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22,922 results for “collections as data”
Velocity and temperature data from Lake Geneva (CH), collected during year 2016
<p>Data collected by 4 Acoustic Doppler Current Profilers (ADCPs) in Lake Geneva (Switzerland), during year 2016. The four files include velocity data, vertically averaged using the depth bins with sufficiently good quality, and corresponding frequency spectra. Temperature data recorded by the ADCPs, at the instruments depth, are also provided, as well as their frequency spectra. All files also include the results from a numerical model of the lake hydrodynamics, at the positions of the ADCPs and at overlapping times.</p> <p>All files are in HDF5 format, and include relevant metadata.</p> <p>Summary of datasets:</p> <ul> <li><strong>16A</strong>, deployed at (517, 137)km (CH1903 coordinates), measured depth range (velocity) 10-70m, deployed on 8 July 2016, recovered on 2 November 2016. ADCP deployed at the bottom, depth of 82m, vertical resolution of 2m.</li> <li><strong>16B</strong>, deployed at (511, 138)km (CH1903 coordinates), measured depth range (velocity) 15-37m, deployed on 8 July 2016, recovered on 29 October 2016. ADCP deployed at the bottom, depth of 45m, vertical resolution of 1m. Data from this ADCP has a low signal-to-noise ratio for velocity.</li> <li><strong>16C</strong>, deployed at (529, 150)km (CH1903 coordinates), measured depth range (velocity) 15-65m, deployed on 18 July 2016, recovered on 16 December 2016. ADCP deployed at the bottom, depth of 77m, vertical resolution of 2m.</li> <li><strong>16D</strong>, deployed at (554, 139)km (CH1903 coordinates), measured depth range (velocity) 15-85m, deployed on 23 September 2016, recovered on 23 January 2017. ADCP deployed at a depth of 90m, bottom depth of approximately 130m, vertical resolution of 2m.</li> </ul> <p> </p>
Data on scientific production on letramento informacional in Brazil: collection procedures and resulting corpus [Dataset of thesis]
<p>Dataset containing two dataset:</p> <p>1 - Description of the data collection procedures carried out for the thesis: Appropriation of the term letramento by Brazilian Library and Information Science: terminological-conceptual tensions surrounding letramento informacional by Alves (2023).</p> <p>2 - Four Spreadsheet in CSV UTF-8 containing in each of them a set of bibliographic references in partially raw data.</p>
Data for: Crall et al., Spatial fidelity of workers predicts collective response to disturbance in a social insect
<p>Dataset for: Crall et al., Spatial fidelity of workers predicts collective response to disturbance in a social insect, in final revision for Nature Communications.</p> <p>Includes two files - one behavioral data from uniquely identified worker bumblebees, and the second containing metadata for the colonies from which these data were generated (including experimental treatments, locations, sizes, etc.).</p>
Bathymetry from multibeam data collected on the RV Heincke, cruises HE-324 and HE-349, North Sea, Helgoland (Germany)
<p>Mosaicked multibeam-derived bathymetry from Simrad EM710 on board RV Heincke collected during Spring 2010 (HE- 324) and 2011 (HE-349). Water depths range from 20 to 50 meters. The range of opening angles of the EM710 multibeam varies between 50 and 65 degrees. EM710 data were used in conjunction with an OCTANS motion sensor, ship’s DGPS and Sound Velocity Profiles (SVP). CRS information: WGS 84 / UTM zone 32N.</p>
Preliminary data collected by 2 prototype Surface Velocity Platform drifters with Barometer and Reference Sensor for Temperature (SVP-BRST)
<p>The SVP-BRST drifter was developed to serve calibration and validation of Sentinel satellite SST retrievals. Two prototypes were deployed in the Mediterranean Sea end of April 2018. Preliminary data collected then until 11 June 2018 are published in this dataset. The drifters were developed and deployed under funding from the European Union's Copernicus Programme. The data are transmitted from the buoy to shore using data format #091 (see References).</p>
