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2,394 results for “Containers”
CALeDNA Anacapa/CRUX Dat Container (Linux/HPC)
<p>As part of the CALeDNA project this includes Anacapa Container which includes all the necessary software dependencies to run the Anacapa and CRUX pipelines on Linux/HPCs.</p> <p>Instructions are available here:</p> <p>https://github.com/datproject/anacapa-container</p> <p>https://github.com/limey-bean/Anacapa</p>
Domain shares on Twitter containing news and misinformation
<p>This dataset contains a set of domain sharing actions that occurred on Twitter during the month of June 2017. Each domain sharing action can be thought of as a triple <em>(user_id, action_id, domain).</em> The user_id is an anonymized Twitter account ID, and the action_id is an anonymized tweet ID. The tweets from which the dataset was created were collected through Twitter's decahose API. Each user in the dataset was responsible for sharing at least one news article, and at least one article that can be labeled as misinformation. </p> <p>The data is distributed in <em>domain-shares.data</em> in the following JSON format:</p> <pre><code class="language-json">{ "<user-id>": { "<action-id>": ["<domain>", "<domain>", ...], ... }, ... }</code></pre> <p>For example:</p> <pre><code class="language-json">{ "22359b28-93e1-4c13-a3eb-e72357b77c65": { "1": ["palmerreport.com"], "2": ["reuters.com", "abcn.ws"], "3": ["mobile.nytimes.com"] }, "ffe79a32-d49d-4780-87b7-bb6417106067": { "4": ["dallasnews.com"] } }</code></pre> <p>In addition, a TAB-separated version with <em>(user id, action id, domain)</em> triples is also available.</p> <p>For further information on how the dataset was constructed and on analyses that have been conducted on it, please refer to the accompanying Github repository at <a href="https://github.com/dimitargnikolov/twitter-bias">https://github.com/dimitargnikolov/twitter-bias</a>.</p>
A set of videos recorded upon long-term thermocycling experiments carried out by using small containers filled with PCM candidates
<p> </p> <p>Electronic Supplementary Material for Deliverable 2.7 "<strong>Report on the final heat storage block design and long term reliability experiments".</strong></p> <p>A set of fast-forward videoclips compiled based on the images recorded during the long-term experiments on small containers filled with PCM candidates and subjected to thermocycling procedure including consecutive melting/solidification. Details on involved materials and applied temperature profiles are described in D2.7.</p> <p> </p> <p>The list of attached movies:</p> <p> </p> <p><strong>2908</strong>: Si+B mixture (3.2B wt%)/small container made of pure h-BN HeBoSint D100 (Henze, Germany)</p> <p><strong>2909</strong>: Si+B mixture (3.2B wt%)/small container made of h-BN composite HeBoSint O120 (Henze, Germany)</p> <p><strong>2910</strong>: Si+B mixture (3.2B wt %)/small container made of porous graphite (Kryzaplast, Poland)</p> <p><strong>2911</strong>: Si+B mixture (3.2B wt %)/small container made of h-BN composite HeBoSint O120 (Henze, Germany)</p> <p><strong>2969:</strong> Fe-Si-B alloy produced by NTNU/small container made of dense graphite IG-15 (Tanso, Sweden)</p> <p><strong>2970</strong>: Fe-Si-B alloy produced by NTNU/small container made of pure h-BN HeBoSint D100 (Henze, Germany)</p> <p><strong>2971:</strong> Fe-Si-B alloy produced by NTNU/small container made of h-BN composite HeBoSint O120 (Henze, Germany)</p> <p>A more detailed description of the experimental complex is shown elsewhere:</p> <p>Sobczak N, Nowak R, Radziwill W, Budzioch J, Glenz A, Experimental complex for investigations of high temperature capillarity phenomena, Mater Sci Eng A 495 (2008) 43–49</p>
A Review on Emerging Organic-containing Microporous Material Membranes for Carbon Capture and Separation
