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.
1,819
datasets available to search
ShareScore release 0.9.0
Dataset results
1,819 results for “Experimental data”
Source code and experimental data of human brain tissue (visual cortex, corona radiata) for poro-viscoelastic parameter identification
<p>Computer code and experimental data that we used for our inverse parameter identification of poro-viscoelastic material parameters for two different brain regions: visual cortex (gray matter) and corona radiata (white matter). The experimental data comprises large-strain cyclic loading and compression/tension relaxation. For details see the corresponding publication: "Model-driven exploration of poro-viscoelasticity in human brain tissue: Be careful with the parameters!".</p> <p>Further explanation regarding the specimen preparation, experimental setup, as well as the assignment of regions and governing regions can be found in Hinrichsen, J., Reiter, N., Bräuer, L. et al. Inverse identification of region-specific hyperelastic material parameters for human brain tissue. Biomech Model Mechanobiol (2023). <a href="https://doi.org/10.1007/s10237-023-01739-w" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s10237-023-01739-w</a>.</p> <p>The file "<span>nonlinear-poro-viscoelasticity.cc</span>" contains our C++ Finite Element code based on the open source library deal.II. It is accompanied by an exemplary parameter file.</p> <p><strong>Funding:</strong> The support from the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) through the grants BU 3728/1-1, BU 3728/3-1, STE 544/70-1 as well as through project number 460333672 CRC1540 Exploring Brain Mechanics is gratefully acknowledged.</p>
Experimental raw data (PbS QDs)
<div> <h2>PL + abs</h2> Absorbance (Abs.txt) and photoluminescence (PLspectra) data. PL spectra were measured under 515 nm laser excitation at power densities of 341 W/cm² (PLspectra_6uW 60x2avg per 1s.txt) and 56.9 kW/cm² (PLspectra_1mW 60x2avg per 1s.txt), respectively.</div> <div> <h2>TR PL</h2> Time-resolved photoluminescence data were measured under long-duration (LD, 25 µs length) and short-duration (SD, 70 ns) excitation laser pulses. Laser power is given in µW. OD filters, if present in the file name, were used to reduce the signal between the sample and the APD. "no.seq" refers to the number of sweeps (repetitions). The time step is 25 µs.</div>
Data from an experiment on the effects of using an experimental framework on the quality of research designs
Open the record for dataset details and reuse information.
Code and data associated with Christiansen et al. 2021 "Facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing"
<p>All code and data input and output files (except reference genome and raw sequencing data) needed to reproduce the results of Christiansen et al. 2021 as released on <a href="https://github.com/notothen/radpilot">https://github.com/notothen/radpilot</a> alongside journal publication. See published paper:</p> <p>Christiansen, H., Heindler, F.M., Hellemans, B. <em>et al.</em> Facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing. <em>BMC Genomics</em> <strong>22, </strong>625 (2021). <a href="https://doi.org/10.1186/s12864-021-07917-3">https://doi.org/10.1186/s12864-021-07917-3</a></p>
Experimental data on plastered rubble stone masonry walls
<p>This repository contains data from experimental tests on plastered rubble stone masonry walls conducted at École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland. </p> <p><strong>Data visualization in RENKU</strong>: <a href="https://renkulab.io/projects/eesd.epfl/plastered-rubble-stone-masonry-walls">Click here</a></p> <p>Please cite the following related publications:</p> <blockquote> <p><br> [1] Rezaie, A., Godio, M., Beyer, K. (2020). Experimental investigation of strength, stiffness and drift capacity of rubble stone masonry walls. Construction and Building Materials, 251, 118972.