cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.3zpb9f
title: Occurrence Download

description: A dataset containing 667 species occurrences available in GBIF matching the query:
{
 "or" : [
 "TaxonKey is Anemia hirta (L.) Sw.",
 "TaxonKey is Aneimia breuteliana C.Presl",
 "TaxonKey is Aneimia hirta (L.) Sw.",
 "TaxonKey is Aneimia incisa Schrad.",
 "TaxonKey is Aneimia macrophylla Hort.",
 "TaxonKey is Aneimia obliqua Schrad.",
 "TaxonKey is Aneimia pohliana J.W.Sturm",
 "TaxonKey is Anemia breuteliana C.Presl",
 "TaxonKey is Anemia incisa Schrad.",
 "TaxonKey is Anemia obliqua Schrad.",
 "TaxonKey is Anemia palmarum Lindm.",
 "TaxonKey is Anemia pohliana J.W.Sturm"
 ]
}

 The dataset includes 667 records from 64 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0229236-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s8yta6
title: Occurrence Download

description: A dataset containing 226748 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Falco naumanni"
 ]
}

 The dataset includes 226748 records from 364 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006475-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28147106
title: Validação dos dados Aplicativo Super Netos- prevenção de violência psicológica

description: Trata-se de um conjunto de dados com a validação do instrumento utilizado para construção do aplicativo Super Netos, com enfoque na violência psicológica.
DOI: 10.6084/m9.figshare.28147106.v1
title: Validação dos dados Aplicativo Super Netos- prevenção de violência psicológica

description: Trata-se de um conjunto de dados com a validação do instrumento utilizado para construção do aplicativo Super Netos, com enfoque na violência psicológica.
DOI: 10.5281/zenodo.17475236
title: Ryo, Western Norway: Monitoring data May 2023-Sept. 2025

description: Meteorological data and data from ground measurements (volumetric water content, matric suction and temperature) from the case study site, Ryo (Western Norway), measured between May 2023 to September 2025. The data is used in the scientific article: "Introducing a methodology to quantify the hydro-mechanical protective effects of forests on slope stability: application to a deciduous forest in Western Norway", submitted to the scientific journal Catena.
DOI: 10.5281/zenodo.17475237
title: Ryo, Western Norway: Monitoring data May 2023-Sept. 2025

description: Meteorological data and data from ground measurements (volumetric water content, matric suction and temperature) from the case study site, Ryo (Western Norway), measured between May 2023 to September 2025. The data is used in the scientific article: "Introducing a methodology to quantify the hydro-mechanical protective effects of forests on slope stability: application to a deciduous forest in Western Norway", submitted to the scientific journal Catena.
DOI: 10.34770/y0p5-gb57
title: Data for "A Hybrid Data-driven and Physics-based Framework for Atmospheric Radiative Transfer Modeling"

description: Simulation data for "A Hybrid Data-driven and Physics-based Framework
 for Atmospheric Radiative Transfer Modeling"
DOI: 10.15468/dl.ngym3r
title: Occurrence Download

description: A dataset containing 1804985 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Material sample, Specimen)",
 "Geometry POLYGON((-123.50745 38.00961,-121.27898 34.15011,-120.45344 33.219,-119.78725 32.73994,-118.60457 32.26837,-117.45809 32.22482,-114.54106 32.24219,-113.72414 34.21455,-114.21238 35.23109,-116.57476 37.56221,-119.92198 39.13989,-123.50745 38.00961))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Arthropoda"
 ]
}

 The dataset includes 1804985 records from 295 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0164889-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.44snqh
title: Occurrence Download

description: A dataset containing 14928 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Rwanda, Uganda, Cameroon)",
 "OccurrenceStatus is Present",
 "TaxonKey is Orchidaceae"
 ]
}

 The dataset includes 14928 records from 78 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006496-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dszgj4
title: Occurrence Download

description: A dataset containing 84 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cavanillesia chicamochae"
 ]
}

