cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.6w2u5g
title: Occurrence Download

description: A dataset containing 193 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ulmus parvifolia",
 "Country is South Africa",
 "HasCoordinate is true"
 ]
}

 The dataset includes 193 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050492-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nrs7dg
title: Occurrence Download

description: A dataset containing 352692 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Plantae of Costa Rica (INBio)"
 ]
}

 The dataset includes 352692 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050466-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g5h29q
title: Occurrence Download

description: A dataset containing 9418 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ulmus parvifolia",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 9418 records from 85 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050493-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kjdxjg
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Cualac tessellatus)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 13 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050494-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bc8eee
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is COL.28.17_2",
 "OccurrenceStatus is Present",
 "TaxonKey is Mammalia"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050495-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/ytwmmr
title: Anti-scarring from eigenstate stacking in a chaotic spinor condensate

description: The data in this dataverse is to generate the figures in paper with arxiv tag 2501.17856 named "Anti-scarring from eigenstate stacking in a chaotic spinor condensate".
DOI: 10.15468/dl.2j2hpc
title: Occurrence Download

description: A dataset containing 113 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Oligosarcus oligolepis"
 ]
}

 The dataset includes 113 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050496-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3rsfx9
title: Occurrence Download

description: A dataset containing 2112 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "TaxonKey is Musa velutina"
 ]
}

 The dataset includes 2112 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050497-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.etecft
title: Occurrence Download

description: A dataset containing 40622 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is VIS - Non-native fish in Flanders, Belgium"
 ]
}

 The dataset includes 40622 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050499-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57783/h383-4t18
title: LibreChat
DOI: 10.15468/dl.3n44m3
title: Occurrence Download

description: A dataset containing 517 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-77.44948 -18.52893,-67.53626 -18.52893,-67.53626 -12.30675,-77.44948 -12.30675,-77.44948 -18.52893))",
 "HasGeospatialIssue is false",
 "TaxonKey is Conirostrum binghami",
 "Year 2020-2025"
 ]
}

 The dataset includes 517 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050502-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mmfg3q
title: Occurrence Download

description: A dataset listing the 94 species recorded in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "GadmGid is BRA.2.77_2",
 "OccurrenceStatus is Present",
 "TaxonKey is Chordata"
 ]
}

 The dataset's 94 records were derived from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050470-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.39mwtp
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Seulocia vittata"
 ]
}

 The dataset includes 10 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050504-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.arw3x6
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Shenius anomalus"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050505-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/6i2q2p
title: Gridded Population of the World, Version 3 (GPWv3): National Identifier Grid

description: The Gridded Population of the World, Version 3 (GPWv3): National Identifier Grid is derived from the land area grid to create a raster surface where pixels (cells) that cover the same country or territory have the same value. Note that the countries and territories are not official representations of countries boundaries; rather, they represent the area covered by the statistical data as provided. GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).
description: To provide a raster representation of nation-states in GPWv3 for use in aggregating population data.
DOI: 10.15468/dl.cbqstz
title: Occurrence Download

description: A dataset containing 23016 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tecoma stans",
 "HasCoordinate is true"
 ]
}

 The dataset includes 23016 records from 497 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050501-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fuz94s
title: Occurrence Download

description: A dataset containing 2022 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Hypolimnas octocula marianensis, Samoana fragilis, Partula gibba, Partula radiolata, Heritiera longipetiolata, Serianthes nelsonii, Eugenia bryanii, Psychotria malaspinae, Tabernaemontana rotensis, Maesa walkeri, Nervilia jacksoniae, Bulbophyllum guamense, Dendrobium guamense, Tuberolabium guamense, Cycas micronesica, Emoia slevini, Todiramphus cinnamominus, Gallirallus owstoni, Aerodramus bartschi, Pteropus mariannus)",
 "HasCoordinate is false",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2022 records from 107 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050506-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nbn4xw
title: Occurrence Download

description: A dataset containing 14734860 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Lepidoptera)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "DatasetKey" : [
 "is 50c9509d-22c7-4a22-a47d-8c784ddf8d78"
 ]
 }
 },
 {
 "not" : {
 "BasisOfRecord" : [
 "is Human Observation"
 ]
 }
 }
 ]
}

