cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17909/y3yy-6w10
title: JWST NIRCam data for Behind the Spotlight: A systematic assessment of outshining using NIRCam medium-bands in the JADES Origins Field

description: NIRCam data products from programs 1210 and 3215 used in the following paper:

Behind the Spotlight: A systematic assessment of outshining using NIRCam medium-bands in the JADES Origins Field
DOI: 10.57783/x4k1-nt37
title: Utah HCUP
DOI: 10.15468/dl.pp45tz
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Exilaria vaucheriae Kützing, 1833",
 "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 ((25.5395 -23.2724,25.1306 -24.0715,25.5395 -24.0715,25.5395 -23.2724))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065618-250525065834625/datasets/export for details.
DOI: 10.15468/dl.zyg8df
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Exilaria vaucheriae Kützing, 1833",
 "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 ((20.2855 -34.7533,20.509 -34.5676,20.509 -32.9007,17.7723 -32.9007,17.8156 -33.0786,18.3471 -33.7176,18.3748 -33.8287,18.2181 -34.0492,18.3197 -34.3408,18.4452 -34.429,18.5435 -34.4213,18.5872 -34.3667,18.5363 -34.167,18.7345 -34.1508,18.7216 -34.3637,18.7808 -34.4521,19.0289 -34.4206,19.0831 -34.4835,19.2655 -34.5017,19.2032 -34.6157,19.2394 -34.6926,19.375 -34.6963,19.6091 -34.8524,19.8251 -34.8396,19.9798 -34.9064,20.1081 -34.8731,20.1517 -34.7847,20.2855 -34.7533))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065620-250525065834625/datasets/export for details.
DOI: 10.5281/zenodo.15723329
title: HyperBulAds: Dataset Of Hyperboles in Bulgarian Health and Beauty Advertising Texts

description: HyperBulAds is a pilot dataset designed to support research on hyperbolic language in Bulgarian advertising texts, specifically within the domain of health and beauty product descriptions. It consists of 623 manually annotated sentences, each labeled for the presence of hyperbole and, when applicable, annotated at the span level with one of three categories:





qualitative




quantitative




generalization



This dataset enables both binary classification (1-hyperbolic vs. 0-non-hyperbolic) and sequence labeling (identifying hyperbolic segments).

Example (non-hyperbolic):

{

    "text": "Чаят има множество положителни действия върху организма.",

    "hyperbole": false,

    "spans": []

}

 

Example (hyperbolic):

{

    "text": "100% натурален супербленд за здрав стомах и тънка талия.",

    "hyperbole": true,

    "spans": [

        {

            "start": 0,

            "end": 14,

            "label": "quantitative",

            "text": "100% натурален"

        }

    ]

}

 

Annotation Methodology

All annotations were conducted manually by a single expert linguist. As this is an exploratory pilot study, the process was carried out without formal guidelines or inter-annotator validation—an acknowledged limitation that will be addressed in future iterations.

Dataset Statistics

Total sentences: 623

Hyperbolic sentences: 263

Non-hyperbolic sentences: 360

Distribution of hyperbole types:

Qualitative: 208 instances

Quantitative: 42 instances

Generalization: 36 instances

 

This distribution illustrates the prevalence of qualitative exaggeration in promotional texts for health and beauty products.

The dataset is provided in JSON format, suitable for direct use in NLP pipelines and machine learning experiments. All content has been anonymized, with brand and product names removed to protect privacy and minimize commercial bias.

Access

HyperBulAds is with open-access to support transparency, reproducibility, and collaborative research.

https://doi.org/10.5281/zenodo.15723330

Authors

Nevena Grigorova, GATE Institute

Silvia Gargova, GATE Institute

Funding

This resource is published with the assistance of the ORBIT project (Open Research Bulgarian Incubator), a cascading initiative supported by the REINFORCING project, funded by the European Commission.

Citation

Please cite this dataset as:

Gargova, S., & Grigorova, N. (2025). HyperBulAds: Dataset Of Hyperboles in Bulgarian Health and Beauty Advertising Texts [Data set]. Zenodo. https://doi.org/10.5281/zenodo.15723330
DOI: 10.5281/zenodo.15723330
title: HyperBulAds: Dataset Of Hyperboles in Bulgarian Health and Beauty Advertising Texts

description: HyperBulAds is a pilot dataset designed to support research on hyperbolic language in Bulgarian advertising texts, specifically within the domain of health and beauty product descriptions. It consists of 623 manually annotated sentences, each labeled for the presence of hyperbole and, when applicable, annotated at the span level with one of three categories:





qualitative




quantitative




generalization



This dataset enables both binary classification (1-hyperbolic vs. 0-non-hyperbolic) and sequence labeling (identifying hyperbolic segments).