<p><strong>Published article:</strong> Prasetya, N., Himma, N. F., Doddy Sutrisna, P., Wenten, I. G. & Ladewig, B. P. <em>Chem. Eng. J.</em> 123575 (2019). <a href="https://doi.org/10.1016/j.cej.2019.123575">https://doi.org/10.1016/j.cej.2019.123575</a></p> <p><strong>Abstract</strong></p> <p>Membrane technology has gained great attention as one of the promising strategies for carbon capture and separation. Intended for such application, membrane fabrication from various materials has been attempted. While gas separation membranes based on dense polymeric materials have been long developed, there is a growing interest to use porous materials as the membrane material. This review then focuses on emerging porous materials to be used for the fabrication of membranes that are designed for CO<sub>2</sub>separation. Criteria for selecting microporous material are first discussed, including physical and chemical properties, and parameters in membrane fabrication. Membranes based on emerging porous materials,such as metal-organic frameworks, porous organic frameworks, and microporous polymers,are then reviewed. Finally, special attention is given to recent advances, challenges, and perspectives in the development of such membranes for carbon capture and separation. </p>
Development of a Self-Healing and Rejuvenating Mechanisms for Asphalt Mixtures Containing Recycled Asphalt Shingle
<p>Corresponding data set for Tran-SET Project No. 17BLSU06. Abstract of the final report is stated below for reference:</p> <p>"The objective of this study was to test the hypothesis that hollow-fibers encapsulating a rejuvenator product could improve both self-healing, rejuvenation, and mechanical properties of asphalt mixtures. Hollow-fibers containing a rejuvenating product were synthesized via a wet spinning procedure with sodium-alginate polymer as the encapsulating material. An optimization of the production parameters for the synthesis of fibers was performed to develop fibers suitable for high-temperature and shear stress environment typical of asphalt mixture production. A self-healing experiment was conducted to evaluate the healing/rejuvenation capabilities of sodium-alginate fibers in asphalt mixtures with varying types of binders and recycled materials. Based on the self-healing experiment, a 5% fiber content was determined to be the optimum fiber content to enhance the self-healing ability of asphalt mixtures. In addition, the effect of different fiber contents on binder blends and asphalt mixtures was evaluated by performing the Multiple Stress Creep Recovery (MSCR) and Semi-Circular Bending (SCB) tests. Results of the self-healing experiment showed that the enhancement in the healing recovery depends on the breakage of the fibers. When the fibers break, the rejuvenator is released resulting in softening of the binder. In contrast, when the fibers do not break, they act as a reinforcement for the mix. Loaded Wheel Tester (LWT) test results showed a performance improvement against permanent deformation for asphalt mixtures containing recycled materials with sodium-alginate fibers compared to conventional asphalt mixtures. Furthermore, SCB test results showed that the addition of sodium-alginate fibers enhanced the fracture properties of asphalt mixtures with Recycled Asphalt Shingle (RAS) at intermediate temperatures. Moreover, the addition of fibers in mixtures with recycled materials resulted in an improved performance against low-temperature cracking as the mixtures resisted higher stresses before failure."</p>
ROS-Specific Huntingtin Interactions: Chromatin retention assay with huntingtin fragments containing PBM3
<p>Huntingtin amino acids 1790-1798 make up a potential PAR binding motif (PBM3). Two huntingtin fragments (1208-1810 and 1775-2413) were tested for chromatin retention upon oxidative stress.</p>
Pitting corrosion of AA1050 in ethanol-containing fuels: Classification dataset
<p>This dataset was used to predict the occurrence of ethanol-based pitting corrosion in AA1050 using binary classification. It consists of five system descriptors:</p> <ul> <li>Temperature (°C)</li> <li>Chloride content (ppm)</li> <li>Water content (ppm)</li> <li>Grit size of polishing paper</li> <li>Ethanol content (% by volume) of the fuel</li> </ul> <p>The target variable, named "corr," indicates corrosion occurrence, where 1 means corrosion occurred and 0 means no corrosion occurred. The dataset comprises 115 samples in total: 105 samples where corrosion occurred and 10 samples where no corrosion occurred.</p>
Data Set for Nickel-Catalyzed Enantio- and Diastereoselective Synthesis of Fluorine-Containing Vicinal Stereogenic Centers
<p>Raw NMR, HPLC and (HR)MS data for the article entitled "Nickel-Catalyzed Enantio- and Diastereoselective Synthesis of Fluorine-Containing Vicinal Stereogenic Centers" published in ACS Central Science. Folder names in "Characterizations" correspond to compound names as given in the article and/or supporting information. </p>
1200 artificial genome sequences containing a single-or-multistep NAHR event each.
