cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.k2mbdg
title: Occurrence Download

description: A dataset containing 45511 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Corallorhiza trifida Châtel."
 ]
}

 The dataset includes 45511 records from 417 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0291226-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nrqkrt
title: Occurrence Download

description: A dataset listing the 7 species recorded in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dreissenidae",
 "StateProvince is Texas",
 "HasGeospatialIssue is false"
 ]
}

 The dataset's 7 records were derived from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0279894-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fquf6z
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Nothoscordum famatinense Ravenna"
 ]
}

 The dataset includes 5 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0291146-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zgjxx6
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Museum of Comparative Zoology, Harvard University",
 "TaxonKey is Leucopternis lacernulatus (Temminck, 1827)"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0279905-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8s7phn
title: Occurrence Download

description: A dataset containing 57 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-73.99928 6.82849,-73.29851 5.87957,-72.30867 6.83719,-73.99928 6.82849))",
 "HasGeospatialIssue is false",
 "TaxonKey is Passalidae"
 ]
}

 The dataset includes 57 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0291131-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tj5b7d
title: Occurrence Download

description: A dataset containing 89 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "DatasetKey is Natural History Museum (London) Collection Specimens",
 "OccurrenceStatus is Present",
 "TaxonKey is Lissotriton helveticus (Razoumovsky, 1789)"
 ]
}

 The dataset includes 89 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0279906-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qfmws7
title: Occurrence Download

description: A dataset containing 163 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Thamnophilus melanothorax P.L.Sclater, 1857)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 163 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0291404-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5gwqvt
title: Occurrence Download

description: A dataset containing 2355544144 species occurrences available in GBIF matching the query:
{ }

 The dataset includes 2355544144 records from 59174 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002746-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9mhyvp
title: Occurrence Download

description: A dataset listing the 15809 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is NSW BioNet Atlas"
 ]
}

 The dataset's 15809 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094380-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc2cmz77
title: CCDC 2193939: Experimental Crystal Structure Determination

description: Related Article: Martin Nieger, Vera Zota, Edgar Niecke|2022|CSD Communication|||
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: 10.15468/dl.ham6c3
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "Geometry POLYGON((-1.24423 42.94677,-1.08048 42.94677,-1.08048 43.04737,-1.24423 43.04737,-1.24423 42.94677))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Erythronium dens-canis L."
 ]
}

 The dataset includes 17 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094440-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2xpark
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "Geometry POLYGON((-1.24423 42.94677,-1.08048 42.94677,-1.08048 43.04737,-1.24423 43.04737,-1.24423 42.94677))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Erythronium dens-canis L."
 ]
}

 The dataset includes 17 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094441-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12527518
title: archaea_masking:v21.1.1

description: Kraken2 DB for archae built with masking option in Jan 2021. Contains 567  accession numbers corresponding to 331 unique taxons.
DOI: 10.5281/zenodo.12527519
title: archaea_masking:v21.1.1

description: Kraken2 DB for archae built with masking option in Jan 2021. Contains 567  accession numbers corresponding to 331 unique taxons.
DOI: 10.15468/dl.e4u5fy
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Hydropotes inermis Swinhoe, 1870, Hydropotes affinis Brooke, 1872, Hydropotes kreyenbergi Hilzheimer, 1905, Hydropotes argyropus Heude, 1884)",
 "Year 1970-2024"
 ]
}

 The dataset includes 25 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094442-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12542214
title: framework-simulation
DOI: 10.5281/zenodo.12542215
title: framework-simulation
DOI: 10.15468/dl.yfnnsc
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Mabuya sloanii (Daudin, 1803)"
 ]
}

 The dataset includes 4 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094443-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3k29gp
title: Occurrence Download

description: A dataset listing the 9303 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is Occurrence Data of Vascular Plants collected or compiled for the Flora of Bavaria"
 ]
}

 The dataset's 9303 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094390-240506114902167/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.26087701
title: ECSIF products

description: ECSIF-based product with six datasets of GPP and ET at the 0.5° spatial resolution and 8-day temporal resolutions during 2001-2020. These datasets were based on Eddy Covariance measurements, three SIF products (CSIF, GOSIF and RTSIF), meteorological forcing, carbon dioxide (CO<sub>2</sub>) and land cover data using two machine learning algorithms (XGB and RF).
DOI: 10.6084/m9.figshare.26087701.v1
title: ECSIF products

description: ECSIF-based product with six datasets of GPP and ET at the 0.5° spatial resolution and 8-day temporal resolutions during 2001-2020. These datasets were based on Eddy Covariance measurements, three SIF products (CSIF, GOSIF and RTSIF), meteorological forcing, carbon dioxide (CO<sub>2</sub>) and land cover data using two machine learning algorithms (XGB and RF).
DOI: 10.15468/dl.ckfn46
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "VerbatimScientificName is mabuya aurae"
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094444-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j9v8k4
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is biodiversity-yellow-river-basin-wetland"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094445-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.8185733
title: Landslide Influencing Factors for Landslide Susceptibility Mapping in Lombardy, Italy

description: A selection of  Landslide Influencing Factors used for Landslide susceptibility mapping through machine learning models covering the Lombardy region in Italy.

