cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.k9cad3
title: Occurrence Download

description: A dataset containing 451 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Pinus fenzeliana, Pinus krempfii, Pinus dalatensis, Pinus kesiya, Pinus latteri, Pinus cernua, Pinus henryi)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2026"
 ]
}

 The dataset includes 451 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000039-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.96c89x
title: Occurrence Download

description: A dataset containing 1730 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mieniplotia scabra"
 ]
}

 The dataset includes 1730 records from 96 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000041-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yg7m8t
title: Occurrence Download

description: A dataset containing 28577 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Aegilops geniculata"
 ]
}

 The dataset includes 28577 records from 416 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000040-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q4mwqb
title: Occurrence Download

description: A dataset containing 635010 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Cladonia"
 ]
}

 The dataset includes 635010 records from 488 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000022-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.74zbae
title: Occurrence Download

description: A dataset containing 149 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Brazil",
 "GadmGid is BRA.14_1",
 "TaxonKey is Neogastropoda"
 ]
}

 The dataset includes 149 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000044-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hn4jtm
title: Occurrence Download

description: A dataset containing 573 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sarangesa purendra"
 ]
}

 The dataset includes 573 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000043-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mfet8j
title: Occurrence Download

description: A dataset containing 868 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Hemisorubim platyrhynchos"
 ]
}

 The dataset includes 868 records from 76 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000045-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vr7b6t
title: Occurrence Download

description: A dataset containing 3191 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Vernicia montana Lour."
 ]
}

 The dataset includes 3191 records from 81 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021757-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nr9p2x
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Oreochromis niloticus (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 ((32.064 -28.9416,32.4847 -28.5786,30.5701 -28.5786,30.5701 -30.7329,30.6252 -30.6659,31.4179 -29.4257,31.8178 -29.0299,32.064 -28.9416))"
 ]
}

 The dataset includes 9 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021758-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15544548
title: Tara Mission Microbiomes metabarcoding SSU V4V5 ASVs (dada2)

description: This repository contains datasets describing the DADA2 ASVs generated from Tara Mission Microbiomes SSU V4V5 rDNA MM-OMICS data. The ASVs were generated using the nf-core workflow ampliseq. Please refer to the readme file (README.html) for more details.
description: We wish to thank the Tara Ocean Foundation, the SV Tara crew and all those who participate in Mission Microbiomes AtlantECO and adopt its Data Sharing & Publication Best Practices (https://zenodo.org/communities/mission-microbiomes-atlanteco/).

This publication has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 862923 (project AtlantECO). This output reflects only the author’s view and the European Union cannot be held responsible for any use that may be made of the information contained therin.

We are keen to thank the commitment of the following institutions for their financial and scientific support that made Mission Microbiomes AtlantECO possible: Stazione Zoologica Anton Dohrn, European Bioinformatics Institute (EMBL-EBI), Centre national de la recherche scientifique (CNRS),  Centre  National  de  Séquençage  (CNS,  Genoscope), agnès  b.,  BIC,  Capgemini  Engineering, Fondation  Groupe  EDF,  Compagnie  Nationale  du  Rhône,  L'Oréal,  Biotherm,  Région  Bretagne,  Lorient Agglomération,  Billerudkorsnas,  Havas  Paris,  Fondation  Rothschild,  Office  Français  de  la  Biodiversité, AmerisourceBergen, Philgood Foundation, UNESCO-IOC, Etienne Bourgois.
DOI: 10.15468/dl.jesn24
title: Occurrence Download

description: A dataset containing 1780833 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is North America",
 "Country is Canada",
 "Geometry POLYGON((-81.64142 42.84258,-81.61019 42.82808,-81.59569 42.79685,-81.45739 42.75223,-81.15654 42.78146,-80.9246 42.92665,-80.91044 43.16213,-81.06979 43.28961,-81.21497 43.32502,-81.39203 43.33742,-81.62574 43.29846,-81.80456 43.16213,-81.69608 43.00542,-81.64588 42.87715,-81.64142 42.84258))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1780833 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000632-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.93dupr
title: Occurrence Download

description: A dataset containing 31 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "Month is January",
 "TaxonKey is Xanthoria candelaria",
 "Year 1994-2024"
 ]
}