 The dataset includes 84 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006498-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18154/rwth-2025-05411
title: Anhang zur Dissertation "Verkehrswende durch Öffentlichkeitsbeteiligung - Policy-Wirkung von konsultativen Invited Spaces am Beispiel zweier Verkehrsplanungsprojekte in Hamburg"

description: The following appendix firstly contains detailed descriptions of the methodological procedure in the dissertation (application of process tracing, interview guidelines, evaluation system for the interviews, procedure for the media analyses, etc.), which can be used as a basis for similar research projects. Secondly, some of the data analyses for the case studies are included in aggregated form, such as the results of the media analysis or the evaluation of the participation contributions. For the context of each table, see the main text of the dissertation.
DOI: 10.5281/zenodo.17475304
title: Datasets and models for Metagenomics-AI

description: Datasets and models for Metagenome-AI framework and related manuscript

4 datasets in total: Global AMP prediction, Gram positive, Gram negative bacteria and toxicity.

3 Base models: ESM2-3B, ESM3 and ProteinTrans.

Proteins collected from extreme environments are given in 11379_corepeptides_scored_cAMP20250915-forRevision.tsv
DOI: 10.5519/qd.zsgfmegk
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (630296 records)
DOI: 10.5281/zenodo.17475297
title: DMRsegaldata

description: Data package providing example DNA methylation files used in the DMRsegal vignette and examples. Includes a sorted beta matrix as a tab-delimited, bgzip-compressed file and a matching phenotype table. The data contains 10 healthy and 10 cancer samples, and preprocessing has already been performed on the beta values.
DOI: 10.5281/zenodo.17475298
title: DMRsegaldata

description: Data package providing example DNA methylation files used in the DMRsegal vignette and examples. Includes a sorted beta matrix as a tab-delimited, bgzip-compressed file and a matching phenotype table. The data contains 10 healthy and 10 cancer samples, and preprocessing has already been performed on the beta values.
DOI: 10.15468/dl.8kfwgz
title: Occurrence Download

description: A dataset containing 76 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Poa takeshimana"
 ]
}

 The dataset includes 76 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006499-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17474522
title: Livestock Pilot: Flock Monitoring Footage Dataset (MP4)

description: Aerial video dataset of sheep herds recorded during the Livestock Pilot to support the training and validation of computer vision models for automated sheep counting. Data were collected in April 2023 across multiple farm environments in Pella, Greece.

Footage was captured using a Parrot Anafi AI drone equipped with a 48 MP RGB camera and integrated GNSS module for georeferenced recording. The dataset consists of a single MP4 video sequence (approximately 5 minutes long), optimized for developing algorithms that can detect and count individual sheep across varying herd sizes and movement patterns.

This dataset aims to enable advancements in precision livestock management and automated animal monitoring through aerial computer vision.

Dataset





2023-04-18-10-27-45



Data Summary








Field
Description




Data format
MP4


Duration
~5 minutes


Resolution
4K (3840 × 2160)


Frame rate
30 fps


Geolocation
Embedded GNSS metadata


Equipment
Parrot Anafi AI drone, 48 MP RGB camera


Date of collection
April 2023


Location
Pella, Greece






Intended Use

The dataset is designed for:



Training and evaluation of sheep identification, detection, segmentation and counting models.

Testing livestock object detection and density estimation algorithms

Benchmarking analytics tools for precision livestock 

Perform ML/DL methods applied to livestock data.
DOI: 10.5281/zenodo.17474521
title: Livestock Pilot: Flock Monitoring Footage Dataset (MP4)

description: Aerial video dataset of sheep herds recorded during the Livestock Pilot to support the training and validation of computer vision models for automated sheep counting. Data were collected in April 2023 across multiple farm environments in Pella, Greece.

Footage was captured using a Parrot Anafi AI drone equipped with a 48 MP RGB camera and integrated GNSS module for georeferenced recording. The dataset consists of a single MP4 video sequence (approximately 5 minutes long), optimized for developing algorithms that can detect and count individual sheep across varying herd sizes and movement patterns.

This dataset aims to enable advancements in precision livestock management and automated animal monitoring through aerial computer vision.

Dataset





2023-04-18-10-27-45



Data Summary








Field
Description




Data format
MP4


Duration
~5 minutes


Resolution
4K (3840 × 2160)


Frame rate
30 fps


Geolocation
Embedded GNSS metadata


Equipment
Parrot Anafi AI drone, 48 MP RGB camera


Date of collection
April 2023


Location
Pella, Greece






Intended Use

The dataset is designed for:



Training and evaluation of sheep identification, detection, segmentation and counting models.