 The dataset includes 14734860 records from 1537 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050421-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13907272
title: Table S1 The spontameous plants recorded in Changchun
DOI: 10.5281/zenodo.13907273
title: Table S1 The spontameous plants recorded in Changchun
DOI: 10.5281/zenodo.13342412
title: Radial dependence of SEP peak fluxes and fluences: Multi-spacecraft observations based on Parker Solar Probe, Solar Orbiter, and near-Earth particle detectors
DOI: 10.5281/zenodo.13342413
title: Radial dependence of SEP peak fluxes and fluences: Multi-spacecraft observations based on Parker Solar Probe, Solar Orbiter, and near-Earth particle detectors
DOI: 10.5281/zenodo.13825287
title: Radial dependence of SEP peak fluxes and fluences: Multi-spacecraft observations based on Parker Solar Probe, Solar Orbiter, and near-Earth particle detectors
DOI: 10.5281/zenodo.13907216
title: Arctic Gridded surface cloud fraction radiative kernels (GCF-CRKs)

description: These gridded surface cloud fraction radiative kernels (GCF-CRKs) are created by integrating refined downwelling surface shortwave radiation (DSSR) estimates and a high-precision cloud fraction (CF). The DSSR is corrected by a CF-dependent model, which leveraging the correlation between the top-of-atmosphere (TOA) shortwave radiative parameters and surface radiation, combined with high-precision fused CF datasets from multiple satellite sources. 

  There are five individual files. “SFC_SW_Kernel_Arc.nc” is for CRKs of all clouds, “SFC_SW_lowcloud_Kernel_Arc.nc” is for CRKs of low-level clouds, “SFC_SW_midlowcloud_Kernel_Arc.nc” is for CRKs of mid-low-level clouds, “SFC_SW_midhighcloud_Kernel_Arc.nc” is for CRKs of mid-high-level clouds, and “SFC_SW_highcloud_Kernel_Arc.nc” is for CRKs of high-level clouds. The four cloud layers are derived from four pressure layers (surface to 700 hPa, 700-500 hPa, 500-300 hPa, and 300-50 hPa, representing low, middle-low, middle-high, and high clouds, respectively) based on the CERES-SYN stratification standard.

 

The file format is netcdf4, and was created by Matlab. To read these files, any software supporting netcdf4 can be used. These files only involved sunlit months from Apr to Sep during 2000-2020, with the longitude from -180°~180° and the latitude from 60°N~90°N.
DOI: 10.5281/zenodo.13374165
title: Data set on Consumer buying behaviour of Cause-related marketing

description: The dataset consists of Consumer buying behaviour of FMCG products in connection with cause-related marketing.Dataset is based on questionnaire having thirteen five point scale likert scale statements along with the demographic variables.The questionnaire is drafted based on factors contributing to consumer buying behaviour of cause-related marketing such as information available on product packaging,Brand image and Celebrity endorsement.The responses of likert scale statements were in the form of 'Strongly Agree', 'Agree', Neutral', 'Disagree', Strongly Disagree', and they were coded as 5,4,3,2,1 respectively for positive statements and 1,2,3,4,5 respectively for negative statements.
DOI: 10.5281/zenodo.13905790
title: Data and Code for "Comparing the Effects of Euclidean Distance Matching and Dynamic Time Warping in the Clustering of COVID-19 Evolution"

description: This repository contains the datasets and data sources, analysis code, and workflow associated with the manuscript "Comparing the Effects of Euclidean Distance Matching and Dynamic Time Warping in the Clustering of COVID-19 Evolution". The following resources are provided:





Data Files:



time_series_data.csv: A curated time series dataset with dates as rows and NUTS 2 regions as columns. Each column is labeled using a 4-letter abbreviation format "CC.RR", where "CC" represents the country code and "RR" represents the region code. This same abbreviation is also included in the accompanying GeoJSON file.

geometry_data.geojson: A GeoJSON file representing the spatial boundaries of the NUTS 2 regions, with the same 4-letter abbreviations used in the CSV file. EPSG:4326.