</p> <p> </p> <p>[2] Rezaie, A., Achanta, R., Godio, M., Beyer, K. (2020). Comparison of crack segmentation using digital image correlation measurements and deep learning. Construction and Building Materials, 261, 120474.</p> <p> </p> <p>[3] Rezaie, A., Godio, M., & Beyer, K. (2021). Investigating the cracking of plastered stone masonry walls under shear–compression loading. Construction and Building Materials, 306, 124831.</p> <p><br> [4] Rezaie, A., Godio, M., Achanta, R., & Beyer, K. (2022). Machine-learning for damage assessment of rubble stone masonry piers based on crack patterns. <em>Automation in Construction</em>, <em>140</em>, 104313.</p> </blockquote>
Supporting data for: "Hybrid Computational-Experimental Data-Driven Design of Self-Assembling π-Conjugated Peptides"
<p>This repository contains supporting data and code for the paper titled "Hybrid Computational-Experimental Data-Driven Design of Self-Assembling π-Conjugated Peptides" by Kirill Shmilovich, Sayak Subhra Panda, Anna Stouffer, John D. Tovar, and Andrew L. Ferguson.</p>
Experimental data for "DeepMetis: Augmenting a Deep Learning Test Set to Increase its Mutation Score" paper
<p>Experimental data for "DeepMetis: Augmenting a Deep Learning Test Set to Increase its Mutation Score" paper</p>
Experimental sloshing pressure data from "Improving stability of moving particle semi-implicit method by source terms based on time-scale correction of particle-level impulses"
<p>3D sloshing in a prismatic tank under translational coupled surge-sway (X and Y axis) motions. The main dimensions are height H<sub>T</sub> = 0.54m, width W<sub>T</sub> = 0.84m and length L<sub>T</sub> = 0.72m. The filling ratio of 50% (H<sub>F</sub> = 0.27m). The periods of surge and sway excitations are T<sub>s</sub> = 1.25s with amplitude motions of A<sub>x</sub> = 0.0144m (0.02 x length) and A<sub>y</sub> = 0.0168m (0.02 x width).</p> <p>Files:</p> <p><strong>experimental_slosh_h50_20cycles_p1_dt0p000100.txt</strong>: Experimental pressure data at sensor P1</p> <p><strong>slosh_3d_exp_timer</strong>: Experimental movie</p> <p><strong>sloshing_tank_dimensions.pdf</strong>: Tank main dimensions</p> <p> </p> <p>The experimental data was used in:</p> <p>Cheng, L.Y., Amaro Junior, R.A., Favero, E.H. (2021). Improving stability of moving particle semi-implicit method by source terms based on time-scale correction of particle-level impulses. Engineering Analysis with Boundary Elements, 131, 118-145. Available at. doi: <a href="https://doi.org/10.1016/j.enganabound.2021.06.018">https://doi.org/10.1016/j.enganabound.2021.06.018</a></p>
Fig. 3 a-h in Ecological characterization of habitats colonized by the freshwater gastropod Viviparus contectus (MILLET, 1813) (Gastropoda, Prosobranchia) - Theoretical and experimental data
Fig. 3 a-h: Logistic regression models of the single environmental variables for the presentation of eventual habitat preferences of V. contectus. For a validation of the models experimental data from diverse field studies were used (e.g., PATZNER & ISARCH 1999, STURM 2000a).
Fig. 1 in Ecological characterization of habitats colonized by the freshwater gastropod Viviparus contectus (MILLET, 1813) (Gastropoda, Prosobranchia) - Theoretical and experimental data
Fig. 1: Stereoscopic photographs showing the front and back of the shell of V. contectus with its typical shape and mouth geometry. The height of the shells measures about 4.5 cm.
Fig. 2 a-h in Ecological characterization of habitats colonized by the freshwater gastropod Viviparus contectus (MILLET, 1813) (Gastropoda, Prosobranchia) - Theoretical and experimental data
Fig. 2 a-h: Box-plots for the statistical evaluation of single environmental variables under incorporation of all malacological data available in the scientific literature and those data with occurrence of V. contectus, respectively. The black boxes range from the first to the third quartile, whereas the ends of the lines mark the minimum and the maximum of the data. The white line indicates the position of the median.
