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7,378 results for “case”
Model output from "Potential impacts of marine fuel regulations on an Arctic stratocumulus case and its radiative response"
<p>Model output from "Potential impacts of marine fuel regulations on an Arctic stratocumulus case and its radiative response", in review at Atmospheric Chemistry and Physics, 2024, same authors.<br>The simulations were done using MIMICA version 4 (Savre at el., 2014) and the data includes all model output presented in the publication.</p>
Figure 8 in From Eradication to Containment: Invasion of French Polynesia by Bactrocera dorsalis (Hendel) (Diptera: Tephritidae) and Releases of Two Natural Enemies: A 17-Year Case Study
Figure 8. Dates of detection of B. dorsalis and introduction of F. arisanus on the various islands of French Polynesia.
Simulation data for Response of the Thermosphere-Ionosphere System to an X-Class Solar Flare: March 30, 2022 Case Study
<p>GITM simulation results for the research article titled "Response of the Thermosphere-Ionosphere System to an X-Class Solar Flare: March 30, 2022 Case Study" submitted to JGR: Space Weather </p>
Fig. 10 in The local forms of Zootecus (Gastropoda: Pulmonata: Subulinidae) of Pakistan: an archaeomalacological case study
Fig. 10 - Zootecus sp.: Examples of different shell shapes. A) Siranda WP 16. B) Siranda WP 31. C) old collection from Uthal with some juvenile individuals. D) Rohri Hills site 59. E) Rohri Hills site 480 (photo A. Girod).
GlacierPINN: Case Study Svalbard
<p>Dataset and code release (v1.0.1) as it was used in the revised manuscript. </p> <div> <div> <div>Changes from v1.0.0.: Updated velocity loss functions and added scripts to analyse importance of individual physics-aware loss components and SHAP values for the ice thickness prediction.</div> <div> <div> <div> </div> <div> <p> </p> <p> </p> </div> </div> </div> </div> </div>
Tab. 1 in The local forms of Zootecus (Gastropoda: Pulmonata: Subulinidae) of Pakistan: an archaeomalacological case study
<p>Tab. 1 - Historical names, dimensions and whorl numbers of the Z <i>ootecus</i> described from Afghanistan and Pakistan. AMNH, American Museum of Natural History; NHMUK, National History Museum, London; PZS, Proceedings of the Zoological Society of London.</p><table><tbody><tr><th><b>Local taxa</b></th><th><b>Collecting areas</b></th><th><b>H mm</b></th><th><b>D mm</b></th><th><b>H/D</b></th><th><b>Whorls</b></th></tr></tbody><tbody><tr><th>1) <i>Zootecus pullus</i> Gray, 1834 - P.Z.S., 2: 66</th><td>Balochistan, Quetta; Kutch; Bank of Ganges; Delhi; Uttar Pradesh</td><td>10</td><td>4</td><td>2.5</td><td>9-10</td></tr><tr><th>2) <i>Zootecus chion</i> (smaller form) <i>gracilior minor</i> (Pfeiffer, 1856)</th><td>Not specified</td><td>11</td><td>4</td><td>2.75</td><td></td></tr><tr><th>3) <i>Zootecus insularis chion</i> (Solem, 1979, tab. IV: 30)</th><td>Afghanistan</td><td>11.8±0.15 (9.8-14.3)</td><td>5.66±0.071 (4.3-6.4)</td><td>2.279 2.234</td><td>7 3/4 + (7 1/8-9)</td></tr><tr><th>4) <i>Zootecus polygyratus</i> Reeve, 1849</th><td>Sindh (Rohri Hills); Baluchistan (Gwadar)</td><td>12</td><td>4</td><td>3</td><td>9</td></tr><tr><th>5) <i>Zootecus chion</i>, Pfeiffer, 1856</th><td>Afghanistan; Punjab; Sindh</td><td>12</td><td>0.5</td><td>2.4</td><td>7-8</td></tr><tr><th>6) <i>Zootecus chion</i> (#2), Pfeiffer, 1856</th><td>Samples from Hyderabad</td><td>14</td><td>6</td><td>2.333</td><td></td></tr><tr><th>7) <i>Zootecus agrensis</i> Kur. r 1856 - Malakozoologische Blätter, 2: 107</th><td>India: Agra</td><td>16</td><td>6</td><td>2.666</td><td>9</td></tr><tr><th>8) <i>Zootecus estellus</i> Benson, 1857 - A.M.N.H. ser. 2, 19: 327</th><td>Punjab; Sindh; Rajasthan; Andhra Pradesh</td><td>18</td><td>6</td><td>3</td><td>8</td></tr><tr><th>9) <i>Zootecus pertica</i> Benson, 1857 - A.M.N.H. ser. 2, 19: 328</th><td>Sindh</td><td>20</td><td>5</td><td>4</td><td>10</td></tr></tbody></table>