COVID19_data_sources.xlsx: This Excel file contains important metadata regarding the sources of COVID-19 data used in this study. It includes:



Source of the data for each country

Official website(s)

The agency responsible for the data

Description of the processing steps used to curate the data into the final time series.







Code:



analysis.py: A Python script used to process and analyze the data. This code can be run using Python 3.x. The libraries required to run this script are listed in the first lines of the code. The code is organized in different numbered sections (1), (2), ... and sub-sections (1a), (1b) ... Make sure to run the script one (sub-)section at a time, so that everything stays overviewable and you don't get all the output at once.





Workflow:



workflow.png : A detailed workflow according to the Knowledge Discovery in Databases (KDD) process, outlining the steps involved in processing and analyzing the data, including the methods used. This workflow provides a comprehensive guide to reproducing the analysis presented in the paper.
DOI: 10.5281/zenodo.13905791
title: Data and Code for "Comparing the Effects of Euclidean Distance Matching and Dynamic Time Warping in the Clustering of COVID-19 Evolution"

description: This repository contains the datasets and data sources, analysis code, and workflow associated with the manuscript "Comparing the Effects of Euclidean Distance Matching and Dynamic Time Warping in the Clustering of COVID-19 Evolution". The following resources are provided:





Data Files:



time_series_data.csv: A curated time series dataset with dates as rows and NUTS 2 regions as columns. Each column is labeled using a 4-letter abbreviation format "CC.RR", where "CC" represents the country code and "RR" represents the region code. This same abbreviation is also included in the accompanying GeoJSON file.

geometry_data.geojson: A GeoJSON file representing the spatial boundaries of the NUTS 2 regions, with the same 4-letter abbreviations used in the CSV file. EPSG:4326.

COVID19_data_sources.xlsx: This Excel file contains important metadata regarding the sources of COVID-19 data used in this study. It includes:



Source of the data for each country

Official website(s)

The agency responsible for the data

Description of the processing steps used to curate the data into the final time series.







Code:



analysis.py: A Python script used to process and analyze the data. This code can be run using Python 3.x. The libraries required to run this script are listed in the first lines of the code. The code is organized in different numbered sections (1), (2), ... and sub-sections (1a), (1b) ... Make sure to run the script one (sub-)section at a time, so that everything stays overviewable and you don't get all the output at once.





Workflow:



workflow.png : A detailed workflow according to the Knowledge Discovery in Databases (KDD) process, outlining the steps involved in processing and analyzing the data, including the methods used. This workflow provides a comprehensive guide to reproducing the analysis presented in the paper.
DOI: 10.5281/zenodo.13374164
title: Data set on Consumer buying behaviour of Cause-related marketing

description: The dataset consists of Consumer buying behaviour of FMCG products in connection with cause-related marketing.Dataset is based on questionnaire having thirteen five point scale likert scale statements along with the demographic variables.The questionnaire is drafted based on factors contributing to consumer buying behaviour of cause-related marketing such as information available on product packaging,Brand image and Celebrity endorsement.The responses of likert scale statements were in the form of 'Strongly Agree', 'Agree', Neutral', 'Disagree', Strongly Disagree', and they were coded as 5,4,3,2,1 respectively for positive statements and 1,2,3,4,5 respectively for negative statements.
DOI: 10.5281/zenodo.13899828
title: Data set on Consumer buying behaviour of Cause-related marketing

description: The dataset consists of Consumer buying behaviour of FMCG products in connection with cause-related marketing.Dataset is based on questionnaire having thirteen five point scale likert scale statements along with the demographic variables.The questionnaire is drafted based on factors contributing to consumer buying behaviour of cause-related marketing such as information available on product packaging,Brand image and Celebrity endorsement.The responses of likert scale statements were in the form of 'Strongly Agree', 'Agree', Neutral', 'Disagree', Strongly Disagree', and they were coded as 5,4,3,2,1 respectively for positive statements and 1,2,3,4,5 respectively for negative statements.
DOI: 10.5281/zenodo.13907349
title: Data set on Consumer buying behaviour of Cause-related marketing

