cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7326480
title: PROCRAFT_Form C_Morane Saulnier 733_B1-1C1

description: Results of scientific analyses on a part collected from a Morane Saulnier wreck (See PROCRAFT_Form A_Morane Saulnier 733_Toulouse) : analysis of alloy, paint and primer layers.
description: Paint Primer
DOI: 10.5281/zenodo.7263586
title: PROCRAFT_Form B_P38-Lightning-Laval_B159-2

description: Information and condition state of a propeller from the P38 Lightning (Lockheed) which crashed near Laval (See PROCRAFT_Form A_P38-Lightning -Laval)
description: American
DOI: 10.5281/zenodo.7263585
title: PROCRAFT_Form B_P38-Lightning-Laval_B159-2

description: Information and condition state of a propeller from the P38 Lightning (Lockheed) which crashed near Laval (See PROCRAFT_Form A_P38-Lightning -Laval)
description: American
DOI: 10.5281/zenodo.7319047
title: PROCRAFT_Form B_Latécoère 298_Fougax_B2

description: Information and condition state of a part from the Latécoère 298 wreck (related to PROCRAFT_Form A_Latécoère 298_Fougax)
description: Paint and primer
DOI: 10.5281/zenodo.7113385
title: PROCRAFT_Form B_Latécoère 298_Fougax_B2

description: Information and condition state of a part from the Latécoère 298 wreck (related to PROCRAFT_Form A_Latécoère 298_Fougax)
description: Paint and primer
DOI: 10.15131/shef.data.21559671
title: Air pollution concentrations in Sheffield, UK - green barrier in school playground study

description: A green barrier was installed in a case study school in Sheffield, UK. This dataset shows the air pollution concentration pre and post such GI intervention at the case study school (Sch-GB site) and at two other sites serving as control for data comparison and contrast. The control sites are located within a 2 km radius from Sch-GB, and comprise a site in the city centre (City site) – providing an urban background – and another school playground without a green barrier (Sch-NoGB site). <br> The dataset show pollution concentrations as monitored by the air quality equipment, and corrected concentrations after data de-seasonalisation.
DOI: 10.6084/m9.figshare.21564030
title: Data for ALS analysis of moose on forest structure across a network of exclosures in boreal forests

description: This dataset includes (1) metadata for a network of moose exclosures across the boreal biome (2) a metadata template that describes the variables in the metadata. (3) LIDAR metrics calculated for each open plot and exclosure. Note that the coordinates of the exclosures in Finland are withheld due to conservation concerns. Contact Jari Kouki for details regarding these.
DOI: 10.6084/m9.figshare.21564363.v2
title: Bathymetry data of glacial lakes in the Himalaya

description: Bathymetry data of glacial lakes in the Himalaya: Raster interpolated by using Kriging geo-statistics method
DOI: 10.34740/kaggle/dsv/4523138
title: YouTube Daily
DOI: 10.5282/ubm/data.338
title: Supplementary data from: Steroid profiling using liquid chromatography mass spectrometry during adrenal vein sampling in patients with primary bilateral macronodular adrenocortical hyperplasia (PBMAH)
DOI: 10.6084/m9.figshare.21564513
title: Belief in Animal Sentience and Affective Owner Attitudes are Linked to Positive Working Equid Welfare across Six Countries Dataset

description: Accompanying Dataset to the paper 'Belief in Animal Sentience and Affective Owner Attitudes are Linked to Positive Working Equid Welfare across Six Countries'.
DOI: 10.6084/m9.figshare.21564513.v1
title: Belief in Animal Sentience and Affective Owner Attitudes are Linked to Positive Working Equid Welfare across Six Countries Dataset

description: Accompanying Dataset to the paper 'Belief in Animal Sentience and Affective Owner Attitudes are Linked to Positive Working Equid Welfare across Six Countries'.
DOI: 10.5281/zenodo.6256917
title: Virtual cohort of fetal cases with suspected coarctation of the aorta from fetal three-dimensional magnetic resonance images

description: The present dataset is a supplementary dataset to the paper: Hermida, U., van Poppel, M.P.M., Lloyd, D.F.A. <em>et al.</em> Learning the Hidden Signature of Fetal Arch Anatomy: a Three-Dimensional Shape Analysis in Suspected Coarctation of the Aorta. <em>J. of Cardiovasc. Trans. Res.</em> (2022). https://doi.org/10.1007/s12265-022-10335-9 <strong>Dataset Description: </strong> We present a database of fetal great arch anatomical models derived from a statistical shape model (SSM) of fetuses with suspected coarctation of the aorta (CoA). The dataset consists of 1000 meshes including the fetal ascending aorta, arterial duct and descending aorta. For each synthetic case, the corresponding PCA coefficients for the 10 first PCA modes, as well as their CoA risk score, are shared. PCA scores are provided both as raw scores and Z-scores. To build the SSM, a dataset of 112 motion-corrected 3D fetal cardiovascular magnetic resonance (CMR) images and their corresponding segmentations from cases with suspected CoA was used. Data included confirmed CoA cases as well as false positive (FP) cases. Centerlines were extracted and aligned to build the SSM of the fetal great arches. <strong>Source of funding</strong> This work was supported by the Wellcome Trust IEH Award [102431] (iFIND project), by core funding from the Wellcome/EPSRC Centre for Medical Engineering [WT203148/Z/16/Z] and by the Rosetrees Trust [A2725]. The research was funded by the National Institute for Health Research (NIHR) Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London and supported by the NIHR Clinical Research Facility. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. D.F.A. Lloyd acknowledges support from the Rothschild Foundation (2020/2017). P. Lamata holds a Wellcome Trust Senior Research Fellowship (209450/Z/17/Z).
description: {"references": ["Lloyd, D. F. et al. (2021). \"Analysis of 3-dimensional arch anatomy, vascular flow, and postnatal outcome in cases of suspected coarctation of the aorta using fetal cardiac magnetic resonance imaging\". Circulation: Cardiovascular Imaging July, pp. 583\u2013593. DOI: 10.1161/CIRCIMAGING.121.012411.", "Hermida, U., van Poppel, M.P.M., Lloyd, D.F.A. et al. Learning the Hidden Signature of Fetal Arch Anatomy: a Three-Dimensional Shape Analysis in Suspected Coarctation of the Aorta. J. of Cardiovasc. Trans. Res. (2022). https://doi.org/10.1007/s12265-022-10335-9"]}
DOI: 10.5281/zenodo.6256918
title: Virtual cohort of fetal cases with suspected coarctation of the aorta from fetal three-dimensional magnetic resonance images

description: The present dataset is a supplementary dataset to the paper: Hermida, U., van Poppel, M.P.M., Lloyd, D.F.A. <em>et al.</em> Learning the Hidden Signature of Fetal Arch Anatomy: a Three-Dimensional Shape Analysis in Suspected Coarctation of the Aorta. <em>J. of Cardiovasc. Trans. Res.</em> (2022). https://doi.org/10.1007/s12265-022-10335-9 <strong>Dataset Description: </strong> We present a database of fetal great arch anatomical models derived from a statistical shape model (SSM) of fetuses with suspected coarctation of the aorta (CoA). The dataset consists of 1000 meshes including the fetal ascending aorta, arterial duct and descending aorta. For each synthetic case, the corresponding PCA coefficients for the 10 first PCA modes, as well as their CoA risk score, are shared. PCA scores are provided both as raw scores and Z-scores. To build the SSM, a dataset of 112 motion-corrected 3D fetal cardiovascular magnetic resonance (CMR) images and their corresponding segmentations from cases with suspected CoA was used. Data included confirmed CoA cases as well as false positive (FP) cases. Centerlines were extracted and aligned to build the SSM of the fetal great arches. <strong>Source of funding</strong> This work was supported by the Wellcome Trust IEH Award [102431] (iFIND project), by core funding from the Wellcome/EPSRC Centre for Medical Engineering [WT203148/Z/16/Z] and by the Rosetrees Trust [A2725]. The research was funded by the National Institute for Health Research (NIHR) Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London and supported by the NIHR Clinical Research Facility. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. D.F.A. Lloyd acknowledges support from the Rothschild Foundation (2020/2017). P. Lamata holds a Wellcome Trust Senior Research Fellowship (209450/Z/17/Z).
description: {"references": ["Lloyd, D. F. et al. (2021). \"Analysis of 3-dimensional arch anatomy, vascular flow, and postnatal outcome in cases of suspected coarctation of the aorta using fetal cardiac magnetic resonance imaging\". Circulation: Cardiovascular Imaging July, pp. 583\u2013593. DOI: 10.1161/CIRCIMAGING.121.012411.", "Hermida, U., van Poppel, M.P.M., Lloyd, D.F.A. et al. Learning the Hidden Signature of Fetal Arch Anatomy: a Three-Dimensional Shape Analysis in Suspected Coarctation of the Aorta. J. of Cardiovasc. Trans. Res. (2022). https://doi.org/10.1007/s12265-022-10335-9"]}
DOI: 10.5519/qd.ljztki4a
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (77 records)
DOI: 10.5281/zenodo.7326406
title: GLAMI-1M: A Multilingual Image-Text Fashion Dataset

description: We introduce GLAMI-1M: the largest multilingual image-text classification dataset and benchmark. The dataset contains images of fashion products with item descriptions, each in 1 of 13 languages. Categorization into 191 classes has high-quality annotations: all 100k images in the test set and 75% of the 1M training set were human-labeled. The paper presents baselines for image-text classification showing that the dataset presents a challenging fine-grained classification problem: The best scoring EmbraceNet model using both visual and textual features achieves 69.7% accuracy. Experiments with a modified Imagen model show the dataset is also suitable for image generation conditioned on text. The dataset, source code and model checkpoints are published at: https://github.com/glami/glami-1m.
DOI: 10.5281/zenodo.7326405
title: GLAMI-1M: A Multilingual Image-Text Fashion Dataset

description: We introduce GLAMI-1M: the largest multilingual image-text classification dataset and benchmark. The dataset contains images of fashion products with item descriptions, each in 1 of 13 languages. Categorization into 191 classes has high-quality annotations: all 100k images in the test set and 75% of the 1M training set were human-labeled. The paper presents baselines for image-text classification showing that the dataset presents a challenging fine-grained classification problem: The best scoring EmbraceNet model using both visual and textual features achieves 69.7% accuracy. Experiments with a modified Imagen model show the dataset is also suitable for image generation conditioned on text. The dataset, source code and model checkpoints are published at: https://github.com/glami/glami-1m.
DOI: 10.34740/kaggle/dsv/4523236
title: Global Genomic Neurofibromatosis Neoplasia
DOI: 10.25824/redu/abulee
title: Banco de dados.csv
DOI: 10.34740/kaggle/dsv/4523243
title: UNET Lung Segmentation Weights for Chest X Rays
DOI: 10.25824/redu/4ropcf
title: Inputs & outputs of national entrepreneurship ecosystems

description: This is a database that we created by collecting data from 3 different sources, namely: Global Entrepreneurship Monitor (GEM), CrunchBase and CB Insights.
DOI: 10.5517/ccdc.csd.cc270qdd
title: CCDC 2056273: Experimental Crystal Structure Determination

description: Related Article: Anton Bannykh, Ekaterina Levashova, Olga Bakulina, Mikhail Krasavin|2022|Org.Biomol.Chem.|20|8643|doi:10.1039/D2OB01675C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bh1lh
title: CCDC 2159416: Experimental Crystal Structure Determination

description: Related Article: You-Ya Zhang, Lin Li, Ai-Jun Ma, Wei-Feng Wang, Jin-Bao Peng|2022|Org.Biomol.Chem.|20|8633|doi:10.1039/D2OB01903E
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bptgb
title: CCDC 2165922: Experimental Crystal Structure Determination

description: Related Article: Anton Bannykh, Ekaterina Levashova, Olga Bakulina, Mikhail Krasavin|2022|Org.Biomol.Chem.|20|8643|doi:10.1039/D2OB01675C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2c10dv
title: CCDC 2175716: Experimental Crystal Structure Determination

description: Related Article: Radik N. Itakhunov, Ivan S. Odin, Dmitry M. Gusev, Stanislav A. Grabovskiy, Kareem V. Gordon, Anna V. Vologzhanina, Sergey A. Sokov, Ilya M. Sosnin, Alexander A. Golovanov|2022|Org.Biomol.Chem.|20|8693|doi:10.1039/D2OB01427K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2c53ym
title: CCDC 2179670: Experimental Crystal Structure Determination

description: Related Article: Yunfei Yao, Bo Lin, Minze Wu, Yafang Zhang, Yangjie Huang, Xiaoyan Han, Zhiqiang Weng|2022|Org.Biomol.Chem.|20|8761|doi:10.1039/D2OB01749K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.7311723
title: Características de películas y programas de televisión más populares en la base de datos de Imdb

description: Se ha realizado una extracción de datos a través de técnicas de web scraping en la web Imdb, con las películas y programas de televisión más populares distribuidos por género. El dataset cuenta con información referente a las películas y programas de televisión más populares según la comunidad cinéfila de Imdb. Esta información se puede utilizar para clasificar estas películas entre las más votadas, las mejores valoradas, las que más actores aparecen, las se pueden enmarcar en más tipos de géneros o incluso saber el género que presenta las películas peor valoradas. Además, el dataset se ha construido con solo las primeras cincuenta películas más populares de cada género ya que la web contiene más de 2 millones de títulos y no nos interesa tener un dataset tan grande para su posterior tratamiento. Toda la información que se ha recogido se presenta en un fichero CSV para facilitar su posterior limpieza y análisis en la siguiente práctica.
DOI: 10.5281/zenodo.7311722
title: Características de películas y programas de televisión más populares en la base de datos de Imdb

description: Se ha realizado una extracción de datos a través de técnicas de web scraping en la web Imdb, con las películas y programas de televisión más populares distribuidos por género. El dataset cuenta con información referente a las películas y programas de televisión más populares según la comunidad cinéfila de Imdb. Esta información se puede utilizar para clasificar estas películas entre las más votadas, las mejores valoradas, las que más actores aparecen, las se pueden enmarcar en más tipos de géneros o incluso saber el género que presenta las películas peor valoradas. Además, el dataset se ha construido con solo las primeras cincuenta películas más populares de cada género ya que la web contiene más de 2 millones de títulos y no nos interesa tener un dataset tan grande para su posterior tratamiento. Toda la información que se ha recogido se presenta en un fichero CSV para facilitar su posterior limpieza y análisis en la siguiente práctica.
DOI: 10.5281/zenodo.4081140
title: Social contact data before and during COVID-19 in China

description: Social contact data for Wuhan and Shanghai, China before and during the COVID-19 outbreak,
description: {"references": ["Zhang, Juanjuan, et al. \"Changes in contact patterns shape the dynamics of the COVID-19 outbreak in China.\" Science (2020)."]}
DOI: 10.5281/zenodo.7326686
title: Social contact data before and during COVID-19 in China

description: Social contact data for Wuhan and Shanghai, China before and during the COVID-19 outbreak.<br> Changelog for Version 2:<br> - Contact data from outbreak and baseline merged. A variable to distinguish the two ("collection_period") is added to "contact_extra".<br> <br> For problems with the dataset, please contact: socialcontactdata@gmail.com
description: {"references": ["Zhang, Juanjuan, et al. \"Changes in contact patterns shape the dynamics of the COVID-19 outbreak in China.\" Science (2020)."]}
DOI: 10.5281/zenodo.4081139
title: Social contact data before and during COVID-19 in China

description: Social contact data for Wuhan and Shanghai, China before and during the COVID-19 outbreak.<br> Changelog for Version 2:<br> - Contact data from outbreak and baseline merged. A variable to distinguish the two ("collection_period") is added to "contact_extra".<br> <br> For problems with the dataset, please contact: socialcontactdata@gmail.com
description: {"references": ["Zhang, Juanjuan, et al. \"Changes in contact patterns shape the dynamics of the COVID-19 outbreak in China.\" Science (2020)."]}
DOI: 10.34810/data543
title: prova

description: dsd
DOI: 10.5282/ubm/data.336
title: Supplementary data for the article "Differences in land-based mitigation estimates reconciled by separating natural and land-use CO2 fluxes at the country level"

description: This dataset contains supplementary data for the article “Differences in land-based mitigation estimates reconciled by separating natural and land-use CO2 fluxes at the country level”. The dataset includes gridded data and country-level estimates of land use, land-use change, and forestry (LULUCF) fluxes from bookkeeping models, gridded data and country-level estimates of the natural land sink, country-level estimates of LULUCF fluxes from UNFCCC reports, and country-level estimates of forest areas.
DOI: 10.5281/zenodo.7326772
title: Dataset Literature Review Digital Forensic AND Digital Forensics

description: Data ini digunakan untuk membuat penelitian sesuai dengan tinjauan literatur dengan kata kunci "Digital "Forensic" dan "Digital Forensics"
DOI: 10.5281/zenodo.7326771
title: Dataset Literature Review Digital Forensic AND Digital Forensics

description: Data ini digunakan untuk membuat penelitian sesuai dengan tinjauan literatur dengan kata kunci "Digital "Forensic" dan "Digital Forensics"
DOI: 10.34740/kaggle/dsv/4523436
title: Elon Musk Tweets
DOI: 10.5281/zenodo.7326792
title: DataRaw22RodoThesisACSBackgroundCyTOFPreprocess

description: Preprocessed ACS CyTOF data for explanatory purposes for Thesis22Rodo
DOI: 10.5281/zenodo.7326791
title: DataRaw22RodoThesisACSBackgroundCyTOFPreprocess

description: Preprocessed ACS CyTOF data for explanatory purposes for Thesis22Rodo
DOI: 10.34740/kaggle/dsv/4523437
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.34740/kaggle/dsv/4523459
title: 2021 World Population (updated daily)
DOI: 10.5281/zenodo.6832284
title: Land Use - Crop - Climate Scenarios Oudlandpolder

description: Regionalized time series for 2020-2100 with a day resolution based on different combinations of 4 climate RCP (Representative Concentration Pathways) and 4 Shared Social-economic Pathways (SSP) scenarios for the Oudlandpolder region in Belgium. This coastal lowland (polder) faces challenges related to climate adaptation and mitigation to be addressed by, amongst others, a proper balance of water distribution for the two main land use categories: agriculture and nature. The following variables are included: land use cover (agriculture and nature) in ha related to SSP crop fractions for 13 crops related to SSP crop factors Kc (dimensionless) precipitation in mm/day related to RCP potential evapotranspiration in mm/day related to RCP sea level in mm wrt January 1, 2020 related to RCP Waste Water Treatment Plant (WWTP) effluence ratio wrt to 2020 RCP scenarios: RCP 2.6; RCP 4.5; RCP 6.0; RCP 8.5 SSP scenarios: SSP1; SSP2; SSP4; SSP5. These SSP scenarios are based on consistent projections for land use change (agriculture vs nature) and crop schemes. Land use cover change was modelled with the VITO spatial-dynamic RuimteModel (see references below). Uncertainty in the RCP scenarios has been addressed by working with an ensemble of the following 8 climate models: BNU-ESM CSIRO-Mk3-6-0 GFDL-ESM2G GFDL-ESM2M IPSL-CM5A-MR MPI-ESM-LR MPI-ESM-MR NorESM1-M The scenarios point at potential seasonal water shortages for certain combinations of RCP and SSP scenarios, in particular during the dry summer season. Climate adaptation actions can also benefit to a limited extent from identifying the climate robust crop schemes. For further information see: https://h2020-coastal.eu https://h2020-coastal.eu/publications/flipbook/171 https://www.vlm.be/nl/projecten/Paginas/Oudlandpolder.aspx https://vito.be/en/spatial-model-flanders-ruimtemodel-vlaanderen
DOI: 10.5281/zenodo.6832285
title: Land Use - Crop - Climate Scenarios Oudlandpolder

description: Regionalized time series for 2020-2100 with a day resolution based on different combinations of 4 climate RCP (Representative Concentration Pathways) and 4 Shared Social-economic Pathways (SSP) scenarios for the Oudlandpolder region in Belgium. This coastal lowland (polder) faces challenges related to climate adaptation and mitigation to be addressed by, amongst others, a proper balance of water distribution for the two main land use categories: agriculture and nature. The following variables are included: land use cover (agriculture and nature) in ha related to SSP crop fractions for 13 crops related to SSP crop factors Kc (dimensionless) precipitation in mm/day related to RCP potential evapotranspiration in mm/day related to RCP sea level in mm wrt January 1, 2020 related to RCP Waste Water Treatment Plant (WWTP) effluence ratio wrt to 2020 RCP scenarios: RCP 2.6; RCP 4.5; RCP 6.0; RCP 8.5 SSP scenarios: SSP1; SSP2; SSP4; SSP5. These SSP scenarios are based on consistent projections for land use change (agriculture vs nature) and crop schemes. Land use cover change was modelled with the VITO spatial-dynamic RuimteModel (see references below). Uncertainty in the RCP scenarios has been addressed by working with an ensemble of the following 8 climate models: BNU-ESM CSIRO-Mk3-6-0 GFDL-ESM2G GFDL-ESM2M IPSL-CM5A-MR MPI-ESM-LR MPI-ESM-MR NorESM1-M The scenarios point at potential seasonal water shortages for certain combinations of RCP and SSP scenarios, in particular during the dry summer season. Climate adaptation actions can also benefit to a limited extent from identifying the climate robust crop schemes. For further information see: https://h2020-coastal.eu https://h2020-coastal.eu/publications/flipbook/171 https://www.vlm.be/nl/projecten/Paginas/Oudlandpolder.aspx https://vito.be/en/spatial-model-flanders-ruimtemodel-vlaanderen