cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15545604
title: Dataset employed in "Operational Modal Analysis from multi-setup measurements with roving references and Stochastic Subspace Identification"

description: This repository contains the dataset used in the scientific article "Operational Modal Analysis from multi-setup measurements with roving references and Stochastic Subspace Identification" by Samuel González-Jiménez, Luis A. Padrón, Guillermo M. Álamo and Jacob D. R. Bordón

These files were used in the paper above to validate the presented methodology with synthetically generated data and experimental meassurements of an elevated pedestrian crossing over a highway. 

The synthetically generated data is obtained from the execution of the file "Gen_num_data.m" which uses the functions "SSI_VB.m" and "add_noise.m", all compressed in the file "Code_for_generating_synthetic_data.zip" . Both functions use the "wgn" function from the Matlab Communications Toolbox.

The experimental measurements acquired from the elevated pedestrian crossing are compiled within the archive titled "Experimental_data_Elevated_pedestrian_crossing.zip." This compressed file contains seven .dat files, each designated by a filename that denotes the corresponding measurement locations. Each .dat file is formatted with two columns, corresponding to the sequential measurement values order at the positions indicated in the filename. These measurements have been recorded with two Tromino® Blu devices used as velocimeters, with a chosen dynamic range of ±0.5mm/s.
DOI: 10.5281/zenodo.15545605
title: Dataset employed in "Operational Modal Analysis from multi-setup measurements with roving references and Stochastic Subspace Identification"

description: This repository contains the dataset used in the scientific article "Operational Modal Analysis from multi-setup measurements with roving references and Stochastic Subspace Identification" by Samuel González-Jiménez, Luis A. Padrón, Guillermo M. Álamo and Jacob D. R. Bordón

These files were used in the paper above to validate the presented methodology with synthetically generated data and experimental meassurements of an elevated pedestrian crossing over a highway. 

The synthetically generated data is obtained from the execution of the file "Gen_num_data.m" which uses the functions "SSI_VB.m" and "add_noise.m", all compressed in the file "Code_for_generating_synthetic_data.zip" . Both functions use the "wgn" function from the Matlab Communications Toolbox.

The experimental measurements acquired from the elevated pedestrian crossing are compiled within the archive titled "Experimental_data_Elevated_pedestrian_crossing.zip." This compressed file contains seven .dat files, each designated by a filename that denotes the corresponding measurement locations. Each .dat file is formatted with two columns, corresponding to the sequential measurement values order at the positions indicated in the filename. These measurements have been recorded with two Tromino® Blu devices used as velocimeters, with a chosen dynamic range of ±0.5mm/s.
DOI: 10.6084/m9.figshare.28816238
title: DATASET: Raman microscopy of high-density polyethylene: rapid mapping of crystallinity domains at the μm spatial resolution

description: Raw data files in support of the key figures in the main manuscript (raw spectral files in Renishaw WiRE format and .txt format).
DOI: 10.6084/m9.figshare.28816238.v2
title: DATASET: Raman microscopy of high-density polyethylene: rapid mapping of crystallinity domains at the μm spatial resolution

description: Raw data files in support of the key figures in the main manuscript (raw spectral files in Renishaw WiRE format and .txt format).
DOI: 10.6084/m9.figshare.28816238.v1
title: DATASET: Raman microscopy of high-density polyethylene: rapid mapping of crystallinity domains at the μm spatial resolution

description: Raw data files in support of the main manuscript (Including raw spectral files in Renishaw WiRE format).
DOI: 10.5281/zenodo.14587214
title: Hourly streamflow events and their characteristics

description: This is the dataset of streamflow events and their characteristics identified from hourly time series of 199 German catchments analyzed in the study by Aala et al. "Exploring Controls on Rainfall-Runoff Events: 3. The Effects of Space-Time Dynamics of Precipitation on the Shape and Timing of Event Hydrographs" (submitted to Water Resources Research)
DOI: 10.15468/dl.cs97mz
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Xenodermichthys copei (Gill, 1884)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((45.5755 -13.3048,45.7911 -12.8231,45.6061 -12.3752,45.0241 -12.1382,44.9648 -12.0572,44.9648 -13.45,45.02 -13.4845,45.5755 -13.3048))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010557-250525065834625/datasets/export for details.
DOI: 10.15468/dl.w75vny
title: Occurrence Download

description: A dataset containing 9902 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Chrysomelidae"
 ]
}

 The dataset includes 9902 records from 151 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014701-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15572219
title: LeafMachine2 Data: Juglandaceae Leaf Outlines and ECT

description: Juglandaceae - 517,187 leaves - 67.4 GB: This repository contains HDF5 (.h5) files with leaf morphological data for species in the Juglandaceae family. Each file represents a single leaf specimen and contains leaf shape outlines, the 128x128 ECT matrix, and associated metadata.

