cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.20318157.v1
title: Data File 1

description: "Data supplementary1.csv" is the data about sensitivity at 5Hz.
DOI: 10.5281/zenodo.6759271
title: Polifonia_Corpus_Pilots_Annotations_Meetups

description: Polifonia_Corpus_Pilots_Annotations_Meetups
DOI: 10.5281/zenodo.6759211
title: Polifonia_Corpus_Periodicals_Annotations_ES

description: Polifonia_Corpus_Periodicals_Annotations_ES
DOI: 10.5281/zenodo.6759230
title: Polifonia_Corpus_Pilots_Annotations_Bells

description: Polifonia_Corpus_Pilots_Annotations_Bells
DOI: 10.5281/zenodo.6759194
title: Polifonia_Corpus_Periodicals_Annotations_DE

description: Polifonia_Corpus_Periodicals_Annotations_DE
DOI: 10.5281/zenodo.6759206
title: Polifonia_Corpus_Periodicals_Annotations_IT

description: Polifonia_Corpus_Periodicals_Annotations_IT
DOI: 10.5281/zenodo.6759229
title: Polifonia_Corpus_Pilots_Annotations_Bells

description: Polifonia_Corpus_Pilots_Annotations_Bells
DOI: 10.5281/zenodo.6759193
title: Polifonia_Corpus_Periodicals_Annotations_DE

description: Polifonia_Corpus_Periodicals_Annotations_DE
DOI: 10.5281/zenodo.6759205
title: Polifonia_Corpus_Periodicals_Annotations_IT

description: Polifonia_Corpus_Periodicals_Annotations_IT
DOI: 10.5281/zenodo.6759188
title: Polifonia_Corpus_Periodicals_Annotations_NL

description: Polifonia_Corpus_Periodicals_Annotations_NL
DOI: 10.5281/zenodo.6759021
title: Polifonia_Corpus_Wikipedia_Annotations_ES

description: Polifonia_Corpus_Wikipedia_Annotations_ES
DOI: 10.5281/zenodo.6759180
title: Polifonia_Corpus_Periodicals_Annotations_FR

description: Polifonia_Corpus_Periodicals_Annotations_FR
DOI: 10.5281/zenodo.6759187
title: Polifonia_Corpus_Periodicals_Annotations_NL

description: Polifonia_Corpus_Periodicals_Annotations_NL
DOI: 10.5281/zenodo.6759020
title: Polifonia_Corpus_Wikipedia_Annotations_ES

description: Polifonia_Corpus_Wikipedia_Annotations_ES
DOI: 10.5281/zenodo.6759179
title: Polifonia_Corpus_Periodicals_Annotations_FR

description: Polifonia_Corpus_Periodicals_Annotations_FR
DOI: 10.5281/zenodo.6759109
title: Polifonia_Corpus_Periodicals_Annotations_EN

description: Polifonia_Corpus_Periodicals_Annotations_EN
DOI: 10.5281/zenodo.6759108
title: Polifonia_Corpus_Periodicals_Annotations_EN

description: Polifonia_Corpus_Periodicals_Annotations_EN
DOI: 10.5281/zenodo.6759025
title: Polifonia_Corpus_Wikipedia_Annotations_FR

description: Polifonia_Corpus_Wikipedia_Annotations_FR
DOI: 10.5281/zenodo.6759017
title: Polifonia_Corpus_Wikipedia_Annotations_IT

description: Polifonia_Corpus_Wikipedia_Annotations_IT
DOI: 10.5281/zenodo.6759024
title: Polifonia_Corpus_Wikipedia_Annotations_FR

description: Polifonia_Corpus_Wikipedia_Annotations_FR
DOI: 10.5281/zenodo.6759016
title: Polifonia_Corpus_Wikipedia_Annotations_IT

description: Polifonia_Corpus_Wikipedia_Annotations_IT
DOI: 10.5281/zenodo.6757537
title: Polifonia_Corpus_Wikipedia_Annotations_NL

description: Polifonia_Corpus_Wikipedia_Annotations_NL
DOI: 10.5281/zenodo.6757536
title: Polifonia_Corpus_Wikipedia_Annotations_NL

description: Polifonia_Corpus_Wikipedia_Annotations_NL
DOI: 10.5281/zenodo.6838716
title: Si /Pb(111)

description: Silicon clusters on the Pb(111) surface.
DOI: 10.5281/zenodo.6838715
title: Si /Pb(111)

description: Silicon clusters on the Pb(111) surface.
DOI: 10.5281/zenodo.6834906
title: Data on the detection of clinically significant prostate cancer by magnetic resonance imaging (MRI)-guided targeted and systematic biopsy

description: This is a dataset from the original publication “Reasons for missing clinically significant prostate cancer by targeted magnetic resonance imaging/ultrasound fusion-guided biopsy”. From 01/2014 to 04/2019 a sample collective of 785 patients with 3T multiparametric magnetic resonance imaging (mp-MRI) of the prostate and subsequent combined systematic biopsy (SB) and magnetic resonance imaging/ultrasound (US) fusion-guided biopsy (TB) was retrospectively analyzed. Prostate carcinoma (PCa) detection by TB and/or additional SB was analyzed.
description: Related research article: Klingebiel M., Arsov C., Ullrich T., Quentin M., Al-Monajjed R., Mally D., Sawicki L.M., Hiester A., Esposito I., Albers P., Antoch G., Schimmöller L., Reasons for missing clinically significant prostate cancer by targeted magnetic resonance imaging/ultrasound fusion-guided biopsy, Eur J Radiol. 2021 Apr;137:109587. DOI: 10.1016/j.ejrad.2021.109587
DOI: 10.5281/zenodo.6834905
title: Data on the detection of clinically significant prostate cancer by magnetic resonance imaging (MRI)-guided targeted and systematic biopsy

description: This is a dataset from the original publication “Reasons for missing clinically significant prostate cancer by targeted magnetic resonance imaging/ultrasound fusion-guided biopsy”. From 01/2014 to 04/2019 a sample collective of 785 patients with 3T multiparametric magnetic resonance imaging (mp-MRI) of the prostate and subsequent combined systematic biopsy (SB) and magnetic resonance imaging/ultrasound (US) fusion-guided biopsy (TB) was retrospectively analyzed. Prostate carcinoma (PCa) detection by TB and/or additional SB was analyzed.
description: Related research article: Klingebiel M., Arsov C., Ullrich T., Quentin M., Al-Monajjed R., Mally D., Sawicki L.M., Hiester A., Esposito I., Albers P., Antoch G., Schimmöller L., Reasons for missing clinically significant prostate cancer by targeted magnetic resonance imaging/ultrasound fusion-guided biopsy, Eur J Radiol. 2021 Apr;137:109587. DOI: 10.1016/j.ejrad.2021.109587
DOI: 10.5281/zenodo.6838651
title: Training and validation data for artificial neural networks using three-dimensional partial convolutions to fill gaps in satellite image time series

description: This dataset contains training and validation data for artificial neural networks using three-dimensional partial convolutions to fill gaps in satellite image time series. The data have been derived from Sentinel-5P total column carbon monoxide observations, using the offline processing stream. <strong>Preprocessing</strong> The following operations have been applied on the original S5P imagery: Images have been resampled to 0.1 by 0.1 degree spatial resolution Pixels with quality assessment value less than or equal to 0.5 have been set to NA Images have been aggregated by day of observation Images have been cropped to -60 to 60 degrees latitude Images have been devided into spatiotemporal blocks of size 128 x 128 pixels and 16 days Imagery has been recorded between 2021-01-01 and 2021-11-25. Notice that both the training and the validation blocks have been randomly sampled from all available blocks. <br> <strong>Data Format and Naming Conventions</strong> Input and output data blocks are stored as GeoTIFF files, where bands represent time. Notice the following file naming conventions: Files starting with <em>X</em> represent input measurements for training, where artificial gaps have been added. Files starting with <em>Y</em> represent true measurements without artificially added gaps (but still containing gaps in many cases). Binary masks of input data where all pixels with valid measurements are 1 and others 0 are stored in files whose name starts with <em>MASK</em> Files starting with <em>VALMASK</em> contain a binary mask where only pixels that are available in Y but not in X are 1. The latter is used for validation on artificially removed pixels only. Numbers in filenames encode spatial and temporal block indexes. In addition, the dataset contains prediction of the validation blocks from different models in the `predictions` directory. The subfolders contain output from different models: mean refers to simple block-wise mean predictions. timeseries refers to simple linear time series interpolation. gapfill refers to the method proposed in [1]. stmra refers to the method proposed in [2]. STpconv refers to predictions passed on an artificial neural netowork with three-dimensional partial convolutions. <strong>References</strong> [1] Gerber, F., de Jong, R., Schaepman, M. E., Schaepman-Strub, G., & Furrer, R. (2018). Predicting missing values in spatio-temporal remote sensing data. IEEE Transactions on Geoscience and Remote Sensing, 56(5), 2841-2853. [2] Appel, M., & Pebesma, E. (2020). Spatiotemporal multi-resolution approximations for analyzing global environmental data. Spatial Statistics, 38, 100465.
DOI: 10.5281/zenodo.5793618
title: The use of Foundational Ontologies in Bioinformatics - Supplementary Material

description: Supplementary material for the paper "The use of Foundational Ontologies in Bioinformatics".
DOI: 10.5281/zenodo.6838751
title: Si/Pb(111)

description: Silicon structures on the Pb(111) surface.
DOI: 10.5281/zenodo.6838750
title: Si/Pb(111)

description: Silicon structures on the Pb(111) surface.
DOI: 10.18112/openneuro.ds004212.v1.0.0
title: THINGS-MEG
DOI: 10.5281/zenodo.6838724
title: The use of Foundational Ontologies in Bioinformatics - SWAT4HCLS - Supplementary Material

description: Supplementary material for the paper "The use of Foundational Ontologies in Bioinformatics".
DOI: 10.5281/zenodo.6770120
title: Human Connectome Project resting-state fMRI Connectivity Matrices (Young Adult + Aging)

description: This database contains the connectivity matrices of the resting-state functional MRI scans that were collected in two databases of the Human Connectome Project, Young Adult and Aging. These matrices contain the functional connectivity between brain regions (here, several different brain atlases were used, leading to several different connectivity matrices for each subject). The connectivity matrices are symmetrical <em>n x n </em>matrices. Here, <em>n</em><em> </em>indicates the number of regions present in the atlas, and any number <em>n<sub>i,j </sub></em>in the matrix is generated by calculating a simple Pearson correlation coefficient between the functional time series that describe the functional activation of regions <em>i </em>and <em>j</em> throughout the resting-state functional scan. The matrices presented in this database are present as .pconn.nii files (which can be handled using software like wb_command) or as .txt file. A full explanation of the database and the brain atlases used here, as well as all the scripts used to generate these connectivity matrices can be found on the GitHub page of this project: floristijhuis/HCP-rfMRI-repository (github.com).
DOI: 10.5281/zenodo.6770119
title: Human Connectome Project resting-state fMRI Connectivity Matrices (Young Adult + Aging)

description: This database contains the connectivity matrices of the resting-state functional MRI scans that were collected in two databases of the Human Connectome Project, Young Adult and Aging. These matrices contain the functional connectivity between brain regions (here, several different brain atlases were used, leading to several different connectivity matrices for each subject). The connectivity matrices are symmetrical <em>n x n </em>matrices. Here, <em>n</em><em> </em>indicates the number of regions present in the atlas, and any number <em>n<sub>i,j </sub></em>in the matrix is generated by calculating a simple Pearson correlation coefficient between the functional time series that describe the functional activation of regions <em>i </em>and <em>j</em> throughout the resting-state functional scan. The matrices presented in this database are present as .pconn.nii files (which can be handled using software like wb_command) or as .txt file. A full explanation of the database and the brain atlases used here, as well as all the scripts used to generate these connectivity matrices can be found on the GitHub page of this project: floristijhuis/HCP-rfMRI-repository (github.com).
DOI: 10.6084/m9.figshare.20318208
title: Tabla 2. Referencias de artículos analizados en la revisión de literatura

description: Referencias de artículos analizados en la revisión de literatura
DOI: 10.6084/m9.figshare.20318208.v1
title: Tabla 2. Referencias de artículos analizados en la revisión de literatura

description: Referencias de artículos analizados en la revisión de literatura
DOI: 10.6084/m9.figshare.20318271
title: Appendix S4 data table v.14.10.2022.FINAL.csv

description: Niche position and width for the flora of Southern France
DOI: 10.34740/kaggle/dsv/3946258
title: YouTube Daily
DOI: 10.5523/bris.1hqjys85s8e392qg3fmqkm2o0i
title: A highly scalable and autonomous spectroscopic radiation mapping system with resilient IoT detector units for dosimetry, safety, and security

description: Data contained within the journal paper "A highly scalable and autonomous spectroscopic radiation mapping system with resilient IoT detector units for dosimetry, safety, and security"
DOI: 10.5517/ccdc.csd.cc274nln
title: CCDC 2060061: Experimental Crystal Structure Determination

description: Related Article: Madasamy Hari Balakrishnan, Madasamy Kanagaraj, Subramaniyan Mannathan|2021|CSD Communication|||
description: Related Article: Kanagaraj Madasamy, Madasamy Hari Balakrishnan, Ramaraju Korivi, Subramaniyan Mannathan|2022|J.Org.Chem.|87|8752|doi:10.1021/acs.joc.2c00354
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.cc296kkn
title: CCDC 2121471: Experimental Crystal Structure Determination

description: Related Article: Ying-Gang Duan, Yi-Hua Chen, Zi-Han Lu, Rong Huang, Sheng-Jiao Yan|2022|J.Org.Chem.|87|8562|doi:10.1021/acs.joc.2c00695
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.cc29ymjf
title: CCDC 2143635: Experimental Crystal Structure Determination

description: Related Article: Lorenzo Serusi, Laura Palombi, Giovanni Pierri, Antonia Di Mola, Antonio Massa|2022|J.Org.Chem.|87|8420|doi:10.1021/acs.joc.2c00518
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.cc2b7ckj
title: CCDC 2152037: Experimental Crystal Structure Determination

description: Related Article: Yubin M. Kwon, Yuri Lee, Anna K. Schmautz, Timothy A. Jackson, Dong Wang|2022|J.Am.Chem.Soc.|144|12072|doi:10.1021/jacs.2c02454
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.cc2bfqq7
title: CCDC 2158149: Experimental Crystal Structure Determination

description: Related Article: Yingwei Li, Yongbo Song, Xinwen Zhang, Tongyu Liu, Tingting Xu, He Wang, De-en Jiang, Rongchao Jin|2022|J.Am.Chem.Soc.|144|12381|doi:10.1021/jacs.2c03948
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.cc2bh5lm
title: CCDC 2159540: Experimental Crystal Structure Determination

description: Related Article: Miho Oga, Yusei Takamatsu, Akihiro Ogura, Ken-ichi Takao|2022|J.Org.Chem.|87|8788|doi:10.1021/acs.joc.2c00753
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.cc2bmw40
title: CCDC 2164052: Experimental Crystal Structure Determination

description: Related Article: Bing-Bing Huang, Kaiyu Lei, Lin-Rui Zhong, Xiaoliang Yang, Zhu-Jun Yao|2022|J.Org.Chem.|87|8685|doi:10.1021/acs.joc.2c00871
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.cc2bmw51
title: CCDC 2164053: Experimental Crystal Structure Determination

description: Related Article: Bing-Bing Huang, Kaiyu Lei, Lin-Rui Zhong, Xiaoliang Yang, Zhu-Jun Yao|2022|J.Org.Chem.|87|8685|doi:10.1021/acs.joc.2c00871
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: 10.6084/m9.figshare.20318157.v2
title: Data File 1

description: "Data supplementary1.csv" is the data about sensitivity at 5Hz.
DOI: 10.6084/m9.figshare.20318157
title: Overcoming the trade-off between the static sensitivity and resonant frequency (Data File 1)

description: "Data supplementary1.csv" is the data about sensitivity at 5Hz.
DOI: 10.6084/m9.figshare.20318157.v4
title: Overcoming the trade-off between the static sensitivity and resonant frequency (Data File 1)

description: "Data supplementary1.csv" is the data about sensitivity at 5Hz.
DOI: 10.6084/m9.figshare.20318157.v3
title: Overcoming the trade-off between the static sensitivity and resonant frequency (Data File 1)

description: "Data supplementary1.csv" is the data about sensitivity at 5Hz.
DOI: 10.6084/m9.figshare.20318196
title: Overcoming the trade-off between the static sensitivity and resonant frequency (Data File 2)

description: "Data supplementary2.csv" is the data about frequency response.
DOI: 10.6084/m9.figshare.20318196.v2
title: Overcoming the trade-off between the static sensitivity and resonant frequency (Data File 2)

description: "Data supplementary2.csv" is the data about frequency response.
DOI: 10.6084/m9.figshare.20318196.v1
title: Data File 2

description: "Data supplementary2.csv" is the data about frequency response.
DOI: 10.5281/zenodo.6838866
title: TDMS data: arc_01

description: TDMS data: arc_01
DOI: 10.5281/zenodo.6838865
title: TDMS data: arc_01

description: TDMS data: arc_01
DOI: 10.5285/42b74017-8907-4067-9c52-ae634864b53d
title: BGS GeoScour v2

description: BGS GeoScour v2 provides river scour susceptibility information for Great Britain using a three-tiered data provision allowing increasing levels of understanding at different resolutions from catchment to local (channel/reach) scales.
GeoScour v2 includes 18 GIS layers, providing information on the natural characteristics and properties of catchment and riverine environments for the assessment of river scour in Great Britain. The dataset product fills a gap in current scour modelling, with the input of geological properties. It provides an improved toolkit to more easily assess and raise the profile of scour risk, now and in the future, to help infrastructure providers and funders prioritise resources, identify remedial works to preclude costly and prevent disruptive failures. The product has broad applications through its adaptation to suit multiple types of asset susceptible to fluvial erosion. GeoScour looks specifically at the geological factors that influence scour and does not consider any hydraulic or hydrodynamic factors.
The GeoScour Dataset Product is designed to be used by multiple stakeholders with differing needs and therefore, can be interrogated at a number of levels. 
Tier 1 A catchment stability dataset provides a summary overview of the catchment characteristics, typical response type, and evolution. It can be used as a high-level overview for incorporation into catchment management plans, national reviews and catchment comparisons using 

Tier 2 datasets are available as smaller catchment areas and focusses on providing data for more detailed catchment management, natural flood management and similar uses. It analyses geological properties such as flood accommodation space, catchment run-off potential, geomorphology types, and additional summary statistics for worst, average, and best-case scenarios for underlying surface geology scour susceptibility, as well as additional summary statistics of key environmental parameters such as protected sites and urban coverage.

Tier 3 datasets provide the detailed riverine information that is designed to be incorporated into more complex river scour models. It provides the baseline geological context for river scour development and processes and identifies important factors that should be considered in any scour model. Factors such as material mineralogy, strength and density are key properties that can influence a river’s ability to scour. In addition, an assessment of river fall, sinuosity and flood accommodation space is also provided. This data is of use to those assessing the propensity for river scour for any given reach of a river across Great Britain and can be used as an input into hydraulic/hydrodynamic models.

Tier 1 and 2 datasets are Open Government Licence (OGL), Tier 3 is licenced.
DOI: 10.5281/zenodo.6474908
title: Tables 2, 3 and 4

description: Experimental results of Okamoto and Hiraga
DOI: 10.5281/zenodo.6474907
title: Tables 2, 3 and 4

description: Experimental results of Okamoto and Hiraga