Example (non-hyperbolic):

{

    "text": "Чаят има множество положителни действия върху организма.",

    "hyperbole": false,

    "spans": []

}

 

Example (hyperbolic):

{

    "text": "100% натурален супербленд за здрав стомах и тънка талия.",

    "hyperbole": true,

    "spans": [

        {

            "start": 0,

            "end": 14,

            "label": "quantitative",

            "text": "100% натурален"

        }

    ]

}

 

Annotation Methodology

All annotations were conducted manually by a single expert linguist. As this is an exploratory pilot study, the process was carried out without formal guidelines or inter-annotator validation—an acknowledged limitation that will be addressed in future iterations.

Dataset Statistics

Total sentences: 623

Hyperbolic sentences: 263

Non-hyperbolic sentences: 360

Distribution of hyperbole types:

Qualitative: 208 instances

Quantitative: 42 instances

Generalization: 36 instances

 

This distribution illustrates the prevalence of qualitative exaggeration in promotional texts for health and beauty products.

The dataset is provided in JSON format, suitable for direct use in NLP pipelines and machine learning experiments. All content has been anonymized, with brand and product names removed to protect privacy and minimize commercial bias.

Access

HyperBulAds is with open-access to support transparency, reproducibility, and collaborative research.

https://doi.org/10.5281/zenodo.15723330

Authors

Nevena Grigorova, GATE Institute

Silvia Gargova, GATE Institute

Funding

This resource is published with the assistance of the ORBIT project (Open Research Bulgarian Incubator), a cascading initiative supported by the REINFORCING project, funded by the European Commission.

Citation

Please cite this dataset as:

Gargova, S., & Grigorova, N. (2025). HyperBulAds: Dataset Of Hyperboles in Bulgarian Health and Beauty Advertising Texts [Data set]. Zenodo. https://doi.org/10.5281/zenodo.15723330
DOI: 10.15468/dl.9d8g9u
title: Occurrence Download

description: A dataset containing 527 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "CoordinateUncertaintyInMeters 0.0-9999.0",
 "Geometry POLYGON((-118.31236 30.96922,-109.63207 30.96922,-109.63207 38.17559,-118.31236 38.17559,-118.31236 30.96922))",
 "TaxonKey is Cylindropuntia acanthocarpa subsp. acanthocarpa"
 ]
}

 The dataset includes 527 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065619-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.djcasc
title: Occurrence Download

description: A dataset containing 48 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-82.381 43.011,-82.377 43.011,-82.377 43.015,-82.381 43.015,-82.381 43.011))",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 48 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065621-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15706949
title: Data from: Passive acoustic monitoring captures large-scale Dryocopus pileatus (Pileated Woodpecker) occupancy patterns in the Pacific Northwest, USA

description: This repository contains the necessary data and code to reproduce the multi-state occupancy analysis featured in our paper, "Passive acoustic monitoring captures large-scale Dryocopus pileatus (Pileated woodpecker) occupancy patterns in the Pacific Northwest, USA," currently in prep. This description will be updated with a link to the paper upon successful publication.

The repository is structured as an R project with a /data folder containing tabular data and a shapefiles subfolder containing one GIS shapefile necessary to complete the analysis. There is a main script called main.r which contains a small amount of contextual information. Running the main.r script will run the other four scripts in order, generating several output directories and a number of output files containing the main results of the analysis. The analysis was conducted in R (version 4.4.1) using several third-party packages, most notably RPresence (2.15.8), the tidyverse family of packages (release 2.0.0), and sf (1.0-20).

The raw data are contained in the file data/PIWO_Encounter_Histories_w_Covariates_Raw.csv, which includes one line for each of 3,948 field sites (recording stations) where we placed autonomous recording units (ARUs) in Mar-Oct of 2023. We processed ca. 1.7 million hours of audio from these stations using the PNW-Cnet v5 deep learning model to detect Pileated Woodpecker vocalizations, treating clips with score >= 0.95 for the HYPI1 class as detections. We constructed encounter histories using detections from the first 6 weeks of recordings after manually reviewing detections from stations that had <= 10 total detections during this period. The data also include site- and survey-level covariate values that were used to construct occupancy models based on these data.

