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275 results for “Data Storage”
Data from: A synthesis of the effects of cheatgrass invasion on U.S. Great Basin carbon storage
<p>Non-native, invasive Bromus tectorum (cheatgrass) is pervasive in sagebrush ecosystems in the Great Basin ecoregion of the western U.S., competing with native plants and promoting more frequent fires. As a result, cheatgrass invasion likely alters carbon (C) storage in the region. Many studies have measured C pools in one or more common vegetation types: native sagebrush, invaded sagebrush, and cheatgrass-dominated (often burned) sites, but these results have yet to be synthesized.</p> <p>We performed a literature review to identify studies assessing the consequences of invasion on C storage in aboveground biomass (AGB), belowground biomass (BGB), litter, organic soil, and total soil. We identified 41 articles containing 386 unique studies and estimated C storage across pools and vegetation types and used linear mixed models to identify the main predictors.</p> <p>We found consistent declines in biomass C with invasion: AGB C was 55% lower in cheatgrass (40 ± 4 g C m-2) than in native sagebrush (89 ± 27 g C m-2) and BGB C was 62% lower in cheatgrass (90 ± 17 g C m-2) than native sagebrush (238 ± 60 g C m-2). In contrast, litter C was > 4x higher in cheatgrass (154 ± 12 g C m-2) compared to native sagebrush (32 ± 12 g C m-2). Soil organic C (SOC) in the top 10 cm was significantly higher in cheatgrass than in native or invaded sagebrush. SOC below 20 cm was significantly related to the time since most recent fire and losses were observed in deep SOC in cheatgrass systems > 5 years after a fire. There were no significant changes in total soil C across vegetation types.</p> <p>Synthesis and Applications: Cheatgrass invasion decreases biodiversity and rangeland productivity and alters fire regimes. Our findings indicate cheatgrass invasion also results in persistent biomass C losses that occur with this state change. We estimate that conversion from native sagebrush to cheatgrass leads to a net reduction of C storage in biomass and litter of 76 g C m-2, or 16 Tg C across the Great Basin without management practices like native sagebrush restoration or cheatgrass removal.10-Sep-2020</p>
Data set related to the manuscript "Simulations of ionic liquids confined in surface-functionalized nanoporous carbons: Implications for energy storage"
<p>Graphical files in the agr format for all the figures in the manuscript entitled "Simulations of ionic liquids confined in surface-functionalized nanoporous carbons: Implications for energy storage". Examples of input files for the three systems simulated.</p>
Compilation of experimental data on water storage capacity in olivine, wadsleyite and ringwoodite (061721 updated)
<p>We compiled high-pressure mineral physics data on water storage capacities in olivine, wadsleyite, and ringwoodite from the literature (published as Tables S1–S3 in Dong et al., 2021). The references are listed in the second tab of each xlsx file.</p> <p>This version was published on Oct. 21, 2020 (version 1.0) and includes "data-olivine-table-s1.xlsx", "data-wadsleyite-table-s2.xlsx", and "data-ringwoodite-table-s3.xlsx"</p> <p>Please cite "Dong, J., Fischer, R. A., Stixrude, L. P., & Lithgow‐Bertelloni, C. R. (2021). Constraining the Volume of Earth's Early Oceans With a Temperature‐Dependent Mantle Water Storage Capacity Model. <em>AGU Advances</em>, <em>2</em>(1), e2020AV000323." for the dataset version 1.0.</p> <p><strong>An update to the data compilation of Dong et al. (2021) (version 1.0) is now published as version 2.0 on Jun. 17, 2021, and includes additional literature data on the water storage capacity in olivine, wadsleyite, and ringwoodite ("additional-data-for-mars-061721.xlsx")</strong></p>
Data from: Decoupling between growth rate and storage remobilization in broadleaf temperate tree species
