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13,499 results for “researcher”
Research data from the survey on Smart Cities professional profiles for the Article "Modelling and analyzing the availability of technical professional profiles for the success of Smart Cities projects in Europe"
<p>The file includes the complete version of data collected through the surrvey on recommended profile for two professional roles in the context of Smart Cities (SC) projects: SC engineer and SC technician. It complements the previous version focused on IoT implementation stired at <a href="../doi/10.5281/zenodo.7492254">https://zenodo.org/doi/10.5281/zenodo.7492254</a></p>
Research Data/Code for "Scale-bridging within a complex model hierarchy for investigation of a metal-fueled circular energy economy by use of Bayesian model calibration with model error quantification"
<p>This repository contains research data and code for supplementing the manuscript <br>"Scale-bridging within a complex model hierarchy for investigation of a metal-fueled circular energy economy by use of Bayesian model calibration with model error quantification" <br>by L. Gossel, E. Corbean, S. Dübal, P. Brand, M. Fricke, H. Nicolai, C. Hasse, S. Hartl, S. Ulbrich, and D. Bothe. </p> <p>There is a corresponding preprint available on Arxiv: https://doi.org/10.48550/arXiv.2404.13092</p> <p><br>Users are referred to the manuscript for background information. This repository shall enable reproduction of the reported results and does not stand alone. </p> <p>Please read important information in the README in the top-level directory. </p> <p>Funded by the Hessian Ministry of Higher Education, Research, Science and the Arts - cluster project Clean Circles. </p>
Evaluating Open Science Practices in Indoor Positioning and Indoor Navigation Research (Supplementary Material: Full Paper Listing and Analysis)
<p>Supplementary material of the paper:</p> <p>Title: "Evaluating Open Science Practices in Indoor Positioning and Indoor Navigation Research"<br>Subtitle: "A Survey of the IPIN's Reference Papers of 2022 and 2023 Editions"</p> <p>The paper is accepted to the "14th International Conference on Indoor Positioning and Indoor Navigation, IPIN 2024, Hong Kong, October 14-17, 2024, IEEE, 2024.</p> <p>An Author's accepted version of the manuscript is available here: <a href="../records/13684170" target="_blank" rel="noopener">https://zenodo.org/records/13684170</a> </p> <p>If you want to refer to this work, please cite this Zenodo entry as well as the published conference version.</p> <p> </p> <p>---------------------------------------</p> <p>This entry contains two files:</p> <ul> <li>"Paper Characterization Spreadsheet.xlsx": <strong>The spreadsheet of the full analysis of this work</strong>, as described in the paper. It characterizes various features of the analyzed papers and forms the raw data on which the analyses of our work were based.</li> <li>"Main features of the manuscripts analysed in Zenodo Record #12088175.pdf": A document summarizing the main features of the IPIN's Reference Papers of the 2022 and 2023 Editions, that contain some form of open resources (Open Data, Code, or Material).</li> </ul> <p> </p> <p> </p> <p> </p>
AJL-Pestell-research/DeakinCams
<p>Code and input data associated with:</p> <p>Pestell, AJL., Rendall, AR., Sinclair, RD., Ritchie, EG., Nguyen, DT., Corva, DM., Eichholtzer, AC., Kouzani, AZ., and Driscoll, DA., (submitted). Smart camera traps and computer vision improve detections of small fauna.</p>
OpenAire Research Graph linked with OpenAlex
<p>This package contains linked datasets of OpenAire Research Graph and OpenAlex. </p> <p>Files descriptions:</p> <p>- author_to_publication_dic.json contains a mapping of authors to their publications</p> <p>- downloads_views_dic.json contains mappings of the publication id to the number of its downloads and views</p> <p>- id_doi_dic.json contains a mapping of the publication id to its doi</p> <p>- merged1..5.json contain all publication data from the OARG dataset</p> <p>- necessary_fields_dic.json contains extracted publications’ fields necessary for the work</p> <p>- oarg_ref_rel_dic.json contains mapping of publication id to referenced and related work present in OpenAlex dataset</p> <p>- openalex_found_publications5_4.json contains all data on found publications from the OpenAlex</p> <p>- publication_to_author_dic.json contains a mapping of publications to their authors</p>
