cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.60797/ecnms.2025.9.5.4
title: Рейтинговая динамика урожайности люпина кормового (сладкого) на зерно в хозяйствах всех категорий в регионах РФ

description: Cifra. Экономика, Выпуск 2 (9) 2025
DOI: 10.60797/ecnms.2025.9.5.5
title: Рейтинговая динамика валовых сборов люпина кормового (сладкого) на зерно в хозяйствах всех категорий в регионах РФ

description: Cifra. Экономика, Выпуск 2 (9) 2025
DOI: 10.48597/6e2a-shjt
title: Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/gwu3-eeq8
title: Precipitation_amount at Kotinen

description: Measurement of Precipitation_amount at Kotinen
DOI: 10.48597/a26n-wgjz
title: Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/hces-7tj4
title: Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.5519/qd.3o9ajbub
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (391 records)
DOI: 10.5517/ccdc.csd.cc2ltxn0
title: CCDC 2408193: Experimental Crystal Structure Determination

description: Related Article: Wen-Jie Pan, Wei-Guo Cao, Ji-Chang Xiao, Jin-Hong Lin|2025|Org.Lett.|27|5275|doi:10.1021/acs.orglett.5c01492
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: 10.18112/openneuro.ds006334.v1.0.0
title: Neocortical and Hippocampal Theta Oscillations Track Audiovisual Integration and Replay of Speech Memories
DOI: 10.15468/dl.c45vab
title: Occurrence Download

description: A dataset containing 99 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sclerophrys garmani (Meek, 1897)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((30.5701 -24.0715,25.5395 -24.0715,25.5395 -28.5786,30.5701 -28.5786,30.5701 -24.0715))"
 ]
}

 The dataset includes 99 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035769-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ynrkp4
title: Occurrence Download

description: A dataset containing 109 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sclerophrys garmani (Meek, 1897)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((27.1332 -20.158,25.5395 -23.2724,25.5395 -24.0715,30.5701 -24.0715,30.5701 -20.3186,29.6496 -19.6123,28.947 -19.4003,28.1821 -19.4609,27.6072 -19.7214,27.1332 -20.158))"
 ]
}

 The dataset includes 109 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035771-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5qa82t
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sclerophrys garmani (Meek, 1897)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((25.0214 -34.0501,25.5395 -34.1098,25.5395 -32.9007,20.509 -32.9007,20.509 -34.5676,20.524 -34.555,20.8859 -34.5419,20.9606 -34.4398,21.2995 -34.5131,21.5296 -34.4338,21.8696 -34.4439,22.0323 -34.2835,22.221 -34.2428,22.2566 -34.1304,22.5993 -34.0741,22.9652 -34.1674,23.4069 -34.1858,23.4955 -34.0792,23.6056 -34.0563,24.8471 -34.2877,24.9447 -34.2397,25.0214 -34.0501))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035772-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15638953
title: Dataset for conference paper called "Highly efficient second and third harmonic generation of a 7J, 10 Hz Yb:YAG laser"

description: This dataset contains relevant data for conference paper called "Highly efficient second and third harmonic generation of a 7J, 10 Hz Yb:YAG laser"
DOI: 10.5281/zenodo.15638954
title: Dataset for conference paper called "Highly efficient second and third harmonic generation of a 7J, 10 Hz Yb:YAG laser"

description: This dataset contains relevant data for conference paper called "Highly efficient second and third harmonic generation of a 7J, 10 Hz Yb:YAG laser"
DOI: 10.15468/dl.33ycp7
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sclerophrys garmani (Meek, 1897)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((32.064 -28.9416,32.4847 -28.5786,30.5701 -28.5786,30.5701 -30.7329,30.6252 -30.6659,31.4179 -29.4257,31.8178 -29.0299,32.064 -28.9416))"
 ]
}

