cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57702/46suru1j
title: Pascal VOC Challenge

description: The Pascal VOC Challenge dataset is a benchmark for object detection and image segmentation.
DOI: 10.57702/dkb1llhp
title: Patent dataset

description: The dataset used in the paper is a text and image dataset, with 5477 instances, 3201 attributes, and 248 categories. The dataset is used for clustering and evaluation of the proposed method.
DOI: 10.57702/33sbjb3i
title: CoherentGS

description: The CoherentGS dataset is used for sparse novel view synthesis with coherent 3D Gaussians.
DOI: 10.57702/bct76job
title: Robust Multilingual Named Entity Recognition with Shallow Semi-Supervised Features

description: Multilingual Named Entity Recognition approach based on a robust and general set of features across languages and datasets.
DOI: 10.57702/zpp24jp4
title: Temperature Effects on Diverse Question Generation by GPT-4

description: A dataset of 52 learning objectives (LOs) spanning across multiple levels of Bloom's Taxonomy and common topics in introductory CS topics.
DOI: 10.57702/v30h1mq5
title: MinAtar

description: MinAtar is a new evaluation platform designed to allow for more thorough and reproducible experiments in reinforcement learning.
DOI: 10.57702/0uu2fsld
title: RRUFF mineral database

description: Raman spectra of solidified agarose and Cy 7.5-infused agarose samples
DOI: 10.26207/2bxd-pe31
title: Data for "Scattering and Dynamical Capture of Two Black Holes: Synergies Between Numerical and Analytical Methods"

description: Gravitational waves and puncture tracker data for "Scattering and Dynamical Capture of Two Black Holes: Synergies Between Numerical and Analytical Methods"

We study initially unbound systems of two black holes using numerical relativity (NR) simulations performed with gr-athena++. We focus on regions of the parameter space close to the transition from scatterings to dynamical captures, considering equal mass and spin-aligned configurations, as well as unequal mass and nonspinning ones. The numerical results are then used to validate the effective-one-body (EOB) model teobresums-dalí for dynamical captures and scatterings. We find good agreement for the waveform phenomenologies, scattering angles, mismatches, and energetics in the low energy regime (E0≲1.02M). In particular, mismatches weighted with the zero-detuned, high-power noise spectral density of Advanced LIGO are typically below or around the 1% level, with only a few cases—corresponding to spinning binaries—slightly above the 3% threshold, thus suggesting the usability of teobresums-dalí for current data analysis of low-energy scatterings and dynamical captures. We also discuss dynamical captures in the test-mass limit by solving numerically the Zerilli equation with the time domain code rwzhyp. The latter analysis provides valuable insights into both the analytical noncircular corrections of the EOB waveform and the integration of NR Weyl scalars.
DOI: 10.57702/oh0q79j0
title: ObMan

description: The ObMan dataset is a large synthetic dataset produced by rendering hand meshes with selected objects from ShapeNet.
DOI: 10.15468/dl.8g8nru
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((88.778069 24.055303, 88.70117 24.049726, 88.626183 24.033134, 88.554973 24.005939, 88.489307 23.968818, 88.43081100000001 23.922692, 88.380927 23.868706, 88.340881 23.808197, 88.31165 23.742665, 88.29393899999999 23.673727, 88.288167 23.603086, 88.29445699999999 23.532482, 88.312636 23.463653, 88.34223799999999 23.398288, 88.38252300000001 23.337992, 88.43248800000001 23.28424, 88.490903 23.238349, 88.55633 23.20144, 88.62716899999999 23.174413, 88.701688 23.157929, 88.778069 23.152389, 88.85445 23.157929, 88.928969 23.174413, 88.999808 23.20144, 89.065235 23.238349, 89.12365 23.28424, 89.173615 23.337992, 89.2139 23.398288, 89.24350200000001 23.463653, 89.261681 23.532482, 89.267971 23.603086, 89.262199 23.673727, 89.244488 23.742665, 89.21525699999999 23.808197, 89.175211 23.868706, 89.125327 23.922692, 89.06683099999999 23.968818, 89.001165 24.005939, 88.92995500000001 24.033134, 88.854968 24.049726, 88.778069 24.055303))"},{"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 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080161-251120083545085/datasets/export for details.
DOI: 10.57702/k15zs7hj
title: Neural Collaborative Filtering Dataset

description: The Neural Collaborative Filtering (NCF) dataset is a collection of user-item interaction data.
DOI: 10.57702/2kcvv4rd
title: Realbook dataset

description: The Realbook dataset contains 2,846 jazz songs based on band-in-a-box files, with time-aligned beat and chord information.
DOI: 10.15468/dl.d9hf8g
title: Occurrence Download

description: A dataset containing 3945 species occurrences available in GBIF matching the query:
{
 "CollectionKey" : [
 "is 5be47fa9-b233-4a83-9bea-48e533d48044"
 ]
}