Supplementary data for the manuscript "Comparison of computational and experimental saturation vapor pressures of α-pinene + O3 oxidation products"
<p>COSMO-files of potential ozonolysis products of α-pinene for the manuscript:<br> Hyttinen, N., Pullinen, I., Nissinen, A., Schobesberger, S., Virtanen, A., and Yli-Juuti, T.: Comparison of computational and experimental saturation vapor pressures of α-pinene + O<sub>3</sub> oxidation products, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2021-775, in review, 2021.</p>
Experimental data of "Novel flow modulation method for R744 two-phase ejectors – Proof of concept, optimization and first experimental results"
<p>Experimental data of "Novel flow modulation method for R744 two-phase ejectors – Proof of concept, optimization and first experimental results"</p>
Data from: Selection on growth rate and local adaptation drive genomic adaptation during experimental range expansions in the protist Tetrahymena thermophila
<p>1. Populations that expand their range can undergo rapid evolutionary adaptation of life-history traits, dispersal behaviour, and adaptation to the local environment. Such adaptation may be aided or hindered by sexual reproduction, depending on the context.</p> <p>2. However, few empirical and experimental studies have investigated the genetic basis of adaptive evolution during range expansions. Even less attention has been given to the question how sexual reproduction may modulate such adaptive evolution during range expansions.</p> <p>3. We here studied genomic adaptation during experimental range expansions of the protist <em>Tetrahymena thermophila</em>in landscapes with a uniform environment or a pH-gradient. Specifically, we investigated two aspects of genomic adaptation during range expansion. Firstly, we investigated adaptive genetic change in terms of the underlying numbers of allele frequency changes from standing genetic variation and <em>de novo</em><span> variants. We focused on how sexual reproduction may alter this adaptive genetic change. Secondly, we identified genes subject to selection caused by the expanding range itself, and directional selection due to the presence or absence of the pH-gradient. We focused this analysis on alleles with large frequency changes that occurred in parallel in more than one population to identify the most likely candidate targets of selection. </span></p> <p><span>4. We found that sexual reproduction altered adaptive genetic change both in terms of <em>de novo</em></span><span> variants and standing genetic variation. However, sexual reproduction affected allele frequency changes in standing genetic variation only in the absence of long-distance gene flow. Adaptation to the range expansion affected genes involved in cell divisions and DNA repair, whereas adaptation to the pH-gradient additionally affected genes involved in ion balance, and oxidoreductase reactions. These genetic changes may result from selection on growth and adaptation to low pH. </span></p> <p><span>5. In the absence of gene flow, sexual reproduction may have aided genetic adaptation. Gene flow may have swamped expanding populations with maladapted alleles, thus reducing the extent of evolutionary adaptation during range expansion. Sexual reproduction also altered the genetic basis of adaptation in our evolving populations via <em>de novo </em>variants, possibly by purging deleterious mutations or by revealing fitness benefits of rare genetic variants. </span></p>
Experimental investigation of composite materials for sliding friction dampers: data, plots, photos and videos of the tests
