cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.u9kcju
title: Occurrence Download

description: A dataset containing 677 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Anura",
 "GadmGid is IDN.23_1",
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Material sample, Material citation, Specimen, Occurrence evidence)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 677 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022932-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kkx8sp
title: Occurrence Download

description: A dataset containing 0 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 = '8598edb6-f762-11e1-a439-00145eb45e9a'
 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 0 records were derived from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022923-250920141307145/datasets/export for details.
DOI: 10.6084/m9.figshare.26028769
title: <b>Crop Statistic to Annual Map: Tracking spatiotemporal dynamics of crop-specific areas through machine learning and statistics disaggregating</b>

description: Mapping spatiotemporal dynamics of crop-specific areas is of great significance in addressing challenges faced by agricultural systems. But comparable multi-phase crop maps in year series have not yet been developed in most regions of the global. In this study, we developed a framework for updating annual crop-specific area maps at 10km resolution based on crop statistics disaggregating, multi-source data integrating and machine learning. In our framework, we collected related spatial indicator used in previous studies and trained random forest regression models to predict spatiotemporal dynamics of crop-specific areas based on them. Annual crop statistics were further disaggregated based on probabilistic layer and harmonized based on multiple constraints. Finally, our results include maps of crop-specific areas covering 42 types from 1961-2022 in Africa, maps of crop-specific areas covering 14 types from 1980-2022 in China and maps of crop-specific areas covering 15 types from 2008-2022 in USA. Results show that our products have a reasonable level of consistency with independent reference map or statistics. Our products could be used as data basis for food security and environmental impact assessments.
DOI: 10.6084/m9.figshare.26028769.v4
title: <b>Crop Statistic to Annual Map: Tracking spatiotemporal dynamics of crop-specific areas through machine learning and statistics disaggregating</b>

description: Mapping spatiotemporal dynamics of crop-specific areas is of great significance in addressing challenges faced by agricultural systems. But comparable multi-phase crop maps in year series have not yet been developed in most regions of the global. In this study, we developed a framework for updating annual crop-specific area maps at 10km resolution based on crop statistics disaggregating, multi-source data integrating and machine learning. In our framework, we collected related spatial indicator used in previous studies and trained random forest regression models to predict spatiotemporal dynamics of crop-specific areas based on them. Annual crop statistics were further disaggregated based on probabilistic layer and harmonized based on multiple constraints. Finally, our results include maps of crop-specific areas covering 42 types from 1961-2022 in Africa, maps of crop-specific areas covering 14 types from 1980-2022 in China and maps of crop-specific areas covering 15 types from 2008-2022 in USA. Results show that our products have a reasonable level of consistency with independent reference map or statistics. Our products could be used as data basis for food security and environmental impact assessments.
DOI: 10.6084/m9.figshare.26028769.v3
title: <b>Crop Statistic to Annual Map: Tracking spatiotemporal dynamics of crop-specific areas through machine learning and statistics disaggregating</b>

description: Mapping spatiotemporal dynamics of crop-specific areas is of great significance in addressing challenges faced by agricultural systems. But comparable multi-phase crop maps in year series have not yet been developed in most regions of the global. In this study, we developed a framework for updating annual crop-specific area maps at 10km resolution based on crop statistics disaggregating, multi-source data integrating and machine learning. In our framework, we collected related spatial indicator used in previous studies and trained random forest regression models to predict spatiotemporal dynamics of crop-specific areas based on them. Annual crop statistics were further disaggregated based on probabilistic layer and harmonized based on multiple constraints. Finally, our results include maps of crop-specific areas covering 42 types from 1961-2022 in Africa, maps of crop-specific areas covering 14 types from 1980-2022 in China and maps of crop-specific areas covering 15 types from 2008-2022 in USA. Results show that our products have a reasonable level of consistency with independent reference map or statistics. Our products could be used as data basis for food security and environmental impact assessments.
DOI: 10.15468/dl.ekbdaf
title: Occurrence Download

description: A dataset containing 40 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ruellia blechum",
 "Country is Honduras",
 "HasCoordinate is true"
 ]
}

 The dataset includes 40 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022935-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3dqhaq
title: Occurrence Download

description: A dataset containing 24 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ruellia blechum",
 "Country is Philippines",
 "HasCoordinate is true"
 ]
}

 The dataset includes 24 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022936-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17208069
title: data for North American freshwater fishes

description: This dataset describes the spatial distribution, functional traits, and phylogenetic relationships of freshwater fishes in North America, and comprises environmental and geographical data for 1,873 watersheds across the continent.
DOI: 10.5281/zenodo.17208070
title: data for North American freshwater fishes

description: This dataset describes the spatial distribution, functional traits, and phylogenetic relationships of freshwater fishes in North America, and comprises environmental and geographical data for 1,873 watersheds across the continent.
DOI: 10.15468/dl.utag7a
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ruellia blechum",
 "Country is Samoa",
 "HasCoordinate is true"
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022937-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jbbkhr
title: Occurrence Download

description: A dataset containing 97932 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Miconia calvescens"
 ]
}