Dataset supporting the paper "Bipolar single-molecule electroluminescence and electrofluorochromism. Physical Review Research 5, 033027 (2023)"
<p>Dataset corresponding to theoretical calculations in the paper "Bipolar single-molecule electroluminescence and electrofluorochromism. Physical Review Research 5, 033027 (2023)" DOI: https://doi.org/10.1103/PhysRevResearch.5.033027</p> <p>Please cite as:</p> <p>Tzu-Chao Hung, Roberto Robles, Brian Kiraly, Julian H. Strik, Bram A. Rutten, Alexander A. Khajetoorians, Nicolas Lorente and Daniel Wegner. Dataset supporting the paper "Bipolar single-molecule electroluminescence and electrofluorochromism. Physical Review Research 5, 033027 (2023)" DOI:10.5281/zenodo.13768737</p> <p>List of files:</p> <p>Several folders corresponding to the figures of the paper. They contain:</p> <p>CONTCAR files: relaxed structures in VASP format. They can be visualized with VESTA (https://jp-minerals.org/vesta/en/).</p> <p>.agr: grace files (https://plasma-gate.weizmann.ac.il/Grace/).</p> <p>Image files in png format.</p>
Navigating the complex policy landscape for carbon farming in The Netherlands and the EU -- Open Research Europe Extended Data-- Tables 1-6, Figures 1-2
<p>This is extended data for the article entitle 'Navigating the complex policy landscape for carbon farming in The Netherlands and the EU' submitted to Open Research Europe by Eise Spijker. </p>
Research data for "Intermediates of Forming Transition Metal Dichalcogenides Heterostructures Revealed by Machine Learning Simulations"
<p>This dataset supports the paper "Intermediates of Forming Transition Metal Dichalcogenides Heterostructures Revealed by Machine Learning Simulations". </p> <p><strong>Included Files:</strong></p> <ul> <li><strong>ocp_active.zip</strong>: Modified version of ocp (https://github.com/Open-Catalyst-Project/ocp) tailored for active learning applications.</li> <li><strong>deployed.pth</strong>: Pre-trained model used in the experiments.</li> <li><strong>chemiscopy_run.py</strong>: Script integrating the chemiscopy and nequip modules, designed for dataset visualization.</li> <li><strong>new_energy.py</strong>: Modified version of the nequip module, featuring a repulsive potential function.</li> <li><strong>test_datasets.extxyz</strong> & <strong>train_datasets.extxyz</strong>: The test and training datasets in extxyz format.</li> </ul> <p>How to use the modified version of the nequip module:</p> <p>To train this version of the potential function, it is recommended to use nequip<=0.5.6 (on Linux). The NequIP training files need to be updated as follows:</p> <pre><code>model_builders: - new_energy.EnergyModel - StressForceOutput min_bond_len: 1.8</code></pre> <p>Then run:</p> <p><code>export PYTHONPATH=${PYTHONPATH}:$PWD</code><br><code>nequip-train config.yml # Train the potential function</code><br><code>nequip-deploy build --train-dir nequipresultsdir build.pth # Deploy the trained model</code></p>
Simulation data for "Characteristics of Wave-Particle Power Transfer as a Function of Electron Pitch Angle in Nonlinear Frequency Chirping" which will be submitted to Journal of Geophysical Research: Space Physics
<p>Simulation data for "Characteristics of Wave-Particle Power Transfer as a Function of Electron Pitch Angle in Nonlinear Frequency Chirping" which will be submitted to Journal of Geophysical Research: Space Physics.</p> <p>Including the simulation input parameter file and the necessary output data to plot each figure in the article. </p>
OpenAIRE Graph: dataset for research community in Virtual Human Twins
<p>This dataset contains metadata records of publications, research data, software and projects relevant for the research community in Virtual Twins in health.<br>The dump contains the records available in the <a href="https://dth.openaire.eu/" target="_blank" rel="noopener">OpenAIRE Gateway on Digital Twins in Health</a> of the <a href="https://www.edith-csa.eu/" target="_blank" rel="noopener">EDITH CSA project </a>of the European Commission (grant agreement n. 101083771).</p> <p>Records are identified via full-text mining and inference techniques applied to the <a href="https://graph.openaire.eu/">OpenAIRE Graph</a>.<br>The OpenAIRE Graph is one of the largest Open Access collections of metadata records and links between publications, datasets, software, projects, funders, and organizations, aggregating thousands of scholarly data sources world-wide.</p> <p>The dump consists of a tar archive containing gzip files with one json per line.<br>Each json is compliant to the schema available at <a href="https://doi.org/10.5281/zenodo.10519297">https://doi.org/10.5281/zenodo.10519297</a>.</p>
