cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2nd2kq
title: CCDC 2454473: Experimental Crystal Structure Determination

description: Related Article: Dieter Schollmeyer, Stefan Laufer, Christian Peifer|2025|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.mwsmam
title: Occurrence Download

description: A dataset containing 50 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dregea abyssinica",
 "Geometry POLYGON ((-17.62504 -34.81917, 51.13387 -34.81917, 51.13387 37.34999, -17.62504 37.34999, -17.62504 -34.81917))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 50 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022632-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17603/ds2-5wa4-p411
title: Kentucky Snow & Ice (Jan 2025): Crisis Cleanup 60-Day Volunteer Cleanup Report

description: [172_1_2 KY Snow & Ice] This report celebrates how communities help themselves after disasters. It quantifies $299 K of services to communities, saving survivors many multiples of that amount and jump-starting long-term recovery. It quantifies the work of 10 dedicated voluntary organizations that help neighbors in 2 individual county reports in 1 states. It is a 60-day snapshot of property cleanup documented by relief organizations through crisiscleanup.org, which is the original source. It covers 103 requests for cleanup, and compares this incident with 4 other incidents of the same type coordinated by Crisis Cleanup in 13 years. It includes data for the following municipalities: Henderson County, KY (102 cases); Corydon, KY (4 cases); Henderson, KY (78 cases).
DOI: 10.15468/dl.5488w2
title: Occurrence Download

description: A dataset containing 757 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is China",
 "OccurrenceStatus is Present",
 "TaxonKey is Aviceda leuphotes",
 "Year 2000-2025"
 ]
}

 The dataset includes 757 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022634-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qkwsmf
title: Occurrence Download

description: A dataset containing 66 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Material sample, Material citation, Specimen, Living Specimen, Occurrence evidence)",
 "Country is Colombia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Pristimantis kelephus",
 "Year 1750-2025"
 ]
}

 The dataset includes 66 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022635-250827131500795/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.30042784
title: WTC dataset (open) Use python libraries to extract

description: WTC dataset (open)
DOI: 10.6084/m9.figshare.30042784.v1
title: WTC dataset (open) Use python libraries to extract

description: WTC dataset (open)
DOI: 10.15468/dl.njnjxs
title: Occurrence Download

description: A dataset containing 3388 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Mimosa tenuiflora, Mimosa tenuiflora)"
 ]
}

 The dataset includes 3388 records from 177 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022636-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xn35ug
title: Occurrence Download

description: A dataset containing 33767 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hesperis matronalis",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 33767 records from 147 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022637-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bptqbv
title: Occurrence Download

description: A dataset containing 191 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Sida abadiana, Sida pernambucensis, Sida coradinii, Sida gertiana, Sida itaparicana, Sida macaibae, Sida macropetala, Sida meloana, Sida meridiana, Sida nordestinensis, Sida pires-blackii, Sida santosii, Sida uchoae, Sida vallsii)"
 ]
}

 The dataset includes 191 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022638-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17047093
title: Lagrangian trajectory data in the Arctic Ocean

description: This dataset contains trajectory data used in Dörr, Mans et al. (2025). The trajectories were produced with the offline trajectory code TRACMASS (Aldama-Campino et al., 2020), and run with monthly output from the ORCA0083-N06 simulation, averaged over 1979 - 2015. 

Ini.csv and Out.csv contain information about each trajectory at seeding, and killing, respectively. Run_split_[01-12]_01.csv contain information about each trajectory during runtime. The csv files have the following variables:

[Trajectory number],[x-position],[y-position],[z-position],[Volume transport (m^3/s],[Time since seeding (s)],[grid cell wall],[pot. Temperature (˚C)],['practical Salinity (psu)],[pot. Density (kg/m^3)],[Mixed-layer depth (m)], [Mixed-layer depth (turbocline, m)]

x,y, and z position are with respect to ORCA0083-N06's native grid (we cut the y-axis from y=2200 until y = 3059 in the original output).
DOI: 10.5281/zenodo.17047094
title: Lagrangian trajectory data in the Arctic Ocean

description: This dataset contains trajectory data used in Dörr, Mans et al. (2025). The trajectories were produced with the offline trajectory code TRACMASS (Aldama-Campino et al., 2020), and run with monthly output from the ORCA0083-N06 simulation, averaged over 1979 - 2015. 

