cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18710/umdoq0/dbnwe5
title: 20230129_KHO_REDTEC_gal.txt
DOI: 10.18710/umdoq0/i40dl5
title: 20230319_KHO_REDTEC_gal.txt
DOI: 10.18710/umdoq0/mv3e7q
title: 20230616_KHO_REDTEC_gal.txt
DOI: 10.18710/umdoq0/s7pmwk
title: 20230603_KHO_REDTEC_glo.txt
DOI: 10.18710/umdoq0/twov9j
title: 20230104_KHO_REDTEC_gal.txt
DOI: 10.18710/umdoq0/u3haom
title: 20230122_KHO_REDTEC_gps.txt
DOI: 10.18710/umdoq0/xwcoot
title: 20230304_KHO_REDTEC_glo.txt
DOI: 10.18710/umdoq0/ziga45
title: 20230417_KHO_REDTEC_glo.txt
DOI: 10.18710/umdoq0/zmywjg
title: 20230215_KHO_REDTEC_gps.txt
DOI: 10.18710/arlx23/8m0fn6
title: 20241012_BJN_REDOBS_glo.txt
DOI: 10.18710/mtuavq/gxgo10
title: 20230520_BJN_REDTEC_glo.txt
DOI: 10.18710/mtuavq/r5a7k9
title: 20230603_BJN_REDTEC_gps.txt
DOI: 10.18710/mtuavq/yddnm4
title: 20230406_BJN_REDTEC_gps.txt
DOI: 10.18710/tynihf/5gbdyw
title: 20230219_HOP_REDTEC_glo.txt
DOI: 10.18710/tynihf/8ubfbl
title: 20230527_HOP_REDTEC_glo.txt
DOI: 10.18710/tynihf/voof5d
title: 20230603_HOP_REDTEC_gal.txt
DOI: 10.18710/umdoq0/5l23li
title: 20230105_KHO_REDTEC_gps.txt
DOI: 10.18710/umdoq0/gz9wub
title: 20230610_KHO_REDTEC_glo.txt
DOI: 10.18710/umdoq0/nrdoou
title: 20230323_KHO_REDTEC_gal.txt
DOI: 10.18710/arlx23/44axmw
title: 20241215_BJN_REDOBS_gps.txt
DOI: 10.18710/arlx23/8igveo
title: 20241126_BJN_REDOBS_glo.txt
DOI: 10.18710/arlx23/azoe1n
title: 20241016_BJN_REDOBS_gps.txt
DOI: 10.18710/arlx23/m1iz6d
title: 20241125_BJN_REDOBS_gps.txt
DOI: 10.18710/arlx23/m8nj1d
title: 20241108_BJN_REDOBS_gps.txt
DOI: 10.18710/arlx23/pk30nb
title: 20241227_BJN_REDOBS_gal.txt
DOI: 10.18710/arlx23/s9gnwe
title: 20241007_BJN_REDOBS_gal.txt
DOI: 10.18710/arlx23/woo54m
title: 20241029_BJN_REDOBS_glo.txt
DOI: 10.18710/l0vpw7/uwaefh
title: SBL118_Subt2__9__18-29-02-793.txt
DOI: 10.18710/m0osle/bsvhgx
title: 20240206_KHO_REDOBS_gps.txt
DOI: 10.18710/mtuavq/bkwzw8
title: 20230513_BJN_REDTEC_gal.txt
DOI: 10.18710/mtuavq/lfo6y6
title: 20230617_BJN_REDTEC_glo.txt
DOI: 10.18710/mtuavq/pmjhdw
title: 20230621_BJN_REDTEC_gps.txt
DOI: 10.18710/tynihf/02evwu
title: 20230222_HOP_REDTEC_gps.txt
DOI: 10.18710/tynihf/2jbohc
title: 20230505_HOP_REDTEC_gal.txt
DOI: 10.18710/tynihf/2smvys
title: 20230625_HOP_REDTEC_gps.txt
DOI: 10.18710/tynihf/afarkw
title: 20230416_HOP_REDTEC_glo.txt
DOI: 10.18710/tynihf/agyqgs
title: 20230405_HOP_REDTEC_gal.txt
DOI: 10.18710/tynihf/atuzrv
title: 20230619_HOP_REDTEC_gal.txt
DOI: 10.18710/tynihf/cf4gof
title: 20230618_HOP_REDTEC_glo.txt
DOI: 10.18710/tynihf/dgtzod
title: 20230522_HOP_REDTEC_gps.txt
DOI: 10.18710/tynihf/duhpvo
title: 20230610_HOP_REDTEC_gal.txt
DOI: 10.18710/tynihf/gk9oi3
title: 20230415_HOP_REDTEC_glo.txt
DOI: 10.18710/tynihf/hqlyaf
title: 20230610_HOP_REDTEC_gps.txt
DOI: 10.18710/tynihf/hwmbop
title: 20230606_HOP_REDTEC_gps.txt
DOI: 10.18710/tynihf/ippdjb
title: 20230418_HOP_REDTEC_glo.txt
DOI: 10.18710/tynihf/jjdeqs
title: 20230401_HOP_REDTEC_gps.txt
DOI: 10.18710/tynihf/kcgrfe
title: 20230423_HOP_REDTEC_gal.txt
DOI: 10.18710/tynihf/knrzvl
title: 20230615_HOP_REDTEC_gps.txt
DOI: 10.18710/tynihf/labexg
title: 20230119_HOP_REDTEC_gal.txt
DOI: 10.18710/tynihf/ltvzpb
title: 20230629_HOP_REDTEC_glo.txt
DOI: 10.18710/tynihf/midwg5
title: 20230602_HOP_REDTEC_gps.txt
DOI: 10.18710/tynihf/mu0bxp
title: 20230310_HOP_REDTEC_gps.txt
DOI: 10.18710/tynihf/mz6l7i
title: 20230614_HOP_REDTEC_gal.txt
DOI: 10.18710/tynihf/qpx1y6
title: 20230611_HOP_REDTEC_glo.txt
DOI: 10.21227/sfv9-p873
title: "A Hybrid End-to-end Neural Network for Accurate Global Natural Gas Trade Forecast"

