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1,320 results for “ar”
PAN-AR: A Multimodal Dataset of Higher-Order Ambisonics Room Impulse Responses, Ambient Noise and Spherical Pictures
<h1>PAN-AR</h1> <p>This is <strong>PAN-AR</strong> (Panoramas, Ambient Noise & Ambisonics RIRs), a dataset described in the following <a href="https://doi.org/10.1145/3678299.3678332" target="_blank" rel="noopener">paper</a>:</p> <blockquote> <p>Filippo Denti, Davide Fantini, Federico Avanzini and Giorgio Presti. PAN-AR: A Multimodal Dataset of Higher-Order Ambisonics Room Impulse Responses, Ambient Noise and Spherical Pictures. In <em>Proceedings of the 19th International Audio Mostly Conference</em>, Milan, Italy, September 2024.</p> </blockquote> <p>The dataset includes Spatial Room Impulse Responses (SRIRs) in second-order Ambisonics format, ambient noise recordings, and spherical photos. These data have been captured in four environments with different configurations of the source and listener positions:</p> <ol> <li>Printer room</li> <li>Meeting room</li> <li>Classroom</li> <li>Underground parking area</li> </ol> <p>Panoramas and planimetries are provided in a temporary version. The final version with post-processed panoramas and complete planimetries will be available soon. An example of the final panoramas is provided for position A of the printer room, while an example of complete planimetry is provided for the printer and the meeting rooms.</p> <h2>SOFA</h2> <p>The SRIRs are also provided in SOFA format <a href="https://sofacoustics.org/data/database/pan-ar/" target="_blank" rel="noopener">here</a>.</p> <h2>How to cite</h2> <p>If you use the PAN-AR dataset, please cite the following <a href="https://doi.org/10.1145/3678299.3678332" target="_blank" rel="noopener">paper</a>:</p> <pre><code>@inproceedings{denti2024panar,</code><br><code> title = {{PAN-AR}: A Multimodal Dataset of Higher-Order Ambisonics Room Impulse Responses, Ambient Noise and Spherical Pictures},</code><br><code> author = {Denti, Filippo and Fantini, Davide and Avanzini, Federico and Presti, Giorgio},</code><br><code> year = {2024},</code><br><code> month = {September},</code><br><code> booktitle = {Proceedings of the 19th International Audio Mostly Conference (AM '24)},</code><br><code> location = {Milan, Italy},</code><br><code> publisher = {ACM},</code><br><code> isbn = {979-8-4007-0968-5/24/09},</code><br><code> doi = {10.1145/3678299.3678332}</code><br><code>}</code></pre>
Genetic characterization of Rarámuri Criollo cattle from the USDA-ARS Jornada Experimental Range, Las Cruces, NM, USA
Rarámuri Criollo (RC) cattle have been raised by isolated Tarahumara communities of Chihuahua, Mexico, for nearly 500 years, mostly under natural selection and minimal management. The RC cattle was introduced to the USDA Jornada Experimental Range (RCJER) in 2005 to begin evaluations of beef production performance and their adaptation to the harsh ecological and climatic conditions of the Northern Chihuahuan Desert. While this research unveiled crucial information on their phenotypic plasticity and adaptation, the genetic diversity and structure of the RCJER population remain poorly understood. This study analyzed the genetic diversity, population structure, ancestral composition, and selection signatures of the RCJER herd using a ~64K SNP array. The RCJER herd exhibits moderate genetic diversity and low population stratification with no evident clustering, suggesting a shared genetic background among different subfamilies. Admixture analysis revealed the RCJER herd represents a distinctive genetic pool within the Criollo cattle biotypes, with significant Iberian ancestry. Selection signatures identified candidate genes and Quantitative Trait Loci for traits associated with milk composition, growth, meat and carcass, reproduction, metabolic homeostasis, health, and coat color. The RCJER population represents a distinctive genetic resource adapted to harsh environmental conditions while maintaining productive and reproductive attributes. These findings are crucial to ensuring the long-term genetic conservation of the RCJER and their strategic expansion to locally adapted beef production systems in the US.
Data for "Ab initio studies of the Rg–NO+(X1Σ+) van der Waals complexes (Rg = He,Ne, Ar, Kr, and Xe)"
<p>This upload contains data files with tabulated values of Potential Energy surfaces calculated with CCSD(T)-F12 method for the Rg-NO(+)(r=re), where Rg=He, Ne, Ar, Kr and Xe published in the following paper: </p> <p>Citation: Cahit Orek, Jacek Kłos, François Lique and Niyazi Bulut, The Journal of Chemical Physics 144, 204303 (2016); <br> doi: 10.1063/1.4950813 <br> View online: http://dx.doi.org/10.1063/1.4950813</p> <p>Files:</p> <p>Readme_RgNOplus.txt<br> He-NO(+): HeNOplus_re_Eint.dat<br> Ne-NO(+): NeNOplus_re_Eint.dat<br> Ar-NO(+): ArNOplus_re_Eint.dat<br> Kr-NO(+): KrNOplus_re_Eint.dat<br> Xe-NO(+): XeNOplus_re_Eint.dat<br> Content of the files: <br> Column 1: r(NO)=re=2.0125 bohr<br> Column 2: Jacobi distance R in bohr describing distance of Rg from the center of mass of NO(+). Grid of ~40 points covers values from 3.5 or 4.5 for larger Rg to 30 bohr. <br> Column 3: Jacobi angle theta between r and R. Grid covers values from 0 to 180 degrees every 10 degrees.<br> Column 4: Interaction energy in cm-1, asymptotic value Eint=0 at infinite separation of Rg from NO(+)(r=re)</p>
ELISITY project; Dataset with the photospheric RFLH and various physical parameters for the ARs examined in the project
<p>Dataset with values of the photospheric relative field line helicity (RFLH) in two gauges and of various physical parameters (energies, helicities, quality metrics) for the seven solar active regions examined in the ELISITY project</p>
SGS-LTER Standard Production Data: 1983-2008 Annual Aboveground Net Primary Production on the Central Plains Experimental Range, Nunn, Colorado, USA 1983-2008, ARS Study Number 6 (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-sgs/700/1. The abstract below was extracted from the Level 0 data package and is included for context: This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. The objective of the long-term ANPP study is to monitor long-term net above ground primary production of the shortgrass steppe community by species. There are 6 sites: ridgetop (ridge), midslope (mid), swale, ESA (replicate 1 not 2), Section 25 (SEC 25), and owl-creek (OC). Each site is located in a different landscape position or soil type on the shortgrass steppe and may be grazed or not. Ridgetop, midslope and swale are grazed and are sampled along a catena. Section 25 is grazed and is located in an upload grassland. ESA is an ungrazed upland grassland an is the control from the Ecosystem Stress Area experiment. Owl Creek is ungrazed and is located in the lowland along the owl creek drainage. There are 3 transects with 5 plots in each transect. Plots in the grazed locations are protected by cages. Because this is a monitoring effort, true replicates across the landscape are not
SGS-LTER Long-Term Monitoring Project: Vegetation Cover on Small Mammal Trapping Webs on the Central Plains Experimental Range, Nunn, Colorado, USA 1999 -2006, ARS Study Number 118 (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-sgs/140/17. The abstract below was extracted from the Level 0 data package and is included for context: This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/83458. The abundance and diversity of small mammals in shortgrass steppe is strongly influenced by the structure and composition of vegetation. Vegetation structure provides cover from predators and harsh abiotic conditions. Plant species composition affects the types of seeds and herbaceous material available to granivores and herbivores, and influences arthropod populations, which are important prey for the omnivorous species that dominate in shortgrass steppe. Both vegetation structure and plant community composition are sensitive to the availability of precipitation as well as the activity of large mammalian herbivores. In 1999, we began measuring vegetation structure and plant community composition on the three grassland and three shrubland trapping webs where we live-trap small mammals
SGS-LTER Long-term Monitoring Project: Spotlight Rabbit Count on the Central Plains Experimental Range, Nunn, Colorado, USA 1994-2006, ARS Study Number 98 (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-sgs/136/17. The abstract below was extracted from the Level 0 data package and is included for context: This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/83448. Rabbits are the most important small-mammal herbivores in shortgrass steppe, and may significant influence the physiognomy and population dynamics of herbaceous plants and woody shrubs. Rabbits also are the most important prey of mammalian carnivores such as coyotes and large raptors such as golden eagles and great horned owls. Two hares (Lepus californicus, L. townsendii) and one cottontail rabbit (Sylvilagus audubonii) occur in shortgrass steppe. In 1994, we initiated long-term studies to track changes in relative abundance of rabbits on the Central Plains Experimental Range (CPER). On four nights each year (one night each season, usually on new moon nights in January, April, July, October), we drove a 32-km route consisting of pasture two-track and gravel roads on the CPER. This wa
SGS-LTER Long-Term Montioring Project: Arthropod Pitfall Trapping on Small Mammal Trapping Webs on the Central Plains Experimental Range, Nunn, Colorado, USA 1998-2006, ARS Study Number 118 (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-sgs/134/17. The abstract below was extracted from the Level 0 data package and is included for context: This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/83450. With the exception of heteromyids, eg kangaroo rats and pocket mice, most small rodents in shortgrass steppe are omnivorous. Depending on season, arthropods (insects and arachnids) make up 40-85% of the diet of grasshopper mice and thirteen-lined ground squirrels, the most widespread rodents in northern shortgrass steppe. Small mammals are among the most important predators of ground-dwelling macroarthropods and herbivorous insects provide a direct resource link between weather and plant production. Understanding temporal variability in the abundance of arthropods is central to determining the mechanisms that drive small rodent populations. At present, there are no long-term studies of arthropods in shortgrass steppe, despite the important role that these taxa play in grassland food w
SGS-LTER Long-Term Monitoring Project: Small Mammals on Trapping Webs on the Central Plains Experimental Range, Nunn, Colorado, USA 1994 -2006, ARS Study Number 118 (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-sgs/137/17. The abstract below was extracted from the Level 0 data package and is included for context: This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/83452. Small mammals (rabbits, rodents) are integral components of semiarid ecosystems because of their roles as consumers of plants, seeds and arthropods, as soil disturbance agents, and as food for raptors, snakes and mammalian carnivores. Because of their vagility and intermediate trophic position, populations of small mammals may track changes in vegetation and the abiotic environment that may result from shifts in land-use and other anthropogenic disturbances. However, these populations are variable over space and time, and their response to environmental changes may not be immediately apparent given their behavioral flexibility and relatively long life-spans and generation times. Patterns in the distribution and abundance of small mammals thus may simultaneously reflect and affect the
SGS-LTER Ecosystem Stress Area - long-term density dataset following nutrient enrichment stress on the Central Plains Experimental Range in Nunn, Colorado, USA 1975-2011, ARS Study Number 3 (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-sgs/520/8. The abstract below was extracted from the Level 0 data package and is included for context: This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Water, nitrogen, and water-plus-nitrogen at levels beyond the range normally experience by shortgrass steppe communities were applied from 1971 through 1975, plant densities were sampled through 1977, and then sampling resumed in 1982, with sampling frequencies changing from annually to every other year. The initial sampling from 1970 to 1974 showed that the water and water plus nitrogen treatments had the strongest effect on plant community structure, both treatments increased biomass, and exotic weed species were noted on the water plus nitrogen treatment. Later sampling from 1982 to 1991 showed a ten-fold increase in exotic weed species on the water plus nitrogen plots as compared to the controls (Milchunas and Lauenroth 1995), a community change that has persisted on this site due to a chronic elevation of soil nitrogen caused by a plant tissue/soil organic matter feedback mec
SGS-LTER Ecosystem Stress Area - long-term point-frame (percent basal cover) dataset following nutrient enrichment stress on the Central Plains Experimental Range in Nunn, Colorado, USA 1982-2011, ARS Study Number 3 (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-sgs/521/7. The abstract below was extracted from the Level 0 data package and is included for context: This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Water, nitrogen, and water-plus-nitrogen at levels beyond the range normally experience by shortgrass steppe communities were applied from 1971 through 1975, plant densities were sampled through 1977, and then sampling resumed in 1982, with sampling frequencies changing from annually to every other year. The initial sampling from 1970 to 1974 showed that the water and water plus nitrogen treatments had the strongest effect on plant community structure, both treatments increased biomass, and exotic weed species were noted on the water plus nitrogen treatment. Later sampling from 1982 to 1991 showed a ten-fold increase in exotic weed species on the water plus nitrogen plots as compared to the controls (Milchunas and Lauenroth 1995), a community change that has persisted on this site due to a chronic elevation of soil nitrogen caused by a plant tissue/soil organic matter feedback mec
Jornada Experimental Range (USDA-ARS) annual stocking rates for cattle, horses, and sheep, 1916-2001
This data package contains data on stocking rates for cattle, horses, and sheep on all pastures of the USDA-ARS Jornada Experimental Range beginning in 1916. Grazing goats were infrequent and are therefore included as part of the sheep category. Stocking rates are expressed in animal unit month (AUM), which is based on metabolic weight and average amount of forage needed by each animal unit per month. Total AUM is calculated for each year for each animal unit. This study was completed in 2001 and will not be updated. NOTE: The USDA-ARS discontinued regular updates to this dataset after 2002 because of de-stocking.
Quantum Monte Carlo data for 4He inside Ar-Preplated MCM-41 Nanopores
<p>Raw quantum Monte Carlo data for argon pre-plated MCM-41 nanopores with L = 50 Å.</p> <p>Details of the simulations are published here: https://journals.aps.org/prb/abstract/10.1103/PhysRevB.102.144505</p>
Scans dataset for evaluation of AR-based assembly pipeline of half-timber dry-stone structures
<p><strong>Dataset description</strong></p> <p><em>The dataset is realized by the EPFL Laboratories of IBOIS, and EESD on the occasion of joint collaboration with the common goal of exploring augmented reality (AR)-based fabrication for half-timber dry-stone construction. It is open sourced and free to be used for anyone's own research.</em></p> <p>The current dataset has been employed to evaluate the designed digital fabrication pipeline. It consists of raw point clouds and reconstructed models of two digitized prototypes of one-layered dry-stone structures with a 1.7 m length, ~0.6 height, and 0.7 m width, each with a different composition of building units. The first wall presents 40 mineral by-products uniquely from by-products of quarry processes involving sawing and water-cutting. In contrast, the second wall features 30 mineral scraps issued from all mixed quarry's operations of transformations.</p> <p>The collection contains both the reconstructed models of the as-built artifacts and the corresponding recorded model of the AR-guided assembly processes for the two walls. The recorded model contains meshes of the placed stones accordingly to the developed geometric planner. By comparing the misalignment between each stone of both models (e.g. Root Mean Square Error distances between two set of points) is possible to obtain metrics about the performance of the proposed AR-assembly method.</p> <p> </p> <p><strong>Dataset labeling guide</strong></p> <table summary="test2"> <thead> <tr> <th scope="row">label</th> <th scope="col">content</th> </tr> </thead> <tbody> <tr> <th scope="row">01/02</th> <td>First or second wall.</td> </tr> <tr> <th scope="row">rs</th> <td>Raw data: unprocessed scans.</td> </tr> <tr> <th scope="row">ab</th> <td>As-built model: model presenting all the registered stones.</td> </tr> <tr> <th scope="row">rc</th> <td>Recorded model: collection of tracked stones during the construction. Each stone has being placed following the AR system is recorded in this sub-set.</td> </tr> <tr> <th scope="row">ev</th> <td>Evaluation set: documentation and working files for the evaluation of the developed AR assembly system.</td> </tr> <tr> <th scope="row">colored_stone</th> <td>Evaluation set outcome: a graphical representation of the misalignment between each stone of the as-built model (ab) with the recorded model (rc).</td> </tr> </tbody> </table> <p> </p> <p><strong>Equipement specs</strong></p> <p>All the raw scans present in the dataset have been obtained from a FARO Freestyle 2 equipped with a Mobile PC for live point cloud processing.</p> <pre><code>@manual{farofreestyle2, title = {FARO Freestyle 2 and Mobile PC}, year = 2022, month = feb, note = {User Manual}, organization = {FARO Technologies Inc.}, url = {https://downloads.faro.com/index.php/s/sqcRBipgSy9GaEq?dir=undefined&openfile=138985} } </code></pre> <p> </p> <p><strong>For extra info</strong></p> <p>The open-sourced code for the developed AR assembly:</p> <pre><a href="https://doi.org/10.5281/zenodo.7181087">https://doi.org/10.5281/zenodo.7181087</a></pre> <p>The complete dataset of digitized mineral scraps:</p> <pre><a href="https://doi.org/10.5281/zenodo.7189478">https://doi.org/10.5281/zenodo.7189478</a></pre> <p> </p> <p><strong>Version notes</strong></p> <p>- The current dataset is published as linked documentation to a future publication, yet not reviewed.</p> <p><strong>Change log</strong></p> <p>- Typos</p> <p>- Correct order of authors</p>
VEL-Ar trajectory prediction model linear, co-seismic, and post-seismic grids for interpolation
<p>VEL-Ar trajectory prediction model linear, co-seismic, and post-seismic interpolation grids in ASCII format. The generation of these grids is described in http://doi.org/10.1007/s00190-015-0871-8</p>
MONNALISA_NUM_DA_45_SA_30_AR_5_TR_0.4_Delta_-15
Upload of the numerical solutions for the Reference plane of the MONNALISA Project. Please, refer to the README file of this folder and to the articles associated.
MONNALISA_NUM_DA_45_SA_30_AR_5_TR_0.4_Delta_-35
Upload of the numerical solutions for the Reference plane of the MONNALISA Project. Please, refer to the README file of this folder and to the articles associated.
MONNALISA_NUM_DA_0_SA_30_AR_5_TR_0.4_Delta_-5
Upload of the numerical solutions for the Reference plane of the MONNALISA Project. Please, refer to the README file of this folder and to the articles associated.
MONNALISA_NUM_DA_45_SA_30_AR_5_TR_0.4_Delta_-10
Upload of the numerical solutions for the Reference plane of the MONNALISA Project. Please, refer to the README file of this folder and to the articles associated.
MONNALISA_NUM_DA_0_SA_30_AR_5_TR_0.4_Delta_15
Upload of the numerical solutions for the Reference plane of the MONNALISA Project. Please, refer to the README file of this folder and to the articles associated.
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.