 The dataset includes 3945 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080162-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/5nyrpmh9
title: Cora Dataset

description: The Cora dataset contains 2,708 nodes representing documents, with edges denoting citations between them, and is used for semi-supervised classification.
DOI: 10.57702/amunr8oe
title: Representer Theorems for Metric and Preference Learning

description: The dataset is used to demonstrate the representer theorem for simultaneous metric and preference learning from paired comparisons and metric learning from triplet comparisons.
DOI: 10.57702/quvv629p
title: SWaT and WADI datasets

description: The dataset is used for multivariate anomaly detection on time series data generated by cyber-physical systems.
DOI: 10.57702/h5hv2hp7
title: Case Western Reserve University Bearing Dataset

description: The CWRU bearing dataset is a vibration signal dataset used for bearing fault classification. It contains vibration signal data from a 2 hp electric motor with artificially induced single point faults.
DOI: 10.57702/4bhm1t89
title: Modeling task relationships in multi-task learning with multi-gate mixture-of-experts

description: Multi-behavior recommendation datasets
DOI: 10.57702/izns016d
title: SafetyPrompts

description: The dataset used in the paper to test the safety issues of Large Language Models (LLMs).
DOI: 10.57702/7tk1f9f1
title: EgoLoc

description: The EgoLoc dataset is a reformulation of the VQ3D task and a modular pipeline that leads to significant improvements on the Ego4D VQ3D benchmark.
DOI: 10.57702/com37v95
title: Multichannel Impulse Response Database

description: The Multichannel Impulse Response Database from Bar-Ilan university consists of measured RIRs with sources placed on a grid of [0◦, 180◦] in steps of 15◦, at distances of 1 m and 2 m from the array.
DOI: 10.57702/0zqopcwm
title: Auto-GPT

description: The Auto-GPT model, an experimental open-source AI application that has been gaining significant attention due to its promising autonomous abilities.
DOI: 10.57702/bvq6yjnb
title: Stochastic Optimal Control Matching

description: The dataset used in the paper is a stochastic optimal control problem, where the goal is to drive the behavior of a noisy system.
DOI: 10.3886/e242575
title: Monthly COVID-19 Death Rates per 100,000 Population by Age Group, Race and Ethnicity, Sex, and Region with Double Stratification

description: Monthly COVID-19 death rates per 100,000 population stratified by age group, race/ethnicity, sex, and region, with race/ethnicity by age group and age group by race/ethnicity double stratification
description: (Downloaded 2026-01-06)
DOI: 10.15156/bio/sh0155796.10fu
title: SH0155796.10FU

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/sh0155797.10fu
title: SH0155797.10FU

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/sh0155798.10fu
title: SH0155798.10FU

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/sh0155799.10fu
title: SH0155799.10FU

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/sh0155800.10fu
title: SH0155800.10FU

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/sh0155801.10fu
title: SH0155801.10FU

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: 10.15468/dl.77vcrx
title: Occurrence Download

description: A dataset containing 3180 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dichorragia nesimachus"
 ]
}

 The dataset includes 3180 records from 124 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013955-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/jhv16z
title: VIS - Estuarine monitoring in Flanders, Belgium (post 2013)

description: VIS - Estuarine monitoring in Flanders, Belgium (post 2013) is a sampling event dataset published by the Research Institute for Nature and Forest (INBO). The dataset contains close to 32,000 fish occurrences sampled between 2013 and 2016 from 33 locations in the estuary of the river Yser and the part of the river Scheldt under tidal influence ("Zeeschelde"). The dataset includes over 60 fish species, as well as a number of non-target crustacean species. The data are retrieved from the Fish Information System (VIS), a database set up to monitor the status of fishes and their habitats in Flanders and are collected in support of the Water Framework Directive, the Habitat Directive, certain red lists, and biodiversity research. The VIS database is described in Brosens et al. 2015 (https://doi.org/10.3897/zookeys.475.8556). Additional information, such as measurements, absence information and abiotic data are available upon request. Issues with the dataset can be reported at https://github.com/inbo/data-publication/tree/master/datasets/vis-estuarine-monitoring-eventsLength and weight measurement data of the individual fishes, absence information, occurrence data since 2015, as well as abiotic data of the sampling points (pH, temperature, etc.) are not included in the Darwin Core Archive and are available upon request.We released the data to the public domain under a Creative Commons Zero waiver (http://creativecommons.org/publicdomain/zero/1.0/). We would appreciate however, if you read and follow these norms for data use (http://www.inbo.be/en/norms-for-data-use) and provide a link to the original dataset (https://doi.org/10.15468/jhv16z) whenever possible. If you use these data for a scientific paper, please cite the dataset following the applicable citation norms and/or consider us for co-authorship. We are always interested to know how you have used or visualized the data, or to provide more information, so please contact us via the contact information provided in the metadata, opendata@inbo.be or https://twitter.com/oscibio.
DOI: 10.25824/redu/8q5vdd
title: Arquivos com valores de demandas para a simulação em 12 semanas do modelo original e dados de suprimentos de três níveis para um único produto

description: Valores de demandas para a simulação em 12 semanas do modelo original da simulação do processo de uma cadeia de suprimentos de três níveis para um único produto.
DOI: 10.5281/zenodo.18495374
title: A Dataset of Peak Ground Acceleration (PGA) Estimates for the Aigio–Lykoporia Zone, Greece

description: A Dataset of Peak Ground Acceleration (PGA) Estimates for the Aigio–Lykoporia Zone, Greece

