cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.5ckpzg
title: Occurrence Download

description: A dataset containing 355 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Syzygium aqueum (Burm.fil.) Alston)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 355 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017780-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eybh37
title: Occurrence Download

description: A dataset containing 361268 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Thailand",
 "TaxonKey is Tracheophyta"
 ]
}

 The dataset includes 361268 records from 281 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017772-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gd6ay3
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Contopus latirostris (J.Verreaux, 1866)",
 "Year is greater than or equal to 1950",
 {
 "or" : [
 "GadmGid is USA",
 "GadmGid is CAN",
 "GadmGid is MEX"
 ]
 }
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017784-250426092105405/datasets/export for details.
DOI: 10.15468/dl.q5z2gf
title: Occurrence Download

description: A dataset containing 588 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Observation",
 "DatasetKey is Bird Observational Records",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Parus major Linnaeus, 1758",
 "Year 1988-2025"
 ]
}

 The dataset includes 588 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017782-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4121/f225eb54-9bcf-491a-baf9-15a933ccb1d0
title: Expert ratings of metaphors for quantum computing concepts

description: This dataset was produced as part of a study which aimed to document metaphors used by quantum computing educators to teach quantum computing concepts, and to evaluate the quality of these metaphors. The dataset contains numerical ratings of 9 metaphors for quantum computing concepts, provided by 7 expert participants. (The 9 metaphors were collected from interviews with a prior, separate group of expert participants.) Each metaphor was rated by the participants along 6 dimensions of metaphor quality (accurate, complete, explainable, understandable, relatable, actionable), with each rating being given as an integer value from 1 to 5. 1 was the lowest possible rating and 5 was the highest. The dataset is organised by metaphor and by dimension, meaning ratings across all participants are collated per metaphor, and within that metaphor, collated per dimension.
DOI: 10.5281/zenodo.15349413
title: Trade Data & Calculation HS Code 03

description: Data & Preliminary Simulated Rebalance of International Trade for HS Code 03
DOI: 10.5281/zenodo.15349414
title: Trade Data & Calculation HS Code 03

description: Data & Preliminary Simulated Rebalance of International Trade for HS Code 03
DOI: 10.4121/f225eb54-9bcf-491a-baf9-15a933ccb1d0.v1
title: Expert ratings of metaphors for quantum computing concepts

description: This dataset was produced as part of a study which aimed to document metaphors used by quantum computing educators to teach quantum computing concepts, and to evaluate the quality of these metaphors. The dataset contains numerical ratings of 9 metaphors for quantum computing concepts, provided by 7 expert participants. (The 9 metaphors were collected from interviews with a prior, separate group of expert participants.) Each metaphor was rated by the participants along 6 dimensions of metaphor quality (accurate, complete, explainable, understandable, relatable, actionable), with each rating being given as an integer value from 1 to 5. 1 was the lowest possible rating and 5 was the highest. The dataset is organised by metaphor and by dimension, meaning ratings across all participants are collated per metaphor, and within that metaphor, collated per dimension.
DOI: 10.15468/dl.ccbsz7
title: Occurrence Download

description: A dataset containing 7341 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((16.84044840224163 48.001738154773086, 16.852301404053875 48.08953850781536, 16.72220353884672 48.097573006494244, 16.710572357725173 48.00975667012748, 16.84044840224163 48.001738154773086))"
 ]
}

 The dataset includes 7341 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017783-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k6u4d8
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is South Africa",
 "Geometry POLYGON((27.97824 -26.2468,28.11542 -26.2468,28.11542 -26.12688,27.97824 -26.12688,27.97824 -26.2468))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Ricinus communis L."
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017785-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10074416
title: GRDC-Caravan: extending the original dataset with data from the Global Runoff Data Centre

description: Large-sample datasets are essential in hydrological science to support modelling studies and global assessments. This dataset is an extension to Caravan, a global community dataset of meteorological forcing data, catchment attributes, and discharge data for catchments around the world (Kratzert et al. 2023).
The extension includes a subset of those hydrological discharge data and station-based watersheds from the Global Runoff Data Centre (GRDC), which are covered by an open data policy (Attribution 4.0 International; CC BY 4.0). In total, the dataset covers stations from 5357 catchments and 25 countries worldwide with a time series record from 1950 – 2023.
GRDC is an international data centre operating under the auspices of the World Meteorological Organization (WMO) at the German Federal Institute of Hydrology (BfG). Established in 1988, it holds the most substantive collection of quality assured river discharge data worldwide. Primary providers of river discharge data and associated metadata are the National Hydrological and Hydro-Meteorological Services of WMO Member States.
Reference:
Kratzert, F., Nearing, G., Addor, N. et al. Caravan - A global community dataset for large-sample hydrology. Sci Data 10, 61 (2023). https://doi.org/10.1038/s41597-023-01975-w
Update:
With version 0.2 a bug has been fixed that affected the time series of four bands of all GRDC gauges in the GRDC extension. The affected bands were total_precipitation, surface_net_solar_radiation, surface_net_thermal_radiation and potential_evaporation, i.e. all features that are accumulated over the day, as per definition of ERA5-Land.For details look at https://github.com/kratzert/Caravan/issues/26.
DOI: 10.5281/zenodo.14006282
title: GRDC-Caravan: extending the original dataset with data from the Global Runoff Data Centre

