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.
1,880
datasets available to search
ShareScore release 0.9.0
Dataset results
1,880 results for “Dimensionality”
Topological states in superlattices of HgTe class of materials for engineering three-dimensional flat bands
<p>In search of materials with three-dimensional flat band dispersions, using ab-initio computations we investigate how topological phases evolve as a function of hydrostatic pressure and uniaxial strain in two types of superlattices: HgTe/CdTe and HgTe/HgSe. In short-period HgTe/CdTe superlattices, our analysis unveils the presence of isoenergetic nodal lines, which could host strain-induced three-dimensional flat bands at the Fermi level without requiring doping, when fabricated, for instance, as core-shell nanowires. In contrast, HgTe/HgSe short-period superlattices are found to harbor a rich phase diagram with a plethora of topological phases. Notably, the unstrained superlattice realizes an ideal Weyl semimetal with Weyl points situated at the Fermi level. A small-gap topological insulator with multiple band inversions can be obtained by tuning the volume: under compressive uniaxial strain, the material transitions sequentially into a Dirac semimetal to a nodal-line semimetal, and finally into a topological insulator with a single band inversion.</p> <p>The provided repository contains data to reproduce the figures of the corresponding article.</p>
Computational Analysis of Two-dimensional High-throughput Data from Large-scale RNAi Screens and Single-cell Transcriptomics
<p>This publication provides a singularity definition file to reproduce the computational environment along with the scripts to reproduce every figure or table in the revised manuscript using ZetaSuite Perl module and R package.</p> <p>First, generate a new folder and then download all the files into the folder.</p> <p>Then, uncompressed the files DataSets_part1.tar.gz,DataSets_part2.tar.gz,DataSets_part3.tar.gz,DataSets_part4.tar.gz, and scripts.tar.gz. within the folder.</p> <p>Next, move all the files in DataSets_part1 folder, DataSets_part2 folder,DataSets_part3 folder and DataSets_part4 folder to a new folder called DataSets.</p> <p>Finally, run the following scripts to generate the figures and tables in our manuscript.</p> <p>Regeneration of Figure2 and S2: singularity exec ZetaSuite.sif sh Figure2andS2.sh </p> <p>Regeneration of Figure3 and S3: singularity exec ZetaSuite.sif sh Figure3andS3.sh </p> <p>Regeneration of Figure4 and S4: singularity exec ZetaSuite.sif sh Figure4andS4.sh </p> <p>Regeneration of Figure5 and S5: singularity exec ZetaSuite.sif sh Figure5andS5.sh </p> <p>Regeneration of Figure6 and S6: singularity exec ZetaSuite.sif sh Figure6andS6.sh </p> <p>Regeneration of Figure7 and S7: singularity exec ZetaSuite.sif sh Figure7andS7.sh </p> <p> </p>
Dataset: Field-induced Bose-Einstein condensation and supersolid in the two-dimensional Kondo necklace
<p>The open Dataset for "Field-induced Bose-Einstein condensation and supersolid in the two-dimensional Kondo necklace". </p>
A low-dimensional, mechanistic water balance model for piñon pine-juniper woodlands in southern Nevada, USA
<p>This is a low-dimensional water balance model developed for pinon pine-juniper woodlands in southern Nevada. It may require extensive revision for use in other similar or dissimilar woodland ecosystems. The model will require parameterization before use in any capacity.</p> <p>This model is mechanistic, but is driven from randomized precipitation. This framework allows the user to estimate the mean and standard deviation of water balance variables by simulating the same average meteorological year 1000s of times, each with randomized precipitation. This technique approximates a normal distribution of precipitation, and will need to be modified for locations/sites that have a non-normal precipitation distribution. It is not recommended to use the model in any other way without first testing and validating its output.</p> <p>I have provided documentation throughout the wrapper, model and parameter files to assist with your use of the model. You are encouraged to learn from, build on, and improve this model. You will need to set your own pathways and build your own meteorological inputs and site parameterizations. You may need to update, revise and add/remove different submodules depending on your intended use.</p>
