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662 results for “seismicity”
Dataset of the seismic noise measurements performed from 2009 to 2012 in Subequana Valley (central Italy)
<p>Use is free, provided the aforementioned reference is appropriately cited.<br> The dataset represents the seismic noise measurements performed in Subequana Valley (central Italy) and used in the publication “Gori, S., Falcucci, E., Ladina, C., Marzorati, S., and Galadini, F.: Active faulting, 3-D geological architecture and Plio-Quaternary structural evolution of extensional basins in the central Apennine chain, Italy, Solid Earth, 8, 319-337, doi:10.5194/se-8-319-2017, 2017”.<br> The measurements are archived in SAC format (http://ds.iris.edu/files/sac-manual/manual/file_format.html”).<br> Each SAC file contains information on the measurement parameters. Main header fields:<br> delta: sampling (s)<br> stla: measurement latitude (°N)<br> stlo: measurement longitude (°E)<br> stel: measurement elevation (m a.s.l.)<br> user0: sensor sensitivity (V/m/s)<br> user1: datalogger sensitivity (µV/count)<br> kstnm: measurement code<br> kevnm: experiment name<br> kuser0: gain<br> kuser1: unit of measure<br> kuser2: type of the sensor<br> kcmpnm: seismic channel<br> knetwk: network code of the experiment<br> kinst: type of the datalogger</p> <p>Description of files:<br> - CSVnoise_fromCV35_toCV87.zip: the archive of SAC files relative to noise measurements from CV35 to CV87<br> - CSVnoise_fromCV90_toC119.zip: the archive of SAC files relative to noise measurements from CV90 to C119<br> - CSVnoise_fromC120_toC218.zip: the archive of SAC files relative to noise measurements from C120 to C218</p>
USGSG16AP00094: Developing a seismic velocity model of the central valley, northern California: models SSJDOPHW95, SSJDGRANW95, SSJDFRAN95, and SSJDFRANG16
<p>Data and Figures for final technical report for:<br> USGS16AP00094: Developing a seismic velocity model the Central Valley, Northern California<br> Justin Lindeman, Donna Eberhart-Phillips, Louise H. Kellogg, and Lorraine J. Hwang<br> University of California, Davis</p> <p>Data for the final velocity model SSJD2016 may be found here:<br> <br> Eberhart-Phillips, Donna. (2017). USGSG16AP00094: Developing a seismic velocity model of the central valley, northern California: model SSJD2016 [Data set]. Zenodo. http://doi.org/10.5281/zenodo.556605</p> <p><br> Data for the shallow velocity models can be found in this repository.</p> <p>DATA FILES</p> <p>SSJDOPHW95.out, SSJDGRANW95.out, and SSJDFRANW95.out are crustal velocity models from velocity vs depth relation (Aagaard et al., 2010) and Wentworth et al., 1995 basement surface contours.</p> <p>SSJDFRANG16.out is the crustal velocity model from velocity-vs-depth relations (Aagaard et al., 2010) and <br> Graymer (written communication) 2016 basement surface contours.</p> <p>FIGURES</p> <p>All figures in the final technical report are included here.</p> <p>Map view slices of Vp (All*VP.pdf) and cross sections (All*crosssectionscomp.pdf) are also included in this package.</p> <p>SCRIPTS<br> shallowvelocityFRAN.m, shallowvelocitytygran.m, and shallowvelocityOPH.m are the matlab scripts used to create the shallow velocity models.</p>
Lateral Variations in Upper Mantle Discontinuities beneath Northeast China Revealed by Seismic Ambient Noise
<div>Data description:</div> <div> </div> <div>CCdata.zip:</div> <div>Re-sampling Cross-Correlation functions (4Hz) which contain three seismic arrays.</div> <div>CEA contains HL, JL, LN and NM networks. </div> <div>NECESSarray contains YP network. NECsaids contains DB network. </div> <div>All the stations are located east of 122E, between 41N and 46N. </div> <div>The cross-correlations are used to retrieved body-wave reflections from mantle transition zone discontinuities.</div> <div> </div> <div>Syntheticdata.zip:</div> <div>contains four parts: rawdata1d, rawdata2d, stackedwaveform-2d, and compare-1d</div> <div> </div> <div>rawdata1d: </div> <div>raw synthetic waveforms calculated by Qseis (Wang, 1999) after data-processings.