<p>This is a companion dataset to Höps et al. 2024: <strong>Impact and characterization of serial structural variations across humans and great apes</strong></p> <p> </p> <p>600 'ancestor'; i.e. source sequences with two pairs of SDs were mutated first. The SD sequences of the two pairs are not overlapping, however the space between SD pairs IS. There are two possible configurations for this: 1-2-2-1 or 1-2-1-2, with 1 and 2 denoting the identity of repeat pair 1 and 2. This configuration as well as the relative orientation of the two SDs (same direction / inverse direction) were randomly chosen.</p> <p>We used four target SD lenghts [100bp, 500bp, 1000bp, 10000bp] and three SD similarity scores [90%, 95%, 99%], totalling 12 combinations. Here, we created 50 artifical sequences for each of these configurations, totalling 600 sequences. </p> <p>From the 600 ancestor sequences, we then simulated several, again randomly chosen NAHR chains up to depth-3 using the mutate_sequences.py script in the attached github. Finally, we chose two 'representative' mutated seuqnces for each ancestor, totalling 1200 sequences published here. </p> <p>This upload contains two (zipped) folders; ancestors and mutated_seqs. The ancestors are enumerated 1-600, and mutated seqs likewise have their corresponding ancestor in the beginning of their filename. </p> <p>The data was created using the generate_mutate script in https://github.com/WHops/nahrwhals_simulate_events release v0.2. </p> <p> </p> <p>contact: wolfram.hoeps@gmail.com</p>
Microscopy images - " Particulate matter constituents trigger the formation of extracellular amyloid β and Tau -containing plaques and neurite shortening in vitro"
<p>This repository contains microscopy data from the manuscript "Particulate matter constituents trigger the formation of extracellular amyloid β and Tau -containing plaques and neurite shortening in vitro" by Aleksandar Sebastijanović, Laura Maria Azzurra Camassa, Vilhelm Malmborg, Slavko Kralj, Joakim Pagels, Ulla Vogel, Shan Zienolddiny-Narui, Iztok Urbančič, Tilen Koklič, and Janez Štrancar (published in Nanotoxicology, 18(4), 335–353. https://doi.org/10.1080/17435390.2024.2362367).</p> <p>Raw data are organized in folders named by image number, containing a subfolder with the date (year-day-month) of image acquisition. Followed by a subfolder named by a nanomaterial to which neurons were exposed. Each folder contains images from individual multi-channel, multi-position time-lapse experiments with different combinations of cells exposed to one nanomaterial. Files are named as: IMGxxxx_[ExperimentCode]_ROIxx_[Channel].tif, where each of the varying elements in [..] denotes the following:<br>• [ExperimentCode]: a short name of the experiment<br>• [Channel]: membrane (MEM), cytoplasm neuronal cells (NEU), nanomaterial (NANO), amyloid beta (AMY)</p>
Copper Ore grade (%) and Contained Copper (MT) from Mudd 2013
<p>Data extracted from Fig. 3 of the paper Mudd, Gavin & Weng, Zhehan & Jowitt, Simon. (2013). A Detailed Assessment of Global Cu Resource Trends and Endowments. Economic Geology. 108. 1163-1183. 10.2113/econgeo.108.5.1163. </p> <p>Note that I only get 718 datapoints, instead of the 730 reported in the paper, yet the mass of copper sums to a very close total (1779.6 MT in my case, 1780.9 in the article).</p>
Datasets of protein models from plasmids containing conjugative Type 4 Secretion Systems
<p>In the connected article, we have created a database of all modelled protein structures encoded on plasmids that contain conjugative type 4 secretion systems. In this deposition, you will find zip files of all structures modelled by AlphaFold, as well as the ones that were modelled using EMS fold. Further, there the csv file containing the DeepFRI output, as well as a fasta file containing the sequences of the plasmids.</p> <p>The AlphaFold and ESM databases contain the structural models of the curated/triaged proteins, as described in the paper.</p> <p> </p>