description: "Our dataset includes carbon dioxide, coal, electricity, natural gas, hydroelectricity, key material, nuclear, oil, primary energy and renewables."
DOI: 10.15468/dl.ep3zsf
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Capensibufo magistratus Channing, Measey, De Villiers, Turner & Tolley, 2017",
 "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 ((27.1586 -33.5889,28.2048 -32.9007,25.5395 -32.9007,25.5395 -34.1098,25.6468 -34.1222,25.7787 -34.0734,25.7098 -33.9109,25.8639 -33.797,26.4806 -33.8473,27.1586 -33.5889))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032631-250525065834625/datasets/export for details.
DOI: 10.15468/dl.mw7yxh
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Capensibufo magistratus Channing, Measey, De Villiers, Turner & Tolley, 2017",
 "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 ((18.2339 -32.5266,18.1411 -32.657,18.1007 -32.7021,18.0224 -32.6366,17.8923 -32.6419,17.754 -32.8255,17.7723 -32.9007,20.509 -32.9007,20.509 -28.5786,16.2782 -28.5786,16.4358 -28.7202,16.726 -29.1235,17.1957 -30.3752,17.6655 -31.1743,18.1322 -31.7679,18.2495 -32.2638,18.2339 -32.5266))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032632-250525065834625/datasets/export for details.
DOI: 10.5281/zenodo.13752762
title: Underestimated input of terrestrial dissolved organic carbon to the ocean
DOI: 10.5281/zenodo.13752778
title: Underestimated input of terrestrial dissolved organic carbon to the ocean
DOI: 10.5281/zenodo.13754176
title: Underestimated input of terrestrial dissolved organic carbon to the ocean
DOI: 10.5281/zenodo.13832573
title: Underestimated input of terrestrial dissolved organic carbon to the ocean
DOI: 10.15468/dl.5cgedj
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Capensibufo magistratus Channing, Measey, De Villiers, Turner & Tolley, 2017",
 "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 ((15.6372 -28.0032,16.2782 -28.5786,20.509 -28.5786,20.509 -24.0715,15.4933 -24.0715,15.4945 -24.1257,16.0509 -25.6631,15.6372 -28.0032))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032633-250525065834625/datasets/export for details.
DOI: 10.5281/zenodo.15629514
title: Dataset for Modulating the electronic properties of Ag/Au implanted 2D chalcogenide layer on polymers