Raw data for Machine learning approach for photocatalysis: An experimentally validated case study of photocatalytic dye degradation
<p>Specification of affiliations:</p> <ul> <li>Hassan Ali - Centre of Polymer Systems</li> <li>Muhammad Yasir - Centre of Polymer Systems</li> <li>Hamza Ul Haq - Laboratory of Alternative Fuel and Sustainability, School of Chemical and Materials Engineering,</li> <li>Ali Can Guler - Centre of Polymer Systems</li> <li>Milan Masar - Centre of Polymer Systems</li> <li>Muhammad Nouman Aslam Khan - Laboratory of Alternative Fuel and Sustainability, School of Chemical and Materials Engineering,</li> <li>Michal Machovsky - Centre of Polymer Systems</li> <li>Vladimir Sedlarik - Centre of Polymer Systems</li> <li>Ivo Kuritka - Centre of Polymer Systems</li> </ul> <p> </p> <p>Raw data for the research paper. Information on the data collection are described in the manuscript. </p>
Narrative economics exemplified: the case of the "pension system collapse" narrative in Poland - dataset
<p>This is a dataset and R script for the paper: Narrative economics exemplified: the case of the "pension system collapse" narrative in Poland, authored by Łukasz Baszczak.</p> <p>Data was collected in November 2022 using online questionnarie.</p>
Supplementary material to the publication entitled "Digital transformation at what cost? A case study from Germany estimating the adoption potential of precision farming technologies under different scenarios" in Smart Agricultural Technology, https://doi.org/10.1016/j.atech.2024.100585
<p>The file '<em>PAT_Descriptions_Assumptions_Supplementary Material.pdf</em>' contains descriptions of the selected Precision Agricultural Technologies (PATs) and detailed explanations of the assumptions made in the calculation model.</p> <p> </p> <p>The file '<em>Calculation Model_NUTS3_BW.xlsx</em>' includes the calculation model created for the publication.</p>
Using ELN Functionality of Kadi4Mat (KadiWeb) in a Materials Science Case Study of a User Facility
<p>This record contains the dataset belonging to the paper "Using ELN Functionality of Kadi4Mat (KadiWeb) in a Materials Science Case Study of a User Facility"</p>
Data from: Low-frequency oscillations in the magnetic nozzle of a Helicon Plasma Thruster (10 sccm case)
<p>- Data from: Low-frequency oscillations in the magnetic nozzle of a Helicon Plasma Thruster (10 sccm case)</p> <p>- Authors: Davide Maddaloni, Borja Bayón-Buján, Jaume Navarro-Cavallé, Mario Merino, Filippo Terragni</p> <p>- Contact email: <a href="mailto:dmaddalo@ing.uc3m.es">dmaddalo@ing.uc3m.es</a></p> <p>- Date: 2024-09-13</p> <p>- Version: 1.0.0</p> <p>- License: This dataset is made available under the <a href="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</a></p> <h2>Abstract</h2> <p>This dataset contains the raw experimental data employed in:</p> <p>Davide Maddaloni, Borja Bayón-Buján, Jaume Navarro-Cavallé, Mario Merino, Filippo Terragni, "Low-frequency oscillations in the magnetic nozzle of a Helicon Plasma Thruster", Plasma Sources Science and Technology, DOI: <a href="https://iopscience.iop.org/article/10.1088/1361-6595/adc40d/meta">10.1088/1361-6595/adc40d</a>.</p> <p>The data within this dataset collect only the 10 sccm case due to file size limits. A companion dataset is available at <a href="https://zenodo.org/records/13913729">10.5281/zenodo.13758358</a>, collecting the data for the 5 sccm case.</p> <h2>Dataset description</h2> <p>The experimental data is gathered by means of three distinct floating Langmuir Probes (LPs).</p> <p>The time-resolved data is provided separately for every spatial position inspected. The data is collected by means of an AC-coupled Yokogawa DLM5058 Mixed Signal Oscilloscope, resolving frequencies up to 50 MHz. The time-averaged I-V curve data obtained by sweeping the LPs is postprocessed according to the routine illustrated in <a href="https://arc.aiaa.org/doi/10.2514/1.B35531">Lobbia et al</a>.</p> <p>Please refer to the corresponding article for further details regarding the data collection (Section 3).</p> <h2>Data files</h2> <p>The data files are in standard Matlab .mat format. A recent version of <a href="https://www.mathworks.com/products/matlab.html">Matlab</a> is recommended.</p> <p>For the time-resolved results, data is subdivided according to the spatial position inspected and the xenon injected mass flow rate. The nomenclature of the files follows the structure "WaveData_[injected mass flow rate]_[axial position]_[angular position]". The file collects the raw waveform data file, labeled "WaveData", and the corresponding time array, labeled "t". For each saptial position within the plume, and for each probe, a total of 3 different waveforms were collected, and each waveform includes 50'000'000 points. The time array also contains 50'000'000 points and is the same for each waveform and/or probe. </p> <p>Each WaveData variable is structured in a 3-dimensional matrix, where:</p> <ul> <li>The first dimension represents the time evolution of the waveform (size 50'000'000)</li> <li>The second dimension represents a different waveform (size 3)</li> <li>The third dimension represents each a different probe (size 3) <ul> <li>Probe 1 along the first position</li> <li>Probe 2 along the second position</li> <li>Probe 3 along the third position</li> </ul> </li> </ul> <p>Please refer to the corresponding article for details regarding the probe labeling and their configuration (Section 3).</p> <p>The time-resolved data is provided in a structure array, containing several fields of two-dimensional matrices with dimensions 21x11 of relevant plasma parameters, as follows:</p> <ul> <li>n: plasma density (in m^-3)</li> <li>Vp: plasma potential (in V)</li> <li>Bx: component along X of the magnetic field (in T)</li> <li>By: component along Y of the magnetic field (in T)</li> <li>X: axial meshgrid coordinate (in mm)</li> <li>Y: radial meshgrid coordinate (in mm)</li> </ul> <p>The electron temperature is not included, since it is considered to be constant within the corresponding article. For the 10 sccm case, it corresponds to 7 eV.</p> <h2>Citation</h2> <p>Works using this dataset or any part of it in any form shall cite it as follows.</p> <p>The preferred means of citation is to reference the publication associated to this dataset, as soon as it is available.</p> <p>Optionally, the dataset may be cited directly by referencing the corresponding DOI: 10.5281/zenodo.13915163.</p> <h2>Acknowledgments</h2> <p>This work has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (project ERC-STG ZARATHUSTRA, grant agreement No 950466). Additionally, F. Terragni was also supported by the FEDER / Ministerio de Ciencia, Innovación y Universidades - Agencia Estatal de Investigación (grant agreement No PID2020-112796RB-C22), while B. Bayón-Buján enjoyed a grant from the Consejería de Educación, Universidades, Ciencia y Portavocía of the Community of Madrid (grant PEJ-2021-AI/TIC-23158).</p>
