cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.kd6nz2
title: Occurrence Download

description: A dataset listing the 18 species recorded in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "DatasetKey is one of (Insect Species Occurrence Data from Multiple Projects Worldwide with Focus on Bees and Wasps in North America, Bee Fauna of National Wildlife Refuges in the Pacific Northwest, 2010-2016, hymenoptera, International Barcode of Life project (iBOL), Illinois Natural History Survey Insect Collection, Snow Entomological Museum Collection, Bee Biology and Systematics Laboratory, Oregon Bee Atlas Survey Data: 2018, Oregon Bee Atlas Survey Data: 2019)",
 "StateProvince is Washington",
 "TaxonKey is one of (, Melissodes)"
 ]
}

 The dataset's 18 records were derived from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054204-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/14170986
title: Egypt Gold Prices | Daily Updated
DOI: 10.15468/dl.eh7pna
title: Occurrence Download

description: A dataset containing 870771 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-76.40442 2.44944,-73.6924 2.44944,-73.6924 6.00105,-76.40442 6.00105,-76.40442 2.44944))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 870771 records from 629 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054199-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25919/tm9h-kq98
title: NBIC-ACS Stage 2 Grass Fire Danger Index - baseline scenario, 20% and 10% annual exceedance probabilities

description: The Grass Fire Danger Index (GFDI) is a fire weather potential index that describes how current weather conditions and recent precipitation patterns could support a fire in grassy areas. GFDI calculations are based on McArthur, A.G. (1966, 1973) and dependent on air temperature, relative humidity, wind speed and grass curing. The metric was developed with the worst event considered corresponding to a value of 100. Here we provide predicted upper-bound GFDI values across the Australian landscape, defined for a set of Annual Exceedance Probabilities. We calculate GFDI based on the latest Bureau of Meteorology historical weather reanalysis BARRA-R2, reporting modelled hourly weather conditions from 1979 to current at a spatial resolution of approximately 11 kilometres. Grass curing values are derived from the 99th percentile of the values modelled from 2000 to 2019 by the Bureau of Meteorology MODIS MapVictoria grass curing dataset. More than 400,000 data points at every location are then processed using the National Bushfire Intelligence Capability (NBIC) Extreme Values Analysis to predict extreme daily maximums and their likelihood. GFDI is used in operational contexts, including land use planning and Australian standards for building in bushfire prone areas, and it is a widely recognised fire weather metric. All these characteristics result in datasets that are a significant advancement in defining extreme fire weather, surpassing previous approaches and offering a robust foundation for informed decision-making in managing and mitigating Australia’s growing bushfire risks in a changing climate.
DOI: 10.25919/wnpr-vp59
title: NBIC-ACS Stage 2 Grass Fire Danger Index - baseline scenario, 5%, 2% and 1% annual exceedance probabilities

description: The Grass Fire Danger Index (GFDI) is a fire weather potential index that describes how current weather conditions and recent precipitation patterns could support a fire in grassy areas. GFDI calculations are based on McArthur, A.G. (1966, 1973) and dependent on air temperature, relative humidity, wind speed and grass curing. The metric was developed with the worst event considered corresponding to a value of 100. Here we provide predicted upper-bound GFDI values across the Australian landscape, defined for a set of Annual Exceedance Probabilities. We calculate GFDI based on the latest Bureau of Meteorology historical weather reanalysis BARRA-R2, reporting modelled hourly weather conditions from 1979 to current at a spatial resolution of approximately 11 kilometres. Grass curing values are derived from the 99th percentile of the values modelled from 2000 to 2019 by the Bureau of Meteorology MODIS MapVictoria grass curing dataset. More than 400,000 data points at every location are then processed using the National Bushfire Intelligence Capability (NBIC) Extreme Values Analysis to predict extreme daily maximums and their likelihood. GFDI is used in operational contexts, including land use planning and Australian standards for building in bushfire prone areas, and it is a widely recognised fire weather metric. All these characteristics result in datasets that are a significant advancement in defining extreme fire weather, surpassing previous approaches and offering a robust foundation for informed decision-making in managing and mitigating Australia’s growing bushfire risks in a changing climate.
DOI: 10.6084/m9.figshare.30889660.v1
title: Effectiveness of a school scientific model to address buoyancy in the training of prospective early childhood teachers