File Contents

This dataset contains 517,187 leaves from taxa in the family Juglandaceae. Some leaves may be partial, predated, broken, or incomplete. Each .h5 file contains the following datasets:



ECT_matrices/ - Euler Characteristic Transform (ECT) matrices capturing topological features of leaf shapes

shapes/shape_0 - Coordinate array (x,y) defining the leaf outline boundary

component_names - Original filename identifier (without extension)

group_labels - Taxonomic classification dictionary containing:



family: Taxonomic family name

genus: Genus classification

genus_species: Binomial species name

fullname: Complete taxonomic identifier




Data Format

Files are organized with standardized naming: [Herbarium]_[ID]_[Family]_[Genus]_[Species]__[LeafID].h5 Shape coordinates are normalized to a unit circle centered at the origin (-0.5 to 0.5 range), vertically oriented.

Uncompressed Size

67.4 GB

Usage

Code for reading, processing, and analyzing these files is available at: https://github.com/Gene-Weaver/LM2-Data-Tools The repository includes functions for extracting data and generating visualizations.

Citation

Please cite the LeafMachine2 paper and this dataset.

Weaver, W. N., & Smith, S. A. (2023). From leaves to labels: Building modular machine learning networks for rapid herbarium specimen analysis with LeafMachine2. Applications in Plant Sciences, 11(5), e11548. https://doi.org/10.1002/aps3.11548
DOI: 10.5281/zenodo.15572220
title: LeafMachine2 Data: Juglandaceae Leaf Outlines and ECT

description: Juglandaceae - 517,187 leaves - 67.4 GB: This repository contains HDF5 (.h5) files with leaf morphological data for species in the Juglandaceae family. Each file represents a single leaf specimen and contains leaf shape outlines, the 128x128 ECT matrix, and associated metadata.

File Contents

This dataset contains 517,187 leaves from taxa in the family Juglandaceae. Some leaves may be partial, predated, broken, or incomplete. Each .h5 file contains the following datasets:



ECT_matrices/ - Euler Characteristic Transform (ECT) matrices capturing topological features of leaf shapes

shapes/shape_0 - Coordinate array (x,y) defining the leaf outline boundary

component_names - Original filename identifier (without extension)

group_labels - Taxonomic classification dictionary containing:



family: Taxonomic family name

genus: Genus classification

genus_species: Binomial species name

fullname: Complete taxonomic identifier




Data Format

Files are organized with standardized naming: [Herbarium]_[ID]_[Family]_[Genus]_[Species]__[LeafID].h5 Shape coordinates are normalized to a unit circle centered at the origin (-0.5 to 0.5 range), vertically oriented.

Uncompressed Size

67.4 GB

Usage

Code for reading, processing, and analyzing these files is available at: https://github.com/Gene-Weaver/LM2-Data-Tools The repository includes functions for extracting data and generating visualizations.

Citation

Please cite the LeafMachine2 paper and this dataset.

Weaver, W. N., & Smith, S. A. (2023). From leaves to labels: Building modular machine learning networks for rapid herbarium specimen analysis with LeafMachine2. Applications in Plant Sciences, 11(5), e11548. https://doi.org/10.1002/aps3.11548
DOI: 10.15468/dl.ybzr86
title: Occurrence Download

description: A dataset containing 585966 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Chloroflexota"
 ]
}

 The dataset includes 585966 records from 623 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018316-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v5vpz6
title: Occurrence Download

description: A dataset containing 282 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Calidris subruficollis (Vieillot, 1819))",
 "Country is one of (Afghanistan, Armenia, Azerbaijan, Bahrain, Bangladesh, Bhutan, Brunei Darussalam, Cambodia, China, Cyprus, Georgia, Hong Kong, India, Indonesia, Iran (Islamic Republic of), Iraq, Israel, Japan, Jordan, Kazakhstan, Korea (Democratic People’s Republic of), Korea, Republic of, Kuwait, Kyrgyzstan, Lao People’s Democratic Republic, Lebanon, Macao, Malaysia, Maldives, Mongolia, Myanmar, Nepal, Oman, Pakistan, Palestine, State of, Philippines, Qatar, Saudi Arabia, Singapore, Sri Lanka, Syrian Arab Republic, Tajikistan, Thailand, Timor-Leste, Türkiye, Turkmenistan, United Arab Emirates, Uzbekistan, Viet Nam, Yemen)"
 ]
}