data for Collective departures and leadership in zebrafish
<p>Txt files with the position (x,y) and confidence probability of the correct identification of the fish. Dataset used for the publication Collective departures and leadership in zebrafish.</p>
Directional wave data collected by R/V Aranda in the Baltic Sea
<p>Data source: Finnish Meteorological Institute</p> <p>This is wave and meteorological data collected on board R/V Aranda in July 2015 in the Baltic Sea. Each netcdf-file contains the data and metadata from one station.</p> <p>The experimental setup is described in the paper: Björkqvist, J.-V., Pettersson, H., Drennan, W. M., and Kahma, K. K., 2019: A new inverse phase speed spectrum of nonlinear gravity wind waves, Journal of Geophysical Research: Oceans, 124, 6097–6119, DOI: 10.1029/2018JC014904</p>
Size-resolved cloud condensation nuclei data collected during the CalWater 2015 field campaign
<p>This repository contains raw and processed data for the size-resolved cloud condensation nuclei instrument deployed during the Calwater-2015 field campaign. It also contains the averaged cluster data presented in the paper "Classification of aerosol population type and cloud condensation nuclei properties in a coastal California littoral environment using an unsupervised cluster model" by Atwood et al. (2019). Details about the datafiles are provided in README.md file in markdown format.</p>
TwitCID: a Collection of Data Sets for Studies on Information Diffusion on Social Networks
<p>The TwitCID collection consists of five Twitter datasets which were extracted from the 1 percent of tweets from Twitter API. </p> <p>The Firstweek and Secondweek data set were collected during the first week and second week of January 2017 while the Iphone, Gucci and Galaxy data sets were collected from 21 September 2015 to 31 May 2017 using the keywords “iphone”, “gucci” and “galaxys” respectively. </p> <p>We publish these datasets on behalf of our academic institution – IRIT, France and for the sole purpose of non-commercial research under the license CC BY-NC-SA (Attribution-NonCommercial-ShareAlike). In accordance with Twitter's Terms of Service, we only provide identifiers of tweets. In order to collect the actual tweets in JSON, you could use the script Collect_JSONtweets.py attached.</p> <p>If you would like to use this collection, please cite our paper: </p> <p>Hoang, T. B. N., Mothe, J., & Baillon, M. (2019, September). TwitCID: a collection of data sets for studies on information diffusion on social networks. In <em>International Conference of the Cross-Language Evaluation Forum for European Languages</em> (pp. 88-100). Springer, Cham.</p>
Raw data supporting Identifying invertebrates from pitfall, flight interception traps and hand collecting
<p>Raw data supporting identifying invertebrates from pitfall, flight interception traps and hand collecting: comparing metabarcoding with traditional methods.</p> <p>Two step PCRs were performed on each sample replicate using modified primers mICOIintF and jgHCO2198 followed by the Nextera XT index kit v2 Set A (Illumina).</p> <p>The pool was loaded onto an illumina MiSeq using a MiSeq Reagent Kit v2 500 cycle kit (Illumina), with 10% Phi-X to generate 250-bp paired-end reads.</p>
Raw metagenomic data from sweep net samples collected in 2016 as part of the Slikok Creek Watershed Biotic Inventory
<p>We set out to inventory vascular plants, bryophytes, lichens, birds, arthropods, and earthworms on a grid of sites in the portion of Slikok Creek watershed that is on the Kenai National Wildlife Refuge, Kenai Peninsula, Alaska. Occurrence data, images, and field data sheets from this project are available via an <a href="https://arctosdb.org/">Arctos</a> project page at <a href="http://arctos.database.museum/project/10002227">http://arctos.database.museum/project/10002227</a>.