 The dataset includes 31 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000655-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18420946
title: Performance Evaluation of AlphaSensor Radon Modules Under Real-World Conditions

description: This dataset comprises raw measurements comparing RD200M, AlphaSensors, and AlphaGuard over a broad concentration range under real-world conditions.
DOI: 10.5281/zenodo.18420947
title: Performance Evaluation of AlphaSensor Radon Modules Under Real-World Conditions

description: This dataset comprises raw measurements comparing RD200M, AlphaSensors, and AlphaGuard over a broad concentration range under real-world conditions.
DOI: 10.7910/dvn/dsexmp
title: Youth Migration Crisis of the 21st Century: A Comprehensive Moderated Mediation Analysis

description: This dataset contains survey responses collected for a study examining the determinants of youth migration among Pakistani individuals who have migrated abroad for work and study purposes. Data were collected through a self-administered structured questionnaire between September 2023 and July 2024 following institutional ethical approval and written informed consent. The dataset includes demographic information (gender, age group, country of study, study program, and academic discipline) and multi-item measures of educational factors, economic factors, social factors, political factors, COVID-19–related factors, and youth migration intention.
DOI: 10.5281/zenodo.18412589
title: BalancedCommitBench: A Language-Balanced Commit Messages Subset Extracted from CommitBench:

description: BalancedCommitBench: A Language-Balanced Commit Messages Subset Extracted from CommitBench:

We base our experiments on CommitBench, a large-scale benchmark for commit message generation introduced by Schall et al.(2024) . CommitBench aggregates more than one million real commits collected from thousands of open-source repositories across six major programming languages: Python, Java, JavaScript, Go, PHP, and Ruby. Each instance contains a git diff, the corresponding human-written commit message, and metadata such as author, timestamp, and repository name.

From this corpus, we derive BalancedCommitBench, a language-balanced subset obtained through systematic preprocessing. The dataset is cleaned via language normalization, de-duplication, removal of bot-generated and low-information commits, and length-based filtering, followed by uniform sampling across the six languages to ensure balanced representation.

 

M. Schall, T. Czinczoll and G. De Melo, "CommitBench: A Benchmark for Commit Message Generation," 2024 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), Rovaniemi, Finland, 2024, pp. 728-739, doi: 10.1109/SANER60148.2024.00080.
DOI: 10.5281/zenodo.18412590
title: BalancedCommitBench: A Language-Balanced Commit Messages Subset Extracted from CommitBench:

description: BalancedCommitBench: A Language-Balanced Commit Messages Subset Extracted from CommitBench:

We base our experiments on CommitBench, a large-scale benchmark for commit message generation introduced by Schall et al.(2024) . CommitBench aggregates more than one million real commits collected from thousands of open-source repositories across six major programming languages: Python, Java, JavaScript, Go, PHP, and Ruby. Each instance contains a git diff, the corresponding human-written commit message, and metadata such as author, timestamp, and repository name.

From this corpus, we derive BalancedCommitBench, a language-balanced subset obtained through systematic preprocessing. The dataset is cleaned via language normalization, de-duplication, removal of bot-generated and low-information commits, and length-based filtering, followed by uniform sampling across the six languages to ensure balanced representation.

 

M. Schall, T. Czinczoll and G. De Melo, "CommitBench: A Benchmark for Commit Message Generation," 2024 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), Rovaniemi, Finland, 2024, pp. 728-739, doi: 10.1109/SANER60148.2024.00080.
DOI: 10.15468/dl.tpbb3d
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sorbus torminalis",
 "BasisOfRecord is one of (Human Observation)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000643-260129131611470/datasets/export for details.
DOI: 10.15468/dl.k6tv5u
title: Occurrence Download

description: A dataset containing 234 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is New Records of Featherwing Beetles (Coleoptera: Ptiliidae) in North America"
 ]
}

