cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14173437
title: Data for "Exploring the Monthly Contribution of Drivers on European Summer Wildfires with Explainable Artificial Intelligence (XAI)"

description: Abstract



We applied an XAI method to analyze the monthly contribution of wildfire drivers on summer fires in European forest, shrub and herbaceous vegetation areas from 2014 to 2023. Using burn area data and 18 features including meteorology, vegetation, topography, and anthropogenic activity, we developed a reliable wildfire occurrence model using the LSTM method.


Methods



The fire point data is provided by the European Forest Fire Information System (EFFIS). A total of 18 features were selected for modeling. Among these features, the four meteorological variables (Prep, LST, SM, and SR), along with the corresponding four condition indexes (RCI, TCI, SMCI, SRCI) derived from them, the Wind Speed (WS), and the two vegetation variables (Normalized Difference Vegetation Index (NDVI) and Leaf Area Index (LAI)), were used as monthly time series. The Lightning Frequency dataset is monthly but represents an average of data from 2012 to 2021, remaining constant across different years. The remaining six feature datasets do not vary over time. Data download and analysis were conducted using Google Earth Engine, QGIS, and Python.


Subject keywords

Deep learning, Europe, Earth and related environmental sciences, vegetation, wildfire

Description of the data and file structure



train_data_no_2023.npy and train_Y_data_no_2023.npy: These contain the features and labels for the training set (excluding data from 2023).

TEST_X_2023.npy and TEST_Y_2023.npy: These represent the features and labels for the test set, specifically for the year 2023.

model.h5: This is the final trained model.

shap_values_train_data.npy: This file contains the SHAP values for the training set, used to explain model predictions.


The order of features:

Label = ['Prep', 'LST', 'SM', 'SR', 'RCI', 'TCI', 'SMCI', 'SRCI', 'WS', 'NDVI', 'LAI', 'LF', 'CH', 'Elevation', 'Slope', 'Aspect', 'DR', 'DS']
DOI: 10.5281/zenodo.14173438
title: Data for "Exploring the Monthly Contribution of Drivers on European Summer Wildfires with Explainable Artificial Intelligence (XAI)"

description: Abstract



We applied an XAI method to analyze the monthly contribution of wildfire drivers on summer fires in European forest, shrub and herbaceous vegetation areas from 2014 to 2023. Using burn area data and 18 features including meteorology, vegetation, topography, and anthropogenic activity, we developed a reliable wildfire occurrence model using the LSTM method.


Methods



The fire point data is provided by the European Forest Fire Information System (EFFIS). A total of 18 features were selected for modeling. Among these features, the four meteorological variables (Prep, LST, SM, and SR), along with the corresponding four condition indexes (RCI, TCI, SMCI, SRCI) derived from them, the Wind Speed (WS), and the two vegetation variables (Normalized Difference Vegetation Index (NDVI) and Leaf Area Index (LAI)), were used as monthly time series. The Lightning Frequency dataset is monthly but represents an average of data from 2012 to 2021, remaining constant across different years. The remaining six feature datasets do not vary over time. Data download and analysis were conducted using Google Earth Engine, QGIS, and Python.


Subject keywords

Deep learning, Europe, Earth and related environmental sciences, vegetation, wildfire

Description of the data and file structure



train_data_no_2023.npy and train_Y_data_no_2023.npy: These contain the features and labels for the training set (excluding data from 2023).

TEST_X_2023.npy and TEST_Y_2023.npy: These represent the features and labels for the test set, specifically for the year 2023.

model.h5: This is the final trained model.

shap_values_train_data.npy: This file contains the SHAP values for the training set, used to explain model predictions.