Three-dimensional in-situ imaging of single-grain growth in polycrystalline In2O3:Zr films
<p>Original data</p> <p>Here, we image a single-grain growth during the amorphous-to-polycrystalline transition in technologically relevant transparent conductive oxide (TCO) film of In<sub>2</sub>O<sub>3</sub>:Zr with <em>in-situ</em> Bragg coherent X-ray diffraction imaging.</p> <p>Data was obtained at 34ID-C end-station at Advanced Photon Source, Argonne National Laboratory (USA).</p> <p>Repository contains all raw datasets of the BCDI measurements, .spec files with corresponding meta-data, and .xlsx table with information on scan numbers related to annealing steps of the sample.</p>
Three-dimensional movement of the beak during seed processing in domestic canaries
<p>Many songbird species rely on seeds as a primary food source and the process of picking up, positioning, cracking, dehusking, and swallowing seeds is one of the most sophisticated tasks of the beak. Still, we lack understanding about how granivorous songbirds move their beak during the different phases of seed processing. In this study, we used multi-view high speed imaging to analyze the three-dimensional movement of the beak in feeding domestic canaries. Our analysis focuses on correlation of upper and lower beak, frequency of mandibulation, and direction of mandible movement in 3D space. We show that the correlation of maxilla and mandible movement differs among the phases of seed processing. Furthermore, we found that the beak moves at extremely high frequencies, up to 25 Hz, which resembles previously reported maximal syllable rates in singing canaries. Finally, we report that canaries use specific 3D mandible movements during the different phases of seed processing. Kinematic parameters do not differ between male and female canaries. Our findings provide an important biomechanical basis for better understanding the beak as a functional tool.</p>
Three-dimensional Digital Outcrop Models of the Tullig Sandstone, Western Irish Namurian Basin, Co. Clare, Ireland
<p>Tullig Sandstone is part of the Tullig Cyclothem, Western Irish Namurian Basin, Co. Clare, Ireland. The Tullig Sandstone is a prominent sandstone interval that represents an ancient fluvial-deltaic system. </p> <p>Outcrops of the Tullig Sandstone were surveyed by an unmanned aerial vehicle (UAV, DJI Mavic Pro Platinum™). Three-dimensional digital outcrop models were generated from images collected from UAV using Agisoft Metashape™.</p>
Data of: Imputation-free reconstructions of three-dimensional chromosome architectures in human diploid single-cells using allele-specified contacts
<p>These files are results obtained in<br><span><span><span><span>Imputation-free reconstructions of three-dimensional chromosome architectures in human diploid single-cells using allele-specified contacts</span></span></span></span><br>by Yoshito Hirata, Arisa H. Oda, Chie Motono, Masanori Shiro & Kunihiro Ohta.</p> <p>There are 33 files for the corresponding each reconstruction of three-dimensional chromosomone structures<br>for each cell.<br>There are 3D structures for 15 GM cells and 18 PBMC cells, which are obtained from the single cell Hi-C data of Tan et al. Science (2018).</p> <p>For each file, there are 6 columns:<br>The first column corresponds to the allele (0: maternal, 1: paternal)<br>The second column corresponds to the chromosome (1-22: chromosome's number, 23: X, 24: Y)<br>The third column corrsponds to the base point.<br>The fourth column, the fifth column and the sixth column correspond to x-, y-, and z-axes of our reconstruction.</p>
Fig. 9. N-dimensional morphospace for the 28 in Taxonomic implications of describing a new species of Loimia (Annelida, Terebellidae) with two size-dependent morphotypes
Fig. 9. N-dimensional morphospace for the 28 species of Loimia Malmgren, 1866, calculated for the larger (body length>100 mm, grey) and smaller (body length <100 mm, pink) species separately; red dots = larger and smaller individuals of Loimia davidi sp. nov.; large points with white borders = centroids of each hypervolume; hypervolume shape and boundaries defined by 5000 random points; table = summary of hypervolume richness, dispersion and evenness.