 The dataset includes 5 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035773-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48597/ud7h-k4sz
title: Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/yvvw-h68z
title: Precipitation_amount at Kotinen

description: Measurement of Precipitation_amount at Kotinen
DOI: 10.48597/m3fs-bde4
title: Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/pjby-apbt
title: Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/wehe-fyvs
title: Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/j8c9-8wwt
title: Measurement of Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/rfet-emtm
title: Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/kzx9-v6x7
title: Measurement of Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/mhav-78bv
title: Measurement of Precipitation_amount at Kotinen

description: Measurement of Precipitation_amount at Kotinen
DOI: 10.48597/wz3n-e6t8
title: Measurement of Precipitation_amount at Kotinen

description: Measurement of Precipitation_amount at Kotinen
DOI: 10.48597/pgtc-cmc6
title: Measurement of Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/zb5s-nhdm
title: Measurement of Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/6muw-k89p
title: Measurement of Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/mf9c-xxse
title: Measurement of Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/yw6c-jbhj
title: Measurement of Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/m96r-r3w8
title: Measurement of Precipitation_amount at Kotinen

description: Measurement of Precipitation_amount at Kotinen
DOI: 10.15468/dl.7kd4az
title: Occurrence Download

description: A dataset containing 26406 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 "year",
 IF(ISNULL(kingdomkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY kingdomkey, "year")) kingdomcount,
 IF(ISNULL(phylumkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY phylumkey, "year")) phylumcount,
 IF(ISNULL(classkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY classkey, "year")) classcount,
 IF(ISNULL(orderkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY orderkey, "year")) ordercount,
 IF(ISNULL(familykey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY familykey, "year")) familycount,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey, "year")) genuscount,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 occurrence.countrycode = 'MW'
 AND occurrence.occurrencestatus = 'PRESENT'
 AND (occurrence."year" &gt;= 2000 AND occurrence."year" &lt;= 2025)
 AND occurrence.hasgeospatialissues = FALSE
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND NOT occurrence.basisofrecord IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')
 AND (occurrence.specieskey IS NOT NULL AND occurrence."year" IS NOT NULL)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 occurrence."year"

 The dataset's 26406 records were derived from 176 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035765-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48597/5ec4-7hs6
title: Measurement of Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/4j3y-wgay
title: Measurement of Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/52an-cags
title: Measurement of Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/c22j-nx9f
title: Measurement of Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/euj3-usq6
title: Measurement of Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/rqta-4nbh
title: Measurement of Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/53qd-dxuu
title: Measurement of Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/6key-n5je
title: Measurement of Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/cpzc-gdvk
title: Measurement of Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/hbkg-ajbd
title: Measurement of Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/p724-ejqy
title: Measurement of Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/pjk6-ty4t
title: Measurement of Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.48597/sj6j-6akf
title: Measurement of Heavy metals at Kotinen

description: Measurement of Heavy metals at Kotinen
DOI: 10.24378/exe.5786
title: A Discrete Element-based Approach to Generate Random Parameters for Soil Fatigue Models (dataset)

description: This dataset contains the scripts, data inputs and results of the investigation performed in A Discrete-Element-Based Approach to Generate Random Parameters for Soil Fatigue Models (https://doi.org/10.3390/jmse13061145). The Python scripts can be used to generate random parameters for calibrating soil fatigue models.
description: The article which this research data supports is available in ORE at http://hdl.handle.net/10871/141140
DOI: 10.15468/dl.6epcvd
title: Occurrence Download

description: A dataset containing 86 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 "year",
 IF(ISNULL(kingdomkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY kingdomkey, "year")) kingdomcount,
 IF(ISNULL(phylumkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY phylumkey, "year")) phylumcount,
 IF(ISNULL(classkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY classkey, "year")) classcount,
 IF(ISNULL(orderkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY orderkey, "year")) ordercount,
 IF(ISNULL(familykey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY familykey, "year")) familycount,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey, "year")) genuscount,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 occurrence.datasetkey = 'a1a10af9-b358-4e8a-b204-cea17e9bccd0'
 AND occurrence.hasgeospatialissues = FALSE
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND NOT occurrence.basisofrecord IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')
 AND occurrence.occurrencestatus = 'PRESENT'
 AND (occurrence.specieskey IS NOT NULL AND occurrence."year" IS NOT NULL)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 occurrence."year"

 The dataset's 86 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035770-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15623257
title: Synthetic shoeprint dataset
DOI: 10.5281/zenodo.15623258
title: Synthetic shoeprint dataset
DOI: 10.15468/dl.nza45n
title: Occurrence Download

description: A dataset containing 396 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Non-American triatomine occurrence data (Reduviidae: Triatominae)"
 ]
}

