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4,230 results for “Energie”
Milling process energy consumption
<p>This dataset is about a CNC machine performing milling processes<br>Each observation means one particular milling process with the machine</p> <p>Axis - the machine's cutting tool was moving along axis X/Y/Z<br>Feed [mm/min] - the cutting tool moved at this speed<br>Path [mm] - the cutting tool moved this distance</p> <p>Energy requirement [kJ] - energy consumption of the process </p>
Surface science and liquid phase investigations of oxanorbornadiene/oxaquadricyclane ester derivatives as molecular solar thermal energy storage systems on Pt(111) [doi: 10.1063/5.0158124]
<p>Primary data, meta data, and corresponding lists of figures & tables are included. [doi: 10.1063/5.0158124]</p>
dataset figures - Assessing the Performance of Fuel Cell Electric Vehicles Using Synthetic Hydrogen Fuel - Article Energies
<p>Dataset for Table 1 - 2 and for Figure 4</p>
The Global and National Energy Systems Techno-Economic (GNESTE) Database: Economic and performance data for nuclear power in current and future electricity systems
<p><span><span>Here, we </span><span>present a</span><span> database </span><span>which collates </span><span>historical, </span><span>current</span><span>,</span><span> and future </span><span>cost and performance</span><span> data</span> <span>and </span><span>assumption</span><span>s</span> <span>for </span></span><span><span>nuclear power generation</span></span><span> <span>from</span><span> the open literature</span><span>. </span></span><span><span>Nuclear energy is the second-largest source of low-carbon generation, supplying 9% of global electricity</span><span>.</span></span><span> <span>The data are </span><span>global in scope but with </span><span>regional and national</span> <span>specificity</span><span>, </span><span>cover</span><span>s</span><span> the years 2015 t</span><span>hrough </span><span>to 2050, </span><span>and </span><span>span</span> </span><span><span>604</span></span><span><span> datapoints from </span></span><span><span>19</span></span><span><span> sources</span><span>.</span> </span></p> <p><span><span>The database </span><span>enables modellers to select and justify</span> <span>model input data and </span><span>provides </span><span>a </span><span>benchmark for comparing assumptions and projections to </span><span>other source</span><span>s</span><span> across the literature</span> <span>to </span><span>validate</span><span> model inputs and outputs</span><span>.</span> <span>It is </span><span>designed to be easily updated with </span><span>new sources of</span><span> data, ensuring its utility</span><span>, comprehensiveness,</span><span> and broad applicability over time.</span></span> Technoeconomic data on nuclear power was collected from websites, reports, academic articles and databases of national and international organisations.</p>
Intel's AI-Powered Initiatives for Sustainable Energy
<p>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?id=yhz_92h96&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?id=yhz_cbegf&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?u=x&id=yhz_1fea8&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?xml=https://dqnko.com&id=yhz_63cdc<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?id=yhz_c3cad&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?id=yhz_f1f19&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?id=yhz_c487b&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?xml=https://dqnko.com&id=yhz_331zd<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?a=s&id=yhz_bgh33&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?e=u&id=yhz_89c62&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?r=g&id=yhz_ed7c6&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?xml=https://dqnko.com&id=yhz_g7agz<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?o=e&id=yhz_7c12h&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?xml=https://dqnko.com&id=yhz_e9z9d<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?id=yhz_d19be&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?id=yhz_cz5de&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?id=yhz_1eeb5&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?a=s&id=yhz_hdggz&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?xml=https://dqnko.com&id=yhz_f3782<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?x=l&id=yhz_gzhg2&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?id=yhz_7bbgg&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?id=yhz_a51fh&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?r=n&id=yhz_a6ddc&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?x=p&id=yhz_bh748&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?xml=https://dqnko.com&id=yhz_933e7<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?id=yhz_326b3&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?g=s&id=ymp_1zg2h&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?a=d&id=ymp_zbc17&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?xml=https://dqnko.com&id=ymp_e6d21<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?p=d&id=ymp_3c897&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?t=l&id=ymp_5h3az&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?id=ymp_79g5g&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?id=ymp_2e734&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?xml=https://dqnko.com&id=ymp_1db2g<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?xml=https://dqnko.com&id=ymp_48ag9<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?id=ymp_he216&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?a=z&id=ymp_caa12&xml=https://dqnko.com<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?xml=https://dqnko.com&id=ymp_524h2<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?xml=https://dqnko.com&id=ymp_h8b7h<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?xml=https://dqnko.com&id=ymp_g69gc<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?xml=https://dqnko.com&id=ymp_f54d2<br>https://media.housing.wisc.edu/virtual-tours/2021-06-22-dejope-triple/tour.html?xml=https://dqnko.com&i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Repository of "How Stress Biaxiality Controls Crack Morphology and Apparent Fracture Energy of Dikes and Sills"
<p>This repository contains the dataset of the future publication "How Stress Biaxiality Controls Crack Morphology and Apparent Fracture Energy of Dikes and Sills". It contains:</p> <ul> <li>1 file recapitulating sample dimensions and informations on the tests.</li> <li>12 “raw” mechanical results of experiments on Carrara marble (6 WST — 3 dry/3 saturated tests, 6 MRT — 3 dry/3 saturated tests) with minimal filtering.</li> <li>12 “computed” mechanical results of experiments on Carrara marble (6 WST — 3 dry/3 saturated tests, 6 MRT — 3 dry/3 saturated tests) with the use of the compliance method.</li> <li>2 compressed and stitched back-scattered SEM scans imaging the crack tip in xz direction after crack arrest on WST and MRT.</li> <li>5 stitched back-scattered SEM scans imaging the crack in yz direction on WST at 20, 40, 60 mm MRT at 10, 25 mm of crack propagation.</li> </ul> <p>For more details and information about the dataset, do not hesitate to contact me at antoine.guggisberg@epfl.ch</p> <p> </p>
Dataset for "Assessing the availability and feasibility of renewable energy on the Great Barrier Reef-Australia"
<p>This repository contains all the dataset used in "Assessing the availability and feasbility of renewable energy on the Great Barrier Reef-Australia"</p>
Spine model and datasets for "Home Energy Optimization using Vehicle-to-Home"
<p>The Spine models are simulated for the publication of "Home Energy Optimization using Vehicle-to-Home" in the journal of Open Reserach Europe.</p> <p>The file lists are explained as follows:</p> <p>"Non-commuter_spine.zip" is the zipped folder of Spine model for non-commuting household.</p> <p>"Spine_commuter.zip" is the zipped folder of Spine model for commuting household.</p> <p>"Recorded Results and Paramater Variation Graphs - ORE.xlsx" describes the figures and outputs applied for the paper.</p> <p>"PV, elec, thermal_non_commuting.zip" denotes the non-commuting model input.</p> <p>"Model_input_commuter (1).zip" denotes the commuting model input.</p> <p>"Model output_commuter (2).xlsx" denotes the commuting model output.</p> <p> </p>
Climate Energy Dataset For Off Grid Electricity Infrastructure
<p>The dataset comprises real-time electrical measurements—including voltages, currents, and power factors—for three-phase and single-phase systems across generation, distribution, and consumption stages showcasing the energy generation and demand within an off-grid electricity infrastructure located in the Kalam Region, a specific climate zone in Pakistan. Collected every five minutes from March 6, 2023, to October 24, 2024, it includes over 45 million instances covering data from four micro-hydropower generators, 26 transformers, and 585 end-users. Additionally, the dataset incorporates climate data—such as temperature, dew point, wind components, precipitation, snowfall, and snow cover—from the ERA5 dataset. This comprehensive collection enhances its utility for research in energy systems analysis, climate change studies, electrical engineering, and artificial intelligence applications.</p> <p>This dataset was originally created with support from Lacuna Fund, the world’s first collaborative effort to provide data scientists, researchers, and social entrepreneurs in low- and middle-income contexts globally with the resources they need to produce labeled datasets that address urgent problems in their communities. Lacuna Fund is a funder collaborative that includes The Rockefeller Foundation, Google.org, Canada’s International Development Research Centre, the German Federal Ministry for Economic Cooperation and Development (BMZ) with GIZ as implementing agency, Wellcome Trust, Gordon and Betty Moore Foundation, Patrick J. McGovern Foundation, and The Robert Wood Johnson Foundation. See https://lacunafund.org/about/ for more information.</p>
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>
Data for: Alchemical free-energy calculations at quantum-chemical precision
<p><span><span>In the last decade, machine-learned potentials (MLP) have </span><span>demonstrated</span><span> the capability to predict vario</span><span>us</span><span> QM properties learned from </span><span>a set of reference</span><span> QM calculations. </span><span>Accordingly</span><span>,</span><span> hybrid QM/MM simulation</span><span>s </span><span>can be accelerated</span><span> by replacement of </span><span>expensive</span><span> QM calculation</span><span>s</span><span> with </span><span>efficient </span><span>MLP </span><span>energy prediction</span><span>s</span><span>.</span> <span>At the same time</span><span>, alchemical free energy </span><span>perturbation</span><span>s</span><span> (FEP) </span><span>remain</span> <span>un</span><span>ach</span><span>ie</span><span>vable</span><span> at the QM level of theory.</span> <span>In this work</span><span>,</span><span> we extend the capabilities of the Buffer Region Neural Network </span><span>(</span><span>BuRNN</span><span>) </span><span>QM</span><span>/MM</span><span> scheme towards </span><span>FEP</span><span>.</span> <span>BuRNN</span> <span>introduces a buffer region that experiences full electronic polarization by the QM region to minimize artifacts</span> <span>at </span><span>the </span><span>QM/MM interface</span><span>. </span><span>A </span><span>MLP</span> <span>is </span><span>used to </span><span>predict the energies for the QM </span><span>region</span><span> and its interactions with the buffer region</span><span>. Furthermore, </span><span>BuRNN</span> <span>allow</span><span>s</span><span> us to implement </span><span>FEP </span><span>directly into</span> <span>the </span><span>MLP </span><span>H</span><span>amiltonian</span><span>. </span><span>Here</span><span>, </span><span>we describe the alchemical change </span><span>from methanol to methane in water </span><span>at</span><span> the </span><span>MLP</span><span>/MM level as a proof of concept.</span></span><span> </span></p>
Observation of Electroluminescence and Energy Transfer of Hyperbolic Polaritons
<p>Includes all codes and data related to the article titled "Electroluminescence and Energy Transfer Mediated by Hyperbolic Polaritons" for the main text, extended data and supplementary information. Version 3.</p>
Bluetooth Low Energy based Dataset for Smartphone localization in moving vehicles for electronic toll collection.
<p><span>The collected Dataset presents a data collection based on Bluetooth Low Energy (BLE) technology and the use of smartphones for the purposes of vehicle localization and tracking. </span><span>The system is based on a two-dimensional 8 switched-beam directive panel antennas mounted on an electronic toll collection (ETC) gateway. The multibeam antenna topology is installed on the ETC at a height of 4.7 m and </span><span>the data collected from several experiments, together with the set-up and methodology, are reported here.</span><span> The data collection can be divided into two main sections. First, the system was calibrated in an 8 x 8 meter area below the ETC. The distance between adjacent test points is 0.5 m, with a total of 100 samples measured for each test point in every 8 switched-beam panel antenna. Secondly, the results of dynamic test with vehicles passing at different speeds carrying smartphones and using BLE are detailed. As a validation of the dataset, a benchmark analysis for data visualization and localization/tracking estimation applying MUltiple SIgnal Classification and fingerprinting algorithms is included.</span></p>
Pair Wavefunction Symmetry in UTe2 from Zero-Energy Surface State Visualization
<p>This dataset contains all the data in "Pair Wavefunction Symmetry in UTe2 from Zero-Energy Surface State Visualization"</p>
Automated identification of small molecules in cryo-electron microscopy data with density- and energy-guided evaluation
<p>Data and turorials for ligand identification with EMERALD-ID. Each Zip file contains ligand models and data used to generate their respective figures in the EMERALD-ID manuscript. For specific details, consult the README file in each directory.</p>
Impact on energy and air quality of connected and autonomous vehicles in an urban context
<p>Despite numerous studies related to autonomous vehicles and connected vehicles (CAVs) and their impact on the economy or on traffic performance (eg, flow management, accidents), there are not many studies that relate these benefits to the environmental component. In this context, the objective of this work consisted in the integrated assessment of the impacts of CAVs on traffic performance, atmospheric emissions CO<sub>2</sub> and NO<sub>x, </sub>and air quality.</p> <p>To this end, a roundabout in the city of Aveiro was selected as a case study, and different scenarios were created: base scenario, considering the current typology of vehicles (conventional); scenario 2, considering defensive behavior CAVs; scenario 3, considering assertive behavior CAVs; and scenario 1, considering all types of vehicles mentioned above. To ensure a comprehensive analysis, all scenarios were evaluated for a period of 24 hours, corresponding to the period of the experimental campaign carried out, and a cascade of models was applied.</p> <p>First, the PTV VISSIM model was applied which allowed, configuring, calibrating and validating the network under study for an evaluation of the traffic performance. Second, the VSP model was applied to estimate atmospheric emissions, Finally, the CFD VADIS model was applied to air quality assessment.</p> <p>The results obtained allowed us to conclude that the introduction of CAVs, promotes longer travel times, especially during times of higher traffic, and an increase in emissions, mainly by the CAVs with defensive behavior. In terms of air quality, there were large differences in terms of NO<sub>2</sub> concentrations, with the CAVs promoting a degradation of air quality, especially during peak traffic hours.</p>
Impact of declining renewable energy costs on electrification in low emission scenarios - Scenario Data
<p>This data archive contains model runs and data analysis files to the research article</p> <p><strong>Impact of declining renewable energy costs on electrification in low emission scenarios</strong></p> <p>by<br> <em>Gunnar Luderer, Silvia Madeddu, Leon Merfort, Falko Ueckerdt, Michaja Pehl, Robert Pietzcker, Marianna Rottoli, Felix Schreyer, Nico Bauer, Lavinia Baumstark, Christoph Bertram, Alois Dirnaichner, Florian Humpenöder, Antoine Levesque, Alexander Popp, Renato Rodrigues, Jessica Strefler, Elmar Kriegler</em></p> <p>forthcoming in <em>Nature Energy (2021).</em></p> <p> </p> <p><em><strong>ModelRuns </strong></em>(directory) contains all model runs of the scenarios underlying the paper.</p> <p><em><strong>DataAnalysis </strong></em>(directory) contains all RMarkDown-Notebooks that were used for the data analysis and the generation of the figures of the paper.</p> <p><em><strong>ScenarioNames.pdf</strong></em> contains the mapping from scenario names used in the paper to the model experiment names (in the directory ModelRuns).<br> <br> <em><strong>ScenarioData_IAMC_Format.xlsx </strong></em>contains the scenario output date in the generic IAMC-format (https://data.ene.iiasa.ac.at/database/) as submitted to the IPCC-AR6-database (https://iiasa.ac.at/web/home/research/researchPrograms/Energy/200513_IPCCwebinar.html)</p>
Spanish energy supply prices
<p>This dataset collects information about energy supply prices by days and hours since June 1st 2021, when prices were changed by the government, which also carried to an inflation of the prices. This dataset pretends to be a reference when studying this inflation, by comparing, for example, hour prices with the performance of energy suppliers' stations, determining whether this inflation is justified or not.</p> <p>Dataset structure goes as follows:</p> <ul> <li><strong>Tarifa</strong>. There are two tax types identified by a three-letter code: "Península, Baleares y Canarias" (pbc) and "Ceuta y Melilla" (cym).</li> <li><strong>Fecha</strong>. Date of the extracted data in DD-MM-YYYY format.</li> <li><strong>Hora</strong>. Hour of the extracted data (int type from 0 to 23).</li> <li><strong>Precio total</strong>. Total tax price in kWh/€.</li> <li><strong>Mercado diario e intradiario</strong>. Price breakdown corresponding to diary and intraday markets in kWh/€.</li> <li><strong>Servicios de ajuste</strong>. Price breakdown corresponding to adjust services in kWh/€.</li> <li><strong>Financiación OS</strong>. Price breakdown corresponding to OS financing in kWh/€.</li> <li><strong>Financiación OM</strong>. Price breakdown corresponding to OM financing in kWh/€.</li> <li><strong>Coste Comercialización variable</strong>. Price breakdown corresponding to variable commercialization cost in kWh/€.</li> <li><strong>Peajes y cargos</strong>. Price breakdown corresponding to tolls and charges in kWh/€.</li> <li><strong>Pago por capacidad. </strong>Price breakdown corresponding to capacity payment in kWh/€.</li> <li><strong>Excedente o deficit subastas renovables</strong>. Price breakdown corresponding to surplus or deficit of renewable energy auctions in kWh/€.</li> <li><strong>Servicio de interrumpibilidad</strong>. Price breakdown corresponding to interruptibility service in kWh/€.</li> </ul>
Evidence of an internal model of friction when controlling kinetic energy at impact to slide an object along a surface toward a target
<p>This repository contains zip files for data (Data.zip) and Matlab functions library (Library.zip), and the Matlab script (Matlab_Script_for_Cumputed_data.m) used in the Famié et al PLOSONE study. In addition, the <em>README FIRST MATLAB program.pdf</em> file explains the Matlab code and data organization. </p>
Supplemental idf files used for paper "Refurbishmet Methodology to Attain Thermally Comfortable near-Zero Energy Buildings Using Customizable Solutions"
<p>These are the idf files used to study different technology alternatives offered by the Reco2st project on an idealized dormitory room located in London, UK. The files are presented "as is" and were done for EnergyPlus v8.9. Includes files that might have not made it to the final paper.</p> <p>Geometry: One zone room with one external window.<br> Materials: External construction is cavity wall, with bricks on both sides, gypsum plaster on internal side<br> Internal walls brick single layer with gypsum plaster.<br> Ceiling and floor reinforced concrete. Plaster finish on ceiling, nylon carpet on floor<br> Double glazed window. Five panes available: one large central fixed, two small clerestory opening, and two large side opening.<br> For simulation purposes a single equivalent area of all openings modelled.<br> Material data sources: gov.scot, puravent.co.uk, nature.com. SHGC from LBL.</p> <p>This is part of work done for ReCO2ST - Residential Retrofit assessment platform and demonstrations for near zero energy and CO2 emissions with optimum cost, health, comfort and environmental quality. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 768576.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.