Two-dimensional vanadium sulfide flexible graphite/polymer films for near-infrared photoelectrocatalysis and electrochemical energy storage
<p>Raw data of published article "Two-dimensional vanadium sulfide flexible graphite/polymer films for near-infrared photoelectrocatalysis and electrochemical energy storage", DOI: 10.1016/j.cej.2022.135131</p>
Hydraulic scale model experiments on the two-dimensional run-up and overtopping of solitary waves at a vertical wall and a dam-like structure
<p>This dataset includes the experimental data, which were generated during the study on the run-up and overtopping of solitary waves at the Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich.</p>
Band structure of KTaO3 two dimensional electron gas: ARPES data and tight binding fits
<p>The dataset contains the angle resolved photoemission spectroscopy measurements of the band structure of the two dimensional electron gas generated at the KTaO3/Al interface. Both dispersion and constant energy maps near the Fermi level are provided.</p> <p>The experimental data are complemented with tight binding fits (eight bands).</p>
ATP binding facilitates target search of SWR1 chromatin remodeler by promoting one-dimensional diffusion on DNA
<p>One-dimensional (1D) target search is a well-characterized phenomenon for many DNA-binding proteins but is poorly understood for chromatin remodelers. Herein, we characterize the 1D scanning properties of SWR1, a conserved yeast chromatin remodeler that performs histone exchange on +1 nucleosomes adjacent to a nucleosome-depleted region (NDR) at gene promoters. We demonstrate that SWR1 has a kinetic binding preference for DNA of NDR length as opposed to gene-body linker length DNA. Using single and dual color single-particle tracking on DNA stretched with optical tweezers, we directly observe SWR1 diffusion on DNA. We found that various factors impact SWR1 scanning, including ATP which promotes diffusion through nucleotide binding rather than ATP hydrolysis. A DNA-binding subunit, Swc2, plays an important role in the overall diffusive behavior of the complex, as the subunit in isolation retains similar, although faster, scanning properties as the whole remodeler. ATP-bound SWR1 slides until it encounters a protein roadblock, of which we tested dCas9 and nucleosomes. The median diffusion coefficient, 0.024 μm2/s, in the regime of helical sliding, would mediate rapid encounter of NDR-flanking nucleosomes at length scales found in cellular chromatin.</p>
Three-dimensional surface scans of tooth surfaces of Sika deer from Torihama shell midden site
<p>Three-dimensional surface scans of tooth surfaces of Sika deer remains from Torihama shell midden site are saved in .sur format and surface analyses files in .mnt format, which are analyzed in:</p> <p>Sato, K., and Sato, T., and Kubo, M. O. "Reconstructing diets of hunted sika deer from Torihama shell midden site (ca. 6000 years ago) by dental microwear texture analysis" submitted to Frontiers in Ecology and Evolution. doi: 10.3389/fevo.2022.957038</p> <p>More details can be found in the information published in this paper.</p>
Weights for automatic two-dimensional bedrock fracture trace mapping from outcrop images
<p>This file contains weights for automatic two-dimensional bedrock fracture trace mapping. The weights have been trained on manually mapped traces (https://doi.org/10.5281/zenodo.7077574) that were digitized from UAV-acquired drone orthomosaics from along the shoreline of Loviisa, South-East Finland (https://doi.org/10.5281/zenodo.7077518). Code for automatic mapping and weights generation is available on GitHub (https://github.com/nialov/ALSA).</p> <p>Data is published as Hierarchical Data Format, version 5 (HDF5).</p> <p>The work in automatic mapping was done as part of a Geological Survey of<br> Finland project, Kallioperän Rikkonaisuus, during 2021-2022.</p>
Three-Dimensional Thermoporoelastic Modeling of Hydrofracturing and Fluid Circulation in Hot Dry Rock: EGS Collab Experiment 1
<p>The data regarding the determined natural fractures, locations of monitoring devices, microseismic events, and well trajectories in EGS Collab Experiment 1.</p>
Raw data accompanying the manuscript "Cost-effective high-speed, three-dimensional live-cell imaging of HIV-1 transfer at the T cell virological synapse"
<p>These are the raw datasets used to generate the figures for the manuscript entitled "Cost-effective high-speed, three-dimensional live-cell imaging of HIV-1 transfer at the T cell virological synapse". The data files are 3D image stacks of a custom-built wide field deconvolution fluorescence microscope (.tif) and super-resolution structured illumination microscopy data (.dv) of Jurkat T cells transferring HIV-1 virus particles to previously uninfected primary T cells.</p>
Eddy Duck Data: Measured Three-Dimensional Structure of Surfzone Velocities