 The dataset includes 396 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035774-250525065834625/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.28051079.v1
title: Final Matrix.phy

description: The assembled matrix of the concatenated mitochondrial and nuclear markers of 43 taxa (22 ingroups, 21 outgroups). Concatenated alignment comprised 1-748 bp for <i>CO1</i>, from 749-1938 bp for <i>28S</i>, from 1939-2299 <i>H3</i> and from 2300-3863 <i>18S</i>. The total length of the final matrix was 3863<b> </b>bp. It is in phylip format
DOI: 10.15468/dl.226em7
title: Occurrence Download

description: A dataset containing 453 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sclerophrys garmani (Meek, 1897)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((35.5808 -24.13,35.5909 -24.0715,30.5701 -24.0715,30.5701 -28.5786,32.4847 -28.5786,32.55 -28.5222,33.0346 -26.8668,32.9741 -26.7838,33.0415 -26.059,32.9304 -26.0011,32.7994 -26.1281,32.6834 -26.0015,32.813 -25.8728,32.8513 -25.7166,33.3048 -25.3731,35.1489 -24.6699,35.5808 -24.13))"
 ]
}

 The dataset includes 453 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035775-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15639163
title: Development and Optimization of a Short-Weapon Wushu Curriculum for Primary School Physical Education Teachers A Delphi Study
DOI: 10.5281/zenodo.15639162
title: Development and Optimization of a Short-Weapon Wushu Curriculum for Primary School Physical Education Teachers A Delphi Study
DOI: 10.5281/zenodo.11258438
title: Conserved genetic markers reveal widespread diatom reproduction in the global ocean

description: Datasets associated with the study "Conserved genetic markers reveal widespread diatom reproduction in the global ocean" (post second revision, V3)
DOI: 10.5281/zenodo.15638841
title: Conserved genetic markers reveal widespread diatom reproduction in the global ocean

description: Datasets associated with the study "Conserved genetic markers reveal widespread diatom reproduction in the global ocean" (post second revision, V3)
DOI: 10.14466/cefasdatahub.71
title: Horizontal and vertical movement data derived from a data storage tag deployed on a single Atlantic cod in the English Channel from 2005 to 2006

description: These data are derived from the deployment of a single data storage tag on an Atlantic cod (Gadus morhua) in the English Channel. The cod was tagged in the Southern North Sea on 25/03/2005 and was recaptured in the Eastern English Channel on the 09/01/2006. The cod migrates down through the English Channel, resides in the Celtic Sea and then returns. The dataset contains 291 days of information. Each day consists of 144 vertical movement rates (in metres), one horizontal movement rate (in kilometres) and one turning angle (in radians, from -pi to pi). Vertical movement rates have been log (natural log) transformed.  A description of tag type, fish capture, tag attachment and tag accuracy can be found in Righton et al. (2010). Righton et al. (2010) is published in Marine Ecology Progress Series and is freely available here http://www.int-res.com/articles/feature/m420p001.pdf. The data storage tag was pre-programmed to record depth (m) at 10-minute intervals for the duration of deployment. Vertical movement rates were calculated as the absolute difference between corresponding 10-minute depth measurements summed to the daily level. Horizontal movement rates were calculated in a two-step approach. First, daily geolocations were estimated via a Fokker-Planck-based method that combines a tidal location method and a Bayesian state-space model (see Pedersen et al. 2008 for model details). Second, the straight-line distance between daily geolocations is calculated using the Great Circle equation. Turning angles between successive geolocations were also calculated. Pedersen et al. (2008) is published in the Canadian Journal of Fisheries and Aquatic Sciences and is freely available here http://www.nrcresearchpress.com/doi/pdf/10.1139/F08-144. Neat et al. (2014) previously used this single Atlantic cod as part of their work into stock structure around the British Isles. The article was published in the Journal of Applied Ecology and is freely available here https://besjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/1365-2664.12343. Griffiths et al. (2018) also used a version of this data to learn about the broad-scale movement behaviours of Atlantic cod in the North Sea and English Channel. Griffiths et al. (2018) was published in Ecology and Evolution and is freely available here https://onlinelibrary.wiley.com/doi/abs/10.1002/ece3.4223.
DOI: 10.14466/cefasdatahub.72
title: A new machine learning approach to seabed biotope classification