</div> <div>H is increased from 0 to 30 km. </div> <div>The distance is 100 km. </div> <div> </div> <div>rawdata2d: </div> <div>raw synthetic waveforms calculated by SPECFEM2D (Tromp et al., 2008).</div> <div>Three models with depressed d660 (model 1-3) and with a slab on the d660 (model 4). </div> <div>100 receiver stations (surface), from 305 km to 1295 km in 10 km increments.</div> <div>49 vertical single-force sources (surface), from 320 km to 1280 km in 20 km increments </div> <div> </div> <div>stackedwaveform-2d:</div> <div>The final depth results with different models.</div> <div> </div> <div>compare-1d:</div> <div>The waveforms used to compare the rf and cc.</div> <div> </div> <div>Code:</div> <div>These codes can be used to make the figures of synthetic and NCFs results. </div> <div> </div> <div> </div> <div>NECsaidsDescription.docx:</div> <div>Detailed description about the NECsaids project conducted in northeast China from October, 2010 to September, 2017.</div> <div> </div> <div>station_loc.txt:</div> <div>Coordinate file (station, longitude, latitude) of the stations.</div> <div> </div> <div>Reference</div> <div>Wang, R. (1999). A simple orthonormalization method for stable and efficient computation of Green's functions. Bulletin of the Seismological Society of America, 89(3), 733-741. doi: 10.1785/BSSA0890030733</div> <div>Tromp, J., Komatitsch, D. and Liu, Q. Y. (2008). Spectral-element and adjoint methods in seismology. Commun Comput Phys 3, 1-32.</div>
Unraveling the Complex Features of the Seismic Scatterers in the Mid-Lower Mantle through Phase Transition of (Al, H)-Bearing Stishovite
<p>Dataset from the paper "Unraveling the Complex Features of the Seismic Scatterers in the Mid-Lower Mantle through Phase Transition of (Al, H)-Bearing Stishovite"</p>
Quantifying the erasure of earthquake surface ruptures from desert landscapes: Implications for seismic hazard assessment
<p><strong>Original Landscapes</strong></p> <p>DEMs of ~120x140m landscapes clipped from:</p> <p>R1-10 = 2019 M7.1 Ridgecrest earthquake, 2019 lidar (Hudnut et al., 2020), and </p> <p>E1-10 = 2010 M7.2 El Mayor-Cucapah earthquake, 2010 lidar (OpenTopography, 2010).</p> <p>Example: "E5.asc"</p> <p> </p> <p><strong>Degraded Landscapes</strong></p> <p>Linearly diffused using <em>Landlab </em>(Hobley et al., 2017; Barnhart et al., 2020) at timesteps (100, 1000, 5000, 10000 yr) using a <em>k</em> of 1 m^2/kyr.</p> <p>Example: "e5_1000_001_eroded.asc"</p> <p> </p> <p><strong>Mapped Faults Shapefiles </strong>- E1_10_shps & R1_10_shps</p> <p>Faults mapped on each degraded landscape using a systematic mapping process (Scott et al., 2023; Adam, 2023)</p> <p> </p> <p><strong>Ridgecrest DEM</strong> - rc_7_1_0424_utm.tif</p> <p>0.014 m/pix DEM of a portion of the 2019 M7.1 Ridgecrest earthquake rupture, from 6 April 2024. Created from Structure from Motion using drone images. </p> <p> </p> <p><strong>Degradation and analysis python code</strong> - landscape_evolution_earthquake_ruptures-main.zip</p> <p>A set of scripts to simulate the effect of surface processes on surface ruptures and quantify the information loss associated with landscape evolution over time. Includes options to simulate surface processes with linear and non-linear diffusion, implemented using open-access code landlab.</p> <p> </p> <p><strong>References</strong></p> <p>Adam, R. (2023). Evaluation of remote mapping of active fault traces. Arizona State University.</p> <p>Barnhart, K.R., Hutton, E.W.H., Tucker, G.E., Gasparini, NM., Istanbulluoglu, E., Hobley, D.E.J., Lyons, N.J., Mouchene, M., Nudurupati, S.S., Adams, J.M., Bandarogoda, C., 2020, Short communication: Landlab v2.0: A software package for Earth surface dynamics: Earth Surface Dynamics Discussions, doi: 10.5194/esurf-2020-12.</p> <p>Hobley, D.E.J., Adams, J.M., Nudurupati, S.S., Hutton, E.W.H. Gasparini, N.M., Istanbulluoglu, E., and Tucker, G.E., 2017, Creative computing with Landlab: an open-source toolkit for building, coupling, and exploring two-dimensional numerical models of Earth-surface dynamics: Earth Surface Dynamics, v. 5, n. 1, p. 21-46, doi: 10.5194/esurf-5-21-2017.