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The International Soundscape Database: An integrated multimedia database of urban soundscape surveys -- questionnaires with acoustical and contextual information
<h1>Introduction</h1> <p>The International Soundscape Database contains the results of a series of soundscape assessment campaigns carried out across Europe and China. The data collection process was conducted according to the <a href="https://www.mdpi.com/2076-3417/10/7/2397">SSID Protocol [1]</a> which integrates in situ questionnaires about users' soundscape experience, with binaural recordings, sound level meter readings, and 360 degree video. The core of this database are individual soundscape questionnaires collected for 3,500+ participants completed in situ in cities across Europe and China, and the psychoacoustic analysis of 30s binaural recordings which can be matched up to each questionnaire.</p> <p>The SSID Protocol was based on the ISO 12913 standard for soundscape data collection [2]. For more information on the specifics of how this data is collected, please see [1].</p> <p>It is the intention that this dataset be added to and augmented with new locations, cities, and contexts in the future. This will be done both by the SSID team at University College London, but we also strongly welcome contributions from other researchers and practicioners. If a soundscape assessment is collected according to the SSID Protocol, it can be integrated with the rest of the database to form a large, cohesive, and ever-growing database of soundscape assessments. </p> <h2>Analysis</h2> <p>Code for exploring and analysing this dataset is included as part of the <a href="https://soundscapy.readthedocs.io/en/latest/">Soundscapy package</a>.</p> <h2>Included Files</h2> <p>This dataset incorporates surveys taken in multiple urban public spaces across several cities in Europe and China. These urban spaces include places like parks, urban squares, green spaces, and market streets. At each location, up to 100 questionnaires were collected over a series of multi-hour long sessions. Therefore the data is organised by LocationID, then SessionID, then GroupID.</p> <p>The basic directory structure and contents can be found below. </p> <h3>Survey Data (.csv)</h3> <p>'ISD v1.0 Data.csv' organises the data according to the labels given above.</p> <h3>Survey Metadata (.xlsx)</h3> <p>In addition a metadata file ('ISD v1.0 Metadata.xlsx') with photos and descriptions of each of the locations is provided. This metadata file also includes Data Dictionaries for each of the survey instrument versions included. These data dictionaries document precisely the questions asked and the available reponse labels and coding, along with the relevant translations.</p> <h3>Psychoacoustic Analysis (.csv)</h3> <p>The compiled csv file is formatted with a row for each individual participant's questionnaire response, then includes the psychoacoustic analysis of the 30s binaural recording taken while the participant was completing the questionnaire. Details about the psychoacoustic analyses is given in the 'Acoustic Settings' tab in the metadata file.</p> <p>The compiled survey and psychoacoustic analysis data is contained in 'ISD v1.0 Data.csv'. This is compiled from raw survey data files contained in 'Survey_Data', with individual cleaned survey and psychoacoustic data files included in 'Survey_Data/Interim_<date>'. The scripts for compiling this data are included in 'Scripts/'.</p> <h3>Sound Level Meter logs (.xlsx)</h3> <p>'SLM_<city>/' folders include session-long (i.e. ~3hrs) sound level meter log data in.xlsx files for each SessionID.</p> <h3>Binaural Recordings (32-bit floating point .wav)</h3> <p>'WAV_<city>/' folders include the ~30s binaural recordings in 32 bit floating point .wav format. Within each city folder are a set of LocationID folders containing their associated recordings. The wav files are titled with its GroupID, which is matched to the corresponding survey GroupIDs. </p> <h3>Cleaning and Compilation Scripts (.py)</h3> <p>Python code for cleaning and compiling the data from the raw survey data (within Survey_Data/source_data) are provided. These can be run within the provided demo notebook, or from the terminal by calling 'python -m ISDv1_main' with the relevant arguments. See the README.md file in this directory for more information.