</p> <p>This dataset includes the raw FASTQ files from metagenomic processing and associated collection data. Of the 160 sweep net samples collected, 125 were selected for High Throughput Sequencing and shipped to RTL Genomics (<a href="http://rtlgenomics.com">http://rtlgenomics.com</a>) for extraction and sequencing steps. Sequencing was performed on an Illumina MiSeq platform and reads were processed using RTL Genomics’ standard methods with the mlCOIlintF/HCO2198 primer set of Leray et al. (2013), yielding a 313 bp region of the COI gene.</p> <p>Collection data are included in the file <code>ArctosData_43C6167EB1.csv</code> downloaded from Arctos. Extraction methods and sequencing methods provided by RTL Genomics are included in the files <code>Bowser 4869.pdf</code> and <code>Illumina MiSeq Two-Step Method 454 profile only.docx</code>. Primers used are provided in the file <code>Bowser_4869M.txt</code>. The archive <code>FASTQ.zip</code> contains all of the resulting FASTQ files.</p> <p>These sequence data have also been been published to GenBank's Sequence Read Archive in accessions <a href="http://trace.ncbi.nlm.nih.gov/Traces/sra/?run=SRR10454582">SRR10454582</a>–<a href="http://trace.ncbi.nlm.nih.gov/Traces/sra/?run=SRR10454706">SRR10454706</a> under BioProject <a href="http://www.ncbi.nlm.nih.gov/bioproject/PRJNA427721">PRJNA427721</a>.</p>
Core log descriptions and sediment grain size data for Hurricane Ian sediment cores collected in Lee County, Florida, USA
<p>These data represent qualitative and quantitative measurements of sediment cores collected from various environments following the landfall of Hurricane Ian. These sediment cores were collected using pound coring techniques up to 2m into the subsurface to characterize the sedimentological signature of storm deposits resulting from Hurricane Ian. More details regarding these measurements and interpretations of storm deposits can be found in the folllowing manuscript:</p> <p>McCormick, W.M., Briggs, T.R., Hauptman, L.H., Wang, P., Morphologic and sedimentological signatures resulting from Hurricane Ian, southwest Florida, USA: Insight into intra-storm bidirectional sediment transport processes (In Review). </p>
Raw data for analysis of archaeological collections using scoring
<p>The file includes data in the form of attributes identifying the cultural or natural origin of archaeological collections composed of flakes and blades made of flint. The collections attributed to the Lower and Middle Palaeolithic in Poland and Germany. The last collection consists of experimentally produced samples. These collections are held at the Muzeum Śląska Opolskiego in Opole, University of Wrocław, University of Silesia in Katowice, Sosnowiec and Landesmuseum für Vorgeschichte in Halle (Saale). The collected data was used to improve the method hitherto applied to distinguish sets composed of artefacts and pseudo-artefacts using so-called scoring. This work was financially supported by the National Science Centre,<br>Poland (Grant 2020/39/B/HS3/02277).</p>
Excel data collection template on descriptive political representation in national parliaments of the projects Pathways to Power and InclusiveParl adapted for the ActEU project
<p>This file contains the empty data collection template and variable and value labels to code biographical data on legislators for WP4 in the ActEU project. It is an abbreviated version of the codebooks produced by the Pathways to Power project and by the InclusiveParl project.</p>
RDF version of the data from Saarimaki et al. Manually curated transcriptomics data collection for toxicogenomic assessment of engineered nanomaterials (Version 1.0.0) [Zenodo Dataset] (2020)
<p>This is an RDFied version of the dataset published by Saarimaki et al. Manually curated transcriptomics data collection for toxicogenomic assessment of engineered nanomaterials (Version 1.0.0) [Zebodo Dataset] (2020)</p> <p>The original dataset publication DOI: <a href="http://doi.org/10.5281/zenodo.4146981">http://doi.org/10.5281/zenodo.4146981</a></p> <p>The Original publication authors: Saarimaki, Laura Aliisa, Federico, Antonio, Lynch, Iseult, Papadiamantis, Anastasios G., Tsoumanis, Andreas, Melagraki, Georgia, Afantitis, Antreas, Serra, Angela, & Greco, Dario</p>
