cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17870/bathspa.30146080
title: word-process-object_3

description: <i>word-process-object</i> was a two-day, practice-based symposium hosted by the Material:Making group of the Art Research Centre, Bath School of Art, Film and Media.Locksbrook Campus Thursday 22 - Friday 23 June (10:00 – 19:00)The symposium was organised by Dr Conor Wilson and grew out of his research project, <i>Random Precision Amendments</i>. The aim of the symposium was to share knowledge and research methods that address language/text as material and relationships between image/object and text.The symposium involved a total of twelve participants, including four workshop leads, staff from a number of different disciplines across the University, external guests and a PGR student.Workshop leads were:Dr Sally O’Reilly (Royal College of Art)Barrie Tullett (University of Lincoln)Astra Papachristodoulou (University of Surrey)Dr Conor Wilson (BSU)The symposium was supported through the BSU central HEQR fund and attendance was free for participants.
DOI: 10.17870/bathspa.30146080.v1
title: word-process-object_3

description: <i>word-process-object</i> was a two-day, practice-based symposium hosted by the Material:Making group of the Art Research Centre, Bath School of Art, Film and Media.Locksbrook Campus Thursday 22 - Friday 23 June (10:00 – 19:00)The symposium was organised by Dr Conor Wilson and grew out of his research project, <i>Random Precision Amendments</i>. The aim of the symposium was to share knowledge and research methods that address language/text as material and relationships between image/object and text.The symposium involved a total of twelve participants, including four workshop leads, staff from a number of different disciplines across the University, external guests and a PGR student.Workshop leads were:Dr Sally O’Reilly (Royal College of Art)Barrie Tullett (University of Lincoln)Astra Papachristodoulou (University of Surrey)Dr Conor Wilson (BSU)The symposium was supported through the BSU central HEQR fund and attendance was free for participants.
DOI: 10.5281/zenodo.17227435
title: GraphRAG Halal Recommendation System
DOI: 10.5281/zenodo.17227434
title: GraphRAG Halal Recommendation System
DOI: 10.5281/zenodo.13306684
title: Material for LORA paper (Veillonella Parvula case)

description: Veillonella dataset

LORA is a LO Read assembly pipeline part of Sequana (https://github.com/sequana/lora)

This dataset corresponds to the Veillonella isolate used in the LORA paper to illustrate bacterial genome assembly from long-read sequencing data.

The raw sequencing data originate from the study available at:🔗 PubMed 32817093

Specifically, the dataset is associated with the SRA run:

ERR3958992

In the original study, sequencing was performed on a PacBio Sequel II platform. The available files in the SRA project contain only raw subreads in FASTQ format. According to the authors, subreads were used without CCS construction. 

For the LORA paper, we aimed to generate higher-quality CCS reads using a minimum of 3 passes and RQ ≥ 70%, which required access to the original subreads BAM file. This BAM file was kindly provided by the authors and is shared here to ensure full reproducibility of our analysis.

For convenience, we provide the following files:





m54091_180306_141024.subreads.fastq.gz — FASTQ file equivalent to the SRA data from the publication. This file contains 338,310 reads.




veillonella.subreads.bam — Original PacBio subreads in BAM format, which generated the data referenced in the  publication.




veillonella.ccs.bam — CCS (Circular Consensus Sequencing) reads generated from the subreads with the following parameters:





Minimum read quality (RQ): 0.7




Minimum number of passes: 0These settings produce CCS reads with relatively few passes.



 




veillonella.ccs.fastq.gz — FASTQ version of the above CCS dataset, provided for convenience.



These data files enable reproducibility of the analyses presented in the LORA paper and can be reused for independent benchmarking or assembly studies.
DOI: 10.5281/zenodo.13306683
title: Material for LORA paper (Veillonella Parvula case)

description: Veillonella dataset

LORA is a LO Read assembly pipeline part of Sequana (https://github.com/sequana/lora)

This dataset corresponds to the Veillonella isolate used in the LORA paper to illustrate bacterial genome assembly from long-read sequencing data.

The raw sequencing data originate from the study available at:🔗 PubMed 32817093

Specifically, the dataset is associated with the SRA run:

ERR3958992

In the original study, sequencing was performed on a PacBio Sequel II platform. The available files in the SRA project contain only raw subreads in FASTQ format. According to the authors, subreads were used without CCS construction. 

For the LORA paper, we aimed to generate higher-quality CCS reads using a minimum of 3 passes and RQ ≥ 70%, which required access to the original subreads BAM file. This BAM file was kindly provided by the authors and is shared here to ensure full reproducibility of our analysis.