 The dataset includes 234 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000656-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/jypgy8
title: Replication data and code for: "The effectiveness of tree-planting PES in food supply chains"

description: Replication data and code for: "The effectiveness of tree-planting PES in food supply chains"
DOI: 10.34740/kaggle/dsv/14667771
title: Balochi Language to English Translation Dataset
DOI: 10.7910/dvn/hxhvs1
title: Replication Data for: The Weakness of Anti-Christian Nationalism: When Religiously-Inclusive Orientations Can’t Increase Tolerance

description: This provides data and R code sufficient to replicate the findings in "The Weakness of Anti-Christian Nationalism: When Religiously-Inclusive Orientations Can’t Increase Tolerance" that is forthcoming in Politics & Religion.
DOI: 10.5281/zenodo.18220953
title: SInAS: A global dataset of native and alien distributions of alien species

description: The SInAS dataset represents a collection of regional lists of alien (also called non-native or non-indigenous) species and includes information about their native ranges, alien ranges, invasion status for alien ranges, habitats and year of first record. This dataset has been generated by standardising and integrating large global databases of alien species occurrences using the SInAS workflow version 2.0. 

The SInAS dataset is described in more detail in the following scientific article, which need to be cited when using this dataset:







Gómez-Suárez M, Laeseke P, Seebens H (2025) A global dataset of native and alien distributions of alien species. Scientific Data 12: 1914. https://doi.org/10.1038/s41597-025-06379-6




The code to generate the dataset is stored on Github (https://github.com/hseebens/SInAS) with releases available on Zenodo (https://doi.org/10.5281/zenodo.3763221).
description: "Version 3.1.1 + geopackage" contains the SInAS version 3.1.1 and the corrected shapefile (now as geopackage). All other files are the same as Version 3.1.1.
DOI: 10.5281/zenodo.5562891
title: SInAS: A global dataset of native and alien distributions of alien species

description: The SInAS dataset represents a collection of regional lists of alien (also called non-native or non-indigenous) species and includes information about their native ranges, alien ranges, invasion status for alien ranges, habitats and year of first record. This dataset has been generated by standardising and integrating large global databases of alien species occurrences using the SInAS workflow version 2.0. 

The SInAS dataset is described in more detail in the following scientific article, which need to be cited when using this dataset:







Gómez-Suárez M, Laeseke P, Seebens H (2025) A global dataset of native and alien distributions of alien species. Scientific Data 12: 1914. https://doi.org/10.1038/s41597-025-06379-6




The code to generate the dataset is stored on Github (https://github.com/hseebens/SInAS) with releases available on Zenodo (https://doi.org/10.5281/zenodo.3763221).
description: "Version 3.1.1 + geopackage" contains the SInAS version 3.1.1 and the corrected shapefile (now as geopackage). All other files are the same as Version 3.1.1.
DOI: 10.15468/dl.9hrcft
title: Occurrence Download

description: A dataset containing 1901 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "Month is January",
 "TaxonKey is Xanthoria",
 "Year 1994-2024"
 ]
}

 The dataset includes 1901 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000658-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vrazug
title: Occurrence Download

description: A dataset containing 126805 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Human Observation)",
 "Geometry POLYGON((-6.11832 36.43035,-5.7455 36.43035,-5.7455 36.69742,-6.11832 36.69742,-6.11832 36.43035))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Aves"
 ]
}

 The dataset includes 126805 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000637-260129131611470/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/14667787
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.duhncs
title: Occurrence Download

description: A dataset containing 579 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "TaxonKey is Inia geoffrensis",
 "Year 2000-2026"
 ]
}

 The dataset includes 579 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000660-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/xocrvu
title: Replication Data for: What electoral outcomes foster electoral consent/dissent?