</p> <pre><code><br>├── ISD v1.0 Data.csv ├── ISD v1.0 Metadata.xlsx ├── SLM_Granada │ ├── CampoPrincipe1_SLM.xlsx │ ├── ... ├── SLM_Groningen │ └── Noorderplantsoen1_SLM.xlsx ├── SLM_etc ├── Scripts │ ├── ISDcleanDemo.ipynb │ ├── ISDcleaning.py │ ├── ISDpsycho.py │ ├── ISDv1_main.py │ ├── README.md │ └── pyproject.toml ├── Survey_Data │ ├── Interim_2024-02-08_cleaned │ └── source_data ├── WAV_Granada_1 │ ├── CampoPrincipe │ ├── ... ├── WAV_etc</code></pre> <p><strong>Citation</strong>: If you use the ISD or part of it, please cite our paper describing the data collection protocol [1] and this dataset itself.</p> <p><strong>License and reuse</strong>: All ISD recordings are provided under the Creative Commons Attribution 4.0 International (CC BY 4.0) License and are free to use. We encourage other researchers to replicate the SSID protocol and contribute new locations to the dataset. We also encourage the use of these recordings and the perceptual data for further soundscape research purposes. Please provide the proper attribution and get in touch with the authors if you would like to contribute new data or for any other collaborations.</p> <p> </p> <p>[1] Mitchell A, Oberman T, Aletta F, Erfanian M, Kachlicka M, Lionello M, Kang J. The Soundscape Indices (SSID) Protocol: A Method for Urban Soundscape Surveys—Questionnaires with Acoustical and Contextual Information. <em>Applied Sciences</em>. 2020; 10(7):2397. <a href="https://www.mdpi.com/2076-3417/10/7/2397">https://doi.org/10.3390/app10072397 </a></p> <p>[2] ISO/TS 12913-2:2018 (2018). “Acoustics – Soundscape – Part 2: Data collection and reporting requirements” International Organization for Standardization, Geneva, Switzerland, 2018</p> <p>[3] Mitchell A, Oberman T, Aletta F, Kachlicka M, Lionello M, Erfanian M, Kang J. Investigating Urban Soundscapes of the COVID-19 Lockdown: A predictive soundscape modeling approach.<em> Journal of the Acoustical Society of America</em>. 2021.</p>
Research in Svalbard international projects edgelist
<p>This dataset lists all the country to country ties derived from the <a href="https://www.researchinsvalbard.no/">Research in Svalbard</a> (RIS) database using the country of origin of the organisations with joint research projects in Svalbard and the projects year. This edgelist is broken down into two time periods: 1972-2004 ; 2005-2022. Per each pair of countries, it gives the number of joint research projects registered in the RIS database per period of time. It can be used for network analysis purposes. It has been created and analysed using a core-periphery approach within the publication: Strouk, M. & Maisonobe, M. (2024). "Field science and scientific collaboration in the Svalbard Archipelago: beyond science diplomacy<em>". Science and Public Policy.</em> DOI: <a href="https://doi.org/10.1093/scipol/scae012">https://doi.org/10.1093/scipol/scae012/</a></p>
Dataset of "A Monte Carlo Approach for Simulating Electrical Conductivity in Highly Porous Ceramic Composites: Impact of Internal Structure"
<p>3D structure of lanthanum strontium manganite and yttria-stabilized zirconia composites is predicted based on conductivity measurements using Monte Carlo 3D equivalent circuit network approach. Validation experimental impedance spectra; scanning electron micrographs; cross sections of model simulation or prediction (MSP).</p>
Meta-analysis and gender classification of 914 national and international surveys in six European countries (2000-2023)
<p><span>This data frame presents the results of a quan</span><span>ti</span><span>ta</span><span>ti</span><span>ve content analysis of the occurrence of gender‐based concepts, themes, issues, and solu</span><span>ti</span><span>ons within large‐scale poli</span><span>ti</span><span>cal and sociological survey ques</span><span>ti</span><span>onnaires fielded cross‐na</span><span>ti</span><span>onally in Europe and in six European countries: Denmark, Germany, Hungary, Switzerland and the UK, spanning 2000‐2023. Data was collected by teams from each country between September 2023‐January 2024. Teams collected ques</span><span>ti</span><span>ons in the original language and provided a transla</span><span>ti</span><span>on into English. Analysis was conducted using the translated text. The unit of analysis (‘CODING_UNIT_TEXT’) was the individual 'gender‐related argument' within a survey ques</span><span>ti</span><span>on. This could be the en</span><span>ti</span><span>re survey ques</span><span>ti</span><span>on, a sub‐ques</span><span>ti</span><span>on (in the case of matrix ques</span><span>ti</span><span>ons), or a singular response op</span><span>ti</span><span>on (for mul</span><span>ti</span><span>ple choice