Authors



Angelos Zymvragakis (National and Kapodistrian University of Athens) — ORCID

Ioannis Spingos (National and Kapodistrian University of Athens) — ORCID

George Kaviris (National and Kapodistrian University of Athens) — ORCID


Description

The dataset contains simulated Peak Ground Acceleration (PGA) data from Probabilistic Seismic Hazard Assessment (PSHA) modelling in the Aigio–Lykoporia Zone (ALZ; Northern Peloponnese, Greece). PSHA was performed through the Cornell-McGuire approach (Cornell, 1968; McGuire, 1976).

Files

The dataset contains PGA for a Return Period (RP) of 475 years, i.e. 10% probability of exceedance in 50 years, in easily parsable CSV format. The following file is included:

alz_intensity_measurement_levels.csv


Field description:



node_id: Node identifier (string).

node_longitude_deg: Longitude in decimal degrees (WGS84) (float).

node_latitude_deg: Latitude in decimal degrees (WGS84) (float).

pga_475_cmps2: Peak Ground Acceleration for a 475‑year return period, in cm/s2 (float).


Additional files



LICENSE: CC BY-NC 4.0 legal code.

README.md: The current README file.


Keywords



Geophysics

Seismology

Probabilistic Seismic Hazard Assessment


Funding



European Commission OSCARS - O.S.C.A.R.S. - Open Science Clusters’ Action for Research and Society Grant agreement ID: 101129751


Version

1.0.0

Publication date (YYYY-MM-DD)

2026-02-05

Size and formats



Total size: 3 KB

File formats: CSV


How to cite

Zymvragakis, A., Spingos, I., Kaviris, G., (2026). A Dataset of Peak Ground Acceleration (PGA) Estimates for the Aigio–Lykoporia Zone, Greece. Zenodo.

Contact



Name: Angelos Zymvragakis

Email: azymvragakis@geol.uoa.gr

Affiliation: National and Kapodistrian University of Athens
DOI: 10.5281/zenodo.18495375
title: A Dataset of Peak Ground Acceleration (PGA) Estimates for the Aigio–Lykoporia Zone, Greece

description: A Dataset of Peak Ground Acceleration (PGA) Estimates for the Aigio–Lykoporia Zone, Greece

Authors



Angelos Zymvragakis (National and Kapodistrian University of Athens) — ORCID

Ioannis Spingos (National and Kapodistrian University of Athens) — ORCID

George Kaviris (National and Kapodistrian University of Athens) — ORCID


Description

The dataset contains simulated Peak Ground Acceleration (PGA) data from Probabilistic Seismic Hazard Assessment (PSHA) modelling in the Aigio–Lykoporia Zone (ALZ; Northern Peloponnese, Greece). PSHA was performed through the Cornell-McGuire approach (Cornell, 1968; McGuire, 1976).

Files

The dataset contains PGA for a Return Period (RP) of 475 years, i.e. 10% probability of exceedance in 50 years, in easily parsable CSV format. The following file is included:

alz_intensity_measurement_levels.csv


Field description:



node_id: Node identifier (string).

node_longitude_deg: Longitude in decimal degrees (WGS84) (float).

node_latitude_deg: Latitude in decimal degrees (WGS84) (float).

pga_475_cmps2: Peak Ground Acceleration for a 475‑year return period, in cm/s2 (float).


Additional files



LICENSE: CC BY-NC 4.0 legal code.

README.md: The current README file.


Keywords



Geophysics

Seismology

Probabilistic Seismic Hazard Assessment


Funding



European Commission OSCARS - O.S.C.A.R.S. - Open Science Clusters’ Action for Research and Society Grant agreement ID: 101129751


Version

1.0.0

Publication date (YYYY-MM-DD)

2026-02-05

Size and formats



Total size: 3 KB

File formats: CSV


How to cite

Zymvragakis, A., Spingos, I., Kaviris, G., (2026). A Dataset of Peak Ground Acceleration (PGA) Estimates for the Aigio–Lykoporia Zone, Greece. Zenodo.

Contact



Name: Angelos Zymvragakis

Email: azymvragakis@geol.uoa.gr

Affiliation: National and Kapodistrian University of Athens