description: Buoyancy is a recurring topic in early childhood education and provides an opportunity to introduce scientific modelling. This study is framed within the need to improve the training of prospective early childhood teachers (PECT) in this scientific practice and examines the effectiveness of a teaching intervention that models the buoyancy of objects in water as balanced forces. The research analyses responses from a pre-test and post-test questionnaire administered before and after the intervention. A qualitative content analysis was used to categorise responses. In general, a positive progression was observed in the models used by the PECT to explain buoyancy as balanced forces. Most PECT correctly assimilated that the upthrust exerted by water is equivalent to the weight of the amount of water displaced by the object, and that this upthrust therefore depends on the volume of the portion of the object submerged. The conclusion is that, with interventions such as this, it is possible (1) to initiate the PECT in the practice of scientific modelling as part of their training to teach science at early childhood education, and that (2) they assimilate a school scientific model to be able to explain buoyancy.
DOI: 10.6084/m9.figshare.30889660
title: Effectiveness of a school scientific model to address buoyancy in the training of prospective early childhood teachers

description: Buoyancy is a recurring topic in early childhood education and provides an opportunity to introduce scientific modelling. This study is framed within the need to improve the training of prospective early childhood teachers (PECT) in this scientific practice and examines the effectiveness of a teaching intervention that models the buoyancy of objects in water as balanced forces. The research analyses responses from a pre-test and post-test questionnaire administered before and after the intervention. A qualitative content analysis was used to categorise responses. In general, a positive progression was observed in the models used by the PECT to explain buoyancy as balanced forces. Most PECT correctly assimilated that the upthrust exerted by water is equivalent to the weight of the amount of water displaced by the object, and that this upthrust therefore depends on the volume of the portion of the object submerged. The conclusion is that, with interventions such as this, it is possible (1) to initiate the PECT in the practice of scientific modelling as part of their training to teach science at early childhood education, and that (2) they assimilate a school scientific model to be able to explain buoyancy.
DOI: 10.15468/dl.v6r8as
title: Occurrence Download

description: A dataset containing 505306 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)"
 ]
 }
 }
 ]
 },
 "DatasetKey is iNaturalist Research-grade Observations",
 "Country is United States of America",
 "Year is 2015"
 ]
}

 The dataset includes 505306 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054205-251120083545085/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.30889643
title: Plot data for manuscript: “Supersymmetric isophase acoustic potentials”

description: The data to plot figure 3 and 4 is given here.
DOI: 10.6084/m9.figshare.30889643.v1
title: Plot data for manuscript: “Supersymmetric isophase acoustic potentials”

description: The data to plot figure 3 and 4 is given here.
DOI: 10.15468/dl.ajx3fx
title: Occurrence Download

description: A dataset containing 879876 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)"
 ]
 }
 }
 ]
 },
 "DatasetKey is iNaturalist Research-grade Observations",
 "Country is United States of America",
 "Year is 2016"
 ]
}