description: See readme in each files.
DOI: 10.5281/zenodo.15629515
title: Dataset for Modulating the electronic properties of Ag/Au implanted 2D chalcogenide layer on polymers

description: See readme in each files.
DOI: 10.15468/dl.7vyg9j
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Capensibufo magistratus Channing, Measey, De Villiers, Turner & Tolley, 2017",
 "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 ((15.4784 -23.4046,15.4933 -24.0715,20.509 -24.0715,20.509 -24.0455,20.0952 -23.5072,19.9968 -23.017,19.7843 -22.5405,19.1988 -21.8785,18.5972 -21.5447,17.8859 -21.3993,17.1626 -21.4805,16.5332 -21.7596,16.1257 -22.0882,15.8234 -22.4662,15.606 -22.8993,15.4784 -23.4046))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032634-250525065834625/datasets/export for details.
DOI: 10.15161/oar.it/ss7w9-jq429
title: Attività conclusiva del Secondo convegno nazionale del gruppo di lavoro Open Science della CoPER. Sondaggio Mentimeter

description: Risultati dei sondaggi sottoposti ai partecipanti durante il Secondo convegno nazionale del gruppo di lavoro Open Science della CoPER. Un lungo cammino: le nuove sfide della scienza aperta.

I risultati sono consultabili anche su Mentimeter: https://www.mentimeter.com/app/presentation/aluhj8vc89wn2eox69u6pjqirwiwbqdk/edit?source=share-invite-modal
DOI: 10.15161/oar.it/xcy27-0a884
title: Attività conclusiva del Secondo convegno nazionale del gruppo di lavoro Open Science della CoPER. Sondaggio Mentimeter

description: Risultati dei sondaggi sottoposti ai partecipanti durante il Secondo convegno nazionale del gruppo di lavoro Open Science della CoPER. Un lungo cammino: le nuove sfide della scienza aperta.

I risultati sono consultabili anche su Mentimeter: https://www.mentimeter.com/app/presentation/aluhj8vc89wn2eox69u6pjqirwiwbqdk/edit?source=share-invite-modal
DOI: 10.5281/zenodo.15628481
title: The maternal microbiome influence on pregnancy success: Breeding comparison of germ-free and conventionalised mice

description: Germ-free (GF) mice are entirely devoid of all microorganisms. GF mice are one of the most powerful tools for studying the role of the microbiome in a phenotype and moving the microbiome field from association to causation. They allow the introduction of specific microbes or microbial communities to interrogate the causality of microbiomes in protecting against or contributing to a phenotype. Here, we report critical and underappreciated challenges in using GF models to investigate intergenerational effects of maternal diet and microbiota on offspring health.
DOI: 10.5281/zenodo.15628482
title: The maternal microbiome influence on pregnancy success: Breeding comparison of germ-free and conventionalised mice

description: Germ-free (GF) mice are entirely devoid of all microorganisms. GF mice are one of the most powerful tools for studying the role of the microbiome in a phenotype and moving the microbiome field from association to causation. They allow the introduction of specific microbes or microbial communities to interrogate the causality of microbiomes in protecting against or contributing to a phenotype. Here, we report critical and underappreciated challenges in using GF models to investigate intergenerational effects of maternal diet and microbiota on offspring health.
DOI: 10.15468/dl.kwvv5y
title: Occurrence Download

description: A dataset containing 2315 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Xeno-canto - Anura sounds from around the world"
 ]
}

 The dataset includes 2315 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032635-250525065834625/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.29278121
title: Supplementary Material for: Tablet-Based Assessment of Picture Naming in Prodromal Alzheimer’s Disease: An Accessible and Effective Tool for Distinguishing Mild Cognitive Impairment from Normal Aging

description: Effective mild cognitive impairment (MCI) screening requires accessible testing. This study compared two tests for distinguishing MCI patients from controls: Rapid Automatized Naming (RAN) for naming speed and Low Contrast Letter Acuity (LCLA) for sensitivity to low contrast letters. Two RAN tasks were used: the Mobile Universal Lexicon Evaluation System (MULES, picture naming) and Staggered Uneven Number test (SUN, number naming). Both RAN tasks were administered on a tablet and in a paper/pencil format. The tablet format was administered using the Mobile Integrated Cognitive Kit (MICK) application. LCLA was tested at 2.5% and 1.25% contrast. Sixty-four participants (31 MCI, 34 controls; mean age 73.2 ± 6.8 years) were included. MCI patients were slower than controls for paper/pencil (75.0 vs. 53.6 sec, p &lt; 0.001), and tablet MULES (69.0 sec vs. 50.2 sec, p = 0.01). The paper/pencil SUN showed no significant difference (MCI: 59.5 sec vs. controls: 59.9 sec, p = 0.07), nor did tablet SUN (MCI: 59.3 sec vs. controls: 55.7 sec, p = 0.36). MCI patients had worse performance on LCLA testing at 2.5% contrast (33 letters vs. 36, p = 0.04*) and 1.25% (0 letters vs. 14. letters, p &lt; 0.001). Receiver operating characteristic (ROC) analysis showed similar performance of paper/pencil and tablet MULES in distinguishing MCI from controls (AUC = 0.77), outperforming both SUN (AUC = 0.63 paper, 0.59 tablet) and LCLA (2.5% contrast: AUC = 0.65, 1.25% contrast: AUC = 0.72). The MULES, in both formats, may be a valuable screening tool for MCI.
DOI: 10.6084/m9.figshare.29278121.v1
title: Supplementary Material for: Tablet-Based Assessment of Picture Naming in Prodromal Alzheimer’s Disease: An Accessible and Effective Tool for Distinguishing Mild Cognitive Impairment from Normal Aging

description: Effective mild cognitive impairment (MCI) screening requires accessible testing. This study compared two tests for distinguishing MCI patients from controls: Rapid Automatized Naming (RAN) for naming speed and Low Contrast Letter Acuity (LCLA) for sensitivity to low contrast letters. Two RAN tasks were used: the Mobile Universal Lexicon Evaluation System (MULES, picture naming) and Staggered Uneven Number test (SUN, number naming). Both RAN tasks were administered on a tablet and in a paper/pencil format. The tablet format was administered using the Mobile Integrated Cognitive Kit (MICK) application. LCLA was tested at 2.5% and 1.25% contrast. Sixty-four participants (31 MCI, 34 controls; mean age 73.2 ± 6.8 years) were included. MCI patients were slower than controls for paper/pencil (75.0 vs. 53.6 sec, p &lt; 0.001), and tablet MULES (69.0 sec vs. 50.2 sec, p = 0.01). The paper/pencil SUN showed no significant difference (MCI: 59.5 sec vs. controls: 59.9 sec, p = 0.07), nor did tablet SUN (MCI: 59.3 sec vs. controls: 55.7 sec, p = 0.36). MCI patients had worse performance on LCLA testing at 2.5% contrast (33 letters vs. 36, p = 0.04*) and 1.25% (0 letters vs. 14. letters, p &lt; 0.001). Receiver operating characteristic (ROC) analysis showed similar performance of paper/pencil and tablet MULES in distinguishing MCI from controls (AUC = 0.77), outperforming both SUN (AUC = 0.63 paper, 0.59 tablet) and LCLA (2.5% contrast: AUC = 0.65, 1.25% contrast: AUC = 0.72). The MULES, in both formats, may be a valuable screening tool for MCI.
DOI: 10.15468/dl.ghq5je
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Capensibufo magistratus Channing, Measey, De Villiers, Turner & Tolley, 2017",
 "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 ((25.5395 -28.5786,20.509 -28.5786,20.509 -32.9007,25.5395 -32.9007,25.5395 -28.5786))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032636-250525065834625/datasets/export for details.
DOI: 10.6084/m9.figshare.29278106
title: BJSP.xlsx

description: the source code of the algorithm, the benchmark data and the optimal solutions.
DOI: 10.6084/m9.figshare.29278106.v1
title: BJSP.xlsx

description: the source code of the algorithm, the benchmark data and the optimal solutions.
DOI: 10.6084/m9.figshare.28714511
title: Chromosome-Level Genome Assembly and Annotations of <b><i>Ainsliaea gracilis</i></b><b> </b><b>Franch. </b>(Pertyeae, Asteraceae)

description: The nuclear whole genome of <i>Ainsliaea gracilis</i> Franch. (Pertyeae, Asteraceae) is firstly sequenced and assembled to chromosome-level by us (Sichuan Normal University, corresponding author: Prof. Dr. Zhixi Fu, fuzx2017@sicnu.edu.cn). The genome assembly and high-quality annotations are provided in this website. The comparative and phylogenomic analyses were subsequently conducted and included in a paper: <b>A </b><b><i>de novo </i></b><b>assembled</b><b><i> </i></b><b>chromosome-level genome of </b><b><i>Ainsliaea gracilis</i></b><b> Franch. (Pertyeae, Asteraceae) with comparative and phylogenomic analyses in Asteraceae</b> (under review).
DOI: 10.6084/m9.figshare.28714511.v1
title: Chromosome-Level Genome Assembly of <b><i>Ainsliaea gracilis</i></b><b> Franch. </b>(Pertyeae, Asteraceae)

description: The genome of <i>Ainsliaea gracilis</i> Franch. (Pertyeae, Asteraceae) is firstly sequenced and assembled to chromosome-level by us (SIchuan Normal University, corresponding author: Associate Prof. Dr. Zhixi Fu, fuzx2017@sicnu.edu.cn). THe high-quality annotation and bioinformatic analyses is subsequently conducted.
DOI: 10.6084/m9.figshare.28714511.v2
title: Chromosome-Level Genome Assembly and Annotations of <b><i>Ainsliaea gracilis</i></b><b> </b><b>Franch. </b>(Pertyeae, Asteraceae)

description: The nuclear whole genome of <i>Ainsliaea gracilis</i> Franch. (Pertyeae, Asteraceae) is firstly sequenced and assembled to chromosome-level by us (Sichuan Normal University, corresponding author: Prof. Dr. Zhixi Fu, fuzx2017@sicnu.edu.cn). The genome assembly and high-quality annotations are provided in this website. The comparative and phylogenomic analyses were subsequently conducted and included in a paper: <b>A </b><b><i>de novo </i></b><b>assembled</b><b><i> </i></b><b>chromosome-level genome of </b><b><i>Ainsliaea gracilis</i></b><b> Franch. (Pertyeae, Asteraceae) with comparative and phylogenomic analyses in Asteraceae</b> (under review).
DOI: 10.15468/dl.4ehub3
title: Occurrence Download

description: A dataset containing 3092787 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Elasmobranchii"
 ]
}

 The dataset includes 3092787 records from 1562 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032629-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a5zm94
title: Occurrence Download

description: A dataset containing 39953 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.continent = 'AFRICA'
 AND occurrence.countrycode = 'NA'
 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 39953 records were derived from 241 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032630-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.y4ss7g
title: Occurrence Download

description: A dataset containing 29906933 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "BasisOfRecord is Human Observation",
 "BasisOfRecord is Specimen"
 ]
 },
 "Geometry POLYGON((-169.10156 70.14036,-168.39844 67.06743,-169.10156 59.17593,-173.32031 54.16243,-123.39844 17.97873,-77.69531 -28.92163,-87.77481 -60.35224,-36.68894 -56.97397,-37.61778 -39.24118,-30.1871 -17.37524,-37.61778 18.25951,-49.69262 45.41349,-36.91406 51.61802,-33.05072 65.16474,-9.87229 71.19014,-2.46094 83.59903,-66.44531 84.40594,-127.61719 81.09321,-149.41406 75.84517,-169.10156 70.14036))",
 "HasGeospatialIssue is false",
 "TaxonKey is Setophaga Swainson, 1827",
 "Year 1980-2021"
 ]
}

 The dataset includes 29906933 records from 361 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0180418-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d452y2
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Liotyphlops haadi Silva-Haad, Franco & Maldonado, 2008"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0293227-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ztpk3g
title: Occurrence Download

description: A dataset containing 15 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Human Observation)",
 "Country is one of (Poland, Spain, Czechia, Netherlands)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Torreya Arn."
 ]
}

 The dataset includes 15 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012562-230810091245214/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xacber
title: Occurrence Download

description: A dataset containing 3672 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Machine Observation",
 "Country is Indonesia",
 "OccurrenceStatus is Present",
 "Year 2010-2021"
 ]
}

 The dataset includes 3672 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0086720-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w69ef8
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mordellistena miyamotoi Nakane, 1956",
 "HasCoordinate is true",
 "Country is Japan",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0226014-220831081235567/datasets/export for details.