Ini.csv and Out.csv contain information about each trajectory at seeding, and killing, respectively. Run_split_[01-12]_01.csv contain information about each trajectory during runtime. The csv files have the following variables:

[Trajectory number],[x-position],[y-position],[z-position],[Volume transport (m^3/s],[Time since seeding (s)],[grid cell wall],[pot. Temperature (˚C)],['practical Salinity (psu)],[pot. Density (kg/m^3)],[Mixed-layer depth (m)], [Mixed-layer depth (turbocline, m)]

x,y, and z position are with respect to ORCA0083-N06's native grid (we cut the y-axis from y=2200 until y = 3059 in the original output).
DOI: 10.15468/dl.uyzjm7
title: Occurrence Download

description: A dataset containing 15243 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Australia",
 "DatasetKey is one of (Fauna Atlas N.T., iNaturalist Research-grade Observations)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Month is May",
 "OccurrenceStatus is Present",
 "Year 2017-2017"
 ]
}

 The dataset includes 15243 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022639-250827131500795/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.29380553
title: Integrating neighboring structure knowledge into a CNN-Transformer hybrid model for global open-access DEM Correction using ICESat-2 altimetry

description: <b>Accurate global digital elevation models (GDEMs) are essential for various geoscience applications. However, the accuracy of GDEMs in vegetated mountainous regions is relatively low due to substantial topographic relief and the penetration limitations of data acquisition techniques. The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) acquires high-precision and high-density elevation measurements along its ground tracks on a global scale, offering reliable reference data for GDEM corrections. However, previous GDEM corrections using ICESat-2 altimetry data primarily focused on pixel-by-pixel vertical elevation corrections, often neglecting inter-pixel neighboring structure information, which is crucial for terrain modeling and analysis, particularly in areas with high relief. Therefore, this study incorporates not only ICESat-2 precise elevation observations and but also its along-track neighboring structure knowledge into a convolutional neural network (CNN)-transformer hybrid model, termed NSCT, to correct GDEMs in global scale. The 1 arc-second Copernicus DEM was selected as the target DEM for correction due to its demonstrated superior accuracy. The proposed NSCT model, trained on a diverse range of globally distributed areas with varying topography and vegetation, was evaluated using ICESat-2, global control points, and high-resolution DEMs. Its performance was compared against eight currently most used DEM correction models and publicly available corrected GDEM products, including FABDEM, FathomDEM, and GEDTM30. Correction results demonstrated that the NSCT model generally improved Copernicus DEM accuracy by 66.34%, and outperformed existing correction models in both vertical elevation and neighboring structure assessment across diverse topographic and vegetation conditions. Furthermore, validation using ICESat-2 data and high-resolution DEMs outside the training area, as well with its application to SRTM and AW3D30 GDEM, demonstrated that the NSCT model exhibited superior transferability capability and consistently outstanding performance. This study is the first to integrate the precise elevation observations of ICESat-2 with along-track neighboring structure knowledge into GDEM corrections, offering valuable insights for future research in terrain modeling and analysis.</b>
DOI: 10.6084/m9.figshare.29380553.v2
title: Integrating neighboring structure knowledge into a CNN-Transformer hybrid model for global open-access DEM Correction using ICESat-2 altimetry

description: <b>Accurate global digital elevation models (GDEMs) are essential for various geoscience applications. However, the accuracy of GDEMs in vegetated mountainous regions is relatively low due to substantial topographic relief and the penetration limitations of data acquisition techniques. The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) acquires high-precision and high-density elevation measurements along its ground tracks on a global scale, offering reliable reference data for GDEM corrections. However, previous GDEM corrections using ICESat-2 altimetry data primarily focused on pixel-by-pixel vertical elevation corrections, often neglecting inter-pixel neighboring structure information, which is crucial for terrain modeling and analysis, particularly in areas with high relief. Therefore, this study incorporates not only ICESat-2 precise elevation observations and but also its along-track neighboring structure knowledge into a convolutional neural network (CNN)-transformer hybrid model, termed NSCT, to correct GDEMs in global scale. The 1 arc-second Copernicus DEM was selected as the target DEM for correction due to its demonstrated superior accuracy. The proposed NSCT model, trained on a diverse range of globally distributed areas with varying topography and vegetation, was evaluated using ICESat-2, global control points, and high-resolution DEMs. Its performance was compared against eight currently most used DEM correction models and publicly available corrected GDEM products, including FABDEM, FathomDEM, and GEDTM30. Correction results demonstrated that the NSCT model generally improved Copernicus DEM accuracy by 66.34%, and outperformed existing correction models in both vertical elevation and neighboring structure assessment across diverse topographic and vegetation conditions. Furthermore, validation using ICESat-2 data and high-resolution DEMs outside the training area, as well with its application to SRTM and AW3D30 GDEM, demonstrated that the NSCT model exhibited superior transferability capability and consistently outstanding performance. This study is the first to integrate the precise elevation observations of ICESat-2 with along-track neighboring structure knowledge into GDEM corrections, offering valuable insights for future research in terrain modeling and analysis.</b>
DOI: 10.6084/m9.figshare.29380553.v1
title: Integrating neighboring structure knowledge into a CNN-Transformer hybrid model for global open-access DEM Correction using ICESat-2 altimetry

