cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.j2x2ng
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Chenopodium album",
 "Country is Libya",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030565-250717081556266/datasets/export for details.
DOI: 10.15468/dl.6wwauf
title: Occurrence Download

description: A dataset containing 141 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Gladiolus watsonioides",
 "HasCoordinate is true",
 "Geometry POLYGON ((-17.66889 -35.11691, 51.34702 -35.11691, 51.34702 37.62, -17.66889 37.62, -17.66889 -35.11691))"
 ]
}

 The dataset includes 141 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030567-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r5x8ju
title: Occurrence Download

description: A dataset containing 496 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Washingtonia robusta",
 "Country is Israel",
 "HasCoordinate is true"
 ]
}

 The dataset includes 496 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030566-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4yu9s3
title: Occurrence Download

description: A dataset containing 0 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 (Athene noctua)",
 "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 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030568-250717081556266/datasets/export for details.
DOI: 10.48610/befec92
title: The unrealised potential of agroforestry (Processed maps GHA 2022 High Shade all exports)

description: This dataset is part of a larger collection supporting the analysis in Becker et al., Nature Sustainability (2025) on the climate mitigation potential of cocoa agroforestry in West Africa. The full dataset is published via UQ eSpace as a series of interlinked records, each representing a different stage of the research workflow—from raw imagery to processed data products and analysis code.

This subset contains processed drone-derived map exports, including orthomosaics, digital surface models (DSM), digital terrain models (DTM), and vegetation height maps. These layers were derived from aerial imagery captured by drones during field surveys conducted across higher shade cocoa farms in Ghana in 2022. These farms were not selected using the original stratified sampling design but were instead targeted specifically for their higher shade levels. 

Vegetation height was calculated by subtracting the DTM from the DSM, providing spatially explicit estimates of canopy height across surveyed farms.
DOI: 10.15468/dl.k6j2db
title: Occurrence Download

description: A dataset containing 0 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 (Athene noctua)",
 "Country is one of (Bermuda, Canada, Greenland, Saint Pierre and Miquelon, United States of America)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030569-250717081556266/datasets/export for details.
DOI: 10.15468/dl.2qxsv8
title: Occurrence Download

description: A dataset containing 3239514 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 (Emberiza schoeniclus)",
 "Country is one of (Åland Islands, Albania, Andorra, Austria, Belarus, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Czechia, Denmark, Estonia, Faroe Islands, Finland, France, Germany, Gibraltar, Greece, Guernsey, Holy See, Hungary, Iceland, Ireland, Isle of Man, Italy, Jersey, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Moldova, Republic of, Monaco, Montenegro, Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, Russian Federation, San Marino, Serbia, Slovakia, Slovenia, Spain, Svalbard and Jan Mayen, Sweden, Switzerland, Ukraine, United Kingdom of Great Britain and Northern Ireland)"
 ]
}

 The dataset includes 3239514 records from 2185 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030541-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ze8evh
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Oxytoxum biconicum",
 "Country is Mexico",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008452-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/pzxjh5368x
title: Data For CLINICAL PERFORMANCE OF DIRECT POSTERIOR RESIN-COMPOSITE RESTORATIONS PLACED OVER A 5-YEAR PERIOD IN SELECTED INSTITUTIONS IN NAIROBI, KENYA

description: Data sets contain results from a study which was done Using 286 posterior resin composite restorations (RCRs) from 95 participants, a cross-sectional study was conducted at a public dental facility; Kenyatta National Hospital Dental Department (KNHDP), a teaching dental clinic; University of Nairobi Dental School (UoNDS), and a private dental facility; University of Nairobi Dental Plaza (UoNDP). Clinical evaluation was done visually using the United States Public Health Survey (USPHS) tool and data was analysed using STATA version 15(College Station TX, USA). Descriptive statistics, Pearson Chi-square and Fischer’s Exact tests were utilized for association between variables.
DOI: 10.17632/pzxjh5368x.1
title: Data For CLINICAL PERFORMANCE OF DIRECT POSTERIOR RESIN-COMPOSITE RESTORATIONS PLACED OVER A 5-YEAR PERIOD IN SELECTED INSTITUTIONS IN NAIROBI, KENYA

description: Data sets contain results from a study which was done Using 286 posterior resin composite restorations (RCRs) from 95 participants, a cross-sectional study was conducted at a public dental facility; Kenyatta National Hospital Dental Department (KNHDP), a teaching dental clinic; University of Nairobi Dental School (UoNDS), and a private dental facility; University of Nairobi Dental Plaza (UoNDP). Clinical evaluation was done visually using the United States Public Health Survey (USPHS) tool and data was analysed using STATA version 15(College Station TX, USA). Descriptive statistics, Pearson Chi-square and Fischer’s Exact tests were utilized for association between variables.
DOI: 10.17632/2tskc6rcfm.2
title: Geochemical data of the Chilean Southern Central Volcanic Zone (26-29°S)

description: This dataset contains supplementary data to the manuscript by S. Homrighausen, K. Hoernle, G. Jacques, F. Hauff, C. Arevalo, W. J. Collins, A. Klügel, and S. Mahlburg Kay: "Geochemical evolution of arc magmatism influenced by the Paraná–Etendeka flood basalt event and variations in subduction-eroded material" prepared for publication in Geochimica et Cosmochimica Acta.
DOI: 10.15468/dl.x4jrrv
title: Occurrence Download

description: A dataset containing 21 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Alouatta ululata"
 ]
}

 The dataset includes 21 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008594-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17485287
title: Dataset – UniProt and RCAAP CBA Case Studies (PathOS Project)

description: This dataset contains the data underlying the Cost–Benefit Analysis (CBA) case studies developed within the Horizon Europe PathOS Project (Grant Agreement No. 101058728).It includes:



Anonymised results from the user survey conducted to estimate benefits in the UniProt and RCAAP case studies.

