Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
567
datasets available to search
ShareScore release 0.9.0
Dataset results
567 results for “Simulated datasets”
WRF 6-km simulation of western US 1981-2010 daily hydrometeorological dataset - part 1
<p>This repo includes the raw input data and scripts (of plots in the main text) for the following manuscript:</p> <p>Chen et al., Antecedent Hydrometeorological Conditions of Wildfire Occurrence in the Western U.S. in a Changing Climate</p> <p>Details and companion scripts will be uploaded after the manuscript is accepted.</p>
Simulated datasets for detector and particle flow reconstruction: CLIC detector, hit-based data, machine learning format
<p>Derived from https://zenodo.org/record/8260741, prepared in a machine-learning friendly TFDS format, ready to be used with https://zenodo.org/record/8397954.</p> <ul> <li>clic_edm_ttbar_hits_pf10k.tar: ee -> ttbar, center of mass energy at 380 GeV, 10k events</li> <li>clic_edm_qq_hits_pf10k.tar: ee -> Z* -> qqbar, center of mass energy at 380 GeV, 10k events</li> </ul> <p><strong>Contents</strong></p> <p>Each .tar file contains the dataset in the <a href="https://github.com/tensorflow/datasets">tensorflow-datasets</a> (minimum version v4.9.1), <a href="https://github.com/google/array_record">array_record</a> format.</p> <p><strong>Dataset semantics</strong></p> <p>Each dataset consists of events that can be iterated over using the tensorflow-datasets library in either tensorflow or pytorch. Each event has the following information available:</p> <ul> <li>X: the reconstruction input features, i.e. tracks and calorimeter hits</li> <li>ygen: the ground truth particles with the features ["PDG", "charge", "pt", "eta", "sin_phi", "cos_phi", "energy", "jet_idx"], with "jet_idx" corresponding to the gen-jet assignment of this particle</li> <li>ycand: the baseline Pandora PF particles with the features ["PDG", "charge", "pt", "eta", "sin_phi", "cos_phi", "energy", "jet_idx"], with "jet_idx" corresponding to the gen-jet assignment of this particle</li> </ul> <p>The full semantics, including the list of features for X, are available at https://github.com/jpata/particleflow/blob/v1.6/mlpf/heptfds/clic_pf_edm4hep_hits/utils_edm.py.</p>
Zika virus prM protein contains cholesterol binding motifs required for virus entry and assembly - Molecular Dynamics Simulation Dataset
<p>The molecular dynamics (MD) simulation dataset. The contents:</p> <ul> <li><strong>5ire_BIOMT_expanded.pdb</strong>: The complete biological assembly of the cryo-EM structure of Zika Virus (PDB ID:5IRE) </li> <li><strong>5ire_Mprotein_BIOMT_expanded.pdb</strong>: The M proteins extracted from the complete biological assembly of the cryo-EM structure of Zika Virus (PDB ID:5IRE). The biological assembly shows the dimeric organization of M proteins.</li> <li><strong>0chol.zip, 10chol.zip, 20chol.zip, and 30chol.zip</strong> contain simulation input and output files for the simulated membrane compositions: 0:100, 10:90, 20:80, 30:70 (mol%:mol%) Cholesterol:POPC, respectively. <ul> <li>In each zip file, there are 5 directories: <strong>wt, R253L+F257A, R253L+F257S, K275L+Y278A, K275L+Y278S</strong> corresponding to each simulated M protein dimer variant: wild type, CARC 2-A, CARC 2-S, CARC 3-A, and CARC 3-S. In each directory, there are the following files: <ul> <li><strong>toppar</strong>: This directory contains all force field topologies and parameters</li> <li><strong>topol.top</strong>: GROMACS topology (top) file</li> <li><strong>index.ndx</strong>: GROMACS index (ndx) file</li> <li><strong>prod.mdp</strong>: GROMACS MD parameters (mdp) file</li> <li><strong>0, 1, 2, 3, 4, 5, 6, 7, 8, 9</strong>: These directories contain the simulation inputs and outputs for each simulation repeat. In each of these directories, there are the following files: <ul> <li><strong>t0.pdb</strong>: The pdb file of the starting coordinates</li> <li><strong>prod0.tpr</strong>: GROMACS binary run input (tpr) file </li> <li><strong>prod0.edr</strong>: GROMACS energy (edr) file</li> <li><strong>prod0.gro</strong>: GROMACS output coordinates and velocities after 1 microsecond of simulation</li> <li><strong>prod0.cpt</strong>: GROMACS checkpoint file after 1 microsecond of simulation</li> <li><strong>noW.pdb</strong>: The pdb file of the starting coordinates with all water molecules removed</li> <li><strong>noW.xtc</strong>: GROMACS compressed trajectory (xtc) file with all water molecules removed</li> </ul> </li> </ul> </li> </ul> </li> </ul>
Impact of Convection-permitting and Model Resolution on the Simulation of Mesoscale Convective System Properties over East Asia: companion dataset
<p>This folder includes the intermediate data for the following manuscript:</p><p>Ding et al., Impact of Convection-permitting and Model Resolution on the Simulation of Mesoscale Convective System Properties over East Asia</p><p>The simulations were done using ICON-NWP (ICON Numerical Weather Prediction) model, version 2.6.1, over Asian monsoon region (62E–150E, 5.5N–54.5N) for 2020 summer. At the moment, we upload the intermediate data for MCS tracking. For more data, please contact the authors.</p>
Dataset from: Numerical simulation of fatigue crack growth in offshore mooring chains
<p>A polynomial solution for approximating the stress intensity factor (SIF) along the front of a semi-elliptical crack in a curved round bar has been developed. The normal stress distribution in the crack plane is assumed to be on a cubic polynomial form. Coefficients for the polynomial SIF solution have been calculated using least-squares fitting of finite element analysis results (<em>n</em>=4480 per stress distribution component). </p>
Dataset and software to analyze and simulate neuronal morphogenesis in Drosophila class IV da neurons
Open the record for dataset details and reuse information.
POLAR-Sim: Augmenting NASA's POLAR dataset for data-driven lunar perception and rover simulation
Open the record for dataset details and reuse information.
Synthetic dataset for the PFC3D simulation of fragmentable blocks sliding experiments
<p>Dataset 1 - The raw data of numerical simulations, including deposit parameters of all simulations, fragments size distribution of all simulations, impact force of D1, breakage bond number of D1, velocity of D1.</p> <p>Simulation code - all the PFC3D simulation code for the fragmentable blocks sliding experiments.</p>
AMIP and AMIP-P4K simulation dataset with Park-RH and Gauss-PDF cloud scheme
<p>This dataset includes AMIP and AMIP-P4K simulations using Park-RH and Gauss-PDF cloud schemes, respectively. </p> <p>Park-RH cloud scheme is the default cloud macrophysical scheme in NCAR CAM5. </p> <p>Gauss-PDF cloud scheme is a statistical cloud scheme, developed by Qin et al. (2018). </p> <p>All simulations are AMIP-type simulations from 1979 to 1988. The monthly output is archived here. </p> <p>Details of the model setup and the difference of two cloud schemes could be found in its related submitted manuscript. </p>
Diurnal cycle of the semi-direct effect from a persistent absorbing aerosol layer over marine stratocumulus in large-eddy simulations: supporting dataset
<p>Relevant data for reproducing figures and tables from Herbert et al., 2020, Atmospheric Chemistry and Physics: "Diurnal cycle of the semi-direct effect from a persistent absorbing aerosol layer over marine stratocumulus in large-eddy simulations".</p> <p>The tar file contains the relevant netcdf files that contain simulation output from the MET Office large eddy model (LEM). Each netcdf file corresponds to a single model setup and experiment - details of which can be found within the published manuscript. Information concerning the LEM, and details on how to obtain access to the code, can be found at http://appconv.metoffice.com/LEM/index.html.</p> <p>The file 'relevant_information.pdf' contains two tables. The first provides the names of each netcdf file that was used to produce each figure in the manuscript. The second provides the metadata for the netcdf variables that were used to produce the figures and tables.</p> <p>The netcdf filename provides information on the experiment setup as follows:</p> <p>run-identifier-number _ length-of-run _ AOD-of-layer _ GAP-between-cloud-and-layer _ THICKNESS-of-layer _ 'bigarray' _ special-setups-for-sensitivity-experiments</p> <p>For example, r1360_8day_transient_aod02_0dz_250th_bigarray_nodrizz is run number r1360, simulating 8 days, with the aerosol layer properties AOD=0.2, cloud-to-aerosol gap of 0m, layer thickness of 250m, in the sensitivity setup where precipitation has been switched off.</p>
Dataset for 'Rotational dependence of turbulent transport coefficients in global convective dynamo simulations of solar-like stars'
<p>For moderate and slow rotation, magnetic activity of solar-like stars is observed to strongly depend on rotation, while for rapid rotation, only a very weak or no dependency is detected. These observations do not yet have a solid explanation in terms of dynamo theory. To work towards such an explanation, we numerically investigated the rotational dependency of dynamo drivers in solar-like stars, that is, stars that have a convective envelope of similar thickness as in the Sun. We ran semi-global convection simulations of stars with rotation rates from 0 to 30 times the solar value, corresponding to Coriolis numbers, Co, of 0 to 110. We measured the turbulent transport coefficients describing the magnetic field evolution with the help of the test-field method, and compared with the dynamo effect arising from the differential rotation, self-consistently generated in the models. The trace of the <strong><span class="math-tex">\(\alpha\)</span></strong> tensor increases for moderate rotation rates with Co<sup>0.5</sup> and levels off for rapid rotation. This behavior is in agreement with the kinetic <span class="math-tex">\(\alpha\)</span> based on the kinetic helicity, if one takes into account the decrease of the convective scale with increasing rotation. The <strong><span class="math-tex">\(\alpha\)</span></strong> tensor becomes highly anisotropic for Co > 1, <span class="math-tex">\(\alpha_{rr}\)</span> dominates for moderate rotation (1<Co<10), and <span class="math-tex">\(\alpha_{\phi\phi}\)</span> for rapid rotation (Co > 10). The effective meridional flow, taking into account the turbulent pumping effects, is markedly different from the actual meridional circulation profile. Hence, the turbulent pumping effect is dominating the meridional transport of the magnetic field. Taking all dynamo effects into account, we find three distinct regimes. For slow rotation, the <span class="math-tex">\(\alpha\)</span> and Rädler effects are dominating in presence of anti-solar differential rotation. For moderate rotation, <span class="math-tex">\(\alpha\)</span> and <span class="math-tex">\(\Omega\)</span> effects are dominant, indicative of <span class="math-tex">\(\alpha\Omega\)</span> or <span class="math-tex">\(\alpha^2\Omega\)</span> dynamos in operation, producing equatorward-migrating dynamo waves with the qualitatively solar-like rotation profile. For rapid rotation, an <span class="math-tex">\(\alpha^2\)</span> mechanism, with an influence from the Rädler effect, appears to be the most probable driver of the dynamo. Our study reveals the presence of a large variety of dynamo effects beyond the classical <span class="math-tex">\(\alpha\Omega\)</span> mechanism, which need to be investigated further to fully understand the dynamos of solar-like stars. The highly anisotropic <strong><span class="math-tex">\(\alpha\)</span></strong> tensor might be the primary reason for the change of axisymmetric to non-axisymmetric dynamo solutions in the moderate rotation regime.</p> <p>For the full article see <a href="https://arxiv.org/abs/1910.06776">https://arxiv.org/abs/1910.06776</a></p>
Dataset of Paper "Enhanced numerical simulation of photocatalytic reactors with an improved solver for the radiative transfer equation"
<p>Dataset of Paper "Enhanced numerical simulation of photocatalytic reactors with an improved solver for the radiative transfer equation":</p> <p>- Data of the incident radiation profiles in the annular reactor.</p> <p>- Average and net values of main radiation magnitudes in the tubular reactor at different photocatalyst concentration </p> <p> </p>
Car sharing simulation dataset
<p>Simulated Car-sharing data-set with multiple fields including activities of anonymized users (e.g. source, destination, travel time, price offers etc.)</p>
Datasets for ``Numerical Simulations of Gravitational Waves from Early-Universe Turbulence''
<pre>The tar archive GW.tar contains an index.html file with links to the run directories for each run in Table 1 of the paper "Numerical Simulations of Gravitational Waves from Early-Universe Turbulence" by A. Roper Pol, S. Mandal, A. Brandenburg, T. Kahniashvili, &amp; A. Kosowsky with the temporary URL http://norlx55.nordita.org/~brandenb/tmp/GW. Corrections and updates are available on the active URL to this tar archive: https://www.nordita.org/~brandenb/projects/GW/</pre>
Dataset for: Quantum cascade lasers with discrete and non equidistant extended tuning tailored by simulated annealing
<p>Dataset used for article 10.1364/OE.27.026701.</p>
Dataset: 2D particle-in-cell (PIC) simulation of the magnetic reconnection for the paper "Electron mixing and isotropization in the exhaust of asymmetric magnetic reconnection with a guide field"
<p>This repository contains pubilicly available numerical data of a 2D magnetic reconnection event, which includes the field data and plasma moment data. The simulation is performed with the VPIC code. The simulated data are used for the paper "Electron mixing and isotropization in the exhaust of asymmetric magnetic reconnection with a guide field". </p>
Dataset of "Gravity Wave Activity in the Atmosphere of Mars During the 2018 Global Dust Storm: Simulations With a High-Resolution Model" (2/2)
<p>This dataset contains the GrADS data of high-resolution Mars GCM results used for figures in the paper "Gravity Wave Activity in the Atmosphere of Mars During the 2018 Global Dust Storm: Simulations With a High-Resolution Model" by T. Kuroda, A.S. Medvedev and E. Yiğit.</p> <p>Each file contains two-dimensional (X: longitude, Y: latitude) data of surface pressure (Ps) and dust opacity in infrared wavelength (tau), and three-dimensional (X: longitude, Y: latitude, Z:sigma-level) data of temperature (T), zonal wind velocity (u), meridional wind velocity (v) and vertical wind velocity (w). Each tar.xz file contains snapshots of those data in every 1/6 Sol for Ls of 30 degrees. The dust scenario implemented for producing this dataset is taken from Montabone et al. (2020).</p> <p>data270rdc-my34.tar.xz: for Ls=270-300 (48 Sols)</p> <p>data300rdc-my34.tar.xz: for Ls=300-330 (51 Sols)</p> <p>data330rdc-my34.tar.xz: for Ls=330-360 (56 Sols)</p>
Implementation of Genomic Variant Calling Using GATK4, SPARK, WDL, CROMWELL and DOCKER Over Simulated Ebola NGS Dataset.
<p>Ebola genome is manually mutated to contain non-structural variants - 10 SNPs, 10 INDELs, 05 TRANSLOCATIONs, 05 INSERSIONs and their reverse complements. Paired-end illumina RNASEQ reads are simulated in fastq format. </p>
Implementation of Genomic Variant Calling Using GATK4, SPARK, WDL, CROMWELL and DOCKER Over Simulated Ebola NGS Dataset.
<p>Ebola genome is manually mutated to contain structural variants. There are seven mutated ebola genomes each one for two large deletions, insertions, duplications, translocations, inversions, one complex variant1 (consecutive three mutations - insertion, duplication and deletion) and one complex variants2 (consecutive three mutations - deletion, duplication and deletion). All insertions are novel sequence insertion. Paired-end illumine RNASEQ reads are simulated in fastq format.</p>
Implementation of Genomic Variant Calling Using GATK4, SPARK, WDL, CROMWELL and DOCKER Over Simulated Ebola NGS Dataset.
<p>Ebola genome is manually mutated to contain structural variants. There are seven mutated ebola genomes each one for large deletion, insertion, duplication, translocation, inversion, complex variant1 (consecutive three mutations - insertion, duplication and deletion) and complex variants2 (consecutive three mutations - deletion, duplication and deletion). All insertions are novel sequence insertion. Paired-end illumine RNASEQ reads are simulated in fastq format.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.