description: Losers’ consent is a key indicator of democratic vitality. In a functioning democracy, citizens should accept electoral outcomes regardless of which party wins. Contrasting with previous studies on the topic, we, in this article, directly measure the types of electoral outcomes to which over 5,000 German adults, representative of the national population, are willing to consent/dissent. We find that respondents are more likely to accept, and less likely to protest, outcomes in which their preferred party performs well, and their most disliked party performs poorly. Meanwhile, structural features of the outcomes, such as the number of parties in government or whether the Chancellor comes from the party with the most seats, have little to no effect. These results support the idea that partisanship is the main driver of electoral consent/dissent, and that negative preferences have a unique explanatory power in this respect.
DOI: 10.7910/dvn/kna5vs
title: Data for the Construction Cybersecurity Crowdsourcing Platform

description: This Dataverse contains data from the Crowdsourcing Platform case study conducted by Muammer Semih Sonkor and Borja García de Soto.
DOI: 10.15468/dl.qsem6q
title: Occurrence Download

description: A dataset containing 4273 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "MediaType is Image",
 "TaxonKey is Ixodes ricinus"
 ]
}

 The dataset includes 4273 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000662-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7267/9593v434z
title: Coastal Resilience Toolkit: Review of Coastal Action Plans in the Pacific Northwest
title: Coastal Resilience Study

description: Coastal communities in the Pacific Northwest are facing growing environmental threats like flooding, rising sea levels, wildfires, and ocean changes. Local governments are in a strong position to act, but they also face compounding challenges such as limited resources, a lack of clear guidance, and the need to work across multiple priorities and jurisdictions. To support governments and communities working to improve resilience, we undertook a review of 70 coastal action plans (CAPs) across Washington, Oregon, and Northern California. Our aim was to understand where and how these plans are being used to respond to environmental challenges and develop resources that can be used to accelerate local action. From 2024 to 2025, we worked with partners along the Oregon coast to develop the study questions, scope the search, and develop this toolkit. The toolkit contains this report summarizing our analysis, a companion dataset, and a set of additional resources.
DOI: 10.7910/dvn/nqnyin
title: Sri Lankan Food dataset

description: This dataset is a curated food recommendation dataset designed to support research in recommender systems, personalised nutrition, and AI-based decision-making. The dataset integrates food metadata, nutritional attributes, user preference profiles, and user–food interaction signals to enable the development and evaluation of content-based, collaborative, and supervised machine learning models.

The dataset is suitable for academic research, prototype system development, and benchmarking of hybrid recommendation approaches.
DOI: 10.5281/zenodo.18173914
title: UAV Multispectral to Hyperspectral Reconstruction Based on the RTM and Deep Learning
title: PROSAIL-PRO simulations with CNN-based learning

description: The dataset is organized as follows:





data/real/Contains experimentally measured data, including:





UAV hyperspectral observations




ASD field spectrometer measurementsThese data are used as real validation and fine-tuning data in our experiments.






data/lut/Contains training data generated using a Look-Up Table (LUT) approach.The LUT is generated based on:





Wheat-related biophysical parameters from our experiment




Parameter ranges reported in relevant literatureThese data are used for LUT-based pretraining of the model.






data/ancillary/Contains soil spectral data, used as ancillary input for LUT generation and simulation.




data/sensor/Contains the spectral response functions (SRFs) of the UAV sensor, used to match simulated spectra with UAV observations.



All data provided in this Zenodo record are raw data only.Source code for data generation, model training, and evaluation is maintained separately on GitHub https://github.com/windying123/M2H-SWIR.git.
DOI: 10.5281/zenodo.18173915
title: UAV Multispectral to Hyperspectral Reconstruction Based on the RTM and Deep Learning
title: PROSAIL-PRO simulations with CNN-based learning

description: The dataset is organized as follows:





data/real/Contains experimentally measured data, including:





UAV hyperspectral observations




ASD field spectrometer measurementsThese data are used as real validation and fine-tuning data in our experiments.






data/lut/Contains training data generated using a Look-Up Table (LUT) approach.The LUT is generated based on:





Wheat-related biophysical parameters from our experiment




Parameter ranges reported in relevant literatureThese data are used for LUT-based pretraining of the model.






data/ancillary/Contains soil spectral data, used as ancillary input for LUT generation and simulation.




data/sensor/Contains the spectral response functions (SRFs) of the UAV sensor, used to match simulated spectra with UAV observations.



All data provided in this Zenodo record are raw data only.Source code for data generation, model training, and evaluation is maintained separately on GitHub https://github.com/windying123/M2H-SWIR.git.