Sampling study and collection phase (q-interline data)
<p>This dataset contains the spectral data acquired on waste wood samples using a FT-NIR spectrophotometer (Q-Interline A/S, Tølløse, Denmark) provided with the patented spiral sampler (Spiral Sampler, Q-Interline A/S, Tølløse, Denmark). The waste wood samples have been collected in a panel board company located in the Northern part of Italy during two days of sampling (February 18-19, 2020). In detail, 64 samples (16 lots x 4 samples from each lot) were obtained; later each sample has been split into two replicates for a total of 128 samples. Because of an unfortunate computer error (i.e. the computer froze without saving the collected data) only realized after arriving back at the University, the spectral data of two sample replicates have not been stored. Hence, the final dataset consists of 26192 observations and 1091 wavenumbers (around 210 NIR scans per sample replicate). The sample has been analysed with a particle size of 5 mm.</p> <p>The CSV file contains the following information in the columns:</p> <ul> <li>Sample code: it is reporting the sample code where S1 is the number of lot, the successive number is the number of subsample and the last number the NIR replicate. E.g. S01-01_122: lot number 1, subsample number 01, NIR replicate number 122. Please note that we have also letter ‘B’ when we are looking at the second subsample replicate.</li> <li>Lot: number of lot to which the sample belongs (from 1 to 16).</li> <li>Subsample: number 1, 7, 13 or 19 indicating the four subsamples;</li> <li>Replicate: number 1 or 2 indicating first or second replicate.</li> <li>Measurement: the number of the NIR measurement.</li> <li>Spectral data: absorbance values for each sample from 3595.05 cm<sup>-1</sup> to 12004.07 cm<sup>-1</sup>.</li> </ul> <p>The aim behind this dataset is to provide information about the frequency of sampling and number of replicates and scans to perform for describing the waste wood variability (WP1 of WoodSpec project). A correct sampling procedure is fundamental to guarantee an accurate and successful use of a NIR sensor into real industrial applications and improve the waste wood management, especially when dealing with heterogeneous material.</p> <p><em>Funding: The project leading to this application has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 838560. </em></p> <p><em>Terms of use: These data are provided "as is", without any warranties of any kind. The data are provided under the Creative Commons Attribution 4.0 International license.</em></p>
Environmental and AIS data collected during the EUMarineRobots Trans-National Access activities experiments using the NATO STO-CMRE Littoral Ocean Observatory Network testbed
<p>Environmental and AIS data collected during the H2020 project EUMarineRobots Trans-National Access activities experiments using the NATO STO-CMRE Littoral Ocean Observatory Network (LOON) testbed. Environmental data consists of temperature measured across the water column; sound velocity measured close to the surface and close to the sea bottom; meteorological data at the surface (i.e., pressure, temperature, wind speed and direction, humidity and rain). The environmental dataset is complemented with Automatic Identification System (AIS) data for the ships transiting close to the LOON area (Gulf of La Spezia, Italy)</p> <p>Temperature measured across the water column in the LOON area (Gulf of La Spezia, Italy). The dataset includes measurements for:<br> i) Nov 12, 19-20, 23-24 - 2020<br> ii) Dec 1-4, 14-20 - 2020<br> iii) Jan 12-13, 15, 18-24, 27-28 - 2021</p> <p><br> Meteorological data at the surface (i.e., pressure, temperature, wind speed and direction, humidity and rain) in the LOON area (Gulf of La Spezia, Italy). The dataset includes measurements for:<br> i) Nov 12, 19-20, 23-24 - 2020<br> ii) Dec 1-4, 14-20 - 2020<br> iii) Jan 12-13, 15, 18-24, 27-28 - 2021</p> <p><br> Sound velocity measured close to the surface (SVP1) and close to the sea bottom (SVP2) in the LOON area (Gulf of La Spezia, Italy). The dataset includes measurements for:<br> i) Nov 12, 19-20, 23-24 - 2020<br> ii) Dec 1-4, 14-20 - 2020<br> iii) Jan 12-13, 15, 18-24, 27-28 - 2021</p> <p>SVP2 data missing for Dec 14-20 (2020) and Jan 24, 27-28 (2021).</p> <p>Automatic Identification System (AIS) data for the ships transiting close to the LOON area (Gulf of La Spezia, Italy). The dataset includes AIS data for:<br> i) Nov 12, 19-20, 23-24 - 2020<br> ii) Dec 1-4, 14-20 - 2020<br> iii) Jan 12-13, 15, 18-24, 27-28 - 2021<br> </p> <p>For reference, see: "Environmental data collected on the CMRE LOON tested during the EUMR project: dataset description", Petroccia, Roberto; Zappa, Giovanni; Cimino, Giampaolo; Grati, Alberto; Alves, João. CMRE-DA-2021-001. July 2021, available at https://www.cmre.nato.int/research/publications/latest-techreports/1638-cmre-da-2021-001</p>
Ouseley mission to Persia 1810-15 – Data on oriental manuscripts collected by the Ouseley brothers
<p>These files form part of an archive of research data relating to the diplomatic mission to Persia 1810-15, led by Sir Gore Ouseley as ambassador. The data have been compiled by independent researchers W H (Bill) Martin and Sandra Mason; their contact details are in the README file.. The files comprise a number of searchable listings relating to the reports produced by members of the mission and other relevant data. The data formed the basis for a published report on the Ouseley Mission referenced below, which is also part of the archive. </p> <p>This section of the archive contains three databases, under the general heading of <em>ouscollect</em>, listing the main items in the Ouseley collections of oriental manuscripts now held at the Bodleian Library in Oxford. Some of these items were undoubtedly acquired during the Ouseley mission to Persia 1810-15. Other were obtained during the brothers earlier stays in India or through booksellers in London and elsewhere. The database files have been saved in two formats: a Microsoft Access database (<em>ouscollect.accdb</em>) covering all the Ouseley holdings, and three separated comma-delimited text files (<em>.txt</em>). The explanatory README text file contains a table showing the fields included in the databases and giving definitions of them and of the codings used in different cases. </p>
Data of publication: "Collective atom-cavity coupling and nonlinear dynamics with atoms with multilevel ground states"
<p>The uploaded files contain the raw data of the measurements and simulations presented in <a href="https://doi.org/10.1103/PhysRevA.107.023714">https://doi.org/10.1103/PhysRevA.107.023714</a></p>
Sea ice core biogeochemical data collected during the 2019 SCALE Winter Cruise
<p><strong>Title: </strong>Biogeochemical profiles of sea ice cores sampled during the Southern oCean seAsonal Experiment (SCALE) winter cruise in 2019.</p> <p> </p> <p><strong>Authors:</strong> Riesna R. Audh, Siobhan Johnson, Mark Hambrock, Hazel Little, Joshua Mirkin, Emmanuel Omatuku, Benjamin Hall, Tokoloho Rampai, Keith MacHutchon, Sebastian Skatulla, Sarah E. Fawcett, Marcello Vichi</p> <p> </p> <p><strong>Data Description:</strong></p> <p> </p> <p><strong>Abstract</strong></p> <p>Biogeochemical profiles of sea ice cores extracted from in situ sea ice floes and lifted pancakes were measured in the Atlantic sector of the Antarctic Marginal Ice Zone during the Southern oCean seAsonal Experiment (SCALE) winter cruise in 2019 (<a href="http://www.scale.org.za">www.scale.org.za</a>) aboard the SA Agulhas II.