description: Large-sample datasets are essential in hydrological science to support modelling studies and global assessments. This dataset is an extension to Caravan, a global community dataset of meteorological forcing data, catchment attributes, and discharge data for catchments around the world (Kratzert et al. 2023).

The extension includes a subset of those hydrological discharge data and station-based watersheds from the Global Runoff Data Centre (GRDC), which are covered by an open data policy (Attribution 4.0 International; CC BY 4.0). In total, the dataset covers stations from 5357 catchments and 25 countries worldwide with a time series record from 1950 – 2023.

GRDC is an international data centre operating under the auspices of the World Meteorological Organization (WMO) at the German Federal Institute of Hydrology (BfG). Established in 1988, it holds the most substantive collection of quality assured river discharge data worldwide. Primary providers of river discharge data and associated metadata are the National Hydrological and Hydro-Meteorological Services of WMO Member States.

Reference:

Kratzert, F., Nearing, G., Addor, N. et al. Caravan - A global community dataset for large-sample hydrology. Sci Data 10, 61 (2023). https://doi.org/10.1038/s41597-023-01975-w

 

Update:

With version 0.2 a bug has been fixed that affected the time series of four bands of all GRDC gauges in the GRDC extension. The affected bands were total_precipitation, surface_net_solar_radiation, surface_net_thermal_radiation and potential_evaporation, i.e. all features that are accumulated over the day, as per definition of ERA5-Land.For details look at https://github.com/kratzert/Caravan/issues/26.

Version 0.3: Data description file added.

 

Dataset structure:

The dataset is provided in the following two file formats:1. caravan-grdc-extension-csv.tar.gz: provides the time series data as comma-separated text files (CSV) (downloadable as 9.6 GB zip archive)2. caravan-grdc-extension-nc.tar.gz: provides the time series data in the Network Common Data Form (NetCDF) (downloadable as 8 GB zip archive)

The data in both versions are identical, users can choose if they require the time series data in CSV or NetCDF format.

Further details of the structure of the dataset are described in the data description file.
DOI: 10.5281/zenodo.14725028
title: GRDC-Caravan: extending the original dataset with data from the Global Runoff Data Centre

description: Large-sample datasets are essential in hydrological science to support modelling studies and global assessments. This dataset is an extension to Caravan, a global community dataset of meteorological forcing data, catchment attributes, and discharge data for catchments around the world (Kratzert et al. 2023).

The extension includes a subset of those hydrological discharge data and station-based watersheds from the Global Runoff Data Centre (GRDC), which are covered by an open data policy (Attribution 4.0 International; CC BY 4.0). In total, the dataset covers stations from 5356 catchments and 25 countries worldwide with a time series record from 1950 – 2023.

GRDC is an international data centre operating under the auspices of the World Meteorological Organization (WMO) at the German Federal Institute of Hydrology (BfG). Established in 1988, it holds the most substantive collection of quality assured river discharge data worldwide. Primary providers of river discharge data and associated metadata are the National Hydrological and Hydro-Meteorological Services of WMO Member States.

Reference:

Kratzert, F., Nearing, G., Addor, N. et al. Caravan - A global community dataset for large-sample hydrology. Sci Data 10, 61 (2023). https://doi.org/10.1038/s41597-023-01975-w

Update:

With version 0.2 a bug has been fixed that affected the time series of four bands of all GRDC gauges in the GRDC extension. The affected bands were total_precipitation, surface_net_solar_radiation, surface_net_thermal_radiation and potential_evaporation, i.e. all features that are accumulated over the day, as per definition of ERA5-Land.For details look at https://github.com/kratzert/Caravan/issues/26.

Version 0.3: Data description file added.Version 0.4: Added FAO Penman-Monteith PET (potential_evaporation_sum_FAO_PENMAN_MONTEITH) in the meteorological forcing data and renamed the ERA5-LAND potential_evaporation band to potential_evaporation_sum_ERA5_LAND. Also added all PET-related climated indices derived with the Penman-Monteith PET band (suffix "_FAO_PM") and renamed the old PET-related indices accordingly (suffix "_ERA5_LAND"). 

 

Dataset structure:

The dataset is provided in the following two file formats:1. caravan-grdc-extension-csv.zip: provides the time series data as comma-separated text files (CSV) (downloadable as 9.5 GB zip archive)2. caravan-grdc-extension-nc.zip: provides the time series data in the Network Common Data Form (NetCDF) (downloadable as 8 GB zip archive)

The data in the versions 0.1-0.3 are identical. Version 0.4 added FAO Penman-Monteith PET (potential_evaporation_sum_FAO_PENMAN_MONTEITH) and renamed the ERA5-LAND potential_evaporation band to potential_evaporation_sum_ERA5_LAND.

Further details of the structure of the dataset are described in the data description file.
DOI: 10.5281/zenodo.15124865
title: GRDC-Caravan: extending the original dataset with data from the Global Runoff Data Centre

description: Large-sample datasets are essential in hydrological science to support modelling studies and global assessments. This dataset is an extension to Caravan, a global community dataset of meteorological forcing data, catchment attributes, and discharge data for catchments around the world (Kratzert et al. 2023).

The extension includes a subset of those hydrological discharge data and station-based watersheds from the Global Runoff Data Centre (GRDC), which are covered by an open data policy (Attribution 4.0 International; CC BY 4.0). In total, the dataset covers stations from 5356 catchments and 25 countries worldwide with a time series record from 1950 – 2023.

GRDC is an international data centre operating under the auspices of the World Meteorological Organization (WMO) at the German Federal Institute of Hydrology (BfG). Established in 1988, it holds the most substantive collection of quality assured river discharge data worldwide. Primary providers of river discharge data and associated metadata are the National Hydrological and Hydro-Meteorological Services of WMO Member States.

Reference:

Kratzert, F., Nearing, G., Addor, N. et al. Caravan - A global community dataset for large-sample hydrology. Sci Data 10, 61 (2023). https://doi.org/10.1038/s41597-023-01975-w

Update:

With version 0.2 a bug has been fixed that affected the time series of four bands of all GRDC gauges in the GRDC extension. The affected bands were total_precipitation, surface_net_solar_radiation, surface_net_thermal_radiation and potential_evaporation, i.e. all features that are accumulated over the day, as per definition of ERA5-Land.For details look at https://github.com/kratzert/Caravan/issues/26.

Version 0.3: Data description file added.Version 0.4: Added FAO Penman-Monteith PET (potential_evaporation_sum_FAO_PENMAN_MONTEITH) in the meteorological forcing data and renamed the ERA5-LAND potential_evaporation band to potential_evaporation_sum_ERA5_LAND. Also added all PET-related climated indices derived with the Penman-Monteith PET band (suffix "_FAO_PM") and renamed the old PET-related indices accordingly (suffix "_ERA5_LAND").Version 0.5: License overview of the respective countries has been added.Dataset description has been modified and improved.

 

Dataset structure:

The dataset is provided in the following two file formats:1. caravan-grdc-extension-csv.zip: provides the time series data as comma-separated text files (CSV) (downloadable as 8.8 GB zip archive)2. caravan-grdc-extension-nc.zip: provides the time series data in the Network Common Data Form (NetCDF) (downloadable as 7.6 GB zip archive)

The data in the versions 0.1-0.3 are identical. Version 0.4 added FAO Penman-Monteith PET (potential_evaporation_sum_FAO_PENMAN_MONTEITH) and renamed the ERA5-LAND potential_evaporation band to potential_evaporation_sum_ERA5_LAND.

Further details of the structure of the dataset are described in the data description file.
DOI: 10.5281/zenodo.8425587
title: GRDC-Caravan: extending the original dataset with data from the Global Runoff Data Centre

description: Large-sample datasets are essential in hydrological science to support modelling studies and global assessments. This dataset is an extension to <em>Caravan</em>, a global community dataset of meteorological forcing data, catchment attributes, and discharge data for catchments around the world (Kratzert et al. 2023<sup>1</sup>). The extension includes a subset of those hydrological discharge data and station-based watersheds from the Global Runoff Data Centre (GRDC), which are covered by an open data policy (Attribution 4.0 International; CC BY 4.0). In total, the dataset covers stations from 5357 catchments and 25 countries worldwide with a time series record from 1950 – 2023. GRDC is an international data centre operating under the auspices of the World Meteorological Organization (WMO) at the German Federal Institute of Hydrology (BfG). Established in 1988, it holds the most substantive collection of quality assured river discharge data worldwide. Primary providers of river discharge data and associated metadata are the National Hydrological and Hydro-Meteorological Services of WMO Member States. <sup>1</sup>Kratzert, F., Nearing, G., Addor, N. et al. Caravan - A global community dataset for large-sample hydrology. Sci Data 10, 61 (2023). https://doi.org/10.1038/s41597-023-01975-w
DOI: 10.15468/dl.5739fz
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Eugenia cumini Merr., 1917)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 8 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017786-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mee3pr
title: Occurrence Download

description: A dataset listing the 21 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((29.47294 -28.70526,29.76352 -28.70526,29.76352 -28.51272,29.47294 -28.51272,29.47294 -28.70526))",
 "OccurrenceStatus is Present",
 "TaxonKey is Mammalia"
 ]
}

 The dataset's 21 records were derived from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017774-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z7rvjd
title: Occurrence Download

description: A dataset containing 683 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Allium tulipifolium Ledeb."
 ]
}

 The dataset includes 683 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017788-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nm43rg
title: Occurrence Download

description: A dataset containing 588 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Observation",
 "DatasetKey is Bird Observational Records",
 "TaxonKey is Parus major Linnaeus, 1758",
 "Year 1984-2025"
 ]
}

 The dataset includes 588 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017787-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15349401
title: Example of reverse Monte Carlo simulation for fcc high-entropy alloy AuCuNiPdPt at 273 K

description: The data set contains the example of reverse Monte Carlo (RMC) simulation of EXAFS spectra collected for fcc high-entropy alloy AuCuNiPdPt at 273 K.

The simulation was performed by the EvAX code freely available from http://www.dragon.lv/evax/.
DOI: 10.5281/zenodo.15349402
title: Example of reverse Monte Carlo simulation for fcc high-entropy alloy AuCuNiPdPt at 273 K

description: The data set contains the example of reverse Monte Carlo (RMC) simulation of EXAFS spectra collected for fcc high-entropy alloy AuCuNiPdPt at 273 K.

The simulation was performed by the EvAX code freely available from http://www.dragon.lv/evax/.
DOI: 10.5281/zenodo.14862165
title: SWMM Hydrology Datasets of ITB Jatinangor Campus

description: Dataset for hydrologic modelling using SWMM



Historical SWMM Model and ResultsThis simulation using 10-years historical data from GSMaP. This dataset includes rainfall data (.DAT), SWMM model (.inp and .ini), simulation result (.xlsx), and map background (.jpg)

Future SWMM Model and ResultsThis simulation using CIMP6's IPSL-CM6A-LR rainfall projections. This dataset includes rainfall data (.DAT), SWMM model (.inp and .ini), simulation result (.txt), and map background (.jpg)
DOI: 10.5281/zenodo.15349417
title: SWMM Hydrology Datasets of ITB Jatinangor Campus

description: Dataset for hydrologic modelling using SWMM



Historical SWMM Model and ResultsThis simulation uses 10 years of historical data from GSMaP. This dataset includes rainfall data (.DAT), SWMM model (.inp and .ini), simulation result (.xlsx), and map background (.jpg)

Future SWMM Model and ResultsThis folder contains 3 models representing undeveloped, developed, and GR-modified scenarios. The model has saved extreme rainfall projections (for each SSP and 25-year period) as time series. The map background is provided in the Historical SWMM Model and Results folder.
DOI: 10.5281/zenodo.14862164
title: SWMM Hydrology Datasets of ITB Jatinangor Campus

description: Dataset for hydrologic modelling using SWMM



Historical SWMM Model and ResultsThis simulation uses 10 years of historical data from GSMaP. This dataset includes rainfall data (.DAT), SWMM model (.inp and .ini), simulation result (.xlsx), and map background (.jpg)

Future Extreme SWMM ModelThis folder contains 3 models representing undeveloped, developed, and GR-modified scenarios. The model has saved extreme rainfall projections (for each SSP and 25-year period) as time series. The map background is provided in the Historical SWMM Model and Results folder.
DOI: 10.5281/zenodo.15349441
title: SWMM Hydrology Datasets of ITB Jatinangor Campus

description: Dataset for hydrologic modelling using SWMM



Historical SWMM Model and ResultsThis simulation uses 10 years of historical data from GSMaP. This dataset includes rainfall data (.DAT), SWMM model (.inp and .ini), simulation result (.xlsx), and map background (.jpg)

Future Extreme SWMM ModelThis folder contains 3 models representing undeveloped, developed, and GR-modified scenarios. The model has saved extreme rainfall projections (for each SSP and 25-year period) as time series. The map background is provided in the Historical SWMM Model and Results folder.
DOI: 10.15468/dl.47ydng
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Eugenia jambos Blanco, 1837)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 20 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017789-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.