ques</span><span>ti</span><span>ons). Coding units were coded in three key domains:(1) Gender concepts, (2) Themes/issues, and (3) Solu</span><span>ti</span><span>ons. Up to two Themes/Issues and Solu</span><span>ti</span><span>ons could be coded per coding unit. Several coding categories within the Themes/Issues and Solu</span><span>ti</span><span>ons domains func</span><span>ti</span><span>on hierarchically, where a coder first assigned a higher‐level category and then as many subcategories as applicable. For example, a ques</span><span>ti</span><span>on concerning government‐funded childcare is coded as B1_Economy ‐> B1_4_LabourMarket ‐> B1_4_1_CareWork ‐> B1_4_1_3_Childcare. The corresponding codebook presents the uni</span><span>ti</span><span>sa</span><span>ti</span><span>on process and coding categories in full detail.</span></p>
International Non-native Insect Establishment Data
<p><span>These data list individual non-native insect species established in nine regions around the globe (New Zealand, South Korea, Japan, Okinawa, Ogasawara, Europe, Great Britain, North America (north of Mexico), Hawaii, Galapagos, Chile and South Africa). Taxonomy, attributes and occurrences for each taxa are included, as well as a source table which can be used to find more details on occurrences. </span></p> <p><span>This dataset was assembled from various sources by an interdisciplinary scientific working group funded by the National Socio-Environmental Synthesis Center. See the main source references in the References metadata section for this publication.</span></p> <p><span>Data have been cleaned of most typographic and taxonomic errors using the code in the R package insectcleanr: Initial release (DOI: 10.5281/zenodo.4555787), which is based on the Global Biodiversity Information Facility (GBIF) taxonomic backbone (GBIF Secretariat (2021). GBIF Backbone Taxonomy. Checklist dataset https://doi.org/10.15468/39omei accessed via GBIF.org on 2022-02-09, i.e. the </span><a href="https://doi.org/10.15468/43g7-9874"><span>https://doi.org/10.15468/43g7-9874</span></a><span> backbone).</span></p> <p><em>DISCLAIMER: This dataset is provisional. Although these data have been subjected to review and the dataset is substantially complete, the authors reserve the right to revise the data pursuant to further analysis and review. There may be remaining errors, and additions and removals of data in future updates may occur. Neither the University of Maryland, U.S. Government, Scion, nor any of their employees, contractors, or subcontractors, make any warranty, express or implied, nor assume any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, nor represent that its use would not infringe on privately owned rights.</em></p>
International Soil Carbon Network version 3 Database (ISCN3)
The ISCN is an international scientific community devoted to the advancement of soil carbon research. The ISCN manages an open-access, community-driven soil carbon database. This is version 3-1 of the ISCN Database, released in December 2015. It gathers 38 separate data set contributions, totaling 67,112 sites with data from 71,198 soil profiles and 431,324 soil layers. For more information about the ISCN, its scientific community and resources, data policies and partner networks visit: http://iscn.fluxdata.org/. For information about processes used to construct the DB: https://iscn.fluxdata.org/data/data-information/.
Light-saturated photosynthetic rate, dark respiration, stomatal conductance and ratio of internal to external carbon dioxide concentration from the 1980-82 Eriophorum vaginatum reciprocal transplant plots from Eagle Creek to Prudhoe Bay, Alaska, 2010
In 1980-1982, six transplant gardens were established along a latitudinal gradient in interior Alaska from Eagle Creek, AK, in the south to Prudhoe Bay, AK, in the north (Shaver et al. 1986) .Three sites, Toolik Lake (TL), Sagwon (SAG), and Prudhoe Bay (PB) are north of the continental divide and the remaining three, Eagle Creek (EC), No Name Creek (NN), and Coldfoot (CF), are south of the continental divide. Each garden consisted of 10 individual tussocks transplanted back to their home-site, as well as 10 individuals from each of the other transplant sites. Data were collected in July 2010 for tussocks transplanted in 1980-82 in a reciprocal transplant experiment and then harvested in 2011. Important variables are garden name, source population, light-saturated photosynthetic rate, dark respiration, stomatal conductance and ratio of internal to external carbon dioxide concentration.