Testing livestock object detection and density estimation algorithms

Benchmarking analytics tools for precision livestock 

Perform ML/DL methods applied to livestock data.
DOI: 10.7910/dvn/m6fofp
title: HDV Highway Cost Allocation Dataset

description: Data supporting allocation of highway costs to light- and heavy-duty vehicles, including funding, expenditures, and VMT by loaded weight.
description: Methodology provided to detail process to arrive at dataset, including citations.
DOI: 10.21334/npolar.2014.fde3fd3b
title: Kjell-G. Kjær's Historic Register of Arctic Vessels
DOI: 10.5281/zenodo.17151917
title: Non-Functional Requirements from 269 Software Development Projects

description: Automated NLP-Based Classification of Non-Functional Requirements in Blockchain and Cross-Domain Software Systems Using BERT and Machine Learning

 

Abstract: 

Automated non-functional requirements (NFRs) classification enhances consistency and traceability by systematically labeling requirements, saving effort, supporting early architectural and testing decisions, improving stakeholder communication, and enabling quality across diverse software domains. While prior work has applied natural language processing (NLP) and machine learning (ML) to NFR classification, existing datasets are often limited in size, domain diversity, and contextual richness. This study presents a novel dataset comprising over 2,400 NFRs spanning 269 software projects across 26 software application domains, including nine blockchain projects. The raw requirements are standardized using Rupp’s boilerplate to reduce vagueness and ambiguity, and the classification of NFRs types follows ISO/IEC 25010 definitions. We employ a range of traditional machine learning, deep learning, and a transformer-based model (i.e., BERT-base) for automated classification of NFRs, evaluating performance across cross-domain and blockchain-specific NFRs. Results highlight that domain-aware adaptation significantly enhances classification accuracy, with traditional ML and deep learning models showing strong performance on blockchain requirements. This work contributes a publicly available, context-rich dataset and provides empirical insights into the effectiveness of NLP-based NFR classification in both general and blockchain-specific settings.
DOI: 10.5281/zenodo.17151916
title: Non-Functional Requirements from 269 Software Development Projects

description: Automated NLP-Based Classification of Non-Functional Requirements in Blockchain and Cross-Domain Software Systems Using BERT and Machine Learning

 

Abstract: 

Automated non-functional requirements (NFRs) classification enhances consistency and traceability by systematically labeling requirements, saving effort, supporting early architectural and testing decisions, improving stakeholder communication, and enabling quality across diverse software domains. While prior work has applied natural language processing (NLP) and machine learning (ML) to NFR classification, existing datasets are often limited in size, domain diversity, and contextual richness. This study presents a novel dataset comprising over 2,400 NFRs spanning 269 software projects across 26 software application domains, including nine blockchain projects. The raw requirements are standardized using Rupp’s boilerplate to reduce vagueness and ambiguity, and the classification of NFRs types follows ISO/IEC 25010 definitions. We employ a range of traditional machine learning, deep learning, and a transformer-based model (i.e., BERT-base) for automated classification of NFRs, evaluating performance across cross-domain and blockchain-specific NFRs. Results highlight that domain-aware adaptation significantly enhances classification accuracy, with traditional ML and deep learning models showing strong performance on blockchain requirements. This work contributes a publicly available, context-rich dataset and provides empirical insights into the effectiveness of NLP-based NFR classification in both general and blockchain-specific settings.
DOI: 10.15468/dl.9n287f
title: Occurrence Download

description: A dataset containing 22 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Poa ullungdoensis"
 ]
}

 The dataset includes 22 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006500-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17459736
title: Curated Experimental MOF Structures with Assigned Charges for Simulation

description: This dataset contains curated experimental metal–organic framework (MOF) structures with assigned atomic charges, prepared for adsorption and binding-site simulations. It was used in the study “How well do conventional atomistic simulations predict adsorption binding sites in MOFs compared to experiment?” The dataset enables direct benchmarking of common force fields and charge-assignment schemes.

Directory Naming Convention

Each directory label encodes the key details of the corresponding simulation. The label is composed of sections separated by a double underscore (__). The directory labels closely match the MOF names reported in Table 1, using filesystem-compatible formatting, following the convention:

<Structure_Name>__<Guest_Molecule>__<Temperature>__<Pressure>

Structure Preprocessing

All structures were obtained from experimental crystallographic data, either from the Cambridge Structural Database (CSD) or from the supplementary information of the original publications. Each structure was carefully corrected to remove artifacts such as missing ligands, disordered fragments, and missing protons. The corrected structures were converted to P1 symmetry and their protons were geometry-optimized using DFT, as detailed in the Methods section of the paper. Atomic charges were then assigned using several commonly employed charge-assignment methods in adsorption simulations.

Each folder contains the following charge-assigned cif files:

Optimized structure: *_opt.cifDDEC6 charges (DFT-fitted via Chargemol): *_opt_ddec6.cifREPEAT charges (DFT-fitted): *_opt_repeat.cifMEPO-QEQ empirical charges: *_opt_mepoqeq.cifMEPO-ML machine-learned charges (trained on REPEAT): *_opt_mepoml.cif

Reference CSV File

These charge-assigned experimental structures are ready for GCMC, isotherm prediction, or binding-site localization studies. The dataset also includes a reference index file named Experimental_MOF_Dataset.csv. This CSV file provides a readable mapping between each directory and its reference DOI. In addition, the columns below were added as well:



In_Table1_Set: Identifies the MOFs included in Table 1 of the main text, where the core binding-site analyses were conducted using UFF and REPEAT.

In_RMSE_RMSD_Set: Marks the MOFs used to calculate RMSE and RMSD differences across all force-field and charge-method combinations.

Has_Isotherms: Indicates the structures for which adsorption isotherms were computed and included in the study.
DOI: 10.5281/zenodo.17193402
title: data
DOI: 10.5281/zenodo.17193403
title: data
DOI: 10.5281/zenodo.16907809
title: CLOVER Dataset

description: This repository contains raw MCD files, fully annotated data frame ("global_data.rds"), and example CLOVER plots ("ClusterPlot") for the CLOVER paper.
DOI: 10.5281/zenodo.16907810
title: CLOVER Dataset

description: This repository contains raw MCD files, fully annotated data frame ("global_data.rds"), and example CLOVER plots ("ClusterPlot") for the CLOVER paper.
DOI: 10.18746/bmth.data.00000464
title: Code for Enhancing Generalization in Sketch-Based Image Retrieval through Single and Multi-Source Domain Adaptation
DOI: 10.5281/zenodo.14938045
title: Impact of ocean acidification to climate-economy interaction - Dataset

description: Data and codes necessary to reproduce the key figures and tables in the article "Impact of ocean acidification to climate-economy interaction" for double blind peer review and editorial assessment.
DOI: 10.5281/zenodo.17475372
title: Impact of ocean acidification to climate-economy interaction - Dataset

description: Data and codes necessary to reproduce the key figures and tables in the article "Impact of ocean acidification to climate-economy interaction" for double blind peer review and editorial assessment.
DOI: 10.6084/m9.figshare.30479363
title: <b><i>Simulation and Test of a V-shaped Seed-guiding Surface and Concave Pit Furrow Opener for Seed Displacement Restriction: Verification on Seeding Uniformity and Post-soil-contact Seed Motion Limitation</i></b>

description: 用作论文数据的提供。
DOI: 10.6084/m9.figshare.30479363.v2
title: <b><i>Simulation and Test of a V-shaped Seed-guiding Surface and Concave Pit Furrow Opener for Seed Displacement Restriction: Verification on Seeding Uniformity and Post-soil-contact Seed Motion Limitation</i></b>

description: 用作论文数据的提供。
DOI: 10.6084/m9.figshare.30479363.v1
title: <b><i>Simulation and Test of a V-shaped Seed-guiding Surface and Concave Pit Furrow Opener for Seed Displacement Restriction: Verification on Seeding Uniformity and Post-soil-contact Seed Motion Limitation</i></b>

description: 用作论文数据的提供。
DOI: 10.6084/m9.figshare.30479291
title: Genome and annotation files of two Ampullariidae snails, <i>Pila celebensis</i> and <i>Pila pesmei</i>.

description: Sequencing, assembling and annotating two Old-World species of the family Ampullariidae, <i>Pila celebensis</i> with genomes at the chromosome level, and <i>Pila pesmei</i> assembled only to the scaffold level.
DOI: 10.6084/m9.figshare.30479291.v1
title: Genome and annotation files of two Ampullariidae snails, <i>Pila celebensis</i> and <i>Pila pesmei</i>.

description: Sequencing, assembling and annotating two Old-World species of the family Ampullariidae, <i>Pila celebensis</i> with genomes at the chromosome level, and <i>Pila pesmei</i> assembled only to the scaffold level.
DOI: 10.6084/m9.figshare.30434637
title: Pepsin, trypsin, and MUC5B are independent risk factors for hearing impairment in patients with laryngopharyngeal reflux-related chronic secretory otitis media

description: This study evaluated the potential diagnostic utility of pepsin, trypsin, and mucin 5B (MUC5B) in hearing impairment in patients with laryngopharyngeal reflux (LPR)-related chronic secretory OM (CSOM). Patients with LPR-related CSOM were enrolled and assigned into the normal hearing (NH), and mild (Mi-HI) and moderate-to-severe hearing impairment (Mo-HI) groups. Pepsin, trypsin, and MUC5B contents were determined by ELISA, with their correlations with Eustachian tube dysfunction questionnaire-7 (ETDQ-7) score and inflammatory factors (interleukin [IL]-2, IL6, IL-8), and diagnostic performance in hearing impairment assessed by Pearson, Spearman, and ROC curves. Factors influencing hearing impairment were identified using logistic regression models. Pepsin, trypsin, and MUC5B contents were upregulated in patients’ middle ear effusion as hearing impairment worsened. The three indicators correlated to EDTQ-7 and inflammatory factors, and exhibited high diagnostic value for hearing impairment in LPR-related CSOM patients. Remarkably, their combination created significantly higher diagnostic value than a single indicator. Abundantly-increased pepsin, trypsin, and MUC5B amplified hearing impairment incidence. Pepsin, trypsin, and MUC5B are independent risk factors for hearing impairment in LPR-related CSOM patients. Their combination assists hearing impairment diagnosis in patients, providing a tool in clinical practice to stratify patients and offering a theoretical basis for exploring therapeutic targets.
DOI: 10.6084/m9.figshare.30434637.v2
title: Pepsin, trypsin, and MUC5B are independent risk factors for hearing impairment in patients with laryngopharyngeal reflux-related chronic secretory otitis media

description: This study evaluated the potential diagnostic utility of pepsin, trypsin, and mucin 5B (MUC5B) in hearing impairment in patients with laryngopharyngeal reflux (LPR)-related chronic secretory OM (CSOM). Patients with LPR-related CSOM were enrolled and assigned into the normal hearing (NH), and mild (Mi-HI) and moderate-to-severe hearing impairment (Mo-HI) groups. Pepsin, trypsin, and MUC5B contents were determined by ELISA, with their correlations with Eustachian tube dysfunction questionnaire-7 (ETDQ-7) score and inflammatory factors (interleukin [IL]-2, IL6, IL-8), and diagnostic performance in hearing impairment assessed by Pearson, Spearman, and ROC curves. Factors influencing hearing impairment were identified using logistic regression models. Pepsin, trypsin, and MUC5B contents were upregulated in patients’ middle ear effusion as hearing impairment worsened. The three indicators correlated to EDTQ-7 and inflammatory factors, and exhibited high diagnostic value for hearing impairment in LPR-related CSOM patients. Remarkably, their combination created significantly higher diagnostic value than a single indicator. Abundantly-increased pepsin, trypsin, and MUC5B amplified hearing impairment incidence. Pepsin, trypsin, and MUC5B are independent risk factors for hearing impairment in LPR-related CSOM patients. Their combination assists hearing impairment diagnosis in patients, providing a tool in clinical practice to stratify patients and offering a theoretical basis for exploring therapeutic targets.