<p><strong>Folder DATA</strong></p> <p>This folder contains the data acquired by testing the friction pads M1, M2, M3, M4 and M5 under the following loading protocols:</p> <ul> <li>Linear static loading (M);</li> <li>Cyclic loading with constant amplitude (CA);</li> <li>Cyclic loading with decreasing amplitude at low rate (DA);</li> <li>Cyclic loading with increasing amplitude at low rate (IA);</li> <li>Cyclic loading with increasing amplitude at moderate rate (IA-H);</li> <li>Cyclic loading with increasing amplitude at high rate (IA-HH);</li> <li>Pulse-like loading protocol (PL);</li> <li>Mainshock-aftershock protocol (MS-AS): mainshock (MS), first aftershock (AS1) and second aftershock (AS2).</li> </ul> <p>The data include:</p> <ul> <li><em>Time</em>: time (unit: second);</li> <li><em>F</em>: axial force experienced by the sliding friction damper (unit: kN);</li> <li><em>N_bolt</em>: bolt preload (unit: kN);</li> <li><em>mu</em>: friction coefficient of the considered pad (unit: dimensionless);</li> <li><em>delta</em>: axial displacement experienced by the sliding friction damper (unit: mm);</li> <li><em>Cum. delta</em>: total cumulative displacement experienced by the sliding friction damper (unit: mm);</li> <li><em>Cum. E</em>: total cumulative energy dissipated by the sliding friction damper (unit: kJ);</li> <li><em>max Tin</em>: maximum temperature tracked close to the sliding interface (unit: Celsius);</li> <li><em>Tout</em>: temperature tracked at the surface of the inner slotted plate (unit: Celsius).</li> </ul> <p> The data are organized as follows:</p> <ul> <li>Folder <strong>T100</strong></li> </ul> <p>This folder contains the data acquired under the linear static loading protocol (M) for a tightening torque of 100 Nm. Each EXCEL file <strong>T100_M_Y</strong> saved in the folder <strong>T100</strong> contains the data obtained by testing the friction pad Y (Y = M1, M2, M3, M4, M5) under the loading protocol M.</p> <ul> <li>Folder <strong>T200</strong></li> </ul> <p>This folder contains the data acquired under the linear static loading protocol (M) for a tightening torque of 200 Nm. Each EXCEL file <strong>T200_M_Y</strong> saved in the folder <strong>T200</strong> contains the data obtained by testing the friction pad Y (Y = M1, M2, M3, M4, M5) under the loading protocol M.</p> <ul> <li>Folder <strong>Fs150</strong></li> </ul> <p>This folder contains the data acquired for an expected slip load of 150 kN. Each subfolder <strong>Fs150_X</strong> contains the data obtained under the loading protocol X (X = M, CA, DA, IA, IA-H). Each EXCEL file <strong>Fs150_X_Y</strong> saved in the subfolder <strong>Fs150_X</strong> contains the data obtained by testing the friction pad Y (Y = M1, M2, M3, M4, M5) under the loading protocol X.</p> <ul> <li>Folder <strong>Fs300</strong></li> </ul> <p>This folder contains the data acquired for an expected slip load of 300 kN. Each subfolder <strong>Fs300_X</strong> contains the data obtained under the loading protocol X (X = M, CA, DA, IA, IA-H, IA-HH, PL, MS, AS1, AS2). Each EXCEL file <strong>Fs300_X_Y</strong> saved in the subfolder <strong>Fs300_X </strong>contains the data obtained by testing the friction pad Y (Y = M1, M2, M3, M4, M5) under the loading protocol X.</p> <p><strong>Folder PHOTOS</strong></p> <p>This folder contains the following photos:</p> <ul> <li>Folder <strong>01_FrictionDamper</strong>: photos of the sliding friction damper and its components.</li> <li>Folder <strong>02_Instrumentation</strong>: photos of the instrumentation used for the data acquisition during the experimental campaign.</li> <li>Folder <strong>03_FrictionPads</strong>: <ul> <li>Subfolder <strong>BeforeTesting</strong>: photos of the friction pads before the experimental campaign.</li> <li>Subfolder <strong>AfterTesting</strong>: photos of the friction pads at the end of each loading protocol. The photo <strong>Fs150vs300_X_Y</strong> shows the condition of the pad Y (Y = M1, M2, M3, M4, M5) at the end of the loading protocol X (X = M, CA, DA, IA, IA-H, IA-HH, PL, MS, AS1, AS2) performed for an expected slip load of 150 kN and 300 kN (the pads shown at the top of each photo are those tested for an expected slip load of 150 kN). Similarly, the photo <strong>Fs300_X_Y</strong> shows the condition of the pad Y at the end of the loading protocol X performed for an expected slip load of 300 kN.</li> </ul> </li> <li>Folder <strong>04_Tests</strong>: photos taken from the east and north side of the sliding friction damper during the loading protocols that caused the fracture of the pads <ul> <li>Subfolder <strong>Fs150</strong>: photos taken during the tests conducted for an expected slip load of 150 kN. Each folder <strong>Fs150_X_Y</strong> contains the photos taken by testing the pad Y (Y = M1, M2, M4, M5) during the loading protocol X (X = CA, DA, IA, IA-H).