The order of features:

Label = ['Prep', 'LST', 'SM', 'SR', 'RCI', 'TCI', 'SMCI', 'SRCI', 'WS', 'NDVI', 'LAI', 'LF', 'CH', 'Elevation', 'Slope', 'Aspect', 'DR', 'DS']
DOI: 10.15468/dl.y6ekrr
title: Occurrence Download

description: A dataset containing 4656 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Medusozoans from the Iberian Peninsula and related archipelagos"
 ]
}

 The dataset includes 4656 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017687-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6e6b25
title: Occurrence Download

description: A dataset containing 1785 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Material sample, Human Observation, Material citation, Specimen, Living Specimen, Occurrence evidence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Bactrocera minax (Enderlein, 1920)"
 ]
}

 The dataset includes 1785 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017688-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6fmkyx
title: Occurrence Download

description: A dataset containing 423 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is one of (Asia, North America)",
 "Country is one of (China, Mongolia, Kazakhstan, United States of America, Pakistan, Tajikistan)",
 "GbifRegion is one of (Asia, North America)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is one of (Geodetic datum assumed WGS84, Coordinate rounded, Continent derived from coordinates)",
 "TaxonKey is Ephedra przewalskii Stapf",
 "Year 1000-2024"
 ]
}

 The dataset includes 423 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017690-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d7wtcz
title: Occurrence Download

description: A dataset containing 925 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-36.44287 6.78680,69.44287 6.78680,69.44287 49.21320,-36.44287 49.21320,-36.44287 6.78680))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Sclerophrys mauritanica (Schlegel, 1841)"
 ]
}

 The dataset includes 925 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017691-241107131044228/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/9925079
title: Mahanagar Yatayat Transport Dataset
DOI: 10.15468/dl.wbw9mg
title: Occurrence Download

description: A dataset listing the 8965 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is CSIC-Real Jardín Botánico-Anthos. Sistema de Información de las Plantas de España"
 ]
}

 The dataset's 8965 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017689-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14173448
title: PROVIDING KNOWLEDGE ABOUT SYLLABLES IN THE MOTHER TONGUE TEXTBOOK FOR CLASS 2
DOI: 10.5281/zenodo.14173449
title: PROVIDING KNOWLEDGE ABOUT SYLLABLES IN THE MOTHER TONGUE TEXTBOOK FOR CLASS 2
DOI: 10.15468/dl.mdnn9u
title: Occurrence Download

description: A dataset listing the 507 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is Medusozoans from the Iberian Peninsula and related archipelagos"
 ]
}

 The dataset's 507 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017692-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nzvjxn
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-18.68811 29.51543,8.68811 29.51543,8.68811 40.48457,-18.68811 40.48457,-18.68811 29.51543))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Alytes maurus Pasteur & Bons, 1962"
 ]
}

 The dataset includes 16 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017697-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12580540
title: Predicting Intrinsic and Extraneous Cognitive Load with Oculo- and Bio-metric Indicators

description: This study focused on the prediction of intrinsic and extraneous cognitive load using eye-tracking metrics, heart rate variability, and galvanic skin response. Intrinsic cognitive load is associated with the inherent complexity of the mental task, whereas extraneous cognitive load is related to the distracting and unrelated elements in the task. Thirty-three participants (aged 21.24 ± 3.51) performed different levels of mental calculations to induce intrinsic cognitive load in the first task and a visual search task to manipulate extraneous cognitive load in the second task. During both tasks, participants’ eye movements, heart rate, and galvanic skin response were continuously recorded. Participants’ working memory was controlled. Subjective cognitive load was also assessed following each experimental task. A discriminant model, consisting of oculo- and bio-metric indicators, could discriminate between cognitive loads (intrinsic vs. extraneous) and levels (low vs. high). In particular, average fixation duration, average saccade amplitude, and K coefficient each have an impact on the model. In addition, task difficulty may be distinguished by the Low-High Index of Pupillary Activity (LHIPA) and heart rate variability.
DOI: 10.5281/zenodo.12580541
title: Predicting Intrinsic and Extraneous Cognitive Load with Oculo- and Bio-metric Indicators

description: This study focused on the prediction of cognitive load types using eye-tracking metrics, heart rate variability, and galvanic skin response using a machine learning model. Intrinsic cognitive load is associated with the inherent complexity of the mental task, whereas extraneous cognitive load is related to the distracting and unrelated elements in the task. Thirty-four participants (aged 21.18 ± 3.42) performed different levels of mental calculations to induce intrinsic cognitive load in the first task and a visual search task to manipulate extraneous cognitive load in the second task. During both tasks, participants’ eye movements, heart rate, and galvanic skin response were continuously recorded. The subjective cognitive load was also assessed following each experimental task. Participants’ working memory was controlled. The discriminant model, which consisted of ocular- and bio-metric indicators, demonstrated that these indicators have a high level of discriminant power to separate low and high cognitive load in mental calculations and visual search. In particular, the average fixation duration, average saccade amplitude, and K coefficient have a greater impact on the model. In addition, the trial difficulty of the tasks may be separated by low and high index of pupillary activity and heart rate variability.
DOI: 10.5281/zenodo.14173461
title: Predicting Intrinsic and Extraneous Cognitive Load with Oculo- and Bio-metric Indicators

description: This study focused on the prediction of intrinsic and extraneous cognitive load using eye-tracking metrics, heart rate variability, and galvanic skin response. Intrinsic cognitive load is associated with the inherent complexity of the mental task, whereas extraneous cognitive load is related to the distracting and unrelated elements in the task. Thirty-three participants (aged 21.24 ± 3.51) performed different levels of mental calculations to induce intrinsic cognitive load in the first task and a visual search task to manipulate extraneous cognitive load in the second task. During both tasks, participants’ eye movements, heart rate, and galvanic skin response were continuously recorded. Participants’ working memory was controlled. Subjective cognitive load was also assessed following each experimental task. A discriminant model, consisting of oculo- and bio-metric indicators, could discriminate between cognitive loads (intrinsic vs. extraneous) and levels (low vs. high). In particular, average fixation duration, average saccade amplitude, and K coefficient each have an impact on the model. In addition, task difficulty may be distinguished by the Low-High Index of Pupillary Activity (LHIPA) and heart rate variability.
DOI: 10.15468/dl.rmdey6
title: Occurrence Download

description: A dataset containing 36323 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Biowide Species data"
 ]
}

 The dataset includes 36323 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017698-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4wgmkr
title: Occurrence Download

description: A dataset containing 305 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Odonata of a heath (kerangas) dominated mosaic forest in Central Kalimantan, Indonesia"
 ]
}

 The dataset includes 305 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017700-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ngv3d6
title: Occurrence Download

description: A dataset containing 108860 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Myiopsitta monachus (Boddaert, 1783)",
 "Country is Spain",
 "Year is greater than or equal to 1500"
 ]
}

 The dataset includes 108860 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017695-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jxk7hr
title: Occurrence Download

description: A dataset listing the 4546 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is Azorean Biodiversity Portal"
 ]
}

 The dataset's 4546 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017694-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cdvb87
title: Occurrence Download

description: A dataset containing 2118887 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CoordinateUncertaintyInMeters 0.0-500.0",
 "Country is Italy",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2118887 records from 248 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017696-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14173469
title: ЗАКОНОДАТЕЛЬНАЯ БАЗА ГАРМОНИЗАЦИИ МЕЖНАЦИОНАЛЬНЫХ ОТНОШЕНИЙ В УЗБЕКИСТАНЕ
DOI: 10.5281/zenodo.14173470
title: ЗАКОНОДАТЕЛЬНАЯ БАЗА ГАРМОНИЗАЦИИ МЕЖНАЦИОНАЛЬНЫХ ОТНОШЕНИЙ В УЗБЕКИСТАНЕ
DOI: 10.15468/dl.nbkx8q
title: Occurrence Download

description: A dataset containing 283 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rubroboletus dupainii (Boud.) Kuan Zhao & Zhu L.Yang"
 ]
}

 The dataset includes 283 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017704-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14173473
title: ХОРИЖИЙ МАМЛАКАТЛАРДА ЖАЗОНИ ИЖРО ЭТИШ ТИЗИМИ ВА МАЪМУРИЙ-ҲУҚУҚИЙ МАҚОМИ ТАҲЛИЛИ
DOI: 10.5281/zenodo.14173474
title: ХОРИЖИЙ МАМЛАКАТЛАРДА ЖАЗОНИ ИЖРО ЭТИШ ТИЗИМИ ВА МАЪМУРИЙ-ҲУҚУҚИЙ МАҚОМИ ТАҲЛИЛИ
DOI: 10.15468/dl.jywn3y
title: Occurrence Download

description: A dataset containing 50980887 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is Norway"
 ]
}

 The dataset includes 50980887 records from 1900 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017701-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gpgv6v
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Insecta)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((-180 7.5,-172.5 7.5,-172.5 15,-180 15,-180 7.5))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042245-251009101135966/datasets/export for details.
DOI: 10.13140/rg.2.2.22324.58244
title: Infectious Diseases 21-04-30
DOI: 10.5517/ccq65xz
title: CCDC 661351: Experimental Crystal Structure Determination

description: Related Article: T.E.Kokina, E.A.Sankova, R.F.Klevtsova, L.A.Glinskaya, S.V.Larionov|2008|Koord.Khim.|34|817|doi:10.1134/S1070328408110043
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: 10.5517/ccq65y0
title: CCDC 661352: Experimental Crystal Structure Determination

description: Related Article: T.E.Kokina, E.A.Sankova, R.F.Klevtsova, L.A.Glinskaya, S.V.Larionov|2008|Koord.Khim.|34|817|doi:10.1134/S1070328408110043
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: 10.5517/cct62vx
title: CCDC 750629: Experimental Crystal Structure Determination

description: Related Article: J.Y.Lee, J.-E.Lee, W.Sim, K.-M.Park|2009|Acta Crystallogr.,Sect.E:Struct.Rep.Online|65|o2369|doi:10.1107/S1600536809035399
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: 10.5517/cct62wy
title: CCDC 750630: Experimental Crystal Structure Determination

description: Related Article: Wei Zhou, Shijie Zhang, Weixiao Hu|2009|Acta Crystallogr.,Sect.E:Struct.Rep.Online|65|o2371|doi:10.1107/S1600536809035120
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: 10.5517/cct62xz
title: CCDC 750631: Experimental Crystal Structure Determination

description: Related Article: Jiong Jia, Yan-qing Ge, Gui-long Zhao, Jian-wu Wang|2009|Acta Crystallogr.,Sect.E:Struct.Rep.Online|65|o2372|doi:10.1107/S1600536809035314
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: 10.5517/cct62y0
title: CCDC 750632: Experimental Crystal Structure Determination

description: Related Article: Yi Zhang|2009|Acta Crystallogr.,Sect.E:Struct.Rep.Online|65|o2373|doi:10.1107/S1600536809032863
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: 10.5517/cct62z1
title: CCDC 750633: Experimental Crystal Structure Determination

description: Related Article: J.E.Hoffman, H.Cheng, A.L.Rheingold, A.DiPasquale, A.Yanovsky|2009|Acta Crystallogr.,Sect.E:Struct.Rep.Online|65|o2374|doi:10.1107/S1600536809035533
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: 10.5517/cct6303
title: CCDC 750634: Experimental Crystal Structure Determination

description: Related Article: J.Schlosser, D.Schollmeyer, S.Laufer, C.Peifer|2009|Acta Crystallogr.,Sect.E:Struct.Rep.Online|65|o2375|doi:10.1107/S1600536809034515
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: 10.5517/cct6314
title: CCDC 750635: Experimental Crystal Structure Determination

description: Related Article: Li-Jing Cui, Hai-Jun Xu|2009|Acta Crystallogr.,Sect.E:Struct.Rep.Online|65|o2376|doi:10.1107/S1600536809034497
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: 10.5517/cct6325
title: CCDC 750636: Experimental Crystal Structure Determination

description: Related Article: Min Min Zhao|2009|Acta Crystallogr.,Sect.E:Struct.Rep.Online|65|o2378|doi:10.1107/S1600536809035429
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.