Research data management consulting requests at Charité - Universitätsmedizin Berlin
<p><strong>The dataset documents</strong> <strong>consulting requests and corresponding consultations on topics related to research data management </strong>at the Charité - Universitätsmedizin Berlin, a university hospital and large biomedical research institution. Version v2.0 includes requests between late 2018 and October 2024.</p> <p>Please note that the documentation is not complete. Sometimes it is detailed, sometimes very brief, and rarely notes are completely absent. In many cases, I made detailed notes outside of this table, and these are not included in the dataset.</p> <p>The shared files all contain the same information or a subset of it. Different file formats have been shared to facilitate reuse and text search.</p> <p>See the readme file for detailed description of data fields and further disclaimers.</p>
Coral growth data for the research article "Reconstruction of long-term sub-lethal effects of warming on a temperate coral in a climate change hotspot" in Journal of Animal Ecology
<p>This repository contains the coral growth data files used to generate the results for the following article:</p> <p> </p> <p>MJ. Vergotti, JP. D’Olivo, T. Brachert, P. Capdevila, J. Garrabou, C. Linares, P. Spreter, DK. Kersting (2024) Reconstruction of long-term sub-lethal effects of warming on a temperate coral in a climate change hot-spot. <em>Journal of Animal Ecology</em>. https://besjournals.onlinelibrary.wiley.com/doi/10.1111/1365-2656.14225</p> <p> </p> <p><strong>Abstract: </strong>The impact of warming on zooxanthellate corals is widespread, from tropical to temperate seas, with their associated mortalities causing global concern. The temperate coral <em>Cladocora caespitosa</em> is the only zooxanthellate coral with reef-building capacity in the Mediterranean Sea, a climate change hotspot with warming rates triple the global average. Over the past two decades, <em>C. caespitosa</em> populations have suffered severe mortality events associated with marine heatwaves (MHWs). However, with monitoring efforts beginning, at best, in the 2000s, the occurrence of MHWs before to that period, as well as the sub-lethal effects of these events remain poorly understood. Here we use sclerochronology to reconstruct the histories of past stress events and long-term sub-lethal effects on <em>C. caespitosa</em> in three locations within the NW Mediterranean Sea, each with different environmental conditions. Skeletal extension, density and calcification rates were compared to the <em>in situ</em> seawater temperature of each site to assess their relationship. Additionally, we assessed the occurrence of skeletal growth anomalies to reconstruct stress events between 1991 and 2021, a period that encompasses the onset and evolution of warming-related mass mortality events in the NW Mediterranean Sea. Our results reveal a positive association between calcification and temperature, following a latitudinal temperature gradient. However, the evolution of the likelihood distribution of growth rates in the warmest site (Columbretes Islands) since the 1990s indicates a decrease in linear extension and calcification rates during the most recent years. With the increase in the frequency of MHWs and growth anomalies during the last decade, this decline suggests a recurrence in physiological stress events. These results unravel information on the long-term impacts of warming on coral growth and highlight the potential of applying sclerochronology to reconstruct sub-lethal effects of warming using <em>C. caespitosa</em>. </p> <p> </p> <p> </p> <p><strong>Funding</strong>: This research is supported by the Horizon 2020 program of research and innovation of the European Union under the MaCoBioS grant agreement, by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, project no. 401447620) and by the Spanish Ministry of Science, Innovation and Universities under the project UndResCoral (project no. PID2022-137539OA-C22). D.K.K. was supported by a Ramon y Cajal postdoctoral grant funded by the Ministry of Science and Innovation (PEICTI 2021–2023; grant no. RYC2021-033576-I). C.L. acknowledges the support by ICREA Academia. J.G. acknowledges the grant “Severo Ochoa Centre of Excellence” accreditation (CEX2019-000928-S) funded by AEI 10.13039/501100011033.</p>