</li> <li>Subfolder <strong>Fs300</strong>: photos taken during the tests conducted for an expected slip load of 300 kN. Each folder <strong>Fs300_X_Y</strong> contains the photos taken by testing the pad Y (Y = M1, M2, M4, M5) during the loading protocol X (X = CA, IA, IA-H). A video was recorded live during the loading protocols IA-HH, PL, MS, AS1 and AS2 (see folder <strong>VIDEOS</strong>).</li> </ul> </li> </ul> <p><strong>Folder PLOTS</strong></p> <p>This folder contains the following MATLAB plots:</p> <ul> <li><em>Force-Disp</em>: axial force – axial displacement response of the sliding friction damper;</li> <li><em>Preload-CumDisp</em>: bolt preload as a function of the total cumulative displacement experienced by the sliding friction damper;</li> <li><em>FrictionCoeff-CumDisp</em>: friction coefficient of the considered pad as a function of the total cumulative displacement experienced by the sliding friction damper;</li> <li><em>Temp-CumDisp</em>: rise in temperature as a function of the total cumulative displacement experienced by the sliding friction damper (the temperature values reported for the expected slip load of 150 kN correspond to “max Tin”, whereas those reported for the expected slip load of 300 kN correspond to “Tout”);</li> <li><em>FrictionCoeff-LoadingHistoryEffect</em>: friction coefficient of the considered pad as a function of the total cumulative displacement experienced by the sliding friction damper under different loading protocols;</li> <li><em>FrictionCoeff-RateEffect</em>: friction coefficient of the considered pad as a function of sliding velocity experienced by the sliding friction damper under different loading protocols;</li> <li><em>FrictionCoeff-TempEffect</em>: friction coefficient of the considered pad as a function of the rise in temperature tracked during different loading protocols;</li> <li><em>FrictionCoeff-PressureDependency</em>: mean and standard deviation of the friction coefficient of the considered pad obtained for different expected slip loads and loading protocols;</li> <li><em>FrictionCoeffStaticDynamic-PressureDependency</em>: mean of the static and dynamic friction coefficient of the considered pad obtained for different expected slip loads and loading protocols.</li> </ul> <p>The MATLAB plots are organized as follows:</p> <ul> <li>Folder <strong>T200</strong></li> </ul> <p>The MATLAB plots saved in this folder illustrate the data obtained by testing the friction pads M1, M2, M3, M4 and M5 under the linear static loading protocol (M) for a tightening torque of 200 Nm.</p> <ul> <li>Folder <strong>Fs150 and Fs300</strong></li> </ul> <p>The MATLAB plots saved in this folder illustrate the data obtained by testing the friction pads M1, M2, M3, M4 and M5 under the considered loading protocol (M, CA, DA, IA, IA-H, IA-HH, PL, MS-AS) for an expected slip load of 150 kN and 300 kN.</p> <p><strong>Folder VIDEOS</strong></p> <p>This folder contains the following videos:</p> <ul> <li>Folder <strong>T100</strong>: videos created from the photos taken during the tests conducted for a tightening torque of 100 Nm under the linear static loading protocol (M). The videos <strong>T100_M_Y_East</strong> and <strong>T100_M_Y_North</strong> show the test conducted on the pad Y (Y = M1, M2, M3, M4, M5) from the east and north side of the sliding friction damper respectively.</li> <li>Folder <strong>T200</strong>: videos created from the photos taken during the tests conducted for a tightening torque of 200 Nm under the linear static loading protocol (M). The videos <strong>T200_M_Y_East</strong> and <strong>T200_M_Y_North</strong> show the test conducted on the pad Y (Y = M1, M2, M3, M4, M5) from the east and north side of the sliding friction damper respectively.</li> <li>Folder <strong>Fs150</strong>: videos created from the photos taken during the tests conducted for an expected slip load of 150 kN. The videos <strong>Fs150_X_Y_East</strong> and <strong>Fs150_X_Y_North</strong> show the loading protocol X (X = M, CA, DA, IA, IA-H) applied to the pad Y (Y = M1, M2, M3, M4, M5) from the east and north side of the sliding friction damper respectively.</li> <li>Folder <strong>Fs300</strong>: videos created from the photos taken during the tests conducted for an expected slip load of 300 kN. The videos <strong>Fs300_X_Y_East</strong> and <strong>Fs300_X_Y_North</strong> show the loading protocol X (X = M, CA, DA, IA, IA-H) applied to the pad Y (Y = M1, M2, M3, M4, M5) from the east and north side of the sliding friction damper respectively. The videos obtained for the loading protocols IA-HH, PL, MS, AS1 and AS2 were recorded live during each test.</li> </ul>
Arabidopsis HapMap screen for salt-induced changes in root:shoot ratio - data for all experimental batches
<p>Quantified root and shoot area of the 360 Arabidopsis accessions exposed to salt stress / control treatment. The data were collected during PhD of Magdalena Julkowska at University of Amsterdam, under supervision of Dr. Christa Testerink. The quantification of root system architecture was performed at University of Amsterdam, under supervision of Dr. Christa Testerink, and was used for the publication of Julkowska et al., 2017 (<a href="https://doi.org/10.1105/tpc.16.00680">https://doi.org/10.1105/tpc.16.00680</a>). The quantification of the root and shoot data was performed with custom developed tool at King Abdullah University of Science and Technology, during Magdalena Julkowska's Postdoc, under supervision of Dr. Mark Tester. </p>
Experimental Data of Edge Energy Management System (EEMS)
<p>Readme>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>><br> This data repository contains the experimental data of low-voltage and <br> industrial settings. Separate folders are provided for both data artefacts.</p> <p>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>></p> <p>Low Voltage Residential Settings >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>><br> Different sub-Folders are provided with respect to the different <br> combination of electrical load</p> <p>Each folder contains .txt file</p> <p>This File Contains Timestamp such that date and time are separated by "!".<br> After parsing time, Voltage and Current are separated by the "Current".<br> Then each voltage and current waveforms can be further parsed by "@@@"<br> because non-consecutive waveform signals are separated using this symbol in <br> project. Furthermore, the variable slab during data acquisition is provided <br> at the end of .txt file and can be parsed using the term "Const"</p> <p>This data parsing process is also provided in all phase calculation files.</p> <p>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>></p> <p>Industrial Islanded Power System >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>><br> This Folder contains the data acquired from 15 diesel gensets. Their <br> operational parameters are logged in MySQL database and are presented using<br> LAMP server. This MySQL data is provided as CSV file in this folder.</p> <p>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>></p> <p> </p>
Assessing-the-role-of-non-linear-contact-mechanics-for-flow-in-fractures---experimental_data
<p>Data to reproduce pressure response spectra from a number of harmonic measurements shown in "Assessing the role of non-linear contact mechanics for<br> flow in fractures"</p> <p><strong>Note:</strong> Data of AFR, BHR and TER has been extracted from papers published by authors others than the ones mentioned in the author list. The publications are referenced in the .txt files and the paper mentioned above.</p>
Using generative adversarial networks to match experimental and simulated inelastic neutron scattering data
<p>Files uploaded here are related to the paper titled "Using generative adversarial networks to match experimental and simulated inelastic neutron scattering data". Here we investigate how generative adversarial networks can be used to match simulated- and experimental INS data.</p>
Experimental Electrical Impedance Tomography Data Set Using the Spectra Bioimpedance and EIT Complete Kit
<p><strong>Abstract</strong></p> <p>The amount of open-source EIT measurement data is low. This data set concerns the acquisition and processing of different measurement data using the SpectraEIT-Kit as well as information about the deposited files.</p> <p><strong>Aknoelegenment</strong><br> Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – SFB 1270/2 - 299150580.</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.