<p>This archive contains data from the 2011 EddyDuck experiment. Three-dimensional structure of surfzone velocity fields was measured using 12 horizontally-spaced Nortek Aquadopp current meters, each instrument measuring vertical profiles of water velocity. The experiment was conducted by folks from Washington State University and Oregon State University, with help from staff of the USACE's Duck Field Research Facility.</p> <p>Funding from the US National Sciences Foundation, Award OCE-1061692</p> <p>An in-review JGR-Oceans manuscript “Depth-Dependence of Nearshore Currents and Eddies” discusses the observations.</p> <p> </p> <p>Data are contained in two zip files.</p> <p>File summary.zip unzips to give a folder containing summary data in matlab 2015b format, and a pdf readme file explaining details.</p> <p>Folder full.zip unzips to give a folder containing full time-resolution data in ASCII format, and a readme file explaining details.</p> <p> </p> <p> </p> <p>Questions to steve_henderson@wsu.edu</p>
Quasi-two-dimensional ferromagnetism in the triangular magnet EuAl12O19: Monte Carlo Calculations
<p>This repository contains all classical Monte Carlo calculations relevant for EuAl12O19 material. All calculations were conducted using the UppASD code.</p> <p>Contents:</p> <ul> <li>in the root directory - all plots published in the Calculations section of the paper, together with underlying data</li> <li><code>ab_plane_nodip</code> - a directory containing calculations for <em>M || H || [100]</em> and <em>M || H || [210]</em>, showing that the orientation of spins within the ab-plane does not have an effect on the magnetization curves. Calculated without dipolar interaction</li> <li><code>dm_effect</code> - a directory containing magnetization curve calculations for a) no Dzyaloshinskii-Moriya interaction (<code>dm_effect/0</code>), b) strong Dzyaloshinskii-Moriya interaction of <em>D = J/2</em> (<code>dm_effect/0.00125</code>)</li> <li><code>fit_nodip</code> - a directory with calculations related to J (exchange interaction energy), K (single-ion anisotropy energy) fitting -- <strong>without</strong> dipolar interaction</li> <li><code>fit_dip</code> - a directory with calculations related to J, K fitting -- <strong>with</strong> dipolar interaction, <strong>source of data for plots in the paper</strong></li> </ul> <p><strong>Note</strong>: all directories were archived to .tar.gz files to comply with the file number limit.</p> <h3>MvsB curves</h3> <p>Each directory contains a set of magnetization calculations for various parameters and follows the same strict directory structure: UppASD calculations necessary for the MvsB magnetization curves are found in subdirectory <code>Hsweep/$J/$K/$axis/$T/$H</code> where:</p> <ul> <li><code>$J</code> is the value of exchange interaction energy (in mRy)</li> <li><code>$K</code> is the value of single-ion anisotropy energy (in mRy)</li> <li><code>$axis</code> is the direction of both the external field and the magnetization measurement (either <code>100</code>, <code>210</code> or <code>001</code>)</li> <li><code>$T</code> is the temperature (in Kelvins)</li> <li><code>$H</code> is the strength of the external field (in Teslas)</li> </ul> <p>Each UppASD calculation contains a set of input files (<code>inpsd.dat</code>, <code>posfile</code>, <code>momfile</code>, <code>jfile</code>, <code>kfile</code>) and output files (<code>*.out</code>).</p> <p>Furthermore, files <code>Hsweep/$J/$K/$axis/$T/MvsB.dat</code> contain the data for specific MvsB magnetization curve. Files <code>Hsweep/$J/$K/MvsB-[$axis].png</code> contain plots of MvsB magnetization curves for a specific axis and all available temperatures.</p> <h3>MvsT curves</h3> <p>A similar directory structure exists for calculations necessary for the MvsT curves - <code>Tsweep/$J/$K/$axis/$T</code> where the parameters have the same meaning as in the Hsweep directory.</p> <p>Files <code>Tsweep/$J/$K/$axis/MvsT.dat</code> contain the data for a specific MvsT magnetization curve. Files <code>Tsweep/$J/$K/MvsT.png</code> contain plots of MvsT curves for all available axes.</p> <p><strong>H = 0.1 T for all MvsT measurements</strong>.</p>
Data from: How many specimens make a sufficient training set for automated three dimensional feature extraction?
<p>Deep learning has emerged as a robust tool for automating feature extraction from 3D images, offering an efficient alternative to labour-intensive and potentially biased manual image segmentation methods. However, there has been limited exploration into the optimal training set sizes, including assessing whether artificial expansion by data augmentation can achieve consistent results in less time and how consistent these benefits are across different types of traits. In this study, we manually segmented 50 planktonic foraminifera specimens from the genus Menardella to determine the minimum number of training images required to produce accurate volumetric and shape data from internal and external structures. The results reveal unsurprisingly that deep learning models improve with a larger number of training images with eight specimens being required to achieve 95% accuracy. Furthermore, data augmentation can enhance network accuracy by up to 8.0%. Notably, predicting both volumetric and shape measurements for the internal structure poses a greater challenge compared to the external structure, due to low contrast differences between different materials and increased geometric complexity. These results provide novel insight into optimal training set sizes for precise image segmentation of diverse traits and highlight the potential of data augmentation for enhancing multivariate feature extraction from 3D images. </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.