Rainfall Stable Isotopes collected at Florida International University-MMC (FCE LTER), Miami, Florida, USA, October 2007 - ongoing
δ18O and δ2H values for precipitation collected at the Modesto A. Maidique Campus of Florida International University (FIU) relative to Vienna Standard Mean Ocean Water. Rainfall was collected from the roof of AHC-1 building (25.75772 ºN, 80.37108 ºW) from October 2007 to November 2022 using an Aerochemitrics wet/dry collector. Since December 2022, rainfall has been collected using a Palmex Rain Collector located in the FIU Organic Garden (25.75490 ºN, 80.37985 ºW). Oxygen and hydrogen isotope ratios were measured on a Los Gatos Research DLT-100 Liquid-Water Isotope Analyzer in the Hydrogeology laboratory at FIU since the project inception.
Topics in Research on International Relations as Clusters of Citation Links
<p>Data, scripts, and results of a memetic topic clustering of citation links in papers published 2011-2015 in the specialty of political science that is dealing with international relations </p> <p>Supplementary Information to the paper about "Topics as clusters of citation links to highly cited sources: The case of research on international relation" by Frank Havemann<em> </em>(published 2021 in the OA-journal<em> Quantitative Science Studies</em> 2 (1): 204–223). <a href="https://doi.org/10.1162/qss_a_00108">https://doi.org/10.1162/qss_a_00108</a></p>
Public Available Data Set of Process Flows from Internal Physical Inspections in the Failure Analysis Laboratory
<p>This data set was generated in accordance with the semiconductor industry and contains data of certain process flows in Failure Analysis (FA) laboratories focusing on the identification and analysis of anomalies or malfunctions in semiconductor devices. It comprises logistic data about the processing steps for the so-called Internal Physical Inspection (IPI).</p><p>A so-called IPI job is given as a sequence of tasks that must be performed to complete the job they belong to. It has an assigned unique ID and timestamps indicating the submission, the end, and the deadline to be met. A job also has an IPI classification assigned to it, providing general guidelines on the operations to be performed.</p><p>Every task within a job has its own type and working time, as well as the assigned resources. There are two main resources involved:</p><p> - the equipment; the machine used to perform the task,</p><p> - the operator; the person who performed the task.</p><p>In addition, general information about the type of the device to be analyzed is also available, such as the given (anonymized) package and basictype. Data also include the number of stressed samples within a device and the samples a task is performed on.</p><p>The dataset includes data from 4 years, specifically from January 2020 to December 2022.</p><p>Finally, the exact column structure is given as follows (python 3.9.5 datatype):</p><ul><li>JOB_ID [int64]: the unique ID of the job</li><li>JOB_SUBMISSION_DATE [object]: the date of the job submission</li><li>JOB_REQ_END_DATE [object]: the required end date (deadline)</li><li>JOB_FINISH_DATE [object]: the actual end date</li><li>JOB_BASICTYPE_H [object]: the given basictype denotation</li><li>JOB_PACKAGE_H [object]: the package denotation of the device</li><li>JSH_QTY_STRESSED [float64]: number of stressed samples</li><li>TASK_SUBMISSION_DATE [object]: the date of the task submission</li><li>TASK_WORKING_TIME [float64]: the amount of time (hours) the task needs to be completed</li><li>TASK_SAMPLE_NO [object]: the samples the task was performed on </li><li>TASK_CEQ_ID [float64]: the ID of the machine used to perform the task</li><li>TASK_CTKS_ID [int64]: the ID representing the task type</li><li>TASK_USR_ID [int64]: the ID of the operator performing the task</li><li>CIPI_LEVEL_0 [object]: a series of IPI classifications, indicating what is required to execute for a specific job</li></ul>
Observations of the Bottom Boundary Layer beneath the World's Largest Internal Solitary Waves_for JGR submission
<p>This folder contains preprocessed data, data processing scripts, Reynolds Averaged Navier Stokes (RANS) simulation scripts, and plotting scripts that produce the results in the manuscript entitled, "Observations of the Bottom Boundary Layer beneath the World's Largest Internal Solitary Waves," for submission to Journal of Geophysical Research Oceans by Trowbridge, Helfrich, Reeder, Medley, Chang, Jan, Ramp, and Yang.</p> <p> </p>
Bicycle Mobility Data: Current Use and Future Potential. An International Survey of Domain Professionals
<p>Active mobility, especially cycling, is an essential building block for sustainable urban mobility. Public and private stakeholders are striving to improve conditions for cycling and subsequently increase its modal share. Data are regarded as key for different measures to become efficient and targeted. There is extensive evidence for an increasing amount of mobility data, availability of new data sources and potential usage scenarios for such data. However, little is known about the current use of these data in policy making, planning and related fields. To the best of our knowledge, it has not been investigated yet to which degree professionals in the broader field of cycling promotion benefit from an increasing amount of cycling-related data. Thus, we conducted a multi-lingual online survey among domain professionals and acquired data on their perspectives on current data availability, use and suitability as well as the potential they see for the use of cycling data in the future. In total, we received 325 complete responses from 32 countries, with the vast majority of 241 valid responses originating from Germany, Austria and Italy. Key findings are: 84% of domain professionals attribute high importance to data, and 89% state that they currently cannot or only partly solve their tasks with the data available to them. Results emphasize the need for making more and better suited data available to professionals in cycling-related positions, in both the private and public sector.</p> <p>Read the full publication: <a href="https://doi.org/10.3390/data6110121">https://doi.org/10.3390/data6110121 </a></p>
DATA SET: Performance Assessment of a Commercial Continuous-Wave Near-Infrared Spectroscopy Tissue Oximeter for Suitability for Use in an International, Multi-Center Clinical Trial
<p>This repository contains the data sets related to the publication:</p> <p>Cortese, L.; Zanoletti, M.; Karadeniz, U.; Pagliazzi, M.; Yaqub, M.A.; Busch, D.R.; Mesquida, J.; Durduran, T. Performance Assessment of a Commercial Continuous-Wave Near-Infrared Spectroscopy Tissue Oximeter for Suitability for Use in an International, Multi-Center Clinical Trial. <em>Sensors</em> <strong>2021</strong>, <em>21</em>, 6957. https://doi.org/10.3390/s21216957</p>
Dataset to "Hygrothermal performance of an internally insulated masonry wall: experimentations without vapour barrier in a historic Italian Palazzo"
<p>This record contains pre-processed data of a ten-and-a-half-month monitoring period of the HeLLo project.</p> <p>The datafiles titled MeasProcessed_YYYY-MM-DD.dat correspond to the prepared data into a form for data analysis and processing as presented in “Hygrothermal performance of an internally insulated masonry wall: experimentations without vapour barrier in a historic Italian Palazzo”, accepted for publication in journal energy and buildings (<a href="https://doi.org/10.1016/j.enbuild.2022.111896">https://doi.org/10.1016/j.enbuild.2022.111896</a>).</p> <p>Each file, format MeasProcessed _YYYY-MM-DD.dat, corresponds to the daily registered data monitored every minute.</p> <p>Each file, format MeasProcessed_YYYY-MM-DD.dat, contains temperature (T) and relative humidity (RH) values, monitored through T-RH sensors (Telaire T9602; Amphenol). The general architecture of the acquisition system is based on a Master Slave configuration, as described in “Development of a Compatible, Low Cost and High Accurate Conservation Remote Sensing Technology for the Hygrothermal Assessment of Historic Walls” (doi:10.3390/electronics8060643).</p> <p>Each file, format MeasProcessed_YYYY-MM-DD.dat is a text-based DAT file and can be opened with a standard text editor.</p>
The 2001 Hawaiian Ocean Mixing Experiment (HOME): Internal-tide Mode-1 Amplitude Data from the Southern Tomographic Array
<p>Ocean acoustic tomography was used to measure tides in the farfield of the Hawaiian Ridge in 2001 during the Hawaiian Ocean Mixing Experiment (HOME). The measurements were components of a suite of large- and small-scale measurements obtained during HOME with the aim of illuminating the pathways of tidal energy that may be driving deep-ocean mixing. Using reciprocal transmissions, the tomographic arrays were designed to measure the radiation of mode-1 internal tides from the Ridge, together with barotropic tidal currents. This publication makes available the tomographic estimates for mode-1 internal-waves derived<br>from the six paths of the southern HOME tomography array.</p>
The 2001 Hawaiian Ocean Mixing Experiment (HOME): Internal-tide Mode-1 Amplitude Data from the Northern Tomographic Array
<p>Ocean acoustic tomography was used to measure tides in the farfield of the Hawaiian Ridge in 2001 during the Hawaiian Ocean Mixing Experiment (HOME). The measurements were components of a suite of large- and small-scale measurements obtained during HOME with the aim of illuminating the pathways of tidal energy that may be driving deep-ocean mixing. Using reciprocal transmissions, the tomographic arrays were designed to measure the radiation of mode-1 internal tides from the Ridge, together with barotropic tidal currents. This publication makes available the tomographic estimates for mode-1 internal-waves derived<br>from the six paths of the northern HOME tomography array.</p>
International and EU funding in the eastern neighbourhood (2005-2022). REDEMOS Dataset 3.2
<p>International, EU and EU Member States’ funding for democracy, human rights, gender equality, the rule of law and good governance in the Eastern Neighbourhood, between 2005 and 2022.</p>
International Soil Radiocarbon Database v1.0
<p>Synthesized soils data associated with v1.0 of the International Soil Radiocarbon Database. Detailed information about this dataset can be found at <a href="http://soilradiocarbon.org">soilradiocarbon.org</a>.</p>
Global Ionosphere Maps of vertical electron content combined in real-time from the RT-GIMs of CAS, CNES, UPC-IonSAT, and WHU International GNSS Service (IGS) centers (from Dec 1, 2020, to March 1, 2021)
<p>The datasets consists on 91 daily files, in IONEX format (<a href="http://ftp.aiub.unibe.ch/ionex/draft/ionex11.pdf">http://ftp.aiub.unibe.ch/ionex/draft/ionex11.pdf</a>) , corresponding to three months of global ionospheric maps (GIM) of vertical total electron content (VTEC) computed in real-time from the assessed and combined real-time GIMs generated by four analysis centers. Indeed, the Real-Time Working Group (RTWG) of International GNSS Service (IGS) is dedicated to providing high-quality data, high-accuracy products for Global Navigation Satellite System (GNSS) navigation, positioning, timing, and Earth observations. As one of the important part of real-time products, the IGS combined Real-Time Global Ionosphere Map (RT-GIM) have been generated by real-time weighting technique with the help of RT-GIMs from IGS real-time ionosphere centers including the Chinese Academy of Sciences (CAS), Centre National d’Etudes Spatiales (CNES), Universitat Politècnica de Catalunya (UPC), and Wuhan University (WHU). Compared with IGS rapid Global Ionosphere Maps (GIMs) (corg, ehrg, emrg, esrg, igrg, jprg, uhrg, uprg, uqrg, whrg) and IGS final combined GIM (igsg), the IGS combined RT-GIM (irtg) is equivalent to the post-processed GIMs and even better than some rapid GIMs. The IGS RT-GIMs are reliable sources of real-time global VTEC information and has great potential for real-time applications including range error correction for transionospheric radio signals (such as GNSS positioning, search and rescue, air traffic, radar altimetry, and radioastronomy), the monitoring of space weather (such as geomagnetic and ionospheric storms, ionospheric disturbance) and detection of natural hazards on a global scale (such as hurricanes/typhoons, ionospheric anomalies associated with earthquakes)</p>
International benchmark for ALS individual tree segmentation
<p>This upload aims to provide an international benchmark dataset for airborne LiDAR-based individual tree segmentation algorithm comparison and development.</p> <p> </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.