 The dataset includes 97932 records from 221 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022895-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m5h9g6
title: Occurrence Download

description: A dataset containing 2517 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Trema orientale",
 "Geometry POLYGON((119.300000 20.500000, 122.100000 20.500000, 122.100000 25.400000, 119.300000 25.400000, 119.300000 20.500000))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2517 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022938-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.btsjuj
title: Occurrence Download

description: A dataset containing 1694 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Fraxinus chinensis",
 "Year 1000-2025"
 ]
}

 The dataset includes 1694 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022934-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.whdcze
title: Occurrence Download

description: A dataset containing 60734358 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is North America",
 "Geometry POLYGON((-180 -58,180 -58,180 84,-180 84,-180 -58))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "License is one of (CC-BY 4.0, CC-BY-NC 4.0)",
 "OccurrenceStatus is Present",
 "TaxonKey is Animalia",
 "Year is 2016"
 ]
}

 The dataset includes 60734358 records from 160 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022824-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13140/rg.2.2.28174.01607
title: Cortaderia selloana
DOI: 10.15468/dl.yg364q
title: Occurrence Download

description: A dataset containing 772 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ficus triloba"
 ]
}

 The dataset includes 772 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022940-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.apmag6
title: Occurrence Download

description: A dataset containing 49924 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Leucaena leucocephala"
 ]
}

 The dataset includes 49924 records from 792 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022941-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.94pjk5
title: Occurrence Download

description: A dataset containing 2074384 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is EOD – eBird Observation Dataset",
 "GadmGid is one of (CHN.11_1, CHN.17_1, CHN.18_1, CHN.2_1, CHN.27_1, CHN.10_1, CHN.23_1, CHN.12_1, CHN.13_1, CHN.1_1, CHN.15_1, CHN.24_1, CHN.31_1, CHN.14_1, CHN.16_1, CHN.4_1, CHN.6_1, CHN.HKG)",
 "TaxonKey is Passeriformes",
 "Year 2015-2025"
 ]
}

 The dataset includes 2074384 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022912-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.su67eh
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is CHN.HKG",
 "OccurrenceStatus is Present",
 "TaxonKey is Gaviiformes",
 "Year 2015-2025"
 ]
}

 The dataset includes 9 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022947-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q6r2w5
title: Occurrence Download

description: A dataset containing 55 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Fraxinus mandshurica",
 "Year 1000-2025"
 ]
}

 The dataset includes 55 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022943-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g79vw5
title: Occurrence Download

description: A dataset containing 73 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ruellia blechum",
 "Country is Trinidad and Tobago",
 "HasCoordinate is true"
 ]
}

 The dataset includes 73 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022945-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fbddva
title: Occurrence Download

description: A dataset containing 245 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Trema tomentosum",
 "Geometry POLYGON((119.300000 20.500000, 122.100000 20.500000, 122.100000 25.400000, 119.300000 25.400000, 119.300000 20.500000))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 245 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022948-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z4rs6r
title: Occurrence Download

description: A dataset containing 8207 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-3.67768 40.16927,-3.58795 40.16927,-3.58795 40.23197,-3.67768 40.23197,-3.67768 40.16927))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 8207 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022949-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jbhwhp
title: Occurrence Download

description: A dataset containing 5063 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hiptage benghalensis"
 ]
}

 The dataset includes 5063 records from 124 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022950-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0185083.10fu
title: SH0185083.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0185084.10fu
title: SH0185084.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0185085.10fu
title: SH0185085.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.xkzf88
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((77.683633 19.627847, 77.609066 19.622271, 77.53635 19.605681, 77.46729000000001 19.578489, 77.403595 19.54137, 77.346842 19.495244, 77.29843 19.441253, 77.259547 19.380735, 77.231146 19.315185, 77.213914 19.246222, 77.208262 19.175548, 77.214314 19.104903, 77.231908 19.036026, 77.26059600000001 18.970609, 77.299662 18.910259, 77.34813699999999 18.856455, 77.404827 18.810516, 77.468338 18.773565, 77.53711199999999 18.746507, 77.609467 18.730004, 77.683633 18.724457, 77.75779900000001 18.730004, 77.83015399999999 18.746507, 77.898928 18.773565, 77.962439 18.810516, 78.01912900000001 18.856455, 78.067604 18.910259, 78.10666999999999 18.970609, 78.135358 19.036026, 78.152952 19.104903, 78.159004 19.175548, 78.153352 19.246222, 78.13612000000001 19.315185, 78.107719 19.380735, 78.068836 19.441253, 78.02042400000001 19.495244, 77.96367100000001 19.54137, 77.899976 19.578489, 77.830916 19.605681, 77.7582 19.622271, 77.683633 19.627847))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001823-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0185086.10fu
title: SH0185086.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.