 The dataset includes 282 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018323-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tspjcf
title: Occurrence Download

description: A dataset containing 6740 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Calidris subruficollis (Vieillot, 1819))",
 "Country is one of (Anguilla, Antigua and Barbuda, Argentina, Aruba, Bahamas, Barbados, Belize, Bolivia (Plurinational State of), Bonaire, Sint Eustatius and Saba, Bouvet Island, Brazil, Cayman Islands, Chile, Colombia, Costa Rica, Cuba, Curaçao, Dominica, Dominican Republic, Ecuador, El Salvador, Falkland Islands (Malvinas), French Guiana, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Montserrat, Nicaragua, Panama, Paraguay, Peru, Puerto Rico, Saint Barthélemy, Saint Kitts and Nevis, Saint Lucia, Saint Martin (French part), Saint Vincent and the Grenadines, Sint Maarten (Dutch part), South Georgia and the South Sandwich Islands, Suriname, Trinidad and Tobago, Turks and Caicos Islands, Uruguay, Venezuela (Bolivarian Republic of), Virgin Islands (British), Virgin Islands (U.S.))"
 ]
}

 The dataset includes 6740 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018324-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.punuqu
title: Occurrence Download

description: A dataset containing 79201 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Brazil",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "TaxonKey is Bryophyta"
 ]
}

 The dataset includes 79201 records from 171 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018320-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xvbv2c
title: Occurrence Download

description: A dataset containing 826 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Calidris subruficollis (Vieillot, 1819))",
 "Country is one of (American Samoa, Australia, Christmas Island, Cocos (Keeling) Islands, Cook Islands, Fiji, French Polynesia, Guam, Heard Island and McDonald Islands, Kiribati, Marshall Islands, Micronesia (Federated States of), Nauru, New Caledonia, New Zealand, Niue, Norfolk Island, Northern Mariana Islands, Palau, Papua New Guinea, Pitcairn, Samoa, Solomon Islands, Tokelau, Tonga, Tuvalu, United States Minor Outlying Islands, Vanuatu, Wallis and Futuna)"
 ]
}

 The dataset includes 826 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018327-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pan7w2
title: Occurrence Download

description: A dataset containing 920005 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "Country is Mexico",
 "Geometry POLYGON((-105.28296 18.05095,-102.74903 18.05095,-102.6564 18.05095,-102.6564 20.00307,-105.28296 20.00307,-105.28296 18.05095))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 920005 records from 831 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018317-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.25tf65
title: Occurrence Download

description: A dataset containing 1626 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Base de datos de los pastos marinos mexicanos."
 ]
}

 The dataset includes 1626 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021500-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hybvde
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tinca tinca (Linnaeus, 1758)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((20.7576 -24.3688,20.529 -24.0715,20.509 -24.0715,20.509 -28.5786,25.5395 -28.5786,25.5395 -24.0715,25.1306 -24.0715,24.9333 -24.4571,23.8962 -24.2467,22.8065 -24.295,22.3719 -24.7207,22.2323 -25.547,22.0387 -25.7188,21.7833 -25.7784,21.5388 -25.7113,21.3553 -25.5415,20.7576 -24.3688))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021880-250525065834625/datasets/export for details.
DOI: 10.17632/3gyrjdgk4y
title: Bacteriophage Therapy Perceptions and Attitudes Towards Therapy
DOI: 10.17632/3gyrjdgk4y.1
title: Bacteriophage Therapy Perceptions and Attitudes Towards Therapy
DOI: 10.17632/3j9kxx6jwc.1
title: Dataset for developing tourist chatbot in the Hill Track Areas of Bangladesh

description: This dataset presents travel duration, season, lodging, well-liked tourist destinations, cuisine, dining options, and details of cultural events in the hill track regions of Bangladesh. The major purpose of the dataset is to develop a tourist chatbot in the hilly visiting places of Bangladesh. Four hill tract regions in Bangladesh—Khagrachhari, Rangamati, Bandarban, and Sylhet—are included in this dataset. Data was gathered from sources such as travelagency.com, community-based travel websites, online and offline surveys with different people, Google Maps, and more. This dataset includes 502 records of hill tract regions from 502 unique users, with 130 records for Khagrachhari, 141 records for Rangamati, 103 records for Bandarban, and 128 records for Sylhet. There were 15 variables (features) considered for the whole 502 data. These features include user ID, district, vehicle, travel time, time to reach destination, season, tourist spots, similar spots, resorts/hotels, restaurants, traditional food, indigenous group, traditional dress/attire, traditional dress shop, and minimum cost (per day).
DOI: 10.17632/3j9kxx6jwc.2
title: Dataset for Developing Tourist Chatbot in the Hill Track Areas of Bangladesh

description: This dataset presents travel duration, season, lodging, well-liked tourist destinations, cuisine, dining options, and details of cultural events in the hill track regions of Bangladesh. The major purpose of the dataset is to develop a tourist chatbot in the hilly visiting places of Bangladesh. Four hill tract regions in Bangladesh—Khagrachhari, Rangamati, Bandarban, and Sylhet—are included in this dataset. Data was gathered from sources such as travelagency.com, community-based travel websites, online and offline surveys with different people, Google Maps, and more. This dataset includes 502 records of hill tract regions from 502 unique users, with 130 records for Khagrachhari, 141 records for Rangamati, 103 records for Bandarban, and 128 records for Sylhet. There were 15 variables (features) considered for the whole 502 data. These features include user ID, district, vehicle, travel time, time to reach destination, season, tourist spots, similar spots, resorts/hotels, restaurants, traditional food, indigenous group, traditional dress/attire, traditional dress shop, and minimum cost (per day).
DOI: 10.17632/3j9kxx6jwc
title: Dataset for Developing Tourist Chatbot in the Hill Track Areas of Bangladesh

description: This dataset presents travel duration, season, lodging, well-liked tourist destinations, cuisine, dining options, and details of cultural events in the hill track regions of Bangladesh. The major purpose of the dataset is to develop a tourist chatbot in the hilly visiting places of Bangladesh. Four hill tract regions in Bangladesh—Khagrachhari, Rangamati, Bandarban, and Sylhet—are included in this dataset. Data was gathered from sources such as travelagency.com, community-based travel websites, online and offline surveys with different people, Google Maps, and more. This dataset includes 502 records of hill tract regions from 502 unique users, with 130 records for Khagrachhari, 141 records for Rangamati, 103 records for Bandarban, and 128 records for Sylhet. There were 15 variables (features) considered for the whole 502 data. These features include user ID, district, vehicle, travel time, time to reach destination, season, tourist spots, similar spots, resorts/hotels, restaurants, traditional food, indigenous group, traditional dress/attire, traditional dress shop, and minimum cost (per day).
DOI: 10.17632/3j9kxx6jwc.3
title: Dataset for Developing Tourist Chatbot in the Hill Track Areas of Bangladesh

description: This dataset presents travel duration, season, lodging, well-liked tourist destinations, cuisine, dining options, and details of cultural events in the hill track regions of Bangladesh. The major purpose of the dataset is to develop a tourist chatbot in the hilly visiting places of Bangladesh. Four hill tract regions in Bangladesh—Khagrachhari, Rangamati, Bandarban, and Sylhet—are included in this dataset. Data was gathered from sources such as travelagency.com, community-based travel websites, online and offline surveys with different people, Google Maps, and more. This dataset includes 502 records of hill tract regions from 502 unique users, with 130 records for Khagrachhari, 141 records for Rangamati, 103 records for Bandarban, and 128 records for Sylhet. There were 15 variables (features) considered for the whole 502 data. These features include user ID, district, vehicle, travel time, time to reach destination, season, tourist spots, similar spots, resorts/hotels, restaurants, traditional food, indigenous group, traditional dress/attire, traditional dress shop, and minimum cost (per day).
DOI: 10.15468/dl.6swzh7
title: Occurrence Download

description: A dataset containing 95 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 "year",
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 occurrence.countrycode = 'CN'
 AND (occurrence.taxonkey = 5389402 OR occurrence.acceptedtaxonkey = 5389402 OR occurrence.kingdomkey = 5389402 OR occurrence.phylumkey = 5389402 OR occurrence.classkey = 5389402 OR occurrence.orderkey = 5389402 OR occurrence.familykey = 5389402 OR occurrence.genuskey = 5389402 OR occurrence.specieskey = 5389402)
 AND occurrence.hasgeospatialissues = FALSE
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND NOT occurrence.basisofrecord IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')
 AND occurrence.occurrencestatus = 'PRESENT'
 AND (occurrence.specieskey IS NOT NULL AND occurrence."year" IS NOT NULL)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 occurrence."year"

 The dataset's 95 records were derived from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021871-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nf3fd2
title: Occurrence Download

description: A dataset containing 898 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Picea asperata Mast."
 ]
}

 The dataset includes 898 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021879-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15599912
title: Software Sustainability Evaluation Data

description: This is the dataset for our paper "Engineering Sustainable Software"