</p> <p>Hudnut, K.W., B. Brooks, K. Scharer, J.L. Hernandez, T.E. Dawson, M.E. Oskin, R. Arrowsmith, C.A. Goulet, K. Blake, M.L. Boggs, S. Bork, C.L. Glennie, J.C. Fernandez-Diaz, A. Singhania, D. Hauser, S. Sorhus (2020). 2019 Ridgecrest, CA Post-Earthquake Lidar Collection. National Center for Airborne Laser Mapping (NCALM). Distributed by OpenTopography. https://doi.org/10.5069/G9W0942Z.. Accessed: 2024-11-25 </p> <p>Opentopography; El Mayor-Cucapah Earthquake (4 April 2010) Rupture LiDAR Scan. Distributed by OpenTopography. https://doi.org/10.5069/G9TD9V7D . Accessed: 2024-11-25</p> <p>Scott, C., Adam, R., Arrowsmith, R., Madugo, C., Powell, J., Ford, J., Gray, B., Koehler, R., Thompson, S., Sarmiento, A., Dawson, T., Kottke, A., Young, E., Williams, A., Kozaci, O., Oskin, M., Burgette, R., Streig, A., Seitz, G., … Ingersoll, S. (2023). Evaluating how well active fault mapping predicts earthquake surface-rupture locations. Geosphere. https://doi.org/10.1130/GES02611.1</p>
Ground-dwelling invertebrates and plants following the application of inverted soil mounding on seismic lines
<p><span>In northern Alberta, Canada, much of treed boreal peatlands are fragmented by seismic lines – linear disturbances where trees and shrubs are cleared for the exploration of fossil fuel reserves. Seismic lines have been shown to have slow tree regeneration, likely due to the loss of microtopography during the creation of seismic lines. Inverted soil mounding is one of the treatments commonly applied in Alberta to restore seismic lines and to mitigate the use of these corridors by wildlife and humans. In 2018, we assessed the effects of mounding on understory plants and arthropod assemblages, three years after treatment application. We sampled in five mounded and five untreated seismic lines, and in their adjacent treed fens (reference fens) within the <span>Canadian Natural Resources Ltd (CNRL) Kirby South in-situ steam-assisted gravity drainage (SAGD) Plant, in the Athabasca oil sands (55°22'37.2" N, 111°10'3" W) of NW Alberta</span>. Here we provide the species composition at these sites.</span></p>
Dataset and LOTOS program code to reproduce the main results of seismic tomography for West Aegean region (Turkey)
<p>This file contains the data to reproduce the results presented in the article: </p><p>Petrov I., Bushenkova N., Gulten, P., (2023). Intracontinental extension settings in the structure of the Aegean region (Turkey): local seismic tomography study., <i>Journal of Geodynamics.</i></p><p>This file includes:</p><p>1. The full version of the LOTOS code for the seismic tomography (Koulakov, 2009);</p><p>2. Folder with the dataset including arrival times of the P and S waves and the location of network from local seismicity in Aegean region of Tukey and it`s surroundings;</p><p>3. README.PDF file with the description of how to reproduce the tomography models and datatests based on data presented in the article. </p><p>Koulakov, I., 2009, LOTOS code for local earthquake tomographic inversion: Benchmarks for testing tomographic algorithms: Bulletin of the Seismological Society of America, v. 99, p. 194–214, https://doi.org/10.1785/0120080013.</p>
Australian sedimentary thickness from seismic receiver functions
<p>This dataset contains data relating to the publication "<a href="https://academic.oup.com/gji/article/237/2/849/7616930?login=true">Sediment thickness across Australia from passive seismic methods</a>" (GJI). The files are as follows:</p> <ol> <li>rfstream.h5 <ul> <li>Contains a <a href="https://rf.readthedocs.io/en/latest/#rf.rfstream.RFStream">rf.RFStream</a> object containing all the receiver functions used in the study</li> </ul> </li> <li>summary_table.csv <ul> <li>Summarises the key seismic measurements of the paper at each seismic station</li> </ul> </li> <li>summary_table.geojson <ul> <li>Same data as summary_table.csv for use in, for example, <a href="https://geopandas.org/en/stable/">GeoPandas</a></li> </ul> </li> </ol> <p> </p>
Seismic and Hydrostratigraphic Characterization of the Onshore-Offshore Freshwater Systems of Martha's Vineyard and Nantucket, Massachusetts, USA: Field Survey Report
