cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.20424582.v1
title: Road Surface Image Dataset with Detailed Annotations for Driving Assistance

description: The preview of the road surface states is essential for improving the safety and the ride comfort of autonomous vehicles. This dataset consists of 1 million (240 x 360 pixels) road surface images captured under a wide range of road and weather conditions in China. The original pictures are acquired with a vehicle-mounted camera and then the patches containing only the road surface area are cropped. The images are classified into 27 categories, containing both the friction level, material, and unevenness properties. This large-scale dataset is useful for developing vision-based road sensing modules to improve the performance of the driving assistance systems.
DOI: 10.34740/kaggle/dsv/4063142
title: tweets
DOI: 10.5281/zenodo.6985540
title: Supplement DataLongitudinal metabolomics and lipidomics analyses reveal markers of envenoming by Bothrops asper and Daboia russelii in an experimental murine model

description: Longitudinal metablolomic and lipidomics analyses were carried out on the blood plasma of mice injected with venoms of the viperid species Northrop's asper and Daboia russelii.
DOI: 10.5281/zenodo.6985539
title: Supplement DataLongitudinal metabolomics and lipidomics analyses reveal markers of envenoming by Bothrops asper and Daboia russelii in an experimental murine model

description: Longitudinal metablolomic and lipidomics analyses were carried out on the blood plasma of mice injected with venoms of the viperid species Northrop's asper and Daboia russelii.
DOI: 10.34740/kaggle/dsv/4063174
title: Mahanagar Yatayat Dataset
DOI: 10.6084/m9.figshare.20481123.v1
title: Ground Truths and Predictions

description: Format This dataset contains the ground truths and predictions of all deep learning models from Sîmpetru et al (<sub>https://doi.org/10.1101/2022.07.29.502064</sub>). Fig. 2-4 The data is formatted as follows: The data used for <em>Fig. 2</em> is stored under <strong>3D_points_{random, testset}</strong> depending on whether the AI was tested with the random or the test set. The data used for <em>Fig. 3</em> is stored under <strong>angle_{random, test set}</strong> depending on whether the AI was tested with the random or the test set. The data used for <em>Fig. 4</em> is stored under <strong>force</strong>. Each of these folders contains the predicted and expected data for each of the 13 subjects stored as <strong>Subject{1, ..., 13}_{predicted, expected}.pkl</strong>. Fig. 5 The data for Fig. 5 is stored under <strong>comparison</strong>. <br> To distinguish between the EMG forms used, we use: 5 Hz low-pass filtered as <strong>3D_points_5</strong> 5 Hz low-pass filtered and rectified as <strong>3D_points_5_rectified</strong> 20 Hz low-pass filtered as <strong>3D_points_20</strong> 20 Hz low-pass filtered and rectified as <strong>3D_points_20_rectified</strong> raw as <strong>3D_points_raw</strong> raw and rectified as <strong>3D_points_raw_rectified</strong> raw and 20 Hz low-pass filtered combined as <strong>3D_points_raw20</strong> <br> Each of these folders contains the predicted and expected data for each of the 4 subjects, stored as <strong>Subject{1, ..., 4}_{predicted, expected}.pkl</strong>.<br> General file format The saved <strong>.pkl</strong> files are tables where the columns represent the joint labels (<em>Fig. 1B</em>) and the rows represent the bin number. <br> Each cell of the table contains a series of 3 values representing the x, y and z coordinates of the respective joint label at a given time.<br> <br> Loading The stored files are <em>pandas</em> (high-level python library for tables manipulation) dataframes stored using <em>pickle</em> (python object serialisation library).<br> <br> To read such a file, we give the following minimal example:<br> <br> import pandas as pd<br> <br> dataframe = pd.read_pickle("PATH_TO_FILE.pkl")<br> <br> # display head (top 5 rows) of the dataframe<br> print(dataframe.head())<br>
DOI: 10.6084/m9.figshare.20481309
title: data-socialnet.xlsx

description: the data for Social Network and Tourism Consumption by Households: An Evidence from China
DOI: 10.6084/m9.figshare.20481318
title: Accipiter rufiventris decontaminated FSCR

description: .....
DOI: 10.6084/m9.figshare.20481318.v1
title: Accipiter rufiventris decontaminated FSCR

description: .....
DOI: 10.17909/4wr8-hh69
title: Data for SMACS0723
DOI: 10.6084/m9.figshare.20481375
title: Bergia catenularis decontaminated FSCR

description: .....
DOI: 10.6084/m9.figshare.20481375.v1
title: Bergia catenularis decontaminated FSCR

description: .....
DOI: 10.5281/zenodo.6656802
title: Reddit photo Critique Dataset

description: <strong>IMPORTANT</strong>: Dataset is now completely accessible from Github: https://github.com/mediatechnologycenter/aestheval Post IDs available here: https://zenodo.org/record/6985507 The Reddit Photo Critique Dataset (RPCD) contains tuples of image and photo critiques. RPCD consists of 74K images<br> and 220K comments and is collected from a Reddit community used by hobbyists and professional photographers to improve their photography skills by leveraging constructive community feedback. The proposed dataset differs from previous aesthetics datasets mainly in three aspects, namely (i) the large scale of the dataset and the extension of the comments criticizing different aspects of the image, (ii) it contains mostly UltraHD images, and (iii) it can easily be extended to new data as it is collected through an automatic pipeline. More info about the dataset can be found at the Github repo: https://github.com/mediatechnologycenter/aestheval
DOI: 10.5281/zenodo.6656801
title: Reddit photo Critique Dataset

description: <strong>IMPORTANT</strong>: Dataset is now completely accessible from Github: https://github.com/mediatechnologycenter/aestheval Post IDs available here: https://zenodo.org/record/6985507 The Reddit Photo Critique Dataset (RPCD) contains tuples of image and photo critiques. RPCD consists of 74K images<br> and 220K comments and is collected from a Reddit community used by hobbyists and professional photographers to improve their photography skills by leveraging constructive community feedback. The proposed dataset differs from previous aesthetics datasets mainly in three aspects, namely (i) the large scale of the dataset and the extension of the comments criticizing different aspects of the image, (ii) it contains mostly UltraHD images, and (iii) it can easily be extended to new data as it is collected through an automatic pipeline. More info about the dataset can be found at the Github repo: https://github.com/mediatechnologycenter/aestheval
DOI: 10.48704/cosb2_fes2
title: CoSb2_FeS2
DOI: 10.6084/m9.figshare.20481408.v1
title: Chrysina resplendens decontaminated FSCR

description: ......
DOI: 10.6084/m9.figshare.20481408
title: Chrysina resplendens decontaminated FSCR

description: ......
DOI: 10.18112/openneuro.ds003876.v1.0.2
title: Epilepsy-iEEG-Interictal-Multicenter-Dataset
DOI: 10.48704/cual2
title: CuAl2
DOI: 10.48704/fesi2_caf2
title: FeSi2_CaF2
DOI: 10.5517/ccdc.csd.cc1ng9zd
title: CCDC 1533104: Experimental Crystal Structure Determination

description: Related Article: Peter G. Jones, Christoph Wolper|2017|CSD Communication|||
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.cc1phjwl
title: CCDC 1564070: Experimental Crystal Structure Determination

description: Related Article: Xiao-Yan Wang, Jing Zhang, Yu-Bao Dong, Yiyue Zhang, Jun Yin, Sheng Hua Liu|2018|Dyes Pigm.|156|74|doi:10.1016/j.dyepig.2018.03.062
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.cc1phk1s
title: CCDC 1564075: Experimental Crystal Structure Determination

description: Related Article: Xiao-Yan Wang, Jing Zhang, Yu-Bao Dong, Yiyue Zhang, Jun Yin, Sheng Hua Liu|2018|Dyes Pigm.|156|74|doi:10.1016/j.dyepig.2018.03.062
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.cc1phkk9
title: CCDC 1564091: Experimental Crystal Structure Determination

description: Related Article: Xiao-Yan Wang, Jing Zhang, Yu-Bao Dong, Yiyue Zhang, Jun Yin, Sheng Hua Liu|2018|Dyes Pigm.|156|74|doi:10.1016/j.dyepig.2018.03.062
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.cc14017f
title: CCDC 1042723: Experimental Crystal Structure Determination

description: Related Article: Brian W. Skelton, Murray V. Baker, James L. Hickey|2018|CSD Communication|||
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: 10.48704/mosi2
title: MoSi2
DOI: 10.5517/ccdc.csd.cc14018g
title: CCDC 1042724: Experimental Crystal Structure Determination

description: Related Article: Brian W. Skelton, Murray V. Baker, James L. Hickey|2018|CSD Communication|||
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.cc14019h
title: CCDC 1042725: Experimental Crystal Structure Determination

description: Related Article: Brian W. Skelton, Murray V. Baker, James L. Hickey|2018|CSD Communication|||
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.cc14015c
title: CCDC 1042721: Experimental Crystal Structure Determination

description: Related Article: Brian W. Skelton, Murray V. Baker, James L. Hickey|2018|CSD Communication|||
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.cc14014b
title: CCDC 1042720: Experimental Crystal Structure Determination

description: Related Article: Brian W. Skelton, Murray V. Baker, James L. Hickey|2018|CSD Communication|||
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.cc23dfml
title: CCDC 1948369: Experimental Crystal Structure Determination

description: Related Article: Tian-yi Li, Daniel Sylvinson Muthiah Ravinson, Ralf Haiges, Peter I. Djurovich, Mark E. Thompson|2020|J.Am.Chem.Soc.|142|6158|doi:10.1021/jacs.9b13755
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: 10.48704/tias2
title: TiAs2
DOI: 10.48704/tisi2
title: TiSi2
DOI: 10.7284/141145
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise AE2011 using a Hawaii UHDAS instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149432
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise AE2011 using a SeaBird SBE-911+ instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/141150
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise AE2012 using a Hawaii UHDAS instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/141155
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise AE2012 using a SeaBird SBE-911+ instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/141158
title: Multiplexed data collected during research cruise AE2013 using a BIOS METOC instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/141159
title: Multiplexed data collected during research cruise AE2013 using a BIOS METOC instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/141160
title: Multiplexed data collected during research cruise AE2013 using a BIOS METOC instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/141162
title: Multiplexed data collected during research cruise AE2013 using a BIOS METOC instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/141157
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise AE2013 using a Hawaii UHDAS instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/141161
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise AE2013 using a SeaBird SBE-911+ instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.20481123.v2
title: Ground Truths and Predictions from "Sensing the Full Dynamics of the Human Hand with a Neural Interface and Deep Learning"

description: Format This dataset contains the ground truths and predictions of all deep learning models from Sîmpetru et al (<sub>https://doi.org/10.1101/2022.07.29.502064</sub>). Fig. 2-4 The data is formatted as follows: The data used for <em>Fig. 2</em> is stored under <strong>3D_points_{random, testset}</strong> depending on whether the AI was tested with the random or the test set. The data used for <em>Fig. 3</em> is stored under <strong>angle_{random, test set}</strong> depending on whether the AI was tested with the random or the test set. The data used for <em>Fig. 4</em> is stored under <strong>force</strong>. Each of these folders contains the predicted and expected data for each of the 13 subjects stored as <strong>Subject{1, ..., 13}_{predicted, expected}.pkl</strong>. Fig. 5 The data for Fig. 5 is stored under <strong>comparison</strong>. <br> To distinguish between the EMG forms used, we use: 5 Hz low-pass filtered as <strong>3D_points_5</strong> 5 Hz low-pass filtered and rectified as <strong>3D_points_5_rectified</strong> 20 Hz low-pass filtered as <strong>3D_points_20</strong> 20 Hz low-pass filtered and rectified as <strong>3D_points_20_rectified</strong> raw as <strong>3D_points_raw</strong> raw and rectified as <strong>3D_points_raw_rectified</strong> raw and 20 Hz low-pass filtered combined as <strong>3D_points_raw20</strong> <br> Each of these folders contains the predicted and expected data for each of the 4 subjects, stored as <strong>Subject{1, ..., 4}_{predicted, expected}.pkl</strong>.<br> General file format The saved <strong>.pkl</strong> files are tables where the columns represent the joint labels (<em>Fig. 1B</em>) and the rows represent the bin number. <br> Each cell of the table contains a series of 3 values representing the x, y and z coordinates of the respective joint label at a given time.<br> <br> Loading The stored files are <em>pandas</em> (high-level python library for tables manipulation) dataframes stored using <em>pickle</em> (python object serialisation library).<br> <br> To read such a file, we give the following minimal example:<br> <br> import pandas as pd<br> <br> dataframe = pd.read_pickle("PATH_TO_FILE.pkl")<br> <br> # display head (top 5 rows) of the dataframe<br> print(dataframe.head())<br>
DOI: 10.5281/zenodo.6983166
title: SPAAM Summer School 2022: Introduction to Ancient Metagenomics - 3c Introduction to Taxonomic Profiling

description: Teaching data for practical session: "3c Introduction to Taxonomic Profiling" of the 2022 SPAAM Summer School: Introduction to Ancient Metagenomics (Aug. 1-5 2022). See: https://spaam-community.github.io/wss-summer-school/#/2022/ or https://doi.org/10.5281/zenodo.6976711 for slides. Once downloaded, run: <pre><code>tar xvfz &lt;session&gt;.tar.gz</code></pre> to decompress the data directory for the session.
DOI: 10.5281/zenodo.6983165
title: SPAAM Summer School 2022: Introduction to Ancient Metagenomics - 3c Introduction to Taxonomic Profiling

description: Teaching data for practical session: "3c Introduction to Taxonomic Profiling" of the 2022 SPAAM Summer School: Introduction to Ancient Metagenomics (Aug. 1-5 2022). See: https://spaam-community.github.io/wss-summer-school/#/2022/ or https://doi.org/10.5281/zenodo.6976711 for slides. Once downloaded, run: <pre><code>tar xvfz &lt;session&gt;.tar.gz</code></pre> to decompress the data directory for the session.
DOI: 10.5281/zenodo.6985594
title: PyFLOWGO Data for Arsia Mons Lava Flows

description: PyFLOWGO results for five lava flows SW of Arsia Mons, Mars Flow measurements for five lava flows SW of Arsia Mons, Mars
DOI: 10.6084/m9.figshare.20481483
title: Circus approximans decontaminated FSCR

description: ......
DOI: 10.6084/m9.figshare.20481483.v1
title: Circus approximans decontaminated FSCR

description: ......
DOI: 10.5281/zenodo.6960879
title: National Survey on the Effects of COVID-19 on the Wellbeing of Mexican Households (ENCOVID-19- DECEMBER 2020)

description: Amid the COVID-19 outbreak, the ENCOVID-19 provides information on the well-being of Mexican households in four main domains: labor, income, mental health, and food insecurity. It offers timely information to understand the social consequences of the pandemic and the lockdown measures. It is a project consisting of a series of cross-sectional telephone surveys collected in key moments of the COVID-19 pandemic. In addition to the four main domains and a set of COVID19-related questions, the survey includes new key indicators every month to capture the impact of the pandemic on issues like education, social programs, and crime. This is the sixth dataset of the project, corresponding to December 2020, collected nine months after the lockdown began in Mexico. Data collection was performed from November 27 to December 11, 2020.
description: The project was approved by the Ethics Committee from Universidad Iberoamericana with the registry: CONBIOÉTICA-09—CEI-008-2016060. Funding for this porject provided by Universidad Iberoamericana and UNICEF. If international researchers require additional information, please contact Victor Perez (victor.hernandez@ibero.mx) or Pablo Gaitán-Rossi (pablo.gaitan@ibero.mx)
description: {"references": ["Teruel Belismelis, G., & Perez-Hern\u00e1ndez, V. (2021). Studying well-being during the COVID-19 Pandemic: The ENCOVID-19 survey. Revista Mexicana de Sociolog\u00eda, 83(SPE), 125-167."]}
DOI: 10.5281/zenodo.4057115
title: Supplementary data: Medicago transcriptomics DRMN analysis

description: Summary of DRMN per-gene module assignments, module motif enrichments, inferred network edge weights, and MTG-LASSO predictions, Supplementary data tables 1-4 of this submission, respectively.
description: Intended
DOI: 10.5281/zenodo.4057114
title: Supplementary data: Medicago transcriptomics DRMN analysis

description: Summary of DRMN per-gene module assignments, module motif enrichments, inferred network edge weights, and MTG-LASSO predictions, Supplementary data tables 1-4 of this submission, respectively.
description: Intended
DOI: 10.7284/141164
title: Multiplexed data collected during research cruise AE2014 using a BIOS METOC instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/141165
title: Multiplexed data collected during research cruise AE2014 using a BIOS METOC instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/141166
title: Multiplexed data collected during research cruise AE2014 using a BIOS METOC instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/141168
title: Multiplexed data collected during research cruise AE2014 using a BIOS METOC instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/141163
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise AE2014 using a Hawaii UHDAS instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/141167
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise AE2014 using a SeaBird SBE-911+ instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.17909/espg-fy96
title: Data used in "Metallicities of Five z > 5 Emission-Line Galaxies in SMACS 0723 Revealed by JWST"

description: Five z>5 galaxies from JWST ERO observations showing [OIII]4363 emission
DOI: 10.6084/m9.figshare.20481564
title: Data.zip

description: Original Data
DOI: 10.6084/m9.figshare.20481564.v1
title: Data.zip

description: Original Data