Overview of the annual costs and benefits of the UniProt and RCAAP resources

Summary tables of the CBA results consistent with the findings presented in the related case studies and factsheets.
DOI: 10.5281/zenodo.17485288
title: Dataset – UniProt and RCAAP CBA Case Studies (PathOS Project)

description: This dataset contains the data underlying the Cost–Benefit Analysis (CBA) case studies developed within the Horizon Europe PathOS Project (Grant Agreement No. 101058728).It includes:



Anonymised results from the user survey conducted to estimate benefits in the UniProt and RCAAP case studies.

Overview of the annual costs and benefits of the UniProt and RCAAP resources

Summary tables of the CBA results consistent with the findings presented in the related case studies and factsheets.
DOI: 10.17632/grcn2dd9st
title: Dentate spikes comprise a continuum of relative input strength from the lateral and medial entorhinal cortex

description: The dataset is related to Dentate spikes comprise a continuum of relative input strength from the lateral and medial entorhinal cortex.
Gergely Tarcsay, Rajat Saxena, Royston Long, Justin L. Shobe, Bruce L. McNaughton, Laura A. Ewell
bioRxiv 2025.10.27.684857; doi: https://doi.org/10.1101/2025.10.27.684857

TestData1: downsampled lfp + configuration file from one mouse as a demo for the dentate spike classification GUI

processedData: needed to reproduced the findings in the manuscript

Codes can be found at our github page: https://github.com/EwellNeuroLab/DentateSpikeClassification
DOI: 10.17632/grcn2dd9st.1
title: Dentate spikes comprise a continuum of relative input strength from the lateral and medial entorhinal cortex

description: The dataset is related to Dentate spikes comprise a continuum of relative input strength from the lateral and medial entorhinal cortex.
Gergely Tarcsay, Rajat Saxena, Royston Long, Justin L. Shobe, Bruce L. McNaughton, Laura A. Ewell
bioRxiv 2025.10.27.684857; doi: https://doi.org/10.1101/2025.10.27.684857

TestData1: downsampled lfp + configuration file from one mouse as a demo for the dentate spike classification GUI

processedData: needed to reproduced the findings in the manuscript

Codes can be found at our github page: https://github.com/EwellNeuroLab/DentateSpikeClassification
DOI: 10.34810/data2103
title: Replication data for Hyperedge prediction and the statistical mechanisms of higher-order and lower-order interactions in complex networks
title: Hyperedge prediction and the statistical mechanisms of higher-order and lower-order interactions in complex networks

description: This dataset contains all the input data and results necessary to reproduce the experiments described in the associated publication on hyperedge prediction and statistical mechanisms in complex networks.

### Folder structure

#### `data/DATA_FOLDS/`

This directory contains the data used for 5-fold cross-validation of the model. Each fold consists of a pair of files:

- `trainX.dat`: the training data for fold X (where X ∈ [0–4])
- `testX.dat`: the corresponding test data for the same fold

Each training set represents 80% of the original dataset, and each test set represents the remaining 20%. The data files are in `.dat` format and contain encoded hyperedges used to fit and evaluate the generative model.

#### `data/REDUCED_DEFINITIVE_RESULTS/`

This directory includes the prediction results for each of the five folds (`fold0` to `fold4`) for different values of the model parameter **K**, which determines the number of latent groups:

- `K2_foldX.csv` → prediction results for fold X using K = 2
- `K3_foldX.csv` → results using K = 3
- ...
- `K5_foldX.csv` → results using K = 5

All result files are in `.csv` format and contain metrics and predicted scores generated by the model.

#### `README.md`

This file describes the usage of the dataset and details the experimental setup.

### Notes

The dataset is provided in support of reproducibility and open research. The full version of this dataset is also structured in a public GitHub repository: 
https://github.com/AleixMT/TrigenicInteractionPredictor

All data is released under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
description: This Dataset contains the data results generated during our research. This results can also be found in a structured git repository in here: https://github.com/AleixMT/TrigenicInteractionPredictor
DOI: 10.15156/bio/sh0168401.10fu
title: SH0168401.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0168402.10fu
title: SH0168402.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0168403.10fu
title: SH0168403.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0168404.10fu
title: SH0168404.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0168405.10fu
title: SH0168405.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0168406.10fu
title: SH0168406.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0168407.10fu
title: SH0168407.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0168408.10fu
title: SH0168408.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.