</p> <p> </p> <p>A total of four sea ice cores (cores) were sampled during the cruise. Two cores were collected overboard on a consolidated floe that was accessed via a personnel carrier suspended by the ship’s forward crane. Two cores were collected from a pancake that was lifted aboard the ship via a net that was attached to the ship’s aft crane and placed on the helideck for sampling. Profiles were obtained by cutting the cores using a bandsaw in a cold laboratory at -10 °C. The cores were cut into approximately 0.05 m segments, starting from the bottom of the core. These segments were allowed to melt in the dark in an insulated box. The meltwater was filtered for chlorophyll measurements (Welschmeyer, 1994) and the filtrate was analysed for oxygen isotopes (Walker and others, 2015), ammonium (Holmes et al., 1999), phosphate, nitrate, nitrite and silicate (using a SEAL AA500 segmented flow autoanalyser). These values are reported at the depth of the top of the segment in the core in μM. In order to facilitate comparison with the seawater concentrations below the ice, the in-ice nutrients (including NH4+) were salinity normalised using the equation of Fripiat and others (2017):</p> <p> </p> <p><em>C</em><em>norm</em><em> = C</em>SwS<em> </em><em> </em></p> <p> </p> <p>Where C is the measured bulk concentration, Sw is the salinity of the seawater, and S is the corresponding measured bulk salinity of the ice segment.</p> <p> </p> <p>Although sampling of the core occurred from the bottom of the core to the top of the core, the data are reported as the top of the core (snow/ice interface) being 0 m (depth=0 m). </p> <p> </p> <p><strong>This research has been funded by the National Research Foundation of South Africa (NRF)</strong></p> <p><br> </p> <p><strong>Cruise:</strong> VOY-038 (SCALE2019-WINTER) (URL: https://scale.org.za/)</p> <p><strong>Station(s):</strong> VOY-038-MIZ3A</p> <p>VOY-038-MIZ1D</p> <p><strong>Position(s):</strong> -58.13783 S; 0.00442 W</p> <p>-56.8017 S; 0.30262 E</p> <p><strong>Date/Time:</strong> 2019-07-27/10:38:00</p> <p>2019-07-28/09:15:00</p> <p><strong>Method(s):</strong> Overboard coring</p> <p>Pancake lifting via aft crane, on deck coring</p> <p><strong>Parameters:</strong><strong> </strong>Station Number (Station)</p> <p>Date/Time of station (Date/Time)</p> <p>Latitude of station (Latitude)</p> <p>Longitude of station (Longitude)</p> <p>Ice type (Ice Type)</p> <p>Core ID(Core), Pancake identifier A/B/C/D</p> <p>Oxygen isotopes (d18O)</p> <p>Chlorophyll (Chl-a)</p> <p>Ammonium (NH4)</p> <p>Nitrate + Nitrite (NO3+NO2)</p> <p>Nitrite (NO2)</p> <p>Phosphate (PO4)</p> <p>Silicate (Si)</p> <p>Nitrate (NO3)</p> <p>Salinity of the ice segment from physical cores (IceSalinity)</p> <p>Standard deviation of the salinity average from physical cores (IceSalinityStdev)</p> <p>Seawater salinity from CTD (SeawaterSalinity)</p> <p>Salinity normalised nitrate+nitrite (N03+N02_Avg_SalinityNormalised)</p> <p>Salinity normalised ammonium (NH4_SalinityNormalised)</p> <p>Salinity normalised nitrite (NO2_SalinityNormalised)</p> <p>Salinity normalised phosphate (PO4_SalinityNormalised)</p> <p>Salinity normalised silicate (Si_SalinityNormalised)</p> <p>Salinity normalised nitrate (NO3_SalinityNormalised)</p> <p><br> </p> <p> </p> <p><strong>Keywords: </strong>sea ice cores, Antarctica, pancake ice, sea ice, biogeochemistry, winter</p> <p> </p> <p><strong>References</strong><strong>:</strong></p> <p> </p> <p>Fripiat, F., Meiners, K.M., Vancoppenolle, M., Papadimitriou, S., Thomas, D.N., Ackley, S.F., Arrigo, K.R., Carnat, G., Cozzi, S., Delille, B. and Dieckmann, G.S., 2017. Macro-nutrient concentrations in Antarctic pack ice: Overall patterns and overlooked processes. Elementa: Science of the Anthropocene, 5. </p> <p> </p> <p>Holmes, R.M., Aminot, A., Kérouel, R., Hooker, B.A. and Peterson, B.J., 1999. A simple and precise method for measuring ammonium in marine and freshwater ecosystems. Canadian Journal of Fisheries and Aquatic Sciences, 56(10), pp.1801-1808. </p> <p> </p> <p>Walker, S.A., Azetsu‐Scott, K., Normandeau, C., Kelley, D.E., Friedrich, R., Newton, R., Schlosser, P., McKay, J.L., Abdi, W., Kerrigan, E. and Craig, S.E., 2016. Oxygen isotope measurements of seawater (18O/16O): A comparison of cavity ring‐down spectroscopy (CRDS) and isotope ratio mass spectrometry (IRMS). Limnology and Oceanography: Methods, 14(1), pp.31-38. </p> <p> </p> <p>Welschmeyer, N., 1994. A method for the determination of chlorophyll a in the presence of chlorophyll b and pheopigments. Limnology and Oceanography, 39, pp.1985-1992. </p> <p> </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.