Data from: Low-frequency oscillations in the magnetic nozzle of a Helicon Plasma Thruster (5 sccm case)
<p>- Data from: Low-frequency oscillations in the magnetic nozzle of a Helicon Plasma Thruster (5 sccm case)</p> <p>- Authors: Davide Maddaloni, Borja Bayón-Buján, Jaume Navarro-Cavallé, Mario Merino, Filippo Terragni</p> <p>- Contact email: <a href="mailto:dmaddalo@ing.uc3m.es">dmaddalo@ing.uc3m.es</a></p> <p>- Date: 2024-09-13</p> <p>- Version: 1.1.0</p> <p>- License: This dataset is made available under the <a href="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</a></p> <h2>Abstract</h2> <p>This dataset contains the raw experimental data employed in:</p> <p>Davide Maddaloni, Borja Bayón-Buján, Jaume Navarro-Cavallé, Mario Merino, Filippo Terragni, "Low-frequency oscillations in the magnetic nozzle of a Helicon Plasma Thruster", Plasma Sources Science and Technology, DOI: <a href="https://iopscience.iop.org/article/10.1088/1361-6595/adc40d/meta">10.1088/1361-6595/adc40d</a>.</p> <p>The data within this dataset collect only the 5 sccm case due to file size limits. A companion dataset is available at <a href="https://doi.org/10.5281/zenodo.13915163">10.5281/zenodo.13915162</a>, collecting the data for the 10 sccm case.</p> <h2>Dataset description</h2> <p>The experimental data is gathered by means of three distinct floating Langmuir Probes (LPs).</p> <p>The time-resolved data is provided separately for every spatial position inspected. The data is collected by means of an AC-coupled Yokogawa DLM5058 Mixed Signal Oscilloscope, resolving frequencies up to 50 MHz. The time-averaged I-V curve data obtained by sweeping the LPs is postprocessed according to the routine illustrated in <a href="https://arc.aiaa.org/doi/10.2514/1.B35531">Lobbia et al</a>.</p> <p>Please refer to the corresponding article for further details regarding the data collection (Section 3).</p> <h2>Data files</h2> <p>The data files are in standard Matlab .mat format. A recent version of <a href="https://www.mathworks.com/products/matlab.html">Matlab</a> is recommended.</p> <p>For the time-resolved results, data is subdivided according to the spatial position inspected and the xenon injected mass flow rate. The nomenclature of the files follows the structure "WaveData_[injected mass flow rate]_[axial position]_[angular position]". The file collects the raw waveform data file, labeled "WaveData", and the corresponding time array, labeled "t". For each saptial position within the plume, and for each probe, a total of 3 different waveforms were collected, and each waveform includes 50'000'000 points. The time array also contains 50'000'000 points and is the same for each waveform and/or probe. </p> <p>Each WaveData variable is structured in a 3-dimensional matrix, where:</p> <ul> <li>The first dimension represents the time evolution of the waveform (size 50'000'000)</li> <li>The second dimension represents a different waveform (size 3)</li> <li>The third dimension represents each a different probe (size 3) <ul> <li>Probe 1 along the first position</li> <li>Probe 2 along the second position</li> <li>Probe 3 along the third position</li> </ul> </li> </ul> <p>Please refer to the corresponding article for details regarding the probe labeling and their configuration (Section 3).</p> <p>The time-resolved data is provided in a structure array, containing several fields of two-dimensional matrices with dimensions 21x11 of relevant plasma parameters, as follows:</p> <ul> <li>n: plasma density (in m^-3)</li> <li>Vp: plasma potential (in V)</li> <li>Bx: component along X of the magnetic field (in T)</li> <li>By: component along Y of the magnetic field (in T)</li> <li>X: axial meshgrid coordinate (in mm)</li> <li>Y: radial meshgrid coordinate (in mm)</li> </ul> <p>The electron temperature is not included, since it is considered to be constant within the corresponding article. For the 5 sccm case, it corresponds to 12.5 eV.</p> <h2>Citation</h2> <p>Works using this dataset or any part of it in any form shall cite it as follows.</p> <p>The preferred means of citation is to reference the publication associated to this dataset, as soon as it is available.</p> <p>Optionally, the dataset may be cited directly by referencing the corresponding DOI: 10.5281/zenodo.13913729.</p> <h2>Acknowledgments</h2> <p>This work has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (project ERC-STG ZARATHUSTRA, grant agreement No 950466). Additionally, F. Terragni was also supported by the FEDER / Ministerio de Ciencia, Innovación y Universidades - Agencia Estatal de Investigación (grant agreement No PID2020-112796RB-C22), while B. Bayón-Buján enjoyed a grant from the Consejería de Educación, Universidades, Ciencia y Portavocía of the Community of Madrid (grant PEJ-2021-AI/TIC-23158).</p>
Linked collectors and determiners for: Streamlining the use of BOLD specimen data to record species distributions: a case study with ten Nearctic species of Microgastrinae (Hymenoptera: Braconidae).
Natural history specimen data linked to collectors and determiners held within, "Streamlining the use of BOLD specimen data to record species distributions: a case study with ten Nearctic species of Microgastrinae (Hymenoptera: Braconidae)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/3a8a3458-675f-46f1-abbc-6e089059e5e8">https://bionomia.net/dataset/3a8a3458-675f-46f1-abbc-6e089059e5e8</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/3a8a3458-675f-46f1-abbc-6e089059e5e8">https://gbif.org/dataset/3a8a3458-675f-46f1-abbc-6e089059e5e8</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Systematics of the enigmatic South American Streblopus Van Lansberge, 1874 dung beetles and their transatlantic origin: a case study on the role of dispersal events in the biogeographical history of the Scarabaeinae (Coleoptera: Scarabaeidae).
Natural history specimen data linked to collectors and determiners held within, "Systematics of the enigmatic South American Streblopus Van Lansberge, 1874 dung beetles and their transatlantic origin: a case study on the role of dispersal events in the biogeographical history of the Scarabaeinae (Coleoptera: Scarabaeidae)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/1668be17-f285-47ef-98b6-c9d90b8cbd6e">https://bionomia.net/dataset/1668be17-f285-47ef-98b6-c9d90b8cbd6e</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/1668be17-f285-47ef-98b6-c9d90b8cbd6e">https://gbif.org/dataset/1668be17-f285-47ef-98b6-c9d90b8cbd6e</a>. Formatted as a Frictionless Data package.
Students' Academic Performance in Case-Based Learning (CBL) based on Machine Learning Approach
<p>Paper title: Students’ Academic Performance in Case-Based Learning (CBL) based on Machine Learning Approach.</p> <p>This paper was registered in 2024 7<sup>th</sup> International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)</p>
Sonic Boom Propagation Results for Case Study 1 of the MORE&LESS Project
<p>This dataset provides the output of sonic boom simulations under various flight conditions, including predictions using Carlson’s method and higher-fidelity nonlinear propagation simulations (using propaBoom). The data is categorized by flight phase (climb, cruise, descent) and atmosphere models (ISA, SBPW3). Each flight phase includes ray tracing results and sonic boom signatures for multiple azimuth angles.</p> <p>The dataset includes:</p> <ul> <li><strong>Carlson Method Predictions</strong>: Peak overpressure and signal duration for various off-track angles.</li> <li><strong>Nonlinear Propagation Simulations</strong>: Ray tracing data (ground intersections and angles) and shock wave signatures at the beginning of the non-linear shock wave propagation and at ground level.</li> </ul> <p>Files are provided in CSV format for easy analysis using standard tools (e.g., Excel, pandas). The dataset contains simulation results for different azimuth angles, e.g., acoustic pressure, and ray intersections for thorough investigation of sonic boom propagation effects.</p> <p><strong>Folder Structure</strong>:</p> <ul> <li><code>carlson_predictions.zip</code>: Carlson method results for climb, cruise, and descent operating conditions.</li> <li><code>nonlinear_propagation_predictions.zip</code>: High-fidelity simulation outputs including ray tracing and propagated ground signatures.</li> <li><code>readme.md</code>: Readme file with information on the datasets.</li> </ul> <p><strong>Usage</strong>: Researchers can use these datasets to compare sonic boom prediction methods under the effects of flight conditions and atmospheric variations on sonic boom ground signatures.</p> <p><strong>Contact</strong>: For any questions or inquiries regarding this dataset, please contact Jacob Jäschke (jacob.jaeschke[at]tuhh.de) (<a title="Orcid Profile of Jacob Jäschke" href="https://orcid.org/0000-0002-5155-4877" target="_blank" rel="noopener">https://orcid.org/0000-0002-5155-4877</a>).</p>
Linked collectors and determiners for: Taxonomic utility of niche models in validating species concepts: A case study in Anthophora (Heliophila) (Hymenoptera: Apidae).
Natural history specimen data linked to collectors and determiners held within, "Taxonomic utility of niche models in validating species concepts: A case study in Anthophora (Heliophila) (Hymenoptera: Apidae)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/1363c785-b3e0-4322-9283-a6d272748735">https://bionomia.net/dataset/1363c785-b3e0-4322-9283-a6d272748735</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/1363c785-b3e0-4322-9283-a6d272748735">https://gbif.org/dataset/1363c785-b3e0-4322-9283-a6d272748735</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Notes on some Tanzanian butterfly specimens in the Suffert Collection: a case of patria falsa.
Natural history specimen data linked to collectors and determiners held within, "Notes on some Tanzanian butterfly specimens in the Suffert Collection: a case of patria falsa". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/6e2f997e-5d4b-4153-ba58-80893e45257a">https://bionomia.net/dataset/6e2f997e-5d4b-4153-ba58-80893e45257a</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/6e2f997e-5d4b-4153-ba58-80893e45257a">https://gbif.org/dataset/6e2f997e-5d4b-4153-ba58-80893e45257a</a>. Formatted as a Frictionless Data package.
Photos from WIDER UPTAKE case study site in the Czech Republic (Camera 4)
<p>Hourly photos from camera 4 at the WIDER UPTAKE H2020 project's case study site in the Czech Republic.</p>
Fig. 1. A in Altai Mountains - cradle of hybrids and introgressants: A case study in Veronica subg. Pseudolysimachium (Plantaginaceae)
Fig. 1. A, Genetic composition based on K = 5 of first-level STRUCTURE results and number of individuals included from that particular locality. Genetic composition of the localities with more than one individual has been averaged. Key to the colors is given in a separate inset. B–D, Probability of ancestry of each individual (horizontal axis; total 233 individuals) to each of K = 4, 5, 6 populations (vertical axis). The five populations correspond mostly to the morphotypes hypothesized for species and putative hybrids. V. ×alt, V. ×altaica; V. ×gri, V. ×grisea; V. ×kol, V. ×kolyvanensis; V. ×sap, V. ×sapozhnikovii; V. ×sch, V. ×schmakovii; V. ×ses, V. ×sessiliflora; V. ×smi, V. ×smirnovii; V. are, V. arenosa; V. inca, V. incana; V. lon, V. longifolia; V. pinn, V. pinnata; V. porp, V. porphyriana; V. reve, V. reverdattoi; V. saj, V. sajanensis; V. spic, V. spicata; V. spur, V. spuria; V. ×taig, V. ×taigischensis; uniden, unidentified.
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.