 The dataset includes 879876 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054206-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25919/x662-2w82
title: NBIC-ACS Stage 2 Forest Fire Danger Index - baseline scenario, 20% and 10% annual exceedance probabilities

description: The McArthur Forest Fire Danger Index (FFDI) is a fire weather potential index that describes how current weather conditions and recent precipitation patterns could support a fire in forested areas. FFDI calculations are based on McArthur, A.G. (1967) and dependent on air temperature, relative humidity, wind speed. The metric was developed with the worst bushfire event at the time – Victoria 1939 – corresponding to a value of 100. Here we provide predicted upper-bound FFDI values across the Australian landscape, defined for a set of Annual Exceedance Probabilities. We calculate FFDI based on the latest Bureau of Meteorology historical weather reanalysis BARRA-R2, reporting modelled hourly weather conditions from 1979 to current at a spatial resolution of approximately 11 kilometres. More than 400,000 data points at every location are then processed using the National Bushfire Intelligence Capability (NBIC) Extreme Values Analysis to predict extreme daily maximums and their likelihood. FFDI was historically used to define bushfire hazard, including the official Fire Danger Rating issued by operational agencies. While its use in this context is no longer recommended, FFDI remains a widely recognised fire weather metric that is commonly understood and informs jurisdictional policies and building standards. All these characteristics result in datasets that are a significant advancement in defining extreme fire weather, surpassing previous approaches and offering a robust foundation for informed decision-making in managing and mitigating Australia’s growing bushfire risks in a changing climate.
DOI: 10.5281/zenodo.17934583
title: Data for "Realistic assessment of a single gravitational wave source localization taking into account precise pulsar distances with pulsar timing arrays"

description: This repository provides CSV files underlying the figures in the Physical Review D article

*"Realistic assessment of a single gravitational wave source localization taking into account precise pulsar distances with pulsar timing arrays"*.


The data contain sky-localization results of gravitational-wave sources obtained with pulsar timing arrays (PTAs) under different analysis settings.

These data are sufficient to reproduce all figures presented in the paper.
DOI: 10.5281/zenodo.17934582
title: Data for "Realistic assessment of a single gravitational wave source localization taking into account precise pulsar distances with pulsar timing arrays"

description: This repository provides CSV files underlying the figures in the Physical Review D article

*"Realistic assessment of a single gravitational wave source localization taking into account precise pulsar distances with pulsar timing arrays"*.


The data contain sky-localization results of gravitational-wave sources obtained with pulsar timing arrays (PTAs) under different analysis settings.

These data are sufficient to reproduce all figures presented in the paper.
DOI: 10.15468/dl.qmhjvh
title: Occurrence Download

description: A dataset containing 1211 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Chosenia arbutifolia"
 ]
}

 The dataset includes 1211 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054212-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17605/osf.io/g4v3w
title: Biomechanical Tradeoffs in Stroller Running: Reduced Vertical Impact Loading and Increased Torsional Injury Risk

description: This OSF project contains the figure-level dataset supporting: Mahoney JM, Lista A, Carbajal D, Infantolino BW, Altman-Singles AR (2025) Biomechanical tradeoffs in stroller running: Reduced vertical impact loading and increased torsional injury risk (PLOS ONE).

Participants (n = 38) completed overground running trials with and without a jogging stroller over a force plate. Primary outcomes include vertical and anterior-posterior ground reaction force metrics and free moment metrics. Resultant tibial acceleration is also included, with usable data for n = 36 participants.

The project currently includes a single Excel file, FP_data.xlsx, that contains the figure-level, paired within-subject data for Figures 1 through 5 in the paper. The workbook includes five worksheets (Fig1 to Fig5). Each worksheet is organized as paired columns for the two conditions (Control and Stroller), with one row per de-identified participant.

Analysis details align with the paper’s processing and statistics (MATLAB-based processing; bootstrapping resample size 10^6).
DOI: 10.15468/dl.s7d32d
title: Occurrence Download

description: A dataset containing 58 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mongolia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Leuzea repens"
 ]
}