The analysis uses a fitted multi-state occupancy model to predict occupancy state across a set of 5-km^2 hexagons within the area monitored under the Northwest Forest Plan; this area includes the western portions of the US states of Washington and Oregon and the northwestern portion of California. The data file called data/Hex_Centroid_Covariate_Values_Raw.csv contains covariate values as measured at the center of each hexagon. Predictions are made only for hexagons that were at least 50% forested or forest-capable (n ~ 38,000); others are shown as NA in the table of predicted values. The data/shapefiles folder contains a shapefile listing all ~47,000 hexagons within the NWFP footprint and lists the percent federal ownership (Pct_Fed) and percentage of forest-capable cover (For_Cap) for each.
DOI: 10.5281/zenodo.15706948
title: Data from: Passive acoustic monitoring captures large-scale Dryocopus pileatus (Pileated Woodpecker) occupancy patterns in the Pacific Northwest, USA

description: This repository contains the necessary data and code to reproduce the multi-state occupancy analysis featured in our paper, "Passive acoustic monitoring captures large-scale Dryocopus pileatus (Pileated woodpecker) occupancy patterns in the Pacific Northwest, USA," currently in prep. This description will be updated with a link to the paper upon successful publication.

The repository is structured as an R project with a /data folder containing tabular data and a shapefiles subfolder containing one GIS shapefile necessary to complete the analysis. There is a main script called main.r which contains a small amount of contextual information. Running the main.r script will run the other four scripts in order, generating several output directories and a number of output files containing the main results of the analysis. The analysis was conducted in R (version 4.4.1) using several third-party packages, most notably RPresence (2.15.8), the tidyverse family of packages (release 2.0.0), and sf (1.0-20).

The raw data are contained in the file data/PIWO_Encounter_Histories_w_Covariates_Raw.csv, which includes one line for each of 3,948 field sites (recording stations) where we placed autonomous recording units (ARUs) in Mar-Oct of 2023. We processed ca. 1.7 million hours of audio from these stations using the PNW-Cnet v5 deep learning model to detect Pileated Woodpecker vocalizations, treating clips with score >= 0.95 for the HYPI1 class as detections. We constructed encounter histories using detections from the first 6 weeks of recordings after manually reviewing detections from stations that had <= 10 total detections during this period. The data also include site- and survey-level covariate values that were used to construct occupancy models based on these data.

The analysis uses a fitted multi-state occupancy model to predict occupancy state across a set of 5-km^2 hexagons within the area monitored under the Northwest Forest Plan; this area includes the western portions of the US states of Washington and Oregon and the northwestern portion of California. The data file called data/Hex_Centroid_Covariate_Values_Raw.csv contains covariate values as measured at the center of each hexagon. Predictions are made only for hexagons that were at least 50% forested or forest-capable (n ~ 38,000); others are shown as NA in the table of predicted values. The data/shapefiles folder contains a shapefile listing all ~47,000 hexagons within the NWFP footprint and lists the percent federal ownership (Pct_Fed) and percentage of forest-capable cover (For_Cap) for each.
DOI: 10.15468/dl.nvg8bh
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Exilaria vaucheriae Kützing, 1833",
 "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 ((35.628 -23.023,35.6007 -22.9702,35.6007 -23.165,35.628 -23.023))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065622-250525065834625/datasets/export for details.
DOI: 10.5281/zenodo.15714531
title: TFG

description: Este depósito contiene resultados, gráficas y archivos de evaluación utilizados en el Trabajo de Fin de Grado titulado “Implementación de un sistema de evaluación de capacidades de grandes modelos de lenguaje a través de bucles de resumen y extensión de textos”. Cada carpeta incluye un archivo README que documenta su contenido.
DOI: 10.5281/zenodo.15723131
title: TFG

description: Este depósito contiene resultados, gráficas y archivos de evaluación utilizados en el Trabajo de Fin de Grado titulado “Implementación de un sistema de evaluación de capacidades de grandes modelos de lenguaje a través de bucles de resumen y extensión de textos”. Cada carpeta incluye un archivo README que documenta su contenido.
DOI: 10.15468/dl.5zk4xb
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Exilaria vaucheriae Kützing, 1833",
 "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 ((35.6306 -23.844,35.6007 -23.8125,35.6007 -24.0157,35.6306 -23.844))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065624-250525065834625/datasets/export for details.
DOI: 10.5281/zenodo.15723403
title: Study on reproducibility for anomaly detection on AIS trajectories

description: This dataset contains the quantitative data and analysis from "Lost at Sea, the Reproducibility Crisis in AIS Anomaly Detection." It currently covers 91 papers in the field of Maritime Anomaly Detection under the following conditions:



The paper was published 2020-2025 (though future dataset versions could include additional studies)

The paper relies primarily on automatic identification system data for maritime anomaly detection (rather than multimodal models or alternate sensing types).

The paper presents an anomaly detection algorithm for maritime trajectories, and at least one anomaly detection experiment demonstrating the capability.


For each study, the dataset includes quantitative markers for data, software, and performance reproducibility, as well as analyst notes that give details on the reproducibility categories.

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
DOI: 10.5281/zenodo.15723404
title: Study on reproducibility for anomaly detection on AIS trajectories

description: This dataset contains the quantitative data and analysis from "Lost at Sea, the Reproducibility Crisis in AIS Anomaly Detection." It currently covers 91 papers in the field of Maritime Anomaly Detection under the following conditions:



The paper was published 2020-2025 (though future dataset versions could include additional studies)

The paper relies primarily on automatic identification system data for maritime anomaly detection (rather than multimodal models or alternate sensing types).

The paper presents an anomaly detection algorithm for maritime trajectories, and at least one anomaly detection experiment demonstrating the capability.


For each study, the dataset includes quantitative markers for data, software, and performance reproducibility, as well as analyst notes that give details on the reproducibility categories.

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
DOI: 10.15468/dl.6qpuun
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Fistulifera H.Lange-Bertalot, 1997",
 "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 ((30.0251 -31.3959,30.5701 -30.7329,30.5701 -28.5786,25.5395 -28.5786,25.5395 -32.9007,28.2048 -32.9007,28.5753 -32.6569,29.4902 -31.7517,30.0251 -31.3959))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065625-250525065834625/datasets/export for details.
DOI: 10.15468/dl.8gt33p
title: Occurrence Download

description: A dataset containing 1160 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Ameerega bilinguis (Jungfer, 1989)"
 ]
}

 The dataset includes 1160 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065626-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f5nke4
title: Occurrence Download

description: A dataset containing 151339 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Material sample)"
 ]
 }
 },
 "TaxonKey is Circus aeruginosus (Linnaeus, 1758)",
 "Continent is one of (Africa)",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 151339 records from 59 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065615-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e2ftnn
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Fistulifera H.Lange-Bertalot, 1997",
 "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 ((30.5701 -24.0715,25.5395 -24.0715,25.5395 -28.5786,30.5701 -28.5786,30.5701 -24.0715))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065627-250525065834625/datasets/export for details.
DOI: 10.5281/zenodo.14887000
title: Dataset for seismic oceanography in the Gulf of Cadiz

description: We make available a comprehensive set of eight 2-D seismic oceanography sections that reveal the complex oceanography setting in the Gulf of Cadiz and SW of Iberian potential and illustrate the potential of this method for oceanographic studies. For more information see Dataset description PDF.
DOI: 10.5281/zenodo.15722256
title: Dataset for seismic oceanography in the Gulf of Cadiz

description: We make available a comprehensive set of eight 2-D seismic oceanography sections that reveal the complex oceanography setting in the Gulf of Cadiz and SW of Iberian potential and illustrate the potential of this method for oceanographic studies. For more information see Dataset description PDF.
DOI: 10.15468/dl.23wzuj
title: Occurrence Download

description: A dataset containing 2822842 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Human Observation, Machine Observation)",
 "DatasetKey is NMNH Extant Specimen Records (USNM, US)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 2822842 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065623-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vw7efc
title: Occurrence Download

description: A dataset containing 348 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Material sample)"
 ]
 }
 },
 "TaxonKey is Circus cyaneus (Linnaeus, 1766)",
 "Continent is one of (Africa)",
 "Year is greater than or equal to 1900"
 ]
}

 The dataset includes 348 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065628-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15723503
title: weecology/PortalData: 5.157.0

description: v5.157.0