<p>This data archive includes three files: field project report, seisimic data (shot gathers) from Martha's Vineyard, and seismic data (shot gathers) from Nantucket. This work was supported by the National Science Foundation (NSF Award 2052794). Technical support was provided by Geophysical Technology, Inc. (<a href="https://geophysicaltechnology.com/">https://geophysicaltechnology.com/</a>), Exploration Instruments (<a href="https://www.exiusa.com/">https://www.exiusa.com/</a>) , and Seismic Source (<a href="https://seismicsource.com/">https://seismicsource.com/</a>). Field work in Manuel F. Correllus State Forest was conducted with the approval of the Massachusetts Department of Conservation and Recreation under Research Access Permit #R-209. Daniel Wright and Conor Laffey of the Massachusetts Department of Conservation and Recreation provided local logistical support on Martha’s Vineyard. Field work on Nantucket was conducted with the approval of Wannacommet Water Company. Mark Willett of Wannacommet water company provided local logistical support on Nantucket.</p>
Seismic data from the HiSEIZE survey
<p>Seismic data from the HiSEIZE acquisition. The data available:</p> <p>Line 1 raw seismic data (.sgy)</p> <p>Line 2 raw seismic data (.sgy)</p> <p>Line 3 raw seismic data (.sgy)</p> <p>Data is unprocessed and fully geometrized.</p> <p>More details about the geometry can me found inside "Data_Description.txt"</p>
Data from: Brittle sedimentary strata focus a multimodal depth distribution of seismicity during hydraulic fracturing in the Sichuan basin, southwest China
<p>The number of background earthquakes (<em>M<sub>L</sub></em> ≥ 0) in the southern Sichuan basin, southwest China, has increased thirtyfold as a result of hydraulic fracturing. Background events are originally deep (4-6 <em>km</em>) within the sedimentary section but build into a multimodal distribution both at depth and in the shallow stimulated reservoir (2-4 <em>km</em>) - representing a counterpoint to the usual triggering of seismicity on deep sub-reservoir basement faults. Surprisingly, the largest events (<em>M<sub>L</sub></em> ≥ 3) evolve in the deep sedimentary strata (4-6 <em>km</em>) that are hydraulically isolated from the injection zone (2-4 <em>km</em>) by low permeability layers. We evaluate the friction-stability rheology of the strata within the full stratigraphic section to define the feasibility of nucleation within these shallow and deep strata. These show velocity-neutral to velocity-weakening behavior in the shallow reservoir transitioning to more strongly velocity-weakening with increase in both depth and temperature. Poroelastic stress calculations confirms that stress transfer, rather than transmitted fluid pressures, are capable of directly reactivating critically-stressed faults at depth, with fluid pressures the triggering source within the shallow reservoir.</p>
Ambient noise from the atmosphere within the seismic hum period band: A case study of hurricane landfall
<p>Spectral analysis results, synthetic Green's functions, and seismic modeling results of this study.</p> <p>This work can be found at GitHub: <a href="https://github.com/NickJi98/Atm_Noise_2024_EPSL.git">https://github.com/NickJi98/Atm_Noise_2024_EPSL.git</a></p>
A Large Fault Partially Reactivated During Two Contiguous Seismic Sequences in Central Italy: The Role of Geometrical and Frictional Heterogeneities
<p>Moment tensor catalog for events with M > 3.0, that occurred between January 2009 and April 2021, in Campotosto area, Italy. Moments tensor were calculated by applying the Time Domain Moment Tensor technique, originally proposed by Dreger and Helmberger (1993) and Pasyanos et al. (1996) and successively implemented at INGV by Scognamiglio et al. (2009).</p> <p>The catalog includes:</p> <p>Location of events: time, depth, lat and lon</p> <p>The moment magnitude: Mw</p> <p>The double-couple value: DC</p> <p>The Variance Reduction value: VR</p> <p>The six moment tensor components: Mxx, Mxy, Mxz, Myy, Myz, Mzz</p> <p>The orientation of nodal planes: strike1, dip1, rake1, strike2, dip2, rake2</p> <p> </p>
SEG-Y Multichannel seismic data collected during RV METEOR expedition M199 and used for publication by Micallef et al., in prep.
<p><span>The dataset comprises 3 multichannel seismic profiles, which have been collected during RV METEOR expedition M199 in February 2024 by the University of Hamburg. Data format is SEG-Y. Trace headers follow SEG-Y Revision 1 standard.</span></p> <p><span>The profiles are:</span></p> <p><span>M199_MCS_HH24-03</span></p> <p><span>M199_MCS_HH24-05</span></p> <p><span>M199_MCS_HH24-29</span></p>
Biaxial seismic response of base-column connections in sub-standard steel buildings: dataset
<p><span>A complete dataset on the response of (semi-rigid and partial strength) column base plate connections in a substandard steel frame tested experimentally, are provided. Free-vibration, cyclic and pseudo-dynamic tests were carried out </span><span>at the Structures Laboratory (STRULAB) of the University of Patras in the framework of </span><span>H2020 EU-funded "</span><span>Engineering Research Infrastructures for European Synergies (ERIES)" project.</span></p> <p><span> </span></p>
Aftershock Relocation of the November 21, 2022 Cianjur (West Java - Indonesia) Earthquake using Temporary Seismic Network
<p>Aftershock Relocation of the November 21, 2022 Cianjur (West Java - Indonesia) Earthquake using Temporary Seismic Network </p>
Upper Crustal Structure of the Xinfengjiang Reservoir from Ambient Noise Double Beamforming Tomography and Its Implications for Induced Seismicity
<p>The file "CC.tar.gz" contains the linearly stacked ZZ component cross-correlations for all station pairs.</p> <p>The file "Model.tar.gz" contains the 3-D upper crustal model of the Xinfengjiang Reservoir via ambient noise Double-Beamforming tomograpy.</p>
"Volcanoes and Seismic Activity Dataset"
<p>El datset “Volcanoes and Seismic Activity Dataset” és el resultat de la PRA1 de l'assignatura de Tipologia i Cicle de Vida de les Dades, del Màster de Ciència de Dades de la UOC.</p> <p>El conjut de dades s'ha generat en aplicació de técniques de web scraping a la pàgina web https://www.volcanodiscovery.com/volcanoes.html, completant el registre de tots els volcans de la pàgina web, certes caracteristiques com d'ubicació, estat i morfologia bàsica i els darrers sísmes asociats a cadascún d'ells a la data dels raspat. </p> <p>El total de volcans únics registrats és de 2.070.</p> <p>El total de registres del dataset és de 3.416. Cada volcà pot tenir diferents sísme associats. </p> <p>El total de camps del dataset és de 10.</p> <p>Descripció dels camps:</p> <ul> <li> <p>Name (nom): Inclou el nom del volcà.</p> </li> <li> <p>URL (enllaç): Inclou els enllaços a la pàgina de cada volcà.</p> </li> <li> <p>Type/Height (tipus i altura): Inclou el tipus de volcà (segons morfologia) i la seva altura en metres (m) i peus (ft).</p> </li> <li> <p>Status (estat): Inclou l’estat del volcà, és a dir, si és un volcà actiu, extingit, i el seu grau d’activació en escala Likert del 0 (extingit) al 5 (actiu).</p> </li> <li> <p>Territory/Geolocation (Territori/coordenades geolocalització): Inclou la regió on es troba el volcà i les coordenades de localització.</p> </li> <li> <p>Eruption style (tipus d’erupcions): Inclou el tipus d’erupció observada per cada volcà. En alguns casos, pot incloure més d’un estil d’erupció.</p> </li> <li> <p>Earthquake date (data del terratrèmol): Si el volcà té un terratrèmol associat, la data i l’hora en què va passar el terratrèmol. En alguns casos, indica també els dies que fa des de la seva ocurrència prenent com a referència el moment en què es va realitzar l’scraping.</p> </li> <li> <p>Magnitude/Depth (magnitud/profunditat): Inclou la magnitud i la profunditat del terratrèmol. Cal separar els dos valors en una posterior neteja de les dades: les dues primeres xifres, normalment separades per un punt, fan referència a la magnitud i les últimes xifres, a la profunditat (ex. 3.4205 km es correspondria a una magnitud de 3.4 i una profunditat de 205 km).</p> </li> <li> <p>Distance (distància): Inclou la distància del terratrèmol respecte del volcà i la direcció.</p> </li> <li> <p>Earthquake location (ubicació del terratrèmol): Inclou el país/estat i l’àrea o regió on s’ha donat el terratrèmol.</p> </li> </ul>
CSRM Level 2 dataset: Seismometer orientation measurements of broadband seismic stations in the China Digital Seismograph Network
<p>This dataset contains detailed information on the azimuths of more than one thousand stations in the China Digital Seismic Network (CDSN) since 2014. Deng <em>et al</em>. (2024) utilized 5,456,816 three-component waveform data recorded by 1,056 broadband seismic stations of the CDSN from 2014 to 2022 to evaluate and correct the azimuths of the network. The primary research method employed was far-field <em>P</em>-wave polarization analysis, including principal component analysis and minimum tangential energy methods. By integrating the advantages of these two methods, they conducted a detailed analysis of the azimuths across the CDSN and carried out in-depth examinations and cause analyses for stations with significant azimuth deviations (>5°). Through a comprehensive analysis of the calculation results, network operation logs, and on-site inspections, they obtained detailed information on the azimuths of more than one thousand stations in the CDSN since 2014. <strong>Appendix I</strong> lists azimuth deviations for 956 stations, while <strong>Appendix II</strong> documents temporal variations in the azimuths for 104 stations.</p> <p>本数据库包含自 2014 年以来中国数字地震台网超过千个台站方位角的详细信息。Deng等 (2024) 依托中国数字地震台网 2014 至 2022 年间 1056 个宽频带地震台站所记录的 5,456,816 个三分量波形数据, 开展了台网方位角的评估与校正工作。研究方法主要采用远场 <em>P</em> 波偏振分析, 包括主成分分析和最小切向能量法。结合这两种方法的优点, 他们对中国数字地震台网的方位角进行了详细分析, 并对方位角偏差较大的台站 (>5°) 进行了深入检查与原因分析。通过对计算结果、台网运维日志及现场检查的综合分析, 他们获得了自 2014 年以来中国数字地震台网超过千个台站方位角的详细信息 (<strong>附件一</strong>列出了 956 个台站的方位角偏差, <strong>附件二</strong>记录了 104 个随时间变化的方位角信息) 。</p> <p><strong>Reference</strong>: Deng, W., Han, G., Li, J., & Sun, L. Seismometer Orientation Measurements of Broadband Seismic Stations in the China Digital Seismograph Network. <strong><a href="https://doi.org/10.1785/0120240075">Paper link</a></strong></p> <p>If you face any problem or issue in the usage of this dataset, please feel free to communicate with the corresponding author Juan Li (<strong>juanli@mail.iggcas.ac.cn</strong>).</p>
Seismic Reflection Data from the Kentland Impact Structure, Indiana from Robitaille MSc (2024)
<p>This repository contains the correlated and stacked shot gathers and the final unmigrated and migrated files (all in SGY format) collected near the Kentland Crater Impact Structure. These data are associated with the MSc thesis of Brian Robitaille at Purdue University (2024). See citation below.</p>
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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.