 The dataset includes 58 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054213-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25919/ehjp-d886
title: NBIC-ACS Stage 2 Forest Fire Danger Index - baseline scenario, 5%, 2% and 1% annual exceedance probabilities

description: The McArthur Forest Fire Danger Index (FFDI) is a fire weather potential index that describes how current weather conditions and recent precipitation patterns could support a fire in forested areas. FFDI calculations are based on McArthur, A.G. (1967) and dependent on air temperature, relative humidity, wind speed. The metric was developed with the worst bushfire event at the time – Victoria 1939 – corresponding to a value of 100. Here we provide predicted upper-bound FFDI values across the Australian landscape, defined for a set of Annual Exceedance Probabilities. We calculate FFDI based on the latest Bureau of Meteorology historical weather reanalysis BARRA-R2, reporting modelled hourly weather conditions from 1979 to current at a spatial resolution of approximately 11 kilometres. More than 400,000 data points at every location are then processed using the National Bushfire Intelligence Capability (NBIC) Extreme Values Analysis to predict extreme daily maximums and their likelihood. FFDI was historically used to define bushfire hazard, including the official Fire Danger Rating issued by operational agencies. While its use in this context is no longer recommended, FFDI remains a widely recognised fire weather metric that is commonly understood and informs jurisdictional policies and building standards. All these characteristics result in datasets that are a significant advancement in defining extreme fire weather, surpassing previous approaches and offering a robust foundation for informed decision-making in managing and mitigating Australia’s growing bushfire risks in a changing climate.
DOI: 10.17605/osf.io/rn63v
title: Roughness giving you the runaround? Investigating the interplay of infiltration and resistance on vegetated hillslopes
DOI: 10.15468/dl.wc3tg4
title: Occurrence Download

description: A dataset containing 245 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Salix dunnii"
 ]
}

 The dataset includes 245 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054215-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qtjaaa
title: Occurrence Download

description: A dataset containing 356236 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Uruguay",
 "OccurrenceStatus is Present",
 "Year 2024-2025"
 ]
}

 The dataset includes 356236 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054198-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s98x42
title: Occurrence Download

description: A dataset containing 33202 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-77.22085 0.98694,-77.07425 0.98694,-77.07425 1.16188,-77.22085 1.16188,-77.22085 0.98694))",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 33202 records from 105 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054216-251120083545085/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.30889691.v1
title: in the USA and consistent global usability

description: makeup, hair care, and health items. It does not require loyalty membership, coupons stacking, or special eligibility
DOI: 10.15468/dl.6vynw4
title: Occurrence Download

description: A dataset containing 773691 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ulmus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is Human Observation"
 ]
}

 The dataset includes 773691 records from 2553 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054207-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qcgbjv
title: Occurrence Download

description: A dataset containing 65 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Country is Viet Nam",
 "Country is China",
 "Country is Lao People’s Democratic Republic"
 ]
 },
 "TaxonKey is Nomascus concolor (Harlan, 1826)"
 ]
}

 The dataset includes 65 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0142712-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8vln9s
title: Occurrence Download

description: A dataset containing 44 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cicer canariense A.Santos & G.P.Lewis",
 "Country is Spain"
 ]
}

 The dataset includes 44 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001531-150528172251762/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wwlfws
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Chionanthus retusus Lindl."
 ]
}

 The dataset includes 12 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001535-180412121330197/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.72r7xe
title: Occurrence Download

description: A dataset containing 376 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Connochaetes gnou (Zimmermann, 1780)"
 ]
}

 The dataset includes 376 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023042-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g6vkp6
title: Occurrence Download

description: A dataset containing 683 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tracheophyta",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "Country is Saint Helena, Ascension and Tristan da Cunha",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 683 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009665-200127171203522/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qxilxs
title: Occurrence Download

description: A dataset containing 1795 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pinus taeda L."
 ]
}

 The dataset includes 1795 records from 114 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001535-180824113759888/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kmqtrm
title: Occurrence Download

description: A dataset containing 60344 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "BasisOfRecord is Observation",
 "BasisOfRecord is Human Observation"
 ]
 },
 "Year 1980-2019",
 "HasCoordinate is true",
 "TaxonKey is Malva sylvestris L.",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 60344 records from 217 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023054-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.