A list of the factors:



Averaged Hourly Precipitation for the year of 2020. Source: Precipitation data from ARPA Lombardia.

Digital Elevation Model [meters], 5m/pix. Source: GeoPortale Lombardia.

Eastness [unitless], 5m/pix. Source: DTM derived.

Faults buffer (50, 100, 200, 500, >500), [meters], 1:10 000. Source: GeoPortale Lombardia, derived.

Land Use Land Cover Map. Source: GeoPortale Lombardia.

Lithology, 5m/pix. Source: GeoPortale Lombardia.

Normalized Difference Vegetation Index, [unitless], 10m/pix. Source: Sentinel-2 derived for the year 2020.

Northness [unitless], 5m/pix. Source: DTM derived.

Orientation of the slope faces [degrees], 5m/pix. Source: DTM derived.

Plan Curvature [unitless], 5m/pix. Source: DTM derived.

Profile Curvature [unitless], 5m/pix. Source: DTM derived.

River buffer (50, 100, 200, 500, >500), [meters], 1:10 000. Source: GeoPortale Lombardia, derived.

Road buffer (50, 100, 200, 500, >500), [meters], 1:10 000. Source: GeoPortale Lombardia, derived.

The 90th percentile of hourly precipitation for the year of 2020. Source: Precipitation data from ARPA Lombardia.

Topographic Wetness Index, 5m/pix . Source: DTM derived


The maps are in WGS 84/ UTM zone 32N (EPSG:32632).

The map production process details are discussed in Xu et al. 2024. If you use the dataset, please, cite also the paper:

Qiongjie Xu, Vasil Yordanov, Lorenzo Amici & Maria Antonia Brovelli (2024) Landslide susceptibility mapping using ensemble machine learning methods: a casestudy in Lombardy, Northern Italy, International Journal of Digital Earth, 17:1, 2346263, DOI:10.1080/17538947.2024.2346263

The maps are produced as part of the "Geoinformatics and Earth Observation for Landslide Monitoring" Italy-Vietnam.

The work is partially funded by the Italian Ministry of Foreign Affairs and International Cooperation within the project “Geoinformatics and Earth Observation for Landslide Monitoring” CUP D19C21000480001.
DOI: 10.5281/zenodo.8185805
title: Landslide susceptibility maps using base machine learning models on basin and regional level in Lombardy, Italy

description: A selection of landslide susceptibility maps computed through base machine learning models for the basins of Val Tartano, Upper Valtellina and Valchiavenna, and on a regional level for the Lombardy region in Italy.

A list of the used machine learning methods:



Bagging,

Random Forest,

AdaBoost,

Gradient Tree Boosting,

Neural Networks.


A full list of the model combinations can be found in the "Case Studies" document.

The maps are in WGS 84/ UTM zone 32N (EPSG:32632).

The map production process details are discussed in Xu et al. 2024. If you use the dataset, please, cite also the paper:

Qiongjie Xu, Vasil Yordanov, Lorenzo Amici & Maria Antonia Brovelli (2024) Landslide susceptibility mapping using ensemble machine learning methods: a casestudy in Lombardy, Northern Italy, International Journal of Digital Earth, 17:1, 2346263, DOI:10.1080/17538947.2024.2346263

The maps are produced as part of the "Geoinformatics and Earth Observation for Landslide Monitoring" Italy-Vietnam.

The work is partially funded by the Italian Ministry of Foreign Affairs and International Cooperation within the project “Geoinformatics and Earth Observation for Landslide Monitoring” CUP D19C21000480001.
DOI: 10.15468/dl.xn75hs
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Mabuya macrorhyncha Hoge, 1946"
 ]
}

 The dataset includes 16 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094446-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.8185869
title: Landslide susceptibility maps using ensemble machine learning models on basin and regional level in Lombardy, Italy

description: A selection of landslide susceptibility maps computed through ensemble machine learning models for the basins of Val Tartano, Upper Valtellina and Valchiavenna, and on a regional level for the Lombardy region in Italy.

A list of the used base machine learning methods:



Random Forest,

AdaBoost,

Neural Networks.


A list of the used ensemble models:



Stacking,

Blending,

Soft Voting.


A full list of the model combinations can be found in the "Case Studies" document.

The maps are in WGS 84/ UTM zone 32N (EPSG:32632).

