cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14961664
title: Submerged Arc Welding Open Repository

description: This dataset collects data from various test coupons subjected to the submerged arc welding (SAW) process. It includes not only the process data, but also the design of the experiment including process window parameterization setup, as well as NDT (Non-Destructive Testing) data.

Motivation

The industrialization of manufacturing processes requires comprehensive data management and system automation to ensure production quality, reliability, and efficiency. In this context, SAW has become a key technology in fabricating of high-strength, high-performance metal components. However, quality control and early defect detection remain critical challenges in ensuring process stability, repeatability, and traceability.

To address this, we present an open dataset on SAW, covering all stages of the manufacturing process, from design and planning to validation and quality control. This resource aims to serve as a foundation for developing new data-driven methodologies, contributing to the continuous optimization and improvement of SAW processes while accelerating their digital transformation.

Authors



Estefanía Tapia Suárez: main contact (estefania.suarez@aimen.es)

Inés Pérez Couñago

Juan Manuel Fernández

Christian Eike Precker

Cristina Ruiz


Entities

This dataset was collected under the PENELOPE project. Attributions:



AIMEN: Process data collection and manufacturing of X-joint coupons.

IDESA: Process window parametrization setup.


Structure

The dataset follows this structure:



Database



[SAMPLE 1 NAME]



process_data



[BEAD 1 NAME]



Photo: pictures of the manufactured bead sample. Format: jpg.

Process data: data recorded from the process. Format hdf5.

Profilometer: data from a 3D bead reconstruction. Format: txt.



[BEAD 2 NAME]



Same structure as for BEAD 1.





NDT_data



X-ray: radiographic test report. Format pdf.

UT: ultrasonic testing report. Format pdf.

PAUT: phase array ultrasonic testing. Format nde.

defects locations: Location of defects identified along each weld bead. Format xlsx.



pics



Photo: pictures of the completed weld coupon. Format jpg.








 







[SAMPLE 2 NAME]



Same structure as for SAMPLE 1. 





Design_materials_settings: information on the welding parameters and welding sequence used in the manufacturing of each coupon. Format: pdf.

README: metadata and information about the sample. Format: txt.


Software

To open the different files that conform the dataset, we recommend the following Open softwares:



hdf5 -> HDF5 Viewer: https://www.hdfgroup.org/downloads/hdfview/

txt -> cloud compare: https://cloudcompare.org/

nde -> ShareCad: https://beta.sharecad.org/


 

More information on how to open the files of the dataset can be found in the README.
DOI: 10.5281/zenodo.14961663
title: Submerged Arc Welding Open Repository

description: This dataset collects data from various test coupons subjected to the submerged arc welding (SAW) process. It includes not only the process data, but also the design of the experiment including process window parameterization setup, as well as NDT (Non-Destructive Testing) data.

Motivation

The industrialization of manufacturing processes requires comprehensive data management and system automation to ensure production quality, reliability, and efficiency. In this context, SAW has become a key technology in fabricating of high-strength, high-performance metal components. However, quality control and early defect detection remain critical challenges in ensuring process stability, repeatability, and traceability.

To address this, we present an open dataset on SAW, covering all stages of the manufacturing process, from design and planning to validation and quality control. This resource aims to serve as a foundation for developing new data-driven methodologies, contributing to the continuous optimization and improvement of SAW processes while accelerating their digital transformation.

Authors



Estefanía Tapia Suárez: main contact (estefania.suarez@aimen.es)

Inés Pérez Couñago

Juan Manuel Fernández

Christian Eike Precker

Cristina Ruiz


Entities

This dataset was collected under the PENELOPE project. Attributions:



AIMEN: Process data collection and manufacturing of X-joint coupons.

IDESA: Process window parametrization setup.


Structure

The dataset follows this structure:



Database



[SAMPLE 1 NAME]



process_data



[BEAD 1 NAME]



Photo: pictures of the manufactured bead sample. Format: jpg.

Process data: data recorded from the process. Format hdf5.

Profilometer: data from a 3D bead reconstruction. Format: txt or hdf5.



[BEAD 2 NAME]



Same structure as for BEAD 1.





NDT_data



X-ray: radiographic test report. Format pdf.

UT: ultrasonic testing report. Format pdf.

PAUT: phase array ultrasonic testing. Format nde.

defects locations: Location of defects identified along each weld bead. Format xlsx.



pics



Photo: pictures of the completed weld coupon. Format jpg.



Design_materials_settings: information on the welding parameters and welding sequence used in the manufacturing of each coupon. Format: pdf.

README: metadata and information about the sample. Format: txt.












[SAMPLE 2 NAME]



Same structure as for SAMPLE 1. 






Software

To open the different files that conform the dataset, we recommend the following Open softwares:



hdf5 -> HDF5 Viewer: https://www.hdfgroup.org/downloads/hdfview/

txt -> cloud compare: https://cloudcompare.org/

nde -> ShareCad: https://beta.sharecad.org/


More information on how to open the files of the dataset can be found in the README.
DOI: 10.5281/zenodo.15083865
title: Submerged Arc Welding Open Repository

description: This dataset collects data from various test coupons subjected to the submerged arc welding (SAW) process. It includes not only the process data, but also the design of the experiment including process window parameterization setup, as well as NDT (Non-Destructive Testing) data.

Motivation

The industrialization of manufacturing processes requires comprehensive data management and system automation to ensure production quality, reliability, and efficiency. In this context, SAW has become a key technology in fabricating of high-strength, high-performance metal components. However, quality control and early defect detection remain critical challenges in ensuring process stability, repeatability, and traceability.

To address this, we present an open dataset on SAW, covering all stages of the manufacturing process, from design and planning to validation and quality control. This resource aims to serve as a foundation for developing new data-driven methodologies, contributing to the continuous optimization and improvement of SAW processes while accelerating their digital transformation.

Authors



Estefanía Tapia Suárez: main contact (estefania.suarez@aimen.es)

Inés Pérez Couñago

Juan Manuel Fernández

Christian Eike Precker

Cristina Ruiz


Entities

This dataset was collected under the PENELOPE project. Attributions:



AIMEN: Process data collection and manufacturing of X-joint coupons.

IDESA: Process window parametrization setup.


Structure

The dataset follows this structure:



Database



[SAMPLE 1 NAME]



process_data



[BEAD 1 NAME]



Photo: pictures of the manufactured bead sample. Format: jpg.

Process data: data recorded from the process. Format hdf5.

Profilometer: data from a 3D bead reconstruction. Format: txt or hdf5.



[BEAD 2 NAME]



Same structure as for BEAD 1.





NDT_data



X-ray: radiographic test report. Format pdf.

UT: ultrasonic testing report. Format pdf.

PAUT: phase array ultrasonic testing. Format nde.

defects locations: Location of defects identified along each weld bead. Format xlsx.



pics



Photo: pictures of the completed weld coupon. Format jpg.



Design_materials_settings: information on the welding parameters and welding sequence used in the manufacturing of each coupon. Format: pdf.

README: metadata and information about the sample. Format: txt.












[SAMPLE 2 NAME]



Same structure as for SAMPLE 1. 






Software

To open the different files that conform the dataset, we recommend the following Open softwares:



hdf5 -> HDF5 Viewer: https://www.hdfgroup.org/downloads/hdfview/

txt -> cloud compare: https://cloudcompare.org/

nde -> ShareCad: https://beta.sharecad.org/


More information on how to open the files of the dataset can be found in the README.
DOI: 10.17871/atto.370.6.1544
title: Atmospheric boundary layer height dataset (2014-2020) measured at the ATTO site

description: This dataset contains estimates of the height of the atmospheric boundary layer obtained through vertical aerosol backscatter profiles with data from the Jenoptik CHM 15k ceilometer located at ATTO Camp 1. The ceilometer is a LIDAR cloud height sensor based on a single wavelength backscattering technique. It detects cloud layers, cloud penetration depths, and also the top of the atmospheric boundary layer. The period starts on Dec 2014 until Dec 2020 every 5 minutes, with the exception of the year 2017.
DOI: 10.5281/zenodo.15079531
title: Synthetic Data from: Generative and Integrative Modeling for Transcriptomics with Formalin Fixed Paraffin Embedded Material

description: This repository contains all synthetic datasets used in the manuscript, "Generative and integrative modeling for transcriptomics with formalin fixed paraffin embedded material", currently published on BioRxiv:

https://www.biorxiv.org/content/10.1101/2025.02.21.639356v1

The datasets consist of AnnData files designed to be used by the PREFFECT (PaRaffin Embedded Formalin-FixEd Cleaning Tool, a probabilistic framework for the analysis of RNA sequencing data from formalin-fixed paraffin embedded (FFPE) samples. This software can be found on GitHub here:

https://github.com/hallettmiket/preffect/

Details of the various AnnData files provided in this repository is given in the 'ReadMe.rtf' file.
DOI: 10.5281/zenodo.15079532
title: Synthetic Data from: Generative and Integrative Modeling for Transcriptomics with Formalin Fixed Paraffin Embedded Material

description: This repository contains all synthetic datasets used in the manuscript, "Generative and integrative modeling for transcriptomics with formalin fixed paraffin embedded material", currently published on BioRxiv:

https://www.biorxiv.org/content/10.1101/2025.02.21.639356v1

The datasets consist of AnnData files designed to be used by the PREFFECT (PaRaffin Embedded Formalin-FixEd Cleaning Tool, a probabilistic framework for the analysis of RNA sequencing data from formalin-fixed paraffin embedded (FFPE) samples. This software can be found on GitHub here:

https://github.com/hallettmiket/preffect/

Details of the various AnnData files provided in this repository is given in the 'ReadMe.rtf' file.
DOI: 10.1594/pangaea.973701
title: Soil properties in the North-Western Kurdistan region, Iraq, derived from laboratory measurements

description: Soil information is valuable for many disciplines (e.g. agriculture, geomorphology, geology, archaeology) and can be used to produce maps or statistics on soil productivity. As part of the project CRC1070 ResourceCulture, we collected information on the soil quality in the Dohuk province of the Kurdistan region of Iraq. In total, 561 samples were collected at 136 locations in 2017, 2018, 2022, and 2023. These samples were collected at different depth increments (0 - 10, 10 - 30, 30 - 50, 50 - 70 and 70 - 100 cm) with an auger before being prepared and measured with mid-infrared (MIR) spectroscopy. Part of these samples (109) were selected to be analyzed in a laboratory, measuring texture, pH, organic and total carbon, nitrogen, sulfur, electrical conductivity, bulk density and calcium carbonate. A Cubist model was used to predict the remaining samples based on the MIR spectra. We then modelled digital soil mapping with machine learning methods (ensemble learning, linear regression, decision trees) for these soil components. Additionally, we mapped the soil depth using the information collected in the field. This dataset can help any researcher regarding soil information, forming a unique regional database.Here, samples were air dried (35 - 45 °C) for 24 h; root fragments were removed and sieved (&lt; 2 mm); for the CNS analysis (Ct, Nt and Corg, with Vario EL III, Elementar), samples were ground below 1 µm (Fritsch, Pulverisette 5/4, classic line). The texture was measured with wet sieving (2 - 0.063 mm fraction) and SediGraph III (Micrometrics) for the lower fractions (0.063 - 0.000063). pH was measured with a ProfiLine pH 3310 (WTW) in Kcl solution, while the CaCO3 was calculated using the calcimeter method. The conductivity was measured in micro siemens per second [µS/cm], with a Cond 330i/340i (WTW). Finally, we calculated the mean weight diameter of the aggregate (mm) based on the texture results and the following formula MWD=Xi∗Wi/100.
DOI: 10.1594/pangaea.973714
title: Soil bulk density and soil depth from on-site observations in the North-Western Kurdistan region, Iraq

description: Soil information is valuable for many disciplines (e.g. agriculture, geomorphology, geology, archaeology) and can be used to produce maps or statistics on soil productivity. As part of the project CRC1070 ResourceCulture, we collected information on the soil quality in the Dohuk province of the Kurdistan region of Iraq. In total, 561 samples were collected at 136 locations in 2017, 2018, 2022, and 2023. These samples were collected at different depth increments (0 - 10, 10 - 30, 30 - 50, 50 - 70 and 70 - 100 cm) with an auger before being prepared and measured with mid-infrared (MIR) spectroscopy. Part of these samples (109) were selected to be analyzed in a laboratory, measuring texture, pH, organic and total carbon, nitrogen, sulfur, electrical conductivity, bulk density and calcium carbonate. A Cubist model was used to predict the remaining samples based on the MIR spectra. We then modelled digital soil mapping with machine learning methods (ensemble learning, linear regression, decision trees) for these soil components. Additionally, we mapped the soil depth using the information collected in the field. This dataset can help any researcher regarding soil information, forming a unique regional database.The observations in this dataset were made on the field during the 2022 and 2023 campaigns. The depth of the soil was measured until the bedrock or sedimental material (eg. slope deposit, alluvial fan). The Blake and Hartge 1986 method was used during dry sampling for the bulk density in top soil (0 - 5 cm), and units are in g/cm3.
DOI: 10.57754/fdat.0be43-86f79
title: Soil information in Kurdistan region, Dohuk governorate (Iraq)

description: This data set is made of eight consists of eight parts containing the maps, scripts, raw data, different parts containing the maps, scripts, raw data and predictions of soil information collected between 2017 and 2023 in the Dohuk governorate of the Kurdistan region of Iraq. This is the supplementary deposit to the paper Soil information in Kurdistan region, Dohuk governorate (Iraq).
A graph describes the entire workflow, and a .csv file contains a list of all the data produced. An additional list with all covariates used is also presented in a .csv file.
Additional visualisation of the final maps computed here can be found at  https://mathias-bellat.shinyapps.io/Northern-Kurdistan-map/
DOI: 10.15468/dl.cp74r6
title: Occurrence Download

description: A dataset containing 177 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Month is one of (June, July, August)",
 "OccurrenceStatus is Present",
 "TaxonKey is Vermivora cyanoptera Olson & Reveal, 2009"
 ]
}

 The dataset includes 177 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000618-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.45rwnu
title: Occurrence Download

description: A dataset containing 278 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Santa Barbara Museum of Natural History - Invertebrate Zoology",
 "TaxonKey is Pycnogonida"
 ]
}

 The dataset includes 278 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000622-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9c4pmp
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "TaxonKey is Peltospira J.H.McLean, 1989"
 ]
}

 The dataset includes 14 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000620-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pzzsze
title: Occurrence Download

description: A dataset containing 6657 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lepomis marginatus (Holbrook, 1855)"
 ]
}

 The dataset includes 6657 records from 53 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000621-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3ekqmt
title: Occurrence Download

description: A dataset containing 213 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "TaxonKey is Cordyceps militaris (L.) Fr."
 ]
}

 The dataset includes 213 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000623-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6352h2
title: Occurrence Download

description: A dataset containing 9517 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Lepomis punctatus (Valenciennes, 1831)"
 ]
}

 The dataset includes 9517 records from 68 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000624-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e3b63v
title: Occurrence Download

description: A dataset containing 101799574 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is North America",
 "Country is United States of America",
 "Month is one of (May, June)",
 "Year 2015-2020"
 ]
}

 The dataset includes 101799574 records from 163 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000598-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/zw7q-z731
title: The Influence Of The Implementation Of The Fire Fighting Education And Training Center (Pusdiklatkar) Website On The Performance Of Fire Fighting Personnel In DKI Jakarta

description: The Influence of the Pusdiklatkar Website Implementation on the Performance of Firefighters in DKI Jakarta This study aims to analyze the impact of implementing the Pusat Pendidikan dan Pelatihan Kebakaran (Pusdiklatkar) website on the performance of firefighters in DKI Jakarta. In the digital era, the utilization of information technology in training and personnel development has become increasingly crucial to enhancing work effectiveness and efficiency. Using a quantitative method, this study adopts a survey approach targeting firefighters who have used the Pusdiklatkar website in their training process. Data were collected through questionnaires distributed to 229 respondents, selected using probability sampling with a simple random sampling technique. The findings indicate that the implementation of the Pusdiklatkar website significantly influences the improvement of personnel performance, particularly in terms of material comprehension, response speed to tasks, and the enhancement of technical skills. Additionally, this study identifies challenges in system implementation, such as technological readiness and users' digital literacy. The implications of this research lead to recommendations for improving the features of the Pusdiklatkar website to better facilitate effective learning and training processes for firefighters. Consequently, this study contributes to the development of digital training systems in the emergency service sector in Indonesia. Keywords:  Website for Performance, IS Success Model, Firefighters, Technology Acceptance Model
DOI: 10.25383/city.28592924
title: The specificity of Statistical Learning

description: Experiments, data and analysis scripts for Endress & de Seyssel, The specificity of Statistical Learning, published in <i>Cognition</i>
DOI: 10.25383/city.28592924.v1
title: The specificity of Statistical Learning

description: Experiments, data and analysis scripts for Endress & de Seyssel, The specificity of Statistical Learning, published in <i>Cognition</i>
DOI: 10.5281/zenodo.13922491
title: Hindawi XML Corpus - 2 April, 2024

description: [ The original description of the XML corpus is provided below.]In order to facilitate the use of Hindawi’s content for data mining purposes, Hindawi makes its full corpus of XML content available for download as a single .zip file. This .zip file is organized using a two-level folder structure, first by publication year, then by journal. For example, the folder called "2011" contains subfolders for any journal that has one or more published articles in 2011, and inside each of these folders are individual XML files for these articles. In addition, the downloaded .zip file contains an XML file called contents.xml, which provides an overview of all of the subfolders that exist within the main .zip file.

The content of this .zip file is updated on a daily basis, and the XML files contained within this corpus download adhere to the JATS 1.1 DTD. If you have questions about Hindawi’s XML corpus download, please contact help@hindawi.com.[ This corpus is no longer updated or hosted publicly by Wiley. This copy was downloaded on April 2, 2024. ]
DOI: 10.5281/zenodo.13922492
title: Hindawi XML Corpus - 2 April, 2024

description: [ The original description of the XML corpus is provided below.]In order to facilitate the use of Hindawi’s content for data mining purposes, Hindawi makes its full corpus of XML content available for download as a single .zip file. This .zip file is organized using a two-level folder structure, first by publication year, then by journal. For example, the folder called "2011" contains subfolders for any journal that has one or more published articles in 2011, and inside each of these folders are individual XML files for these articles. In addition, the downloaded .zip file contains an XML file called contents.xml, which provides an overview of all of the subfolders that exist within the main .zip file.

The content of this .zip file is updated on a daily basis, and the XML files contained within this corpus download adhere to the JATS 1.1 DTD. If you have questions about Hindawi’s XML corpus download, please contact help@hindawi.com.[ This corpus is no longer updated or hosted publicly by Wiley. This copy was downloaded on April 2, 2024. ]