Data set accompanying the research article "Complete representation of action space and value in all striatal pathways"
<p>GCaMP6s calcium imaging data set recorded from freely behaving mice performing open field and 2-choice decision-making tasks using miniscopes. Mice were implanted in the right dorsomedial striatum and three types of output neurons were genetically targeted using transgenic Cre-lines. The data set comprises single-cell spatial filters and calcium activity traces extracted using CaImAn (https://github.com/flatironinstitute/CaImAn) as well as behavioral event logs and tracking coordinates. For more details please refer to the article "Complete representation of action space and value in all striatal pathways" published by the data sets' authors. Analysis code can be found at https://doi.org/10.5281/zenodo.5034618.</p>
Doctoral Students' Educational Needs in Research Data Management: Quantitative Data of Perceived Importance and Current Competencies
<p>These data sets include numerically coded answers to Likert-like scale questions concerning the importance and perceived current research data management competencies of doctoral students. Interviewees were 35 doctoral students and faculty members. Interview forms are attached. The data is connected with the research article: https://doi.org/10.2218/ijdc.v16i1.684</p>
UAV outputs and associated field measurement of the herbaceous and tree of the Senegalese savanna of the Dahra Djoloff research center
<p>The dataset contains UAV outputs (mosaic , surface model and terrain) and the associated measurements of vegetation( herbaceous and woody) that were made within the research isra station of Dahra Djoloff.</p> <p>Sites</p> <p>The sites were 38 ha-1 plots across the research station. The UAV were collected on the same site at the same date in October 2018(end of the wet season and maximum of the biomass). The sites were the sites of previous studies (Raynal 1964, Ndiaye et al. 2014, Ndiaye et al. 2015). The plots were chosen based on several studies of vegetation dynamics and these plots were judged to be representative of the diversity of vegetation type within the research station.</p> <p>UAV flight plan</p> <p>We used a low-cost UAV with an RGB (Red Green Blue) captor integrated in the UAV. The plots were mapped using a Dji Spark UAV with the litchi application for the automatic flight. The flight plan was six 100 m transects each separated by 20 m was performed at an altitude of 80 m and at a speed of 5 m.s-1. Images were acquired in autofocus mode (ISO exposure were automatically adjusted) at two-second intervals throughout the flight. The angle of view was 80°. The frontal overlap was about 90% and the side overlap about 80% with 80° angle</p> <p>Field measurement.</p> <p>Herbaceous Biomass.</p> <p>For the Landscape dataset, 10 squares of 1 m² were sampled; All the aboveground biomass was cut and weighted in fresh. A composite sample was made for each site and weighted dry to evaluated the dry matter content and so the dry matter of each sample.</p> <p>The positions of the squared was mark r with a plastic bag on the ground.</p> <p>Tree measurement.</p> <p>For the landscape, we selected 10 trees on the UAV maps. The measurements were made after image analysis in January 2019 and January 2020. The trees were not measured on all the site.</p> <p>The measured variables were the maximum height of the tree (using a clinometer), the diameter of the tree crown in the north-south direction and in the west-east direction. Their tree crown area was calculated assuming that the crown was a circle. The trunk diameters were measured at 0.30 cm in both direction and the circumference were calculated. All woody species were identified at the species and genus levels.