For convenience, we provide the following files:





m54091_180306_141024.subreads.fastq.gz — FASTQ file equivalent to the SRA data from the publication. This file contains 338,310 reads.




veillonella.subreads.bam — Original PacBio subreads in BAM format, which generated the data referenced in the  publication.




veillonella.ccs.bam — CCS (Circular Consensus Sequencing) reads generated from the subreads with the following parameters:





Minimum read quality (RQ): 0.7




Minimum number of passes: 0These settings produce CCS reads with relatively few passes.



 




veillonella.ccs.fastq.gz — FASTQ version of the above CCS dataset, provided for convenience.



These data files enable reproducibility of the analyses presented in the LORA paper and can be reused for independent benchmarking or assembly studies.
DOI: 10.5281/zenodo.17226345
title: Intactness from HMI
DOI: 10.5281/zenodo.17226346
title: Intactness from HMI
DOI: 10.5281/zenodo.17187084
title: Fortifying NLP models - dataset + code

description: Dataset and software for the paper:

@article{ferdinan2025fortifying,
  title={Fortifying nlp models against poisoning attacks: The power of personalized prediction architectures},
  author={Ferdinan, Teddy and Koco{\'n}, Jan},
  journal={Information Fusion},
  volume={114},
  pages={102692},
  year={2025},
  publisher={Elsevier}
}
DOI: 10.5281/zenodo.17187085
title: Fortifying NLP models - dataset + code

description: Dataset and software for the paper:

@article{ferdinan2025fortifying,
  title={Fortifying nlp models against poisoning attacks: The power of personalized prediction architectures},
  author={Ferdinan, Teddy and Koco{\'n}, Jan},
  journal={Information Fusion},
  volume={114},
  pages={102692},
  year={2025},
  publisher={Elsevier}
}
DOI: 10.6084/m9.figshare.30200242
title: SUPPLEMENTAL MATERIAL.pdf

description: Changes in muscle sympathetic nerve activity (MSNA) based on sympathetic burst incidence before and after training intervention (running, cycling, and sedentary control) during head-down rotation (HDR).
DOI: 10.6084/m9.figshare.30200242.v1
title: SUPPLEMENTAL MATERIAL.pdf

description: Changes in muscle sympathetic nerve activity (MSNA) based on sympathetic burst incidence before and after training intervention (running, cycling, and sedentary control) during head-down rotation (HDR).
DOI: 10.20387/bonares-kztq-2h96
title: Agricultural management events at the SUSALPS sites Fendt, Graswang, Rottenbuch and Esterberg 2019-2023

description: The dataset contains slurry analysis results from laboratory tests conducted by the commercial lab Raiffeisen Laborservice, Raiffeisen Rhein-Ahr-Eifel Handelsgesellschaft mbH, Im Mühlenfeld 22–28, 53881 Euskirchen, Germany. The slurry was applied to intensively and extensively managed lysimeters and mesocosms located in Graswang, Fendt, Rottenbuch, and Esterberg during manuring events between 2019 and 2023. The dataset includes application dates as well as measurements of overall dry matter, dry matter content (%), total carbon, total nitrogen (N), organic N, ammonium N, phosphate, and pH.

Research domain: Soil Sciences

Research question: The data set contains fundamental information for
environmental sciences and, thus, serves as the base for many research
questions. The fundamental research question in SUSALPS is how
mountainous grassland can be managed in a sustainable way in a changing
climate.
DOI: 10.34740/kaggle/dsv/13218088
title: Fictional Client Demographics for Clustering
DOI: 10.7910/dvn/chktsx
title: University of Ibadan {UI}, 2025/2026 Admission List (1st & 2nd) is Out☎07081101151)(07081101151 DR Lilian Ojukwu for Admission Help into Third and Final Batch Call Registrar :07081101151 To check your admission status on the Admission List, Processing Of Admission Into Any Department And Purchasing Of 2025/2026 Last Supplementary Form For New Student Into Any Program, call the School's Admissions Office now on 07081101151.

description: University of Ibadan {UI}, 2025/2026 Admission List (1st & 2nd) is Out☎07081101151)(07081101151 DR Lilian Ojukwu for Admission Help into Third and Final Batch Call Registrar :07081101151 To check your admission status on the Admission List, Processing Of Admission Into Any Department And Purchasing Of 2025/2026 Last Supplementary Form For New Student Into Any Program, call the School's Admissions Office now on 07081101151.
description: University of Ibadan {UI}, 2025/2026 Admission List (1st & 2nd) is Out☎07081101151)(07081101151 DR Lilian Ojukwu for Admission Help into Third and Final Batch Call Registrar :07081101151 To check your admission status on the Admission List, Processing Of Admission Into Any Department And Purchasing Of 2025/2026 Last Supplementary Form For New Student Into Any Program, call the School's Admissions Office now on 07081101151.
DOI: 10.17632/8tty62wkwt.1
title: Pasenger Transport companies CZE-AUT

description: Data for Austrian companies will be sourced from the ORBIS (Bureau van Dijk) database, while data for Czech companies will be drawn from the MagnusWeb (Dun & Bradstreet Czech Republic, a.s.) database. When necessary, data were cross-referenced and validated using annual reports from the Register of Deeds, particularly in cases of extreme values or missing information.
We collected data for companies that published their reports and were active more than 3 years in the period of 2015 and 2019. These five years were selected as a the most distant period in time for the Czech companies as the first one started to operate in 2011 and others joined in years to come with Arriva in 2013. We wanted the companies to be somewhat established as most of the Austrian non-incumbent Companies were already longer in the market.
Table 1: Overview of Passenger Railway Companies (2015-2019)
COMPANY OBSERVATIONS SERVICES
Czech companies
České dráhy, a.s. 5 (2015-2019) Passenger
ARRIVA vlaky s.r.o. 5 (2015-2019) Passenger
CityRail, a.s. 5 (2015-2019) Mixed
GW Train Regio a.s. 4 (2016-2019) Passenger
Jindřichohradecké místní dráhy, a.s. 5 (2015-2019) Passenger
Leo Express Global a.s. 5 (2015-2019) Passenger
RegioJet a.s. 5 (2015-2019) Passenger
Austrian companies
Innsbrucker Verkehrsbetriebe 
und Stubaitalbahn GmbH 5 (2015-2019) Passenger
Lokalbahn Mixnitz-St. Erhard AG 5 (2015-2019) Mixed
Montafonerbahn AG 5 (2015-2019) Passenger
ÖBB-Personenverkehr Aktiengesellschaft 5 (2015-2019) Passenger
Salzburg AG fuer Energie, Verkehr 
und Telekommunikation 5 (2015-2019) Passenger
Stern & Hafferl 
Verkehrsgesellschaft M.B.H. 5 (2015-2019) Passenger
WESTbahn Management GmbH 5 (2015-2019) Passenger
Wiener Lokalbahnen GmbH 5 (2015-2019) Passenger
Zillertaler Verkehrsbetriebe AG 5 (2015-2019) Passenger
DOI: 10.17632/pdzp4c5t5s
title: Geospatial Dataset for Spatial Heterogeneity Assessment of Gully Erosion in Northeast China's Black Soil Region Using GWR,and TOPSIS Models

description: This dataset provides geospatial data for assessing the spatial heterogeneity of gully erosion in the black soil region of Northeast China, specifically focusing on the Songnen Plain area. It includes measurements and derived indicators from 2525 gully samples, extracted using multi-source remote sensing data. This dataset was compiled as part of a research manuscript titled "An Integrated Framework for Assessing Spatial Heterogeneity of Gully Erosion and its Risk Based on GWR and TOPSIS Models in Black Soil Region of Northeast China" and is intended to facilitate replication, validation, and extension of gully erosion studies in similar agricultural ecosystems. The data emphasizes factors like topography , gully morphology, highlighting risks to soil productivity and food security in black soil areas.
Variables and Column Descriptions:
ID: Unique identifier for each gully sample (integer, e.g., 1 to n).

GAS: Slope aspect– Orientation of the slope face, influencing erosion exposure to wind and sun.

GSL: Slope gradient – Steepness of the slope, a key driver of erosion velocity.

ELMIN: Minimum elevation – Lowest elevation point within the gully.

ELMAX: Maximum elevation – Highest elevation point within the gully.

GA: Area – Total planar area of the gully.

TW: Width – Average or maximum width of the gully cross-section.

GP: Perimeter– Perimeter of the gully boundary.

SI: Shape index – A dimensionless index describing gully shape complexity (e.g., ratio of perimeter to area).

V: Volume – Estimated volume of soil displaced by the gully.

GPR: Profile curvature – Curvature along the gully's vertical profile, affecting flow acceleration.

GED: Euclidean distance – Straight-line distance metric, possibly between gully points or to reference features.

L: Gully length– Total length of the gully channel.

TI: Tortuosity index – Measure of gully path sinuosity or deviation from straight line.

LW: Length–width ratio– Ratio of gully length to width, indicating elongation.

GLO: Longitudinal curvature – Curvature along the gully's main axis.

GPL: Plan curvature – Curvature in the horizontal plane, influencing water convergence.

X: X-coordinate – Geographic coordinate for gully centroid or starting point.

Y: Y-coordinate – Geographic coordinate for gully centroid or starting point.

Missing values are denoted as "NA" or empty cells; no imputation was performed to preserve raw integrity.
DOI: 10.17632/pdzp4c5t5s.1
title: Geospatial Dataset for Spatial Heterogeneity Assessment of Gully Erosion in Northeast China's Black Soil Region Using GWR,and TOPSIS Models

description: This dataset provides geospatial data for assessing the spatial heterogeneity of gully erosion in the black soil region of Northeast China, specifically focusing on the Songnen Plain area. It includes measurements and derived indicators from 2525 gully samples, extracted using multi-source remote sensing data. This dataset was compiled as part of a research manuscript titled "An Integrated Framework for Assessing Spatial Heterogeneity of Gully Erosion and its Risk Based on GWR and TOPSIS Models in Black Soil Region of Northeast China" and is intended to facilitate replication, validation, and extension of gully erosion studies in similar agricultural ecosystems. The data emphasizes factors like topography , gully morphology, highlighting risks to soil productivity and food security in black soil areas.
Variables and Column Descriptions:
ID: Unique identifier for each gully sample (integer, e.g., 1 to n).

GAS: Slope aspect– Orientation of the slope face, influencing erosion exposure to wind and sun.

GSL: Slope gradient – Steepness of the slope, a key driver of erosion velocity.

ELMIN: Minimum elevation – Lowest elevation point within the gully.

ELMAX: Maximum elevation – Highest elevation point within the gully.

GA: Area – Total planar area of the gully.

TW: Width – Average or maximum width of the gully cross-section.

GP: Perimeter– Perimeter of the gully boundary.

SI: Shape index – A dimensionless index describing gully shape complexity (e.g., ratio of perimeter to area).

V: Volume – Estimated volume of soil displaced by the gully.

GPR: Profile curvature – Curvature along the gully's vertical profile, affecting flow acceleration.

GED: Euclidean distance – Straight-line distance metric, possibly between gully points or to reference features.

L: Gully length– Total length of the gully channel.

TI: Tortuosity index – Measure of gully path sinuosity or deviation from straight line.

LW: Length–width ratio– Ratio of gully length to width, indicating elongation.

GLO: Longitudinal curvature – Curvature along the gully's main axis.

GPL: Plan curvature – Curvature in the horizontal plane, influencing water convergence.

X: X-coordinate – Geographic coordinate for gully centroid or starting point.

Y: Y-coordinate – Geographic coordinate for gully centroid or starting point.

Missing values are denoted as "NA" or empty cells; no imputation was performed to preserve raw integrity.
DOI: 10.17632/rfvjs3kgy7
title: Supplementary information files: Transcriptomic Analysis Reveals the Metabolic Changes in the Liver, Subcutaneous Adipose and Mammary Gland Tissues During the Process of Conjugated Linoleic Acid-Induced Milk Fat Depression in Dairy Cows

description: Supplymentary information files for the article “Transcriptomic Analysis Reveals the Metabolic Changes in the Liver, Subcutaneous Adipose and Mammary Gland Tissues During the Process of Conjugated Linoleic Acid-Induced Milk Fat Depression in Dairy Cows”
DOI: 10.6084/m9.figshare.30246487
title: Export Quality, Employment (Skill level and aggregate) and other variables dataset for research article titled - Dual Edge of Export Quality: Does it Boost Employment? Insights from OECD and G20 Countries

description: The analysis has been carried out for a sample of 45 countries belonging to the G20 and OECD for the period–1990-2022. For skill level analysis, the data is available for 33 countries for low-, high-, and semi-skill employment. For low- and high-skill employment, data is available for 1995-2022. The employment datasets are obtained from the International Labour Organization (ILO) website and export quality indicators from the International Monetary Fund (IMF) online database website. The datasets on R&D, FDI, Gross Fixed capital formation, Medium and high technology exports, ICT indicators, and export unit value index are obtained from the World Bank’s World Development Indicators (WDI) and average Tariff data from the World Integrated Trade Solution (WITS) website.
DOI: 10.6084/m9.figshare.30246487.v1
title: Export Quality, Employment (Skill level and aggregate) and other variables dataset for research article titled - Dual Edge of Export Quality: Does it Boost Employment? Insights from OECD and G20 Countries

description: The analysis has been carried out for a sample of 45 countries belonging to the G20 and OECD for the period–1990-2022. For skill level analysis, the data is available for 33 countries for low-, high-, and semi-skill employment. For low- and high-skill employment, data is available for 1995-2022. The employment datasets are obtained from the International Labour Organization (ILO) website and export quality indicators from the International Monetary Fund (IMF) online database website. The datasets on R&D, FDI, Gross Fixed capital formation, Medium and high technology exports, ICT indicators, and export unit value index are obtained from the World Bank’s World Development Indicators (WDI) and average Tariff data from the World Integrated Trade Solution (WITS) website.
DOI: 10.17632/rfvjs3kgy7.1
title: Supplementary information files: Transcriptomic Analysis Reveals the Metabolic Changes in the Liver, Subcutaneous Adipose and Mammary Gland Tissues During the Process of Conjugated Linoleic Acid-Induced Milk Fat Depression in Dairy Cows

description: Supplymentary information files for the article “Transcriptomic Analysis Reveals the Metabolic Changes in the Liver, Subcutaneous Adipose and Mammary Gland Tissues During the Process of Conjugated Linoleic Acid-Induced Milk Fat Depression in Dairy Cows”
DOI: 10.17632/p2cnk99rjs.1
title: CEL truncation mutant unveils lipotoxicity induced β-cell demise

description: This study demonstrates that a truncating mutation in CEL results in loss of lipolytic function and accumulation of mutant protein (MUT CEL) in acinar cells.
DOI: 10.17632/j5rcsr9698
title: The Moon's formation time recorded in lunar mare basalts

description: The Moon’s formation time is a key factor for understanding the early evolution of the Earth-Moon system. The lunar magma ocean (LMO) model explains how cumulate mafic materials crystallizing from the LMO form the source of mare basalts (SMB). If the magma ocean was well-stirred, cumulates from it should share an identical initial Pb isotope signature (PbSMB). Because Pb is volatile while U is refractory, PbSMB can provide constraints for the timing of volatile depletion, most likely dating the time of Moon formation via a giant impact into the proto-Earth. The PbSMB is a link between the initial Pb composition of lunar mare basalts and the Moon's early evolution via a two-stage Pb evolution model that provides a simplified but informative framework. Using four mare basalts with well-constrained ages and initial Pb isotopic compositions, we determine the Moon’s formation time at 4516 (-18/+21) Ma and the SMB solidification time at 4377(-27/+57) Ma. Our modelling strategy facilitates the dating of mare basalt fragments lacking Zr-bearing minerals using the initial Pb isotopic compositions constrained by U-poor minerals. This work sheds light on the early evolution of the Moon and taps the potential capacity in chronological studies of mare basalts.
DOI: 10.17632/j5rcsr9698.2
title: The Moon's formation time recorded in lunar mare basalts

description: The Moon’s formation time is a key factor for understanding the early evolution of the Earth-Moon system. The lunar magma ocean (LMO) model explains how cumulate mafic materials crystallizing from the LMO form the source of mare basalts (SMB). If the magma ocean was well-stirred, cumulates from it should share an identical initial Pb isotope signature (PbSMB). Because Pb is volatile while U is refractory, PbSMB can provide constraints for the timing of volatile depletion, most likely dating the time of Moon formation via a giant impact into the proto-Earth. The PbSMB is a link between the initial Pb composition of lunar mare basalts and the Moon's early evolution via a two-stage Pb evolution model that provides a simplified but informative framework. Using four mare basalts with well-constrained ages and initial Pb isotopic compositions, we determine the Moon’s formation time at 4516 (-18/+21) Ma and the SMB solidification time at 4377(-27/+57) Ma. Our modelling strategy facilitates the dating of mare basalt fragments lacking Zr-bearing minerals using the initial Pb isotopic compositions constrained by U-poor minerals. This work sheds light on the early evolution of the Moon and taps the potential capacity in chronological studies of mare basalts.
DOI: 10.17632/k7pck5hmcm
title: H&M Indonesia_Google Play Store Review Dataset

description: This dataset contains 1,975 customer reviews of H&M application from 2020 until first quarter of 2025, collected through web scraping from the Google Play Store. The data was gathered to analyze preferences and factors influencing customer satisfaction, aiming to provide strategic recommendations for H&M. This dataset can be used for research in application optimization based on customer preference.
DOI: 10.17632/k7pck5hmcm.1
title: H&M Indonesia_Google Play Store Review Dataset

description: This dataset contains 1,975 customer reviews of H&M application from 2020 until first quarter of 2025, collected through web scraping from the Google Play Store. The data was gathered to analyze preferences and factors influencing customer satisfaction, aiming to provide strategic recommendations for H&M. This dataset can be used for research in application optimization based on customer preference.
DOI: 10.17632/3d85sw6mhg
title: AI_Communication Student

description: The dataset is about the perceptions of Communication Students' on AI in general and AI in media use.