cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17880564
title: ShortRangeRadar-60-SynReal

description: Synthetic 60 GHz FMCW radar dataset for short-range object detection. Contains simulated Range-Doppler maps of humans and fork lifters in indoor industrial scenarios. Data were generated using a physics-based simulation pipeline that combined Blender for scene modeling, WinProp for ray tracing, and Feko for electromagnetic simulation. Radar parameters: 60 GHz carrier frequency, 4 GHz bandwidth, 0.11 m range resolution, 28.1 m maximum range, 0.18 m/s Doppler resolution. Annotations are provided in YOLO format.

 

Measured 60 GHz FMCW radar dataset for short-range object detection. Contains Range-Doppler maps of humans and bicycles in outdoor scenarios, recorded with a commercial 60 GHz FMCW radar sensor. Radar parameters: 60 GHz carrier frequency, 4 GHz bandwidth, 0.136 m range resolution, 13.968 m maximum range, 0.510 m/s Doppler resolution. Annotations are provided in YOLO format.
DOI: 10.14473/csda/wvgqi8
title: Vnímání negativity

description: Cílem výzkumu bylo pomocí experimentu zjistit efekty různého typu negativní komunikace na vnímání násilí v kontextu politického stranictví a polarizace.
DOI: 10.15468/dl.dhes4s
title: Occurrence Download

description: A dataset containing 332 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pherecardia striata",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 332 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044882-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/lnaa5x
title: Replication Data for: The interplay of news media, social media, and public search behavior during the 2022–2023 South Korea drought

description: Code and Data used for "The interplay of news media, social media, and public search behavior during the 2022–2023 South Korea drought"

DOI: 10.1057/s41599-025-06398-z
DOI: 10.15468/dl.hpqype
title: Occurrence Download

description: A dataset containing 105 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((-74.958 -8.192913000000001, -75.02898399999999 -8.198472000000001, -75.098225 -8.215014, -75.16402600000001 -8.242133000000001, -75.224768 -8.279163, -75.278961 -8.325194, -75.32526900000001 -8.379097, -75.362554 -8.439546, -75.389892 -8.505056, -75.40660800000001 -8.574017, -75.412285 -8.644731, -75.40677599999999 -8.715458, -75.39021099999999 -8.784454999999999, -75.36299200000001 -8.850023999999999, -75.325784 -8.910546999999999, -75.27950199999999 -8.964530999999999, -75.225283 -9.010643999999999, -75.164464 -9.047746999999999, -75.098544 -9.074925, -75.029151 -9.091504, -74.958 -9.097077000000001, -74.886849 -9.091504, -74.81745600000001 -9.074925, -74.751536 -9.047746999999999, -74.69071700000001 -9.010643999999999, -74.636498 -8.964530999999999, -74.590216 -8.910546999999999, -74.55300800000001 -8.850023999999999, -74.525789 -8.784454999999999, -74.509224 -8.715458, -74.503715 -8.644731, -74.50939200000001 -8.574017, -74.52610799999999 -8.505056, -74.55344599999999 -8.439546, -74.59073100000001 -8.379097, -74.637039 -8.325194, -74.691232 -8.279163, -74.751974 -8.242133000000001, -74.817775 -8.215014, -74.887016 -8.198472000000001, -74.958 -8.192913000000001))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 105 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044883-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15131/shef.data.30849326
title: The Development of a Miniaturized Spectroscopic Reflectance System for Thin-Film Multilayer Thickness Measurements

description: The in-process inspection of multilayer thin-film thickness across the width of a substrate is a requirement in roll-to-roll (R2R) manufacturing. However, the current inspection systems present limitations related to the nature of the techniques, in addition to the low scalability, modularity, high cost and complexity of implementation on the manufacturing floor. This work introduces the in-house development of a dimension-reduced and modular, single-sensor reflectometer instrument, enabling precise measurement of individual layers within multi-layer coated samples. This work includes the development of a new hardware design integrating a microprocessor, a light source, a logic converter and a spectrometer sensor; additionally, a unique software platform was developed to perform near real-time multilayer coating thickness measurements. Seven electrodeposited samples were created for testing and validation purposes. The results of more than one hundred and thirty measurements per sample show that the thickness of an Indium Tin Oxide (ITO) layer ranged between 125.48 to 138.82 ± 2.87 nm, achieving less than 7% error compared to vendor specifications (specification: 130 nm). Additionally, the thickness measurements from the sensor revealed a linear response of the Poly(3,4-ethylenedioxythiophene):Poly sodium 4-styrene sulfonate (PEDOT:PSS) layer with increasing electrodeposition charge, resulting in thicknesses ranging from 201.47 to 506.03 ± 2.73 nm. The successful thickness single-point measurements lay the foundations for the development multi-sensor array to allow thickness measurements along the full width of coated substrates in R2R manufacturing.This repository contains the data set for the Table VI in the paper in the journal: IEEE - Transactions on Instrumentation and Measurement. <b>DOI:</b><b> </b>10.1109/TIM.2025.3638918
DOI: 10.15131/shef.data.30849326.v1
title: The Development of a Miniaturized Spectroscopic Reflectance System for Thin-Film Multilayer Thickness Measurements