description: Files for use with the R script accompanying the paper Cooper (2019). Note that this script also uses files from https://doi.org/10.14466/CefasDataHub.34 (details provided in script). Cooper, K.M. (2019). A new machine learning approach to seabed biotope classification. Science Advances. Files include: BiotopePredictionScript.R (R script), EUROPE.shp (European Coastline), EuropeLiteScoWal.shp (European Coastline with UK boundaries), DEFRADEMKC8.shp (Seabed bathymetry), C5922DATASETFAM13022017.csv (Training dataset), PARTC16112018.csv (Test dataset), PARTCAGG16112018.csv (Aggregation data). Description of C5922DATASETFAM13022017.csv: This file is based on the RSMP dataset (see https://www.cefas.co.uk/cefas-data-hub/dois/rsmp-baseline-dataset/), but with macrofaunal data output at the level of family or above. A variety of gear types have been used for sample collection including grabs (0.1m2 Hamon, 0.2m2 Hamon, 0.1m2 Day, 0.1m2 Van Veen and 0.1m2 Smith McIntrye) and cores. Of these various devices, 93% of samples were acquired using either a 0.1m2 Hamon grab or a 0.1m2 Day grab. Sieve sizes used in sample processing include 1mm and 0.5mm, reflecting the conventional preference for 1mm offshore and 0.5mm inshore. Of the samples collected using either a 0.1m2 Hamon grab or a 0.1m2 Day grab, 88% were processed using a 1mm sieve. Taxon names were standardised according to the WoRMS (World Register of Marine Species) list using the Taxon Match Tool (http://www.marinespecies.org/aphia.php?p=match). Of the initial 13,449 taxon names, only 774 remained after correction and aggregation to family level. The final dataset comprises of a single sheet comma-separated values (.csv) file. Colonials accounted for less than 20% of the total number of taxa and, where present, were given a value of 1 in the dataset. This component of the fauna was missing from 325 out of the 777 surveys, reflecting either a true absence, or simply that colonial taxa were ignored by the analyst. Sediment particle size data were provided as percentage weight by sieve mesh size, with the dataset including 99 different sieve sizes. Sediment samples have been processed using sieve, and a combination of sieve and laser diffraction techniques. Key metadata fields include: Sample coordinates (Latitude & Longitude), Survey Name, Gear, Date, Grab Sample Volume (litres) and Water Depth (m). A number of additional explanatory variables are also provided (salinity, temperature, chlorophyll a, Suspended particulate matter, Water depth, Wave Orbital Velocity, Average Current, Bed Stress). In total, the dataset dimensions are 33,198 rows (samples) x 900 columns (variables/factors), yielding a matrix of 29,878,200 individual data values.
DOI: 10.5281/zenodo.14989127
title: The TRB repertoires for ElAbd et al.; 2025; Nat Med

description: The current collection contains the TRB repertoires of the 904 healthy individuals and 504 individuals with PSC as described in ElAbd et al. Nat Med, 2025
DOI: 10.5281/zenodo.14989128
title: The TRB repertoires for ElAbd et al.; 2025; Nat Med

description: The current collection contains the TRB repertoires of the 904 healthy individuals and 504 individuals with PSC as described in ElAbd et al. Nat Med, 2025
DOI: 10.6084/m9.figshare.28051079
title: <b>Final Matrix.phy; </b><b>Evolution of South Asian Mountain biota: dispersal, fine-scale biogeography, phylogenetics and systematics of Nannenini jumping spiders</b>

description: The assembled matrix of the concatenated mitochondrial and nuclear markers of 43 taxa (22 ingroups, 21 outgroups). Concatenated alignment comprised 1-748 bp for <i>CO1</i>, from 749-1938 bp for <i>28S</i>, from 1939-2299 <i>H3</i> and from 2300-3863 <i>18S</i>. The total length of the final matrix was 3863<b> </b>bp. It is in phylip format