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496 results for “Volcan”
Major element and volatile compositons of volcanic glasses and related datasets for paleobathymetry of the Samail & Troodos ophiolites
<p>This archived dataset accompanies the article "<em>Paleobathymetry of submarine lavas in the Samail and Troodos ophiolites: insights from volatiles in glasses and implications for hydrothermal systems</em>" in the Journal of Geophysical Research: Solid Earth (Belgrano et al. 2021). Comprehensive details on the aquisition and selection of this data are given in the accompanying article.</p> <p>This dataset archive consists of a multi-sheet Excel file containing: (1) Newly measured major element and H<sub>2</sub>O (± CO<sub>2</sub>) compositions for volcanic glasses recovered from the Samail ophiolite, respectively determined by electron microprobe analysis (EMPA) and Fourier Transform infrared spectroscopy (FTIR). (2) The raw Beer-Lambert equation parameters as used to determine these H<sub>2</sub>O (± CO<sub>2</sub>) compositions. (3) The H<sub>2</sub>O (± CO<sub>2</sub>) compositions of volcanic glasses from the Troodos ophiolite reproduced from Woelki et al. (2020) together with newly calculated volatile saturation pressures and their depth equivalents. (4) A compilation of previously published volcanic glass data used to calibrate and test the paleobathymetric approach at the centre of the related publication. (5) A reference list for previously published data.</p>
LOTOS files for Local earthquake tomography of the Aegean crust: Implications for active deformation, large earthquakes, and arc volcanism
<p>This archive contains LOTOS codes and model files/folders associated with the publication "Local earthquake tomography of the Aegean crust: Implications for active deformation, large earthquakes, and arc volcanism" (inside Aeg_tomo.zip)</p> <p> </p> <p>New in version 2:</p> <p>3D model files as well as lateral sections for Vp, Vs, and Vp/Vs (inside nc_3d_model.zip)</p>
CAIRT FL2S Results of Case Study Scenario 4 (CSS4) for Volcanic Eruption
<p>Results of the fast level-2 simulator (FL2S) of CAIRT developed within the Earth Explorer 11 Phase 0 Science and Requirements Consolidation Study (SciReC) – CAIRT. The files contain altitude-time cross-sections of atmospheric parameters along simulated CAIRT-orbits. The variable extensions denote the original field ('_ori'), the application of the averaging kernel ('_ak'), additional application of noise ('_aknoi'), application of systematic uncertainties ('_sys'), and application of all effects ('_aknoisys'). Further information is available from the authors.</p>
CatVolc: A new database of geochemical and geochronological data of volcanic-related materials from the Catalan Volcanic Zone (Spain)
<p>The Catalan Volcanic Zone (CVZ) (NE Spain) consists of an intraplate alkaline volcanic zone associated with the opening of the Western Mediterranean and the development of the European Rift System. Volcanic activity in the CVZ started in the L’Empordà area (ca. > 12 - 8 Ma), extended to La Selva (7.9 - 1.7 Ma), and finally migrated to the Garrotxa Volcanic Field (< 0.7 - 0.01Ma). Despite the scientific interest in the CVZ since the early 19th century, certain aspects remain poorly constrained. These include a full understanding of the spatial and temporal evolution of the magma plumbing system and ascent mechanisms, as well as the chronology of volcanism across the CVZ. Addressing these unresolved questions requires geochemical, petrological, and geochronological data, which, in the case of the CVZ, are scattered and have never been integrated or analyzed within a unified framework. Here, we present the CatVolc (Catalan Volcanism) database, which compiles available geochemical and geochronological data of volcanic-related materials of the CVZ. For each sample, the CatVolc database lists general information about the sampling site, sample lithology, whole-rock analyses (including major and trace elements), isotopic ratios, mineral chemistry, and radiometric/thermoluminescence dating information, if available. A preliminary analysis of the information contained in the CatVolc database highlights the critical limitations of the current state of knowledge and allows suggesting potential future directions for volcanic-driven investigations in the CVZ. Additionally, the results obtained validate the CatVolc database as a key tool for comprehending the spatial and temporal evolution of the magmatic system(s) and volcanic activity in the CVZ, particularly in the Garrotxa Volcanic Field. This aspect is critical for advancing in the assessment of the volcanic hazards in the region and for gaining a comprehensive understanding of future volcanic activity.</p> <p>The current database version consists of three MS Excel files dedicated to primary magmatic rocks (<em>CatVolc_magmatic_rocks.xlsx</em>), xenoliths (<em>CatVolc_xenoliths.xlsx</em>) and radiometric/thermoluminescence dating information (<em>CatVolc_dating.xlsx</em>). Each MS Excel file is structured around a main table (<em>Samples_general_info</em>) containing general information (e.g., location, age, sampling site) of the listed samples, and a certain number of secondary tables. Secondary tables included in the MS Excel files for magmatic rocks and xenoliths report: (i) whole-rock geochemistry (<em>Major_elements</em> and <em>Trace_elements</em>); (ii) isotopic relations data (<em>Isotopic_relations</em>); and (iii) mineral and volcanic glass chemistry (<em>Amphibole</em><strong>, </strong><em>Feldspar</em><strong>, </strong><em>Felspathoid</em><strong>, </strong><em>Glass</em><strong>, </strong><em>Mica</em><strong>, </strong><em>Olivine</em><strong>, </strong><em>Pyroxene</em><strong>, </strong><em>Oxides</em><strong>, </strong><em>Serpentines</em><strong> </strong>and<strong> </strong><em>Sulphides</em><em>)</em>. In addition to the <em>Samples_general_info </em>table, the <em>CatVolc_dating.xlsx </em>also includes radiometric/thermoluminescence dating information (<em>Dating</em>). Finally, in all three Excel files, we have incorporated a table with consulted references (<em>References</em><em>) </em>and a glossary of the acronyms used for the parameters included in the main and secondary tables (<em>Codes</em>). </p> <p> </p>
Data for A volcanic inventory of the Moon
<p>This archive contains shapefiles for <em>A volcanic inventory of the Moon Broquet A. & Andrews-Hanna, J. C., submitted to Icarus (2023). </em>Each shapefile contains an associated .dbf, .prj, and .shx file.</p> <p>RinglikeAnomalies.shp: Shapefile providing our mapping of ring-like gravity anomalies that are associated to dikes. </p> <p>LinearAnomalies.shp: Shapefile providing our mapping of linear gravity anomalies that are associated to intrusive materials.</p>
Major and trace elements abundance of the Belbashani Pumice and other Hasandag deposits, Central Anatolian Volcanic Province
<p>Glass microchemical data, including major and trace elements, of the Belbashani Pumice, a Plinian eruption produced by Hasandag volcano about 400ka ago within the Central Anatolian Volcanic Province (CAVP)</p>
Dataset generated and/or analyzed in the paper "Volcanic unrest after the 2021 eruption of La Palma"
<p>Data generated and/or analyzed in the paper "Volcanic unrest after the 2021 eruption of La Palma" by Jose Fernandez, Joaquin Escayo, Juan F. Prieto, Kristy F. Tiampo, Antonio G. Camacho, and Eumenio Ancochea, submitted to Geophysical Research Letters. Also readme files are included describing the data files.</p>
Tremor catalogs produced (output data) in the paper "Dynamics of the 2021 Fagradalsfjall eruption (Iceland) revealed by volcanic tremor patterns"
<p>This repository contains tremor catalogs produced as output data in the paper "Dynamics of the 2021 Fagradalsfjall eruption (Iceland) revealed by volcanic tremor patterns" submitted to Journal of Geophysical Research - Solid Earth by Soubestre J., Caudron C., Melnik O., Lecocq T., Jaupart C., Shapiro N.M., Journeau C., Çubuk-Sabuncu Y., and Jónsdóttir K.</p> <p>In particular, it contains three catalogs :<br>+ time and 3-D location of <strong>tremor sources</strong> shown in Figure 5 ;<br>+ time and duration of <strong>tremor bursts</strong> associated with pulsating lava fountains shown in Figure 6 ;<br>+ time and duration of <strong>repose times</strong> associated with pulsating lava fountains shown in Figure 6 ;</p>
Earthquake catalogue for the Taupō Volcanic Zone, New Zealand, 2007–2024
<p>These files contain information on the earthquake catalogue presented in Illsley-Kemp & Mestel (2024). This contains earthquakes which occurred in the Taupō Volcanic Zone, New Zealand, between 2007–2024. For detail on methodology please refer to the original publication. There are two types of file; an xml file for each year which is in QuakeML format, this can be read with ObsPy, there is also two csv files, one for the absolute location catalogue, and one for the relocated catalogue.</p> <p>All methodological details can be found in the associate paper, which can be found here: https://seismica.library.mcgill.ca/article/view/1490</p> <p>If using this dataset please cite the orginal paper:</p> <p>Illsley-Kemp, F. and Mestel, E., 2025. A new consistent and high-precision earthquake catalogue for the Taupō Volcanic Zone, New Zealand. <em>Seismica</em>, <em>4</em>(1).</p>
Data & code repository for "A re-appraisal of the ENSO response to volcanism with paleoclimate data assimilation"
<p>This repository includes the data and code that can be used to reproduce the figures for the paper entitled <em>A re-appraisal of the ENSO response to volcanism with paleoclimate data assimilation</em>.</p>
2018 NSF Large Scale Experiment Workshop on Volcanic Blasts
<p><em><strong>A collection of datasets which were recorded at the 2018 NSF Large Scale Experiment Multiblast workshop on volcanic hazards</strong></em>. The workshop aimed to facilitate interdisciplinary collaboration and improve field-scale testing of monitoring methods and models. The workshop had 47 participants from US-based and international institutions. <a href="https://doi.org/10.1029/2018EO109237">Read some more details in this EOS article</a> or a <a href="https://doi.org/10.31223/X55W4F">full manuscript which is currently in review</a>.</p> <p><strong>attention</strong>: This dataset is UNDER CONSTRUCTION. It is close to, but not absolutely complete. We will publish version 1.0 once the accompanying JGR manuscript has been approved for publication.</p> <p>All data is provided in several zip archives, and small files containing metadata and descriptions. Large data chunks are separated into 'pads' (1–4), which refer to the four experiments that were performed. The archives contain a folder structure, which should allow for compatible extractions, so that archives can be downloaded to a common local folder (e.g. using a script) and extracted there without running into file name conflicts.</p> <p>Several teams collaborated to come up with this dataset. Below we list the teams from which data was used and is part of the current version of the dataset. More data may be published in the future and added in a later version. The teams collaborated to varying degrees for different tasks.</p> <p><strong>Teams</strong> in <em>alphabetical</em> order:</p> <ul> <li>Baylor<br> Baylor University<br> Lead by Kenneth Befus</li> <li>BYU<br> Brigham Young University<br> Lead by Neilsen<br> Contributors: TODO</li> <li>INGV<br> Istituto Nazionale di Geofisica e Vulcanologia, Rome<br> Lead by Taddeucci<br> Contributors: Ricci</li> <li>LDEO<br> Lamont Doherty Earth Observatory, Columbia University<br> Lead by Lev, Oppenheimer</li> <li>MTU<br> Michigan Tech University<br> Lead by Waite<br> Contributors: TODO</li> <li>UB<br> University at Buffalo<br> Lead by Sonder, Valentine<br> Contributors: David Hyman, Kayley DiemKaye, Norman Yu</li> <li>UCSB<br> University of California Santa Barbara<br> Lead by Matoza<br> Contributors: Sean Maher, Richard Sanderson</li> <li>UMKC<br> University of Missouri, Kansas City<br> Lead by Graettinger<br> Contributors: Kadie Bennis</li> <li>Yamagata<br> Yamagata University<br> Lead by Kae Tsunematsu</li> </ul> <p><strong>Parts of This Dataset</strong></p> <ul> <li><em>Coordinates & Positions:</em><br> Lead by the UB team.<br> Coordinates and Locations of Blast Charges, Sensors etc.</li> <li> <p><em>Elevation Data of Craters:</em><br> Lead by the UMKC and LDEO teams (Graettinger, Lev).<br> Elevation data were created from photographs taken right after charge detonations. The 3D-data was derived in a standard photogrammetry software (Metashape™). This data was then rasterized and imported into ArcGIS™, and is provided here. Fine adjustments were made to better match reference locations of the available site coordinate system.</p> </li> <li> <p><em>Ejecta Data:</em><br> Lead by the UMKC team.<br> Spatial distribution of ejected material.<br> The <code>.csv</code> files contain the same information as the Excel sheet, but do not contain any graphs.</p> </li> <li> <p><em>Airborne Pressure Data:</em><br> Lead by the BYU team.<br> Archive files: <code>buy_pad[i].zip</code>.<br> Data is arranged in four zip-archives, one for each blast sequence ("Pad"). Each file contains time and pressure arrays and some metadata of one microphone channel. Individual sensor locations are in the <code>positions.zip</code>.</p> <ul> <li>Format: Matlab <code>.mat</code></li> <li>File name patterns after unpacking:<br> <code>data/BYU Acoustics/Data/Aligned with Infra peaks/Pad [i]/TimeSyncPad[i]Ch[k].mat</code><br> <code>[i]</code>: Pad number (1 ... 4)<br> <code>[k]</code>: Channel number.</li> </ul> </li> <li> <p><em>Seismo-Acoustic Data:</em><br> Lead by two teams, UCSB and MTU, who deployed horizontally distributed (UCSB) and vertically distributed (MTU) seismometer stations, and infrasound sensors. MTU also provided a geophone chain. Some of the UCSB sensors were combined with the rapid BYU provided microphones to record a very wide frequency spectrum in ground and atmosphere.</p> <ul> <li> <p>UCSB data structure:<br> Data archives are provided in sensor groups for all experiments (pads). Archive file names are <code>ucsb_[sensor_type]_[sensor_gid].zip</code>. <code>[sensor_type]</code> is one of <code>inf</code> or <code>seis</code>. <code>[sensor_gid]</code> is an identifier for the sensor group (may also be a single sensor) the archive contains. E.g. <code>inf_nyi1</code> contains infrasound data of sensors <code>NYI1.1</code>, <code>NYI1.2</code> and <code>NYI1.3</code>. Use the preview window above to look into the archives. The <code>position</code> archive contains the sensor locations.</p> </li> <li> <p>MTU data structure:<br> Data archives (<code>mtu_seis-infr_pad[i].zip</code>) are organized in 'pads' 1 ... 4 and contain all sensors (infrasound, seismometer, geophones).</p> </li> </ul> </li> <li> <p><em>Video Material:</em><br> No leading team here. Cameras were contributed teams by INGV, LDEO, Yamagata, UB.<br> A drone was deployed for a map-view. Six or more cameras for each pad. Read the <code>video_readme.pdf</code> for details about camera locations and types.</p> </li> </ul> <p><strong>Changes</strong></p> <ul> <li>v0.5:<br> Added the <code>drone2</code> videos from Baylor. (All video zips were updated!)</li> <li>v0.4:<br> Added analysis pack 1 (<code>multiblast_analysis-pack1.zip</code>) code that produced figures and tables of the ms in review. This code is also available on <a href="https://gitlab.com/isonder/2018_blasts">gitlab.com/isonder/2018_blasts</a>.</li> <li>v0.3:<br> Added <code>mtu_seis_infr_metadata.zip</code>. Metadata for the MTU dataset.</li> <li>v0.2:<br> Second batch of main data. >90% complete, I guess.</li> <li>v0.1:<br> First batch of main data.</li> </ul>
WWLLN Datasets for "A Terrestrial Gamma-ray Flash from the 2022 Hunga Tonga–Hunga Ha'apai Volcanic Eruption"
<p>These data files contain data used in the paper "A Terrestrial Gamma-ray Flash from the 2022 Hunga Tonga–Hunga Ha’apai Volcanic Eruption", M. S. Briggs, S. Lesage, C. Schultz, B. Mailyan, R. H. Holzworth, Geophysical Research Letters, 2022.</p> <p>The authors wish to thank the World Wide Lightning Location Network (WWLLN), a collaboration among over 50 universities and institutions, for providing the lightning location data used in these datasets and in the paper. Additional WWLLN data are available at nominal cost from http://wwlln.net.</p> <p>The file named Fig_1.txt contains the data used to generate Figure 1 in the paper.</p> <p>The first two columns list the time ranges for each histogram bin, in UTC on 2022 January 15, while the final column lists the lightning detection rate, in counts per minute, for all WWLLN sferics located within a 400 km radius of the Hunga Tonga–Hunga Ha’apai volcano.</p> <p>The times when Fermi passed within 1000 km of the volcano, shown as grey bars in Figure 1, are:<br> 03:47:58.5 to 03:52:56.2 UTC<br> 05:29:25.1 to 05:33:59.7 UTC<br> 07:11:04.0 to 07:15:18.3 UTC<br> 08:52:04.8 to 08:57:05.1 UTC<br> 10:33:48.1 to 10:37:32.7 UTC</p> <p>The time of the Fermi TGF detection, shown as a red line in Figure 1, is:<br> 08:52:40.011500 UTC</p> <p><br> The file named Fig_2.txt contains the WWLLN sferic data used to generate Figure 2 in the aforementioned paper.</p> <p>This file has the same format as the text files for the WWLLN maps provided in the Fermi GBM TGF catalog, https://fermi.gsfc.nasa.gov/ssc/data/access/gbm/tgf/.</p> <p>Line 1 is the network_name<br> Line 2 is TGF_name<br> Line 3 is the coordinates of Fermi at the time of the TGF (2022-01-15 08:52:40.011500 UTC).<br> Line 4 is the coordinates of the center of the map<br> The second number on line 5 is the number of sferics in a +/- 1 minute interval about the TGF.<br> The remaining 104 lines list the properties of each sferic in columns containing the following information:<br> sequence_number, longitude, latitude, time_separation_between_sferic_and_TGF_corrected_for_light-travel-time</p> <p>The two GLM lightning flashes, shown as magenta dots in Figure 2, have longitude and latitude values:<br> -175.27394, -20.9348<br> -175.29301, -20.8466</p> <p>All of the aforementioned longitudes are East longitudes.<br> </p>
Data depository - "Quantifying the effect of wind on volcanic plumes: implications for plume modelling"
<p>This depository contains all data to understand, evaluate, and build upon the research reported in the manuscript: "Quantifying the effect of wind on volcanic plumes: implications for plume modelling", submitted to Journal of Geophysical Research.</p> <p><strong>Abstract</strong></p> <p>The considerable effects that wind can have on estimates of mass eruption rates (MERs) in explosive eruptions based on volcanic plume height are well known but difficult to quantify rigorously. Many explicitly wind-affected plume models have the additional difficulty that they require the use of centerline heights of bent-over plumes, a parameter not easily obtained directly from observational data. We tested two such models by using the time series of varying plume heights and wind speeds of the 2010 Eyjafjallajökull eruption. The mapped fallout and photos taken during this eruption allow us to estimate the plume geometry and to empirically constrain input parameters for the two models tested. Two strategies are presented to correct the difference in maximum plume height and centerline height: (i) based on plume radius, and (ii) by using the plume type parameter ∏, which quantifies the relative influence of buoyancy and cross-wind on the plume dynamics, to discriminate weak, intermediate and strong plumes. The results indicate that it may be more appropriate to classify plumes as either wind-dominated, intermediate or buoyancy-dominated, where the relative effects of both wind and MER define the type. The analysis of the Eyjafjallajökull data shows that the MER estimates from both models are considerably improved when a plume-type dependent centreline-correction is applied and the wind entrainment coefficient <em>β</em> is refined. For this particular eruption, we find that the best value for <em>β</em> lies between 0.22 and 0.34, unlike previous suggestions that set this parameter to 0.50.</p>
Text-fig. 4. Correlations of the strata in the Urema Graben, the Cheringoma Plateau and other parts of Mozambique proposed by various authors. The positions of fossiliferous units such as the Grudja and Cheringoma formations have been reasonably stable, whereas correlations of other rock units, especially the Mazamba Formation and the volcanics, have varied a great deal. The time scale is from Gradstein et al. (2020). in Stratigraphy, Chronology And Palaeontology Of The Tertiary Rocks Of The Cheringoma Plateau, Mozambique
Text-fig. 4. Correlations of the strata in the Urema Graben, the Cheringoma Plateau and other parts of Mozambique proposed by various authors. The positions of fossiliferous units such as the Grudja and Cheringoma formations have been reasonably stable, whereas correlations of other rock units, especially the Mazamba Formation and the volcanics, have varied a great deal. The time scale is from Gradstein et al. (2020).
CONVERSE 2022 Distributed Volcanism Scenario Exercise materials
<p>The CONVERSE research coordination network, aimed at organizing the US volcano science community towards better organization and collaboration, ran an eruption scenario exercise in February 2022. The exercise simulated an unrest and eruption event in a distributed volcanic field in the southwestern US (Arizona). During the activity, the organizers shared synthetic and re-purposed data and "official" information statements with the participants. Data types included seismic, geodetic (GPS / InSAR), gas, remote-sensing, and imagery. </p> <p>This dataset accompanies the publication "Lessons Learned from the 2022 CONVERSE Monogenetic Volcanism Response Scenario Exercise", by Yolanda Lin et al. </p>
Data Set for "Alteration's control on frictional behavior and the depth of the ductile shear zone in geothermal reservoirs in volcanic arcs" II: Cascade Volcanic Arc
<p>Data set for the 48 friction experiments performed for gouge samples (altered andesitic rocks) from the Cascades used in the manuscript, "Alteration's control on frictional behavior and the depth of the ductile shear zone in geothermal reservoirs in volcanic arcs". This data set can be used in combination with the data set for the Lesser Antilles used in the same manuscript (doi:10.5281/zenodo.10912445). This large combined data set (of 108 frictional experiments) represents a unique opportunity to systematically study frictional behaviour in the framework of rate and state. All samples are tested in wet and dry conditions at 10, 30, and 50 MPa with velocity steps and slide-hold-slides. These two data sets have the further advantage of being performed with exactly the same protocol (same run in, same initial gouge thickness, same velocity steps, same hold periods), in the same machine, by the same operator (or by an operator who was trained and supervised by the original operator). </p>
Fig. 5 in The oldest birotule-bearing freshwater sponges from the Upper Cretaceous-lower Paleocene Deccan volcanic-associated sediments of India
Fig. 5. Spicular complement of skeleton and gemmules of palaeospongillid sponge Longibirotula antiqua gen. et sp. nov. from Upper Cretaceous–lower Paleocene of Naskal GSI Quarry (India) (slides PGNU/NSKQ/ST-1, 2). A, B. Acanthoxeas short with dense spines. C, D. Oxeas fusiform, long and with acute tips. E, F. Birotules with long shaft. Diagenetic processes affect all spicules to various degree. Scale bars 20 µm.
Fig. 3 in The oldest birotule-bearing freshwater sponges from the Upper Cretaceous-lower Paleocene Deccan volcanic-associated sediments of India
Fig. 3. Megascleres of palaeospongillid sponge Longibirotula antiqua gen. et sp. nov. from Upper Cretaceous–lower of Paleocene of Naskal GSI Quarry India). A–H. Acanthoxeas (slides PGNU/NSKQ/SL-1–13) with large spines. Diagenetic processes affect all spicules to various degree. Scale bars 20 µm.
Fig. 1 in The oldest birotule-bearing freshwater sponges from the Upper Cretaceous-lower Paleocene Deccan volcanic-associated sediments of India
Fig. 1. Map of India showing Deccan volcanic province (green area). A. Location of Naskal intertrappean, Naskal B (white star) and Naskal GSI Quarry sections (red star); map modified after Ahluwalia (1990) and Wilson Mantilla et al. (2022). B. Sponge spicule and diatom bearing horizon in Naskal GSI Quarry section. C. Palynomorph bearing Naskal B section (modified after Wilson Mantilla et al. 2022).
Fig. 4 in The oldest birotule-bearing freshwater sponges from the Upper Cretaceous-lower Paleocene Deccan volcanic-associated sediments of India
Fig. 4. Gemmuloscleres of palaeospongillid sponge Longibirotula antiqua gen. et sp. non. from Upper Cretaceous–lower Paleocene of Naskal GSI Quarry (India). A–O. Birotules (slides PGNU/NSKQ/SL-1–13) slender, spiny, with long shaft. Diagenetic processes affect all spicules to various degree. Scale bars 20 µm.
ScienceDex guides
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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.