description: The dataset consists of Consumer buying behaviour of FMCG products in connection with cause-related marketing.Dataset is based on questionnaire having thirteen five point scale likert scale statements along with the demographic variables.The questionnaire is drafted based on factors contributing to consumer buying behaviour of cause-related marketing such as information available on product packaging,Brand image and Celebrity endorsement.The responses of likert scale statements were in the form of 'Strongly Agree', 'Agree', Neutral', 'Disagree', Strongly Disagree', and they were coded as 5,4,3,2,1 respectively for positive statements and 1,2,3,4,5 respectively for negative statements.
DOI: 10.15468/dl.eht3j7
title: Occurrence Download

description: A dataset listing the 1 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((144.71261 42.38850,162.26823 42.38850,162.26823 49.40774,144.71261 49.40774,144.71261 42.38850))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Eupithecia scribai Prout, 1938"
 ]
}

 The dataset's 1 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004039-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ecqc26
title: Occurrence Download

description: A dataset containing 191 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Afrixalus spinifrons (Cope, 1862)"
 ]
}

 The dataset includes 191 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004057-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13902415
title: Data described in the article "New Bacterial Aryl Sulfotransferases: Effective Tools for Sulfation ofPolyphenols"

description: Supporting Information contains additional data, Tables,and Figures on the production and biochemicalcharacterization of recombinant ASTs, on the screeningof their sulfation abilities, and structural characterizationof isolated sulfate products.
DOI: 10.5281/zenodo.13902417
title: Data described in the article "New Bacterial Aryl Sulfotransferases: Effective Tools for Sulfation ofPolyphenols"

description: Supporting Information contains additional data, Tables,and Figures on the production and biochemicalcharacterization of recombinant ASTs, on the screeningof their sulfation abilities, and structural characterizationof isolated sulfate products.
DOI: 10.48677/7d624e69-06b2-429f-8f0d-2ee1202f0469
title: Kartographisches Modell 1:500 000 Vektor Stichtag 15.01.2018

description: Das Kartographische Modell 1:500 000 - Vektor (KM500-V) beinhaltet die maßstabsbezogenen generalisierten Vektordaten der topographischen Übersichtskarte von Österreich im Maßstab 1:500 000.

Das KM500-V ist in folgende Objektbereiche gegliedert:
• Bodenbedeckung (Waldfläche und Felsen)
• Geländedarstellung
• Gewässer
• Grenzen (Verwaltung, natürliche und kulturelle Raumgliederung)
• Siedlung
• Verkehr

Stichtag = Erstellungsdatum:
Die Daten sind zu diesem Tag der aktuellste Datenbestand des BEV.
Dies ist nicht ident mit dem Aufnahme- bzw. Vermessungsdatum.
DOI: 10.5281/zenodo.13907383
title: QCA-2024-SCC-YE31673 R&D data

description: Project Code: QCA-2024-SCC-YE31673.This project is classified as CONFIDENTIAL. All information, data, and results associated with this project are strictly restricted to authorized personnel only. Any dissemination, distribution, or copying of the project details is strictly prohibited without prior approval from the project lead and the university's Office of Research Compliance.
DOI: 10.5281/zenodo.13907384
title: QCA-2024-SCC-YE31673 R&D data

description: Project Code: QCA-2024-SCC-YE31673.This project is classified as CONFIDENTIAL. All information, data, and results associated with this project are strictly restricted to authorized personnel only. Any dissemination, distribution, or copying of the project details is strictly prohibited without prior approval from the project lead and the university's Office of Research Compliance.
DOI: 10.15468/dl.w97pnn
title: Occurrence Download

description: A dataset containing 24730 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Åland Islands",
 "DatasetKey is EOD – eBird Observation Dataset",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 24730 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004058-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7y5jxj
title: Occurrence Download

description: A dataset containing 2242536 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "DatasetKey is Observation.org, Nature data from around the World",
 "OccurrenceStatus is Present",
 "TaxonKey is Mammalia",
 "Year 1962-2024"
 ]
}

 The dataset includes 2242536 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004051-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.