The map production process details are discussed in Xu et al. 2024. If you use the dataset, please, cite also the paper:

Qiongjie Xu, Vasil Yordanov, Lorenzo Amici & Maria Antonia Brovelli (2024) Landslide susceptibility mapping using ensemble machine learning methods: a casestudy in Lombardy, Northern Italy, International Journal of Digital Earth, 17:1, 2346263, DOI:10.1080/17538947.2024.2346263

The maps are produced as part of the "Geoinformatics and Earth Observation for Landslide Monitoring" Italy-Vietnam.

The work is partially funded by the Italian Ministry of Foreign Affairs and International Cooperation within the project “Geoinformatics and Earth Observation for Landslide Monitoring” CUP D19C21000480001.
DOI: 10.5281/zenodo.8185886
title: The best performing landslide susceptibility maps using ensemble machine learning models and precipitation data on basin and regional level in Lombardy, Italy

description: A selection of landslide susceptibility maps computed through ensemble machine learning models with included precipitation data for the basin of Valchiavenna, and the Lombardy region in Italy.

A list of the used base machine learning methods:



Neural Networks.


A list of the precipitation data included in the models:



Average hourly precipitation for the year of 2020,

90th percentile for the hourly precipitation for the year of 2020 ,

Averaged + 90th percentile for the hourly precipitation for the year of 2020.


A full list of the model combinations can be found in the "Case Studies" document.

The maps are in WGS 84/ UTM zone 32N (EPSG:32632).

The map production process details are discussed in Xu et al. 2024. If you use the dataset, please, cite also the paper:

Qiongjie Xu, Vasil Yordanov, Lorenzo Amici & Maria Antonia Brovelli (2024) Landslide susceptibility mapping using ensemble machine learning methods: a casestudy in Lombardy, Northern Italy, International Journal of Digital Earth, 17:1, 2346263, DOI:10.1080/17538947.2024.2346263

The maps are produced as part of the "Geoinformatics and Earth Observation for Landslide Monitoring" Italy-Vietnam.

The work is partially funded by the Italian Ministry of Foreign Affairs and International Cooperation within the project “Geoinformatics and Earth Observation for Landslide Monitoring” CUP D19C21000480001.
DOI: 10.5281/zenodo.8185906
title: Estimated No Landslide Zone for the Lombardy region, Italy

description: Areas with a very low probability of shallow landslide occurrence according to a geological criterion. The zonation considers as variables the terrain slope and the Intact Uniaxial Compressive Strength (IUCS), an index dependent on the lithology that describes the maximum stress that a material can take before failing. In broad terms, areas with very low inclination (<5°) were included with no other constraint. On the other hand, terrains with low (5°-20°) or very high (>70°) inclination required a resistant terrain (with an IUCS of at least 100 MPa) in order to be included.

The vector layers is in WGS 84/ UTM zone 32N (EPSG:32632), covering the whole region of Lombardy, Italy, with an area of 13,325 km2.

The map production process details are discussed in Xu et al. 2024. If you use the dataset, please, cite also the paper:

Qiongjie Xu, Vasil Yordanov, Lorenzo Amici & Maria Antonia Brovelli (2024) Landslide susceptibility mapping using ensemble machine learning methods: a casestudy in Lombardy, Northern Italy, International Journal of Digital Earth, 17:1, 2346263, DOI:10.1080/17538947.2024.2346263

The layer is produced as part of the "Geoinformatics and Earth Observation for Landslide Monitoring" Italy-Vietnam.

The work is partially funded by the Italian Ministry of Foreign Affairs and International Cooperation within the project “Geoinformatics and Earth Observation for Landslide Monitoring” CUP D19C21000480001.
DOI: 10.6103/share.w8coviddataw9.900
title: Survey of Health, Ageing and Retirement in Europe (SHARE) Combined COVID data
DOI: 10.15468/dl.wa9uf7
title: Occurrence Download

description: A dataset containing 36 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Mabuya heathi Schmidt & Inger, 1951"
 ]
}

 The dataset includes 36 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094448-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4gtmpf
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Mabuya caissara Reboucas-Spieker, 1974"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094449-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fjnubk
title: Occurrence Download

description: A dataset containing 7223098 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Occurrence Data of Vascular Plants collected or compiled for the Flora of Bavaria"
 ]
}

 The dataset includes 7223098 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094408-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9g5cur
title: Occurrence Download

description: A dataset containing 60 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Mabuya agilis (Raddi, 1823)"
 ]
}

 The dataset includes 60 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094450-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ggp28t
title: Occurrence Download

description: A dataset containing 1495776 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lathyrus L.",
 "HasCoordinate is true",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1495776 records from 3837 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094418-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1378247.10fu
title: SH1378247.10FU

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.