality is one of (HANGZHOU. UNIVERSITY OF HANGZHOU, HangZhou, HangZhou Region, Zhejiang Province, Hangzhou, Hangzhou (30.0085, 120.579), Hangzhou (30.0691, 120.866), Hangzhou (= Hangchow), Zhejiang Province, eastern , Hangzhou (Hang Chow)., Hangzhou (Hangchow))",
 "OccurrenceStatus is Present",
 "Year 2020-2020"
 ]
}

 The dataset includes 9 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0076706-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.caswcg
title: Occurrence Download

description: A dataset containing 60 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "TaxonKey is Cryptotomus roseus Cope, 1871"
 ]
}

 The dataset includes 60 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0076707-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/ds/5564382
title: A Dataset of 11,300 Labeled AI Generated Images
DOI: 10.15468/dl.zmr8hy
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-75.77743 4.93489,-75.85181 4.8557,-75.55711 4.68482,-75.47338 4.80031,-75.77743 4.93489))",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Characiformes, Siluriformes, Salmoniformes, Perciformes, Cyprinodontiformes, Gymnotiformes, Synbranchiformes, Myliobatiformes)"
 ]
}

 The dataset includes 19 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0076708-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nvbbgp
title: Occurrence Download

description: A dataset containing 96 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-85.65255459787237 9.319186918135738,-83.78811288966564 9.319186918135738,-83.78811288966564 11.183628626342465,-85.65255459787237 11.183628626342465,-85.65255459787237 9.319186918135738))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Incilius periglenes (Savage, 1967)"
 ]
}

 The dataset includes 96 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0076710-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m65tgf
title: Occurrence Download

description: A dataset containing 76 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Peru",
 "TaxonKey is Joosia dielsiana Standl."
 ]
}

 The dataset includes 76 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0076713-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25345/c5wp9tj6w
title: MassIVE MSV000095666 - Volatilome of Theobroma grandiflorum at Different Stages of Maturation Analyzed by HS-SPME-GC-MS
title: This dataset comprises the raw mass spectrometry files generated from the analysis of VOCs extracted from the pulp of Theobroma grandiflorum (Copoazu) at three distinct maturation stages (ripe, overripe, and medium). The study used HS-SPME-GC-MS. A Divinylbenzene/carbon wide-range/polydimethylsiloxane (DVB/CWR/PDMS) 80 um x 10 mm fiber was used in combination with a Gas Chromatograph HP 6890 Series equipped with an Agilent Mass Selective Detector 5973. The VOCs were separated on a capillary GC column of 5% Phenyl/95% Dimethyl Polysiloxane (30 m x 0.25 mm x 0.25 um).
DOI: 10.15468/dl.vfsfzd
title: Occurrence Download

description: A dataset listing the 7 species recorded in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Heleioporus Gray, 1841",
 "TaxonomicStatus is Accepted"
 ]
}

 The dataset's 7 records were derived from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0076709-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tn4heb
title: Occurrence Download

description: A dataset containing 96 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-85.65255459787237 9.319186918135738,-83.78811288966564 9.319186918135738,-83.78811288966564 11.183628626342465,-85.65255459787237 11.183628626342465,-85.65255459787237 9.319186918135738))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Incilius periglenes (Savage, 1967)"
 ]
}

 The dataset includes 96 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0076715-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tp56f7
title: Occurrence Download

description: A dataset containing 31 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Peru",
 "TaxonKey is Joosia sericea (Standl.) C.M.Taylor"
 ]
}

 The dataset includes 31 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0076717-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13352271
title: Were they soldiers or citizens in revolt?
title: Osteological activity examination of the Alkmaar mass burial from the beginning of the Dutch 80-year war
title: Osteological data for 2024 MSc thesis of A. V. Artto

description: Tables contain the collected and calculated osteological data of the cohort used in an MSc Archaeological Science (Human Osteology) thesis for the Leiden University. The cohort was formed from three different collections of human remains originating from Dutch Early Modern era. Cohort consists of 45 individuals whose sex has been osteologically determined to be male or probably male. Dataset is in three tables: one for raw data, which contains the collected measurements of long bones (excl. fibulae), acetabulums and notes made during collections as well as individual identifiers. Second table contains Directional asymmetry values on long bones as well as vertical acetabular ovalisation values. The third table contains stabilised Second Moment of Area values of long bones, calculated on anteroposterior and mediolateral axes while stabilised for size using bone length calculated body mass of the individual. The used formulae are listed in the thesis' appendix and the methodology is presented in the methodology section. Thesis itself is open access.
DOI: 10.5281/zenodo.13352272
title: Were they soldiers or citizens in revolt?
title: Osteological activity examination of the Alkmaar mass burial from the beginning of the Dutch 80-year war
title: Osteological data for 2024 MSc thesis of A. V. Artto

description: Tables contain the collected and calculated osteological data of the cohort used in an MSc Archaeological Science (Human Osteology) thesis for the Leiden University. The cohort was formed from three different collections of human remains originating from Dutch Early Modern era. Cohort consists of 45 individuals whose sex has been osteologically determined to be male or probably male. Dataset is in three tables: one for raw data, which contains the collected measurements of long bones (excl. fibulae), acetabulums and notes made during collections as well as individual identifiers. Second table contains Directional asymmetry values on long bones as well as vertical acetabular ovalisation values. The third table contains stabilised Second Moment of Area values of long bones, calculated on anteroposterior and mediolateral axes while stabilised for size using bone length calculated body mass of the individual. The used formulae are listed in the thesis' appendix and the methodology is presented in the methodology section. Thesis itself is open access.