<p>1. Temperate trees rely on carbon (C) and nutrient remobilisation from storage to resume growth after winter. Minimum storage levels during the growing season suggest that remobilisation could signify that C availability is insufficient to meet growth demands; consequently, growth might be C and/or nutrient limited. However, it remains unclear whether higher growth demands are covered by higher remobilization. This study examined whether higher C and nutrient demands associated with fast growth or deciduousness, rely on greater remobilisation.</p> <p>2. In 11 sympatric deciduous and evergreen angiosperm tree species from southern South América, the magnitude of seasonal remobilisation of C and nutrient storage was assessed as the seasonal minimums (relative to seasonal maximums) of whole tree non-structural carbohydrates (NSC), nitrogen (N), and phosphorus (P) concentrations and pools. The basal area increment and stem wood density were determined for each tree, from which the biomass radial increment (BRI) was estimated. The effects of leaf habit and BRI on the seasonal minimums NSCs and nutrient concentrations and pools were analysed using linear mixed-effects models.</p> <p>3. Radial growth was not related to seasonal minimum NSC or nutrient concentrations and pools in either the evergreens or deciduous angiosperms; thus, faster growth was not associated with greater remobilisation of C or nutrient stores. Further, larger trees grew faster than smaller ones, but did not have higher remobilisation. Deciduous species had higher year-round whole tree NSC and nutrient concentrations than evergreens; however, both groups had similar BRI and seasonal minimum concentrations and pools of NSCs and nutrients.</p> <p>4. Neither growth rate nor leaf habit drove the magnitude of C and nutrient remobilisation in the angiosperm trees examined here, indicating no C or nutrient limitation. This result contradicts the view that growth and storage strongly regulate one another, as proposed by a growth-storage trade-off.</p>
Data from: Soil carbon response to woody plant encroachment: Importance of spatial heterogeneity and deep soil storage
1. Recent global trends of increasing woody plant abundance in grass-dominated ecosystems may substantially enhance soil organic carbon (SOC) storage and could represent a strong carbon (C) sink in the terrestrial environment. However, few studies have quantitatively addressed the influence of spatial heterogeneity of vegetation and soil properties on SOC storage at the landscape scale. In addition, most studies assessing SOC response to woody encroachment consider only surface soils, and have not explicitly assessed the extent to which deeper portions of the soil profile may be sequestering C. 2. We quantified the direction, magnitude, and pattern of spatial heterogeneity of SOC in the upper 1.2 m of the profile following woody encroachment via spatially-specific intensive soil sampling across a landscape in a subtropical savanna in the Rio Grande Plains, USA, that has undergone woody proliferation during the past century. 3. Increased SOC accumulation following woody encroachment was observed to considerable depth, albeit at reduced magnitudes in deeper portions of the profile. Overall, woody clusters and groves accumulated 12.87 and 18.67 Mg C ha-1 more SOC compared to grasslands to a depth of 1.2 m. 4. Woody encroachment significantly altered the pattern of spatial heterogeneity of SOC to a depth of 5 cm, with marginal effect at 5-15 cm, and no significant impact on soils below 15 cm. Fine root density explained greater variability of SOC in the upper 15 cm, while a combination of fine root density and soil clay content accounted for more of the variation in SOC in soils below 15 cm across this landscape. 5. Synthesis: Substantial SOC sequestration can occur in deeper portions of the soil profile following woody encroachment. Furthermore, vegetation patterns and soil properties influenced the spatial heterogeneity and uncertainty of SOC in this landscape, highlighting the need for spatially specific sampling that can characterize this variability and enable scaling and modeling. Given the geographic extent of woody encroachment on a global scale, this undocumented deep soil C sequestration suggests this vegetation change may play a more significant role in regional and global C sequestration than previously thought.
Data from: Effect of storage condition on the physicochemical properties of corn-wheat starch / zein edible bilayer films
<p>The functional properties of biopolymer-based film packaging materials are susceptible to external storage conditions. The effects of different storage temperature, relative humidity (RH) and duration on the apparent form, barrier properties, mechanical properties and microstructure of corn-wheat starch/zein bilayer films were studied. From 0 to 150 d, storage temperature and RH, but not storage time, affected the appearance and colour of the bilayer films. The increase in haze of the bilayer films stored at 25°C was much greater than that at low temperatures. With increased storage time, the moisture content first increased and then decreased, while the water resistance and oxygen barrier properties of the bilayer films worsened. After 150 d, the bilayer film stored at 25°C with 54% RH had better water resistance properties. The oxygen barrier properties of the bilayer film stored at 25°C with 43% RH were preferable to those of other groups because the peroxide value of vegetable oil packed in the former bilayer film was the lowest. The tensile strength of bilayer films stored at 25°C with RH of 43%, 54%, and 65% decreased, but were still better than those stored at low temperatures (-17°C, 4°C), which were tough due to their high elongation at break. SEM results showed tight bonds between the bilayer films, and the network structure inside the films disappeared and reappeared during storage. The cross-sectional compactness changed, and there was no film separation after 150 d.</p>
Data from: Effects of condition and sperm competition risk on sperm allocation and storage in neriid flies
<p>Ejaculate traits can be sexually selected and often exhibit heightened condition-dependence. However, the influence of sperm competition risk in tandem with condition-dependent ejaculate allocation strategies is relatively unstudied. Because ejaculates are costly to produce, high-condition males may be expected to invest more in ejaculates when sperm competition risk is greater. We examined the condition-dependence of ejaculate size by manipulating nutrient concentration in the juvenile (larval) diet of the neriid fly Telostylinus angusticollis. Using a fully factorial design we also examined the effects of perceived sperm competition risk (manipulated by allowing males to mate first or second) on the quantity of ejaculate transferred and stored in the three spermathecae of the female reproductive tract. To differentiate male ejaculates, we fed males non-toxic rhodamine fluorophores (which bind to proteins in the body) prior to mating, labelling their sperm red or green. We found that high-condition males initiated mating more quickly and, when mating second, transferred more ejaculate to both of the female's posterior spermathecae. This suggests that males allocate ejaculates strategically, with high-condition males elevating their ejaculate investment only when facing sperm competition. More broadly, our findings suggest that ejaculate allocation strategies can incorporate variation in both condition and perceived risk of sperm competition.</p>
Data from: Ecosystem context illuminates conflicting roles of plant diversity in carbon storage
Plant diversity can increase biomass production in plot‐scale studies, but applying these results to ecosystem carbon (C) storage at larger spatial and temporal scales remains problematic. Other ecosystem controls interact with diversity and plant production, and may influence soil pools differently from plant pools. We integrated diversity with the state‐factor framework, which identifies key controls, or 'state factors', over ecosystem properties and services such as C storage. We used this framework to assess the effects of diversity, plant traits and state factors (climate, topography, time) on live tree, standing dead, organic horizon and total C in Québec forests. Four patterns emerged: (1) while state factors were usually the most important model predictors, models with both state and biotic factors (mean plant traits and diversity) better predicted C pools; (2) mean plant traits were better predictors than diversity; (3) diversity increased live tree C but reduced organic horizon C; (4) different C pools responded to different traits and diversity metrics. These results suggest that, where ecosystem properties result from multiple processes, no simple relationship may exist with any one organismal factor. Integrating biodiversity into ecosystem ecology and assessing both traits and diversity improves our mechanistic understanding of biotic effects on ecosystems.
Data and results related to "Fattori et al. 2017 - High Solar Photovoltaic Penetration in the Absence of Substantial Wind Capacity: Storage Requirements and Effects on Capacity Adequacy - Energy"
<p>The file includes data used for the analysis and results coming from the study (which was focused on the Italian "Nord" bidding zone). In particular:</p> <p>(i) Series of hourly load data [MW], from 01.01.2006 to 31.12.2015. The data come from elaborations based on ENTSO-E (https://www.entsoe.eu/db-query/country-packages/production-consumption-exchange-package) and Terna S.p.A. (http://www.terna.it/en-gb/sistemaelettrico/transparencyreport/load/actualload.aspx). All the elaborations are described in details on the paper.</p> <p>(ii) Data related to the penetration of PV. Installed capacity of PV is assumed to increase from zero up to the capacity needed so that the average annual PV generation (based on the years 1986-2015) potentially equals the average annual demand (based on the years 2006-2015).</p> <p>(iii) Synthesis of the results about: residual load (with and w/o storage), ramps (with and w/o storage), excess energy (with and w/o storage), storage requirements</p>
Spatial data for Chaplin-Kramer et al. "Spatial heterogeneity in forest carbon storage affects priorities for reforestation"
<p>Spatial data generated for the forest carbon edge effects analysis and optimization performed in Chaplin-Kramer et al. "Spatial heterogeneity in forest carbon storage affects priorities for reforestation". The files included are described below.</p><p>fc_stack_hansen_forest_cover2014_compressed_std_forest_edge_result.tif - Carbon (Mg/ha) predicted by the regression model for Hansen forest cover 2014 (this is the LULC map that produced the model with the best fit and was used in the model validation)</p><p>fig1_edge_effect_hansen_compressed_nr_md5_63366a.tif – Figure 1 in the manuscript</p><p>fig2_ipcc1_regression2_overlap3_md5_43e130.tif – Figure 2 in the manuscript</p><p>figS5_ipcc1_regression2_overlap3_avgov_md5_fe8b72.tif – Alternate styling of manuscript Fig. 2 (resampling with "average" instead of "near"), shown in Supplemental Fig. S5</p><p>ipcc_carbon_restoration_limited_md5_cd012d.tif - Carbon (Mg/ha) in restoration LULC calculated with the IPCC Tier 1 approach</p><p>ipcc_tier1_carbon_data.zip - Data needed to run the IPCC approach are contained within two files in the zip folder: the carbon table (carbon zones are rows and ESA LULC codes are columns) IPCC_carbon_table_md5_a91f7ade46871575861005764d85cfa7.csv; and the carbon zones map: carbon_zones_md5_aa16830f64d1ef66ebdf2552fb8a9c0d.gpkg</p><p>ipcc_carbon_esa_compressed_md5_5b4803.tif - Carbon (Mg/ha) in ESA 2014 LULC calculated with the IPCC Tier 1 approach (shown in Fig. S1)</p><p>PNV_jsmith_060420_md5_8dd464e0e23fefaaabe52e44aa296330.tif – Potential Natural Vegetation (PNV) created by Jeff Smith (unpublished) through a cross-walk of ESA to Dinerstein biomes</p><p>regression_carbon_esa_compressed_md5_c867a0.tif - Carbon (Mg/ha) in ESA 2014 LULC calculated with the regression approach (shown in Fig. S1)</p><p>regression_carbon_restoration_md5_1f5ca8.tif - Carbon (Mg/ha) in restoration LULC calculated with the regression approach</p><p>restoration_limited_md5_372bdfd9ffaf810b5f68ddeb4704f48f.tif – the LULC scenario of reforestation (based on PNV, but excluding agriculture and urban areas) </p>
GC raw data of sodium ion electrolytes before and after battery storage
<p>Raw data of the GC measurements before and after battery storage. Additionally, the pure electrolyte as well as the pure solvent (DCM, dichloromethane) is mentioned. </p>
Terrestrial water storage data based on the generalized three-cornered hat fusion method
<ul> <li>The dataset combines three GRACE Mascon products (CSR, JPL and GSFC) using the generalized three-cornered hat method (GTCH) to generate, referred to as TWS_GTCH. The dataset spans from 2003 to 2022, with a spatial resolution of 0.5 degrees and a temporal resolution of monthly.</li> <li>We deduct 2004-2009 means from the three GRACE terrestrial water storage (TWS) Mascon products to ensure that they have the same reference period. To enhance the reliability of the results and eliminate differences between datasets, we employ the GTCH method to calculate the root mean square error (rmse) of the GRACE TWS data to assess uncertainty. Finally, we utilize the least squares method to fuse the data based on their uncertainties.</li> </ul>
Input data and modelling files for a model of the Finnish energy system with focus on cascade hydropower and the addition of a hydrogen storage system realised in Backbone
<p>The files show the input data and modelling files used for the publication "Cascade hydropower integration in a techno-economic power system model: A study of Finnish hydropower plants" (Kiehle et al., 2025 - submitted). The paper's <a title="Preprint on SSRN" href="https://dx.doi.org/10.2139/ssrn.4971685" target="_blank" rel="noopener">preprint</a> is available. A model of the Finnish energy system in 2022 was built in the techno-economic modelling framework Backbone (available on GitLab: https://gitlab.vtt.fi/backbone/backbone). The focus was on implementing cascading hydropower plants in a power system model, including individual reservoirs, generation and spillage capacities. </p> <p>"ModellingFiles_Debug" are GAMS-based data that can be used to run the scenario in Backbone or display the results. "ModellingResults" are gdx files that purely list the results. Those are also presented in more detail in the scientific paper. The Excel files present the input data used for modelling and can also be used to run the model. </p>
Results Data for "Price Formation Without Fuel Costs: The Interaction of Elastic Demand with Storage Bidding"
<h2>Abstract</h2> <p>Studies on electricity market design for high shares of wind and solar often predict the breakdown of energy-only markets, citing a lack of fuel costs to set prices. Issues include prolonged zero prices, politically unacceptable scarcity prices, price collapses from minor capacity changes, low market value cost recovery, revenue variability across different weather years, and challenges in long-term storage operation. These issues arise from modeling with perfectly inelastic demand. Introducing even a small amount of short-term elasticity (-5%) significantly mitigates these problems. A simplified model with wind, solar, batteries, and hydrogen storage shows that demand elasticity and storage opportunity costs stabilize pricing, smoothing the price duration curve, reducing zero-price hours from 90% to 30%, and ensuring price stability across capacities and weather years. Green hydrogen-derived fuels replace fossil fuels as backup. The long-term model matches the short-term model prices with identical capacities, guiding storage bidding strategies for short-term operations. A model trained on 35 years of weather data and tested on another 35 years demonstrates the energy-only market's potential in future dispatch and investment coordination.</p> <h2>Data Sources</h2> <p>- <strong>Solar and Wind Time Series (1950-2020):</strong> <a href="https://doi.org/10.17864/1947.000321">Bloomfield and Brayshaw (2021)</a><br>- <strong>Techno-Economic Assumptions:</strong><a href="https://github.com/PyPSA/technology-data/tree/v0.8.1"> technology-data (v0.8.1)</a>, <a href="https://ens.dk/en/our-services/technology-catalogues">Danish Energy Agency</a><br>- <strong>Demand Elasticity Assumptions:</strong> <a href="https://doi.org/10.1016/j.eneco.2024.107652">Hirth et al. (2024)</a>, <a href="https://www.ewi.uni-koeln.de/en/publications/on-the-functional-form-of-short-term-electricity-demand-response-insights-from-high-price-years-in-germany-2/">Arnold (2023)</a></p> <h2>Installation</h2> <p>Use <code>conda</code> environment manager:</p> <p><br><code>conda update conda</code><br><code>conda env create -f workflow/envs/environment.fixed.yaml</code><br><code>conda activate price-formation</code></p> <p><strong>Main Dependencies:</strong></p> <ul> <li>pypsa (v0.27.1)</li> <li>linopy (v0.3.8)</li> <li>snakemake (v8.5)</li> <li>gurobi (v11.0.2)</li> </ul> <h2>Run</h2> <p>From the root of the repository:</p> <p><br><code>snakemake -call --use-conda --conda-frontend conda</code></p> <p>Or with a specific scenario configuration file:</p> <p><br><code>snakemake -call --use-conda --conda-frontend conda --configfile config/config.foo.yaml</code></p> <h2>Cluster</h2> <p>On an HPC cluster, run:</p> <p><br><code>snakemake -call --profile slurm --use-conda --conda-frontend conda</code></p> <h2>Compress Results</h2> <p>Use <code>tar</code> to compress results (excluding the report directory):</p> <p><br><code>tar -cJf price-formation-results.tar.xz \</code><br><code> config data figures results resources workflow \</code><br><code> .gitignore .pre-commit-config.yaml .syncignore-receive \</code><br><code> .syncignore-receive CITATION.cff LICENSE matplotlibrc README.md</code></p> <h2>Licenses</h2> <p>The code in this repository is MIT licensed.</p> <p>The data in this repository is CC-BY-4.0 licensed.</p> <h2>Amendments</h2> <p>In <code>v0.2.0</code>, we added the file <code>revision-1-amendments.tar.xz</code>, which includes additional results for sensitivity runs with cross-elastic terms.</p>
Data from: Reindeer control over subarctic treeline alters soil fungal communities with potential consequences for soil carbon storage
<p>Here we present the data and R script from "<em>Reindeer control over subarctic treeline alters soil fungal communities with potential consequences for soil carbon storage</em>" by Henni Ylänne, Rieke L. Madsen, Carles Castaño, Daniel B. Metcalfe and Karina E. Clemmensen (Global Change Biology, 2021). In this study we reported the impacts of grazing regime and mountain birch vicinity on the abundance, diversity and community composition of the soil fungal community, and explored how the soil fungal communities relate to vegetation and, ultimately, to the observed variation in soil carbon stocks. The study was conducted at a treeline ecotone in northern Fennoscandia, where two adjacent 65-year-old grazing regimes with or without summer grazing by reindeer (<i>Rangifer tarandus</i>) could be compared. As these grazing regimes differ in the abundance of mountain birch (<i>Betula pubescens</i> ssp. <i>czerepanovii</i>), the own effects of mountain birch vicinity on the fungal communities were assessed by collecting soil samples directly underneath and > 3 m away from mountain birches.</p> <p>This dataset includes data of soil properties, soil carbon and nitrogen stocks, vegetation community composition (as deterred from plant reads captured by the high-throughput sequencing of ITS2 region), fungal abundance (ITS2 copy numbers), fungal diversity and the taxonomic and functional composition of the soil fungal communities.</p>
Cost reductions in renewables can substantially erode the value of carbon capture and storage in mitigation pathways: supporting data
<p>This provides supporting data for the paper, <em><strong>Cost reductions in renewables can substantially erode the value of carbon capture and storage in mitigation pathways</strong></em>, published in <em>One Earth</em>. The full paper can be accessed at the following DOI: https://doi.org/10.1016/j.oneear.2021.10.024, published on the 19th November 2021.</p>
Supplementary data: Na2.4Al0.4Mn2.6O7 anionic redox cathode material for sodium ion batteries- a combined experimental and theoretical approach to elucidate its charge storage mechanism
<p>This data repository contains the output files of density-functional theory (DFT) calculations that were used for the paper "Na2.4Al0.4Mn2.6O7 anionic redox cathode material for sodium ion batteries- a combined experimental and theoretical approach to elucidate its charge storage mechanism". </p>
Conceptualizing relationships among hyporheic exchange, storage, and water age: data represented in published figures
<p>Hyporheic exchange is a key driver of ecosystem processes in streams, yet stream ecologists often fail to leverage detailed conceptual models developed by engineers and hydrologists describing the relationship between water storage, water balance, and water age (time elapsed since a conceptual parcel of water entered the hyporheic zone) in hyporheic zones. In a companion paper (G.C. Poole et al. <em>Hyporheic Hydr</em><em>au</em><em>lic Geometry: Conceptualizing relationships among hyporheic exchange, storage, and water age</em>, published in PLoS ONE; doi:<a href="https://doi.org/10.1371/journal.pone.0262080">10.1371/journal.pone.0262080</a>), we provide visualizations of these relationships in an effort to allow non-hydrologists to grasp four primary concepts along with associated research and management implications: 1) the rate of hyporheic exchange, size of the hyporheic zone, and hyporheic water age are inexorably linked; 2) such linkages can be leveraged to build understanding of hyporheic processes; 3) the age distribution of hyporheic water and hyporheic discharge is heavily skewed toward young water ages -- at any temporal scale of observation (minutes, hours, days, or months) older hyporheic water is rare relative to younger water; 4) the age distribution of water discharged from any hyporheic zone is not the same as the age distribution of water stored within that hyporheic zone. The data set presented here represents the numerical values represented by the figures published in the companion paper.</p>
Data for heat transfer characterisation of inserts of ASTEP thermal storage system
<p>Dataset for heat transfer characterisation of Honeycomb inserts and Y-Inserts considered in ASTEP project.</p>
Description of Data Resources Used to Analyze Benefits of Forest and Forest Resource-based Substitution and Carbon Storage in Sweden
<p>The data deposited here has been used for the publication: “On the role of forests and the forest sector for climate change mitigation in Sweden” (Petersson et al., 2022). This document describes in detail how the initial starting data was collected and what the resources were. It further describes the parameter settings used to generate the data using the Swedish Heureka decision support tool. </p>
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.