Supplementary Table S1. Combined analysis of variance containing the degrees of freedom (DF), mean squares (MS), P value (P val.), mean, coefficient of experimental variation (CEV%) and selective accuracy (SA) for the traits of luminosity (L*), chromaticity a* (a*), chromaticity b* (b*), grain length (length, mm), grain width (width, mm), grain thickness (thickness, mm), mass of 100 grains (Mass, g), normal grains (Ng, %), water absorption (absorption, %), cooking time (Ct, min:s), and concentrations of potassium (K, g kg-1 dry matter - DM), phosphorus (P, g kg-1 DM), calcium (Ca, g kg-1 DM), magnesium (Mg, g kg-1 DM), iron (Fe, mg kg-1 DM), zinc (Zn, mg kg-1 DM), and copper (Cu, mg kg-1 DM) obtained in 25 common bean cultivars evaluated in four experiments carried out from 2019 to 2021
<p><strong><span>Table S1.</span></strong><span> Combined analysis of variance.</span></p> <p><strong><span>Indirect selection for multiple technological and nutritional traits in common bean cultivars under different degrees of multicollinearity</span></strong></p> <p><strong><span>Bragantia, 2024.</span></strong></p>
Furrer_dataset_PoD: Dataset containing results from the research project Points of Discontinuity concerning Beat Furrer, spur für Klavier und Streichquartett (1998)
<p>The complete datasets resulting from the research project <em>Points of Discontinuity</em> contain 23 datasets for the musical works or excerpts that were part of the online listening experiment, with each dataset containing seven or eight files (all audio files are stored in a dataset with restricted access), as well as a dataset (PoD_general_dataset) with five additional files.</p> <p>This dataset<strong> Furrer_dataset_PoD </strong>contains eight files:</p> <ul> <li>Furrer_01_ReadMe.pdf</li> <li>Furrer_02_data.xlsx (processed data for this work)</li> <li>Furrer_03_individual_data.xlsx (raw data for each participant obtained from the experiment)</li> <li>Furrer_04_audio.mp3 <strong>[non-public] </strong>(audio recording used in the experiment) [stored in the restricted dataset <a href="https://doi.org/10.5281/zenodo.13981214" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13981214</a>]</li> <li>Furrer_05_model_results.sv (graphical representation of results and the model in Sonic Visualiser) [requires audio file Furrer_04_audio.mp3 to display correctly]</li> <li>Furrer_06_SV-data_model+results.zip (text files with the marker locations for all layers in Sonic Visualiser)</li> <li>Furrer_07_model+results_SV-screenshot.pdf (a screenshot of the full-screen display of the SV-file)</li> <li>Furrer_08_annotated_score.pdf (model analysis annotated in the score)</li> </ul>
Sciarrino_dataset_PoD: Dataset containing results from the research project Points of Discontinuity concerning Salvatore Sciarrino, Sei capricci per violino (1976), no. 1: Vivace
<p>The complete datasets resulting from the research project <em>Points of Discontinuity</em> contain 23 datasets for the musical works or excerpts that were part of the online listening experiment, with each dataset containing seven or eight files (all audio files are stored in a dataset with restricted access), as well as a dataset (PoD_general_dataset) with five additional files.</p> <p>This dataset<strong> Sciarrino_dataset_PoD </strong>contains eight files:</p> <ul> <li>Sciarrino_01_ReadMe.pdf</li> <li>Sciarrino_02_data.xlsx (processed data for this excerpt)</li> <li>Sciarrino_03_individual_data.xlsx (raw data for each participant obtained from the experiment)</li> <li>Sciarrino_04_audio.mp3 <strong>[non-public] </strong>(audio recording used in the experiment) [stored in the restricted dataset <a href="https://doi.org/10.5281/zenodo.13981214" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13981214</a>]</li> <li>Sciarrino_05_model_results.sv (graphical representation of results and the model in Sonic Visualiser) [requires audio file Sciarrino_04_audio.mp3 to display correctly]</li> <li>Sciarrino_06_SV-data_model+results.zip (text files with the marker locations for all layers in Sonic Visualiser)</li> <li>Sciarrino_07_model+results_SV-screenshot.pdf (a screenshot of the full-screen display of the SV-file)</li> <li>Sciarrino_08_annotated_score.pdf (model analysis annotated in the score)</li> </ul>
Barrett_dataset_PoD: Dataset containing results from the research project Points of Discontinuity concerning Natasha Barrett, Animalcules (2010, electronic work)
<p>The complete datasets resulting from the research project <em>Points of Discontinuity</em> contain 23 datasets for the musical works or excerpts that were part of the online listening experiment, with each dataset containing seven or eight files (all audio files are stored in a dataset with restricted access), as well as a dataset (PoD_general_dataset) with five additional files</p> <p>This dataset<strong> Barrett_dataset_PoD </strong>contains seven files:</p> <ul> <li>Barrett_01_ReadMe.pdf</li> <li>Barrett_02_data.xlsx (processed data for this excerpt)</li> <li>Barrett_03_individual_data.xlsx (raw data for each participant obtained from the experiment)</li> <li>Barrett_04_audio.mp3 <strong>[non-public] </strong>(audio recording used in the experiment) [stored in the restricted dataset <a href="https://doi.org/10.5281/zenodo.13981214" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13981214</a>]</li> <li>Barrett_05_model_results.sv (graphical representation of results and the model in Sonic Visualiser) [requires audio file Barrett_04_audio.mp3 to display correctly]</li> <li>Barrett_06_SV-data_model+results.zip (text files with the marker locations for all layers in Sonic Visualiser)</li> <li>Barrett_07_model+results_SV-screenshot.pdf (a screenshot of the full-screen display of the SV-file)</li> </ul>
Xenakis_dataset_PoD: Dataset containing results from the research project Points of Discontinuity concerning Iannis Xenakis, Pithoprakta for two trombones, percussion, and strings (1955–56)
<p>The complete datasets resulting from the research project <em>Points of Discontinuity</em> contain 23 datasets for the musical works or excerpts that were part of the online listening experiment, with each dataset containing seven or eight files (all audio files are stored in a dataset with restricted access), as well as a dataset (PoD_general_dataset) with five additional files.</p> <p>This dataset<strong> Xenakis_dataset_PoD </strong>contains eight files:</p> <ul> <li>Xenakis_01_ReadMe.pdf</li> <li>Xenakis_02_data.xlsx (processed data for this work)</li> <li>Xenakis_03_individual_data.xlsx (raw data for each participant obtained from the experiment)</li> <li>Xenakis_04_audio.mp3 <strong>[non-public] </strong>(audio recording used in the experiment) [stored in the restricted dataset <a href="https://doi.org/10.5281/zenodo.13981214" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13981214</a>]</li> <li>Xenakis_05_model_results.sv (graphical representation of results and the model in Sonic Visualiser) [requires audio file Xenakis_04_audio.mp3 to display correctly]</li> <li>Xenakis_06_SV-data_model+results.zip (text files with the marker locations for all layers in Sonic Visualiser)</li> <li>Xenakis_07_model+results_SV-screenshot.pdf (a screenshot of the full-screen display of the SV-file)</li> <li>Xenakis_08_annotated_score.pdf (model analysis annotated in the score)</li> </ul>
Harrison_dataset_PoD: Dataset containing results from the research project Points of Discontinuity concerning Jonty Harrison, Klang (1982, electronic work), excerpt
<p>The complete datasets resulting from the research project <em>Points of Discontinuity</em> contain 23 datasets for the musical works or excerpts that were part of the online listening experiment, with each dataset containing seven or eight files (all audio files are stored in a dataset with restricted access), as well as a dataset (PoD_general_dataset) with five additional files</p> <p>This dataset<strong> Harrison_dataset_PoD </strong>contains seven files:</p> <ul> <li>Harrison_01_ReadMe.pdf</li> <li>Harrison_02_data.xlsx (processed data for this excerpt)</li> <li>Harrison_03_individual_data.xlsx (raw data for each participant obtained from the experiment)</li> <li>Harrison_04_audio.mp3 <strong>[non-public] </strong>(audio recording used in the experiment) [stored in the restricted dataset <a href="https://doi.org/10.5281/zenodo.13981214" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13981214</a>]</li> <li>Harrison_05_model_results.sv (graphical representation of results and the model in Sonic Visualiser) [requires audio file Harrison_04_audio.mp3 to display correctly]</li> <li>Harrison_06_SV-data_model+results.zip (text files with the marker locations for all layers in Sonic Visualiser)</li> <li>Harrison_07_model+results_SV-screenshot.pdf (a screenshot of the full-screen display of the SV-file)</li> </ul>
Chen_dataset_PoD: Dataset containing results from the research project Points of Discontinuity concerning Chen Yi, Ge Xu (Antiphony) for chamber orchestra (1994)
<p>The complete datasets resulting from the research project <em>Points of Discontinuity</em> contain 23 datasets for the musical works or excerpts that were part of the online listening experiment, with each dataset containing seven or eight files (all audio files are stored in a dataset with restricted access), as well as a dataset (PoD_general_dataset) with five additional files.</p> <p>This dataset<strong> Chen_dataset_PoD </strong>contains eight files:</p> <ul> <li>Chen_01_ReadMe.pdf</li> <li>Chen_02_data.xlsx (processed data for this work)</li> <li>Chen_03_individual_data.xlsx (raw data for each participant obtained from the experiment)</li> <li>Chen_04_audio.mp3 <strong>[non-public] </strong>(audio recording used in the experiment) [stored in the restricted dataset <a href="https://doi.org/10.5281/zenodo.13981214" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13981214</a>]</li> <li>Chen_05_model_results.sv (graphical representation of results and the model in Sonic Visualiser) [requires audio file Chen_04_audio.mp3 to display correctly]</li> <li>Chen_06_SV-data_model+results.zip (text files with the marker locations for all layers in Sonic Visualiser)</li> <li>Chen_07_model+results_SV-screenshot.pdf (a screenshot of the full-screen display of the SV-file)</li> <li>Chen_08_annotated_score.pdf (model analysis annotated in the score)</li> </ul>
Saariaho_dataset_PoD: Dataset containing results from the research project Points of Discontinuity concerning Kaija Saariaho, Lichtbogen for nine musicians and live-electronics (1985–86)
<p>The complete datasets resulting from the research project <em>Points of Discontinuity</em> contain 23 datasets for the musical works or excerpts that were part of the online listening experiment, with each dataset containing seven or eight files (all audio files are stored in a dataset with restricted access), as well as a dataset (PoD_general_dataset) with five additional files.</p> <p>This dataset<strong> Saariaho_dataset_PoD </strong>contains eight files:</p> <ul> <li>Saariaho_01_ReadMe.pdf</li> <li>Saariaho_02_data.xlsx (processed data for this work)</li> <li>Saariaho_03_individual_data.xlsx (raw data for each participant obtained from the experiment)</li> <li>Saariaho_04_audio.mp3 <strong>[non-public] </strong>(audio recording used in the experiment) [stored in the restricted dataset <a href="https://doi.org/10.5281/zenodo.13981214" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13981214</a>]</li> <li>Saariaho_05_model_results.sv (graphical representation of results and the model in Sonic Visualiser) [requires audio file Saariaho_04_audio.mp3 to display correctly]</li> <li>Saariaho_06_SV-data_model+results.zip (text files with the marker locations for all layers in Sonic Visualiser)</li> <li>Saariaho_07_model+results_SV-screenshot.pdf (a screenshot of the full-screen display of the SV-file)</li> <li>Saariaho_08_annotated_score.pdf (model analysis annotated in the score)</li> </ul>
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.