description: The in-process inspection of multilayer thin-film thickness across the width of a substrate is a requirement in roll-to-roll (R2R) manufacturing. However, the current inspection systems present limitations related to the nature of the techniques, in addition to the low scalability, modularity, high cost and complexity of implementation on the manufacturing floor. This work introduces the in-house development of a dimension-reduced and modular, single-sensor reflectometer instrument, enabling precise measurement of individual layers within multi-layer coated samples. This work includes the development of a new hardware design integrating a microprocessor, a light source, a logic converter and a spectrometer sensor; additionally, a unique software platform was developed to perform near real-time multilayer coating thickness measurements. Seven electrodeposited samples were created for testing and validation purposes. The results of more than one hundred and thirty measurements per sample show that the thickness of an Indium Tin Oxide (ITO) layer ranged between 125.48 to 138.82 ± 2.87 nm, achieving less than 7% error compared to vendor specifications (specification: 130 nm). Additionally, the thickness measurements from the sensor revealed a linear response of the Poly(3,4-ethylenedioxythiophene):Poly sodium 4-styrene sulfonate (PEDOT:PSS) layer with increasing electrodeposition charge, resulting in thicknesses ranging from 201.47 to 506.03 ± 2.73 nm. The successful thickness single-point measurements lay the foundations for the development multi-sensor array to allow thickness measurements along the full width of coated substrates in R2R manufacturing.This repository contains the data set for the Table VI in the paper in the journal: IEEE - Transactions on Instrumentation and Measurement. <b>DOI:</b><b> </b>10.1109/TIM.2025.3638918
DOI: 10.15468/dl.gm3fxq
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Phyllodoce quadraticeps",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 5 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044884-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gc6pe6
title: Occurrence Download

description: A dataset containing 74 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((-74.926 -7.731902, -74.996904 -7.737462, -75.066068 -7.754006, -75.131794 -7.781127, -75.19246699999999 -7.818159, -75.246596 -7.864194, -75.292849 -7.9181, -75.33008700000001 -7.978553, -75.35739100000001 -8.044066000000001, -75.374083 -8.113028999999999, -75.37974800000001 -8.183745, -75.374241 -8.254473000000001, -75.357691 -8.323472000000001, -75.330501 -8.389041000000001, -75.293336 -8.449562999999999, -75.247108 -8.503546, -75.192953 -8.549658000000001, -75.13220800000001 -8.58676, -75.06636899999999 -8.613936000000001, -74.997062 -8.630515000000001, -74.926 -8.636088000000001, -74.854938 -8.630515000000001, -74.785631 -8.613936000000001, -74.719792 -8.58676, -74.659047 -8.549658000000001, -74.60489200000001 -8.503546, -74.55866399999999 -8.449562999999999, -74.52149900000001 -8.389041000000001, -74.494309 -8.323472000000001, -74.47775900000001 -8.254473000000001, -74.472252 -8.183745, -74.47791700000001 -8.113028999999999, -74.494609 -8.044066000000001, -74.521913 -7.978553, -74.559151 -7.9181, -74.60540399999999 -7.864194, -74.659533 -7.818159, -74.720206 -7.781127, -74.785932 -7.754006, -74.855096 -7.737462, -74.926 -7.731902))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 74 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044885-251120083545085/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.30842780
title: Data for "Heterochromatin-based silencing of a foreign tandem repeat in

description: datasets for "Heterochromatin-based silencing of a foreign tandem repeat in <i>Drosophila melanogaster </i>shows unusual biochemistry and temperature sensitivity"
DOI: 10.6084/m9.figshare.30842780.v1
title: Data for "Heterochromatin-based silencing of a foreign tandem repeat in

description: datasets for "Heterochromatin-based silencing of a foreign tandem repeat in <i>Drosophila melanogaster </i>shows unusual biochemistry and temperature sensitivity"
DOI: 10.5281/zenodo.17880418
title: The original G4Jy catalogue plus its updated 'multiwavelength' version

description: The original G4Jy catalogue -- G4Jy_catalogue_18012020.fits (White et al., 2020a, 2020b) -- contains comprehensive radio data (via the GLEAM Extragalatic Catalogue), as well as host-galaxy identifications (in AllWISE) for 86% of the G4Jy Sample. We provide an updated version of the catalogue -- G4Jy_catalogue_28072025.fits (White et al., 2025c, 2025d) -- that includes: 93% identification-completeness, 64% redshift-completeness, optical photometry (via DESI Legacy Surveys DR10), and near-infrared photometry (via 2MASS). The easiest way to combine information from both catalogues is to crossmatch on the radio-centroid positions (centroid_RAJ2000, centroid_DEJ2000).
DOI: 10.5281/zenodo.17880419
title: The original G4Jy catalogue plus its updated 'multiwavelength' version

description: The original G4Jy catalogue -- G4Jy_catalogue_18012020.fits (White et al., 2020a, 2020b) -- contains comprehensive radio data (via the GLEAM Extragalatic Catalogue), as well as host-galaxy identifications (in AllWISE) for 86% of the G4Jy Sample. We provide an updated version of the catalogue -- G4Jy_catalogue_28072025.fits (White et al., 2025c, 2025d) -- that includes: 93% identification-completeness, 64% redshift-completeness, optical photometry (via DESI Legacy Surveys DR10), and near-infrared photometry (via 2MASS). The easiest way to combine information from both catalogues is to crossmatch on the radio-centroid positions (centroid_RAJ2000, centroid_DEJ2000).
DOI: 10.5281/zenodo.17845382
title: A Dataset for the Medical Support Vehicle Location-Allocation Problem

description: In mass-casualty incidents, emergency responders require access to accurate and timely information to support informed decision-making and ensure the efficient allocation of resources. This dataset presents hypothetical scenarios involving multiple demand points and large numbers of victims, making it suitable for analysis using optimization techniques. It integrates voluntary collaborative geographic information, open government data sources, and historical records, and details the data collection, cleaning, and preprocessing stages. The accompanying Python 3 source code enables users to update the original data for consistent analysis and processing. Researchers can adapt this dataset to other cities with similar risk characteristics, such as Santiago (Chile), Los Angeles (USA), or Tokyo (Japan), and extend it to other types of catastrophic events, including floods, landslides, or epidemics, to support emergency response and resource allocation planning.

This repository contains eight structured Jupyter Notebooks located within the notebooks/ directory, designed for reproducible data analysis. The entire workflow must be executed sequentially by the user within the Google Colaboratory (Colab) platform. The process begins with the notebooks/PreProcessing.ipynb file, which handles the initial data preparation. The precise order of execution for all eight notebooks is detailed in the Materials and Methods section of the associated published article.
DOI: 10.5281/zenodo.17845383
title: A Dataset for the Medical Support Vehicle Location-Allocation Problem

description: In mass-casualty incidents, emergency responders require access to accurate and timely information to support informed decision-making and ensure the efficient allocation of resources. This dataset presents hypothetical scenarios involving multiple demand points and large numbers of victims, making it suitable for analysis using optimization techniques. It integrates voluntary collaborative geographic information, open government data sources, and historical records, and details the data collection, cleaning, and preprocessing stages. The accompanying Python 3 source code enables users to update the original data for consistent analysis and processing. Researchers can adapt this dataset to other cities with similar risk characteristics, such as Santiago (Chile), Los Angeles (USA), or Tokyo (Japan), and extend it to other types of catastrophic events, including floods, landslides, or epidemics, to support emergency response and resource allocation planning.

This repository contains eight structured Jupyter Notebooks located within the notebooks/ directory, designed for reproducible data analysis. The entire workflow must be executed sequentially by the user within the Google Colaboratory (Colab) platform. The process begins with the notebooks/PreProcessing.ipynb file, which handles the initial data preparation. The precise order of execution for all eight notebooks is detailed in the Materials and Methods section of the associated published article.
DOI: 10.15468/dl.3ddywj
title: Occurrence Download

description: A dataset containing 12383 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Spain",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Milvus milvus",
 "Year 1971-2010"
 ]
}

 The dataset includes 12383 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044886-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/da75us
title: Full transcript of class for "The dream of the six-legged dog"

description: This class contained the entire experiment on this dream. Interpreted knowing nothing of dreamer, and having none of dreamer's associations. Then tested interpretation against newly acquired information about the dreamer.
Also an abstract. Also link to YouTube audio-record of complete class.
All names deleted.
DOI: 10.15468/dl.r2t8xt
title: Occurrence Download

description: A dataset containing 1421 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Spain",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Aythya nyroca",
 "Year 1971-2010"
 ]
}

 The dataset includes 1421 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044887-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sprmyu
title: Occurrence Download

description: A dataset containing 5256 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Spain",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Oenanthe leucura",
 "Year 1971-2010"
 ]
}

 The dataset includes 5256 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044888-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p4hcnt
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Phyllodoce fristedti",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 19 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044889-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.byxumj
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((107.66 -7.14189, 107.58919 -7.147451, 107.520119 -7.163996, 107.454482 -7.19112, 107.393893 -7.228156, 107.339839 -7.274194, 107.293653 -7.328105, 107.25647 -7.388562, 107.22921 -7.454079, 107.212546 -7.523045, 107.206895 -7.593764, 107.2124 -7.664494, 107.228931 -7.733493, 107.256087 -7.799061, 107.293202 -7.859583, 107.339366 -7.913565, 107.393442 -7.959675, 107.454099 -7.996776, 107.519841 -8.023949999999999, 107.589044 -8.040528999999999, 107.66 -8.046101, 107.730956 -8.040528999999999, 107.800159 -8.023949999999999, 107.865901 -7.996776, 107.926558 -7.959675, 107.980634 -7.913565, 108.026798 -7.859583, 108.063913 -7.799061, 108.091069 -7.733493, 108.1076 -7.664494, 108.113105 -7.593764, 108.107454 -7.523045, 108.09079 -7.454079, 108.06353 -7.388562, 108.026347 -7.328105, 107.980161 -7.274194, 107.926107 -7.228156, 107.865518 -7.19112, 107.799881 -7.163996, 107.73081 -7.147451, 107.66 -7.14189))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 19 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044890-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11187300
title: 2025_Dengue_WNV_vector_Models_modeledsuitability_EU

description: Abstract:

Ensembled spatial models were produced for disease vectors  by combining Random Forest and Boosted Regression Trees spatial modelling outputs, implemented using the VECMAP modelling suite, using a standard set of covariates including Fourier Processed Remotely Sensed environmental variables, land use proportions, human population and elevation. The training data offered to the model process include point location and polygon data from the VectorNet project (https://www.ecdc.europa.eu/en/about-us/partnerships-and-networks/disease-and-laboratory-networks/vector-net), from the Global Biodiversity Information Facility (www.gbif.org) and a series of national databases.  Absence data assembled from absence records, complemented by points assigned to unsuitable areas defined by environmental and climatic thresholds obtained from experts or from the literature

 

These models are updates of the ones provided at:  https://zenodo.org/records/11187301 



Potential Dengue Vectors (Regional = Aedes albopictus, Aedes caspius).  Models provided as Mean, Minimum, Maximum and Standard Deviation. Aedes detritus provided only as MEAN, masked by the suitability layer. Values are the probability of presence. Filename e4DENGUEVECTORMODELSUPDATE2025.zip


 



Potential WNV vectors (Global=Culex pipiens, ). Model provided as Mean, Minimum, Maximum and Standard Deviation. Values are the probability of presence. Filename e4WNVVECTORMODELSUPDATE2025.zip
DOI: 10.5281/zenodo.17866441
title: 2025_Dengue_WNV_vector_Models_modeledsuitability_EU

description: Abstract:

Ensembled spatial models were produced for disease vectors  by combining Random Forest and Boosted Regression Trees spatial modelling outputs, implemented using the VECMAP modelling suite, using a standard set of covariates including Fourier Processed Remotely Sensed environmental variables, land use proportions, human population and elevation. The training data offered to the model process include point location and polygon data from the VectorNet project (https://www.ecdc.europa.eu/en/about-us/partnerships-and-networks/disease-and-laboratory-networks/vector-net), from the Global Biodiversity Information Facility (www.gbif.org) and a series of national databases.  Absence data assembled from absence records, complemented by points assigned to unsuitable areas defined by environmental and climatic thresholds obtained from experts or from the literature

 

These models are updates of the ones provided at:  https://zenodo.org/records/11187301 



Potential Dengue Vectors (Regional = Aedes albopictus, Aedes caspius).  Models provided as Mean, Minimum, Maximum and Standard Deviation. Aedes detritus provided only as MEAN, masked by the suitability layer. Values are the probability of presence. Filename e4DENGUEVECTORMODELSUPDATE2025.zip


 



Potential WNV vectors (Global=Culex pipiens, ). Model provided as Mean, Minimum, Maximum and Standard Deviation. Values are the probability of presence. Filename e4WNVVECTORMODELSUPDATE2025.zip