description: <b>Accurate global digital elevation models (GDEMs) are essential for various geoscience applications. However, the accuracy of GDEMs in vegetated mountainous regions is relatively low due to substantial topographic relief and the penetration limitations of data acquisition techniques. The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) acquires high-precision and high-density elevation measurements along its ground tracks on a global scale, offering reliable reference data for GDEM corrections. However, previous GDEM corrections using ICESat-2 altimetry data primarily focused on pixel-by-pixel vertical elevation corrections, often neglecting inter-pixel neighboring structure information, which is crucial for terrain modeling and analysis, particularly in areas with high relief. Therefore, this study incorporates not only ICESat-2 precise elevation observations and but also its along-track neighboring structure knowledge into a convolutional neural network (CNN)-transformer hybrid model, termed NSCT, to correct GDEMs in global scale. The 1 arc-second Copernicus DEM was selected as the target DEM for correction due to its demonstrated superior accuracy. The proposed NSCT model, trained on a diverse range of globally distributed areas with varying topography and vegetation, was evaluated using ICESat-2, global control points, and high-resolution DEMs. Its performance was compared against eight currently most used DEM correction models and publicly available corrected GDEM products, including FABDEM, FathomDEM, and GEDTM30. Correction results demonstrated that the NSCT model generally improved Copernicus DEM accuracy by 66.34%, and outperformed existing correction models in both vertical elevation and neighboring structure assessment across diverse topographic and vegetation conditions. Furthermore, validation using ICESat-2 data and high-resolution DEMs outside the training area, as well with its application to SRTM and AW3D30 GDEM, demonstrated that the NSCT model exhibited superior transferability capability and consistently outstanding performance. This study is the first to integrate the precise elevation observations of ICESat-2 with along-track neighboring structure knowledge into GDEM corrections, offering valuable insights for future research in terrain modeling and analysis.</b>
DOI: 10.15468/dl.gxrb4z
title: Occurrence Download

description: A dataset containing 1424 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Podocarpus sellowii"
 ]
}

 The dataset includes 1424 records from 149 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022641-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yn78z3
title: Occurrence Download

description: A dataset listing the 459 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((2.53028 46.53129,2.60831 46.53129,2.60831 46.59796,2.53028 46.59796,2.53028 46.53129))",
 "HasCoordinate is true",
 "TaxonKey is Plantae",
 "Year 2010-2025"
 ]
}

 The dataset's 459 records were derived from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022633-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rcycge
title: Occurrence Download

description: A dataset containing 161 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Misgurnus bipartitus"
 ]
}

 The dataset includes 161 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022642-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z3ebwk
title: Occurrence Download

description: A dataset containing 16800 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sorbus chamaemespilus"
 ]
}

 The dataset includes 16800 records from 264 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022640-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g83x58
title: Occurrence Download

description: A dataset containing 4321019 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "Country is Kenya",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 4321019 records from 882 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022612-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xpas58
title: Occurrence Download

description: A dataset containing 42 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Philippines",
 "OccurrenceStatus is Present",
 "TaxonKey is Callosciurus finlaysonii (Horsfield, 1823)",
 "Year 1000-2025"
 ]
}

 The dataset includes 42 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022584-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3atmmf
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Helianthus annuus"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007709-180412121330197/datasets/export for details.
DOI: 10.15468/dl.k8n4x9
title: Occurrence Download

description: A dataset containing 110 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is ETH",
 "TaxonKey is Ziziphus Mill."
 ]
}

 The dataset includes 110 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038108-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zwyr3f
title: Occurrence Download

description: A dataset containing 23036 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Potentilla aurea L.",
 "HasCoordinate is true",
 "Continent is Europe",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2000",
 "CoordinateUncertaintyInMeters is less than 10000"
 ]
}

 The dataset includes 23036 records from 105 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003617-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zvfgck
title: Occurrence Download

description: A dataset containing 35 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Clivia nobilis Lindl.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 35 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008277-170714134226665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6jq9t4
title: Occurrence Download

description: A dataset containing 76 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rhododendron setosum D.Don",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 76 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0321230-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fr5fzf
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Eugenia jeremiensis Urb. & Ekman"
 ]
}

 The dataset includes 5 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0160496-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qzupub
title: Occurrence Download

description: A dataset containing 867 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Bolivia (Plurinational State of), Peru)",
 "TaxonKey is Phoenicoparrus andinus (Philippi, 1854)"
 ]
}

 The dataset includes 867 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003708-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xccen9
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Elaphoglossum diminutum Mickel"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0160497-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4exx9m
title: Occurrence Download

description: A dataset containing 975046 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is NatureServe Network Species Occurrence Data"
 ]
}

 The dataset includes 975046 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0043708-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.twdqr5
title: Occurrence Download

description: A dataset containing 777 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Australia",
 "TaxonKey is Adansonia gregorii F.Muell."
 ]
}

 The dataset includes 777 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008277-171219132708484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.