</p> <p>Image analysis.</p> <p>The images taken during each flight were processed using a PiX4D mapper (Pix4D SA, Lausanne, Switzerland). 3D mapping is the basic parameter proposed in the software. For each plot, an orthophotograph, a digital surface model, and a digital elevation model were computed and exported in GeoTIFF format.</p> <p>Data organization</p> <p>For each plot, we had</p> <ul> <li>DSM that contains the surface model in tiff</li> <li>DTM that contains the terrain model in tiff</li> <li>Mosaic that the orthomosaic in tiff.</li> </ul> <p>All the different geotiff can directly be download.</p> <p>Data are in a zip file that contains the shapefile with the position and table with the field measurements.</p> <p>The shapefile “Herbaceous.shp” contain the positions of the squared sample but also of squared that contains only soil (squared cut before the flight).</p> <p>The CSV “Herbaceous-landscape.csv” contains the measurement of Aboveground biomass. (FM fresh mass and DM dry mass). Both are in g (g.m-²). The biomass was available for 346 squared.</p> <p>The shapefile “tree.shp” contains the positions of the tree. Here the shapefile contains the positions of all the tree preselected on the map. Only a selection of theses tree was measured on the field.</p> <p>The file “Tree-landscape.csv” contains the tree measurements with the species, the height (in m), the trunk circumference (TC) in cm and the area of the crown(area) in m². The tree measurements were available for 240 trees.</p> <p> </p><p>reference</p> <p></p> <p>Ndiaye, O., A. T. Diop, L. E. Akpo, and M. Diène. 2014. Dynamique de la teneur en carbone et en azote des sols dans les systèmes d’exploitation du Ferlo: cas du CRZ de Dahra. Journal of Applied Biosciences <strong>83</strong>:7554-7569.</p> <p>Ndiaye, O., A. T. Diop, M. Diène, and L. E. Akpo. 2015. Étude comparée de la végétation de 1964 et 2011 en milieu pâturé: Cas du CRZ de Dahra. Journal of Applied Biosciences <strong>88</strong>:8235–8248.</p> <p>Raynal, J. 1964. Etude botanique de pâturages du Centre de Recherches Zootechniques de Dahra-Djoloff (Sénégal).</p> <p> </p>
Research data for a scoping review on circular cities
<p>This dataset includes the research data used in a scoping review of the social impacts associated with a transition to circular cities. The dataset is a supplement to the article "The lack of social impact considerations in transitioning towards urban circular economies: a scoping review", which was published in the Sustainable Cities and Society journal (<a href="https://doi.org/10.1016/j.scs.2021.103394">https://doi.org/10.1016/j.scs.2021.103394</a>).</p>
DOI's with SDG labels on Target level | 1.4M research articles (2009-2020) related to Sustainable Development Goals
<p>Table content: This data set contains 1.4 million publication DOI's related to the <a href="http://metadata.un.org/sdg/">Targets of the Sustainable Development Goals</a> in the period 2009 - 2020.</p> <p>Table dimensions: rows: 1.4 million, columns: 4 / rows: 1.4 million, columns: 180</p> <p>Table columns: <a href="https://en.wikipedia.org/wiki/Digital_object_identifier">doi</a> | date | <a href="http://metadata.un.org/sdg/ontology#Target">sdg_target</a> | <a href="http://metadata.un.org/sdg/ontology#Goal">sdg_goal</a> / <a href="https://en.wikipedia.org/wiki/Digital_object_identifier">doi</a> | date | <a href="http://metadata.un.org/sdg/ontology#Target">169 sdg_targets</a> | <a href="http://metadata.un.org/sdg/ontology#Goal">17 sdg_goalsl</a></p> <p>Table formats: <a href="https://en.wikipedia.org/wiki/Comma-separated_values">.csv</a> | <a href="https://en.wikipedia.org/wiki/Microsoft_Excel">.xlsx</a> | <a href="https://en.wikipedia.org/wiki/Apache_Parquet">.parquet</a></p> <p><em>How we made this data:</em></p> <p>We have made a search on <a href="https://scopus.com">Scopus </a>using the <a href="https://aurora-network-global.github.io/sdg-queries/">Aurora SDG queries version 5</a> for each of the targets, with a limited year range from 2009 till 2020.</p> <p>Good to know: don't be alarmed if you can find a doi that is labeled with more than one target (~16%). This is not a bug, this is a feature... We used 169 queries, one for each target, a publication can appear in more han one result set.</p> <p>Read this <a href="https://zenodo.org/record/4964606/files/Evaluation_on_accuracy_of_mapping_science_to_the_United_Nations__Sustainable_Development_Goals__SDGs__of_the_Aurora_SDG_queries.pdf?download=1">report to learn more about the accuracy</a> of the queries and the data result sets.</p> <p><em>How can you use this data:</em></p> <p>You can use this data to 1. quickly match your existing publication lists to this list to see how that your publications are related to the targets of the SDG's. 2. use these as a basis / seed set / gold set to train more advanced text / graph classifiers (after you have extracted title, abstract or even full-text using crossref.org, unpaywall.org, etc)</p> <p><em>How can you help:</em></p> <p><a href="https://sites.google.com/vu.nl/aurora-sdg-research-dashboard/sdg-knowledge-base#h.d2pd3c39k276">Let us know</a> how you use this data. We'll put your project on the list in our <a href="https://sites.google.com/vu.nl/aurora-sdg-research-dashboard/sdg-knowledge-base">SDG matching knowledge base.</a></p>
Desk research of 107 case studies on state-of-the-art of cultural tourism interventions
<p>The aim of Work Package 3 of the SmartCulTour project (<a href="http://www.smartcultour.eu">www.smartcultour.eu</a>) is to provide a state-of-the-art overview of cultural tourism interventions implemented in European cities and regions, thereby identifying best practices and the impacts and success conditions of cultural tourism interventions. To this end, the consortium identified 107 interesting cultural tourism interventions throughout Europe, with a <strong>geographical coverage</strong> of: Belgium (9), Italy (8), The Netherlands (8), Serbia (7), Romania (6), Croatia (5), Hungary (4), Portugal (4), Spain (4), United Kingdom (4), Finland (3), France (3), Sweden (3), Other countries (24), Multiple countries (15). The "Overview and taxonomy of 107 interventions" lists every intervention that was studied, as well as their respective classification given, based on the description and objective of the intervention. Within this table, a value of "1" is its primary categorization, with a value of "2" assigned to a secondary taxonomy. Each intervention can have multiple purposes and therefore belong to different categories.The taxonomy of cultural tourism interventions is further described in "State of the art of cultural tourism interventions" (DOI: 10.5281/zenodo.5270321).</p> <p>The 107 cultural tourism interventions were analyzed via desk research only during the period September 2020-January 2021, based on available secondary data and following a standardized <strong>data collection form</strong>. This form is included here as "Internal data collection form used for analysis". The forms collect data on:</p> <ul> <li>Context and background information;</li> <li>The 'reason why' of the intervention;</li> <li>The intervention;</li> <li>Resources and tools necessary to design and implement the interventions;</li> <li>Impacts (expected, perceived and measured);</li> <li>(Perceived) success conditions and limiting factors.</li> </ul> <p>The zip-file "Internal forms of 107 interventions" contains all 107 completed data collection forms.</p> <p> </p>
Research Data Identification - RDAlliance
<p>A diagram that aims to align with an elaboration of the Research Data Alliance Dynamic Data Citation Working Group recommendations, as documented in:</p> <p>Andreas Rauber, Ari Asmi, Dieter van Uytvanck, and Stefan Pröll. (2016). Identification of reproducible subsets for data citation, sharing and re-use. https://www.force11.org/sites/default/files/d7/project/81/ieee-tcdl-dc-2016_paper_1.pdf</p> <p>(Which later lead to: Rauber, Andreas, Asmi, Ari, van Uytvanck, Dieter, & Proell, Stefan. (2015). Data Citation of Evolving Data: Recommendations of the Working Group on Data Citation (WGDC). https://doi.org/10.15497/RDA00016)</p>
COVRIN D0.3.1: Database of COVID-19 research activities
<p>OHEJP project: COVRIN "One Health research integration on SARS-CoV-2 emergence, risk assessment and preparedness".</p> <p>Since the start of the pandemic in early 2020, a huge number of research projects have been initiated on SARS-CoV-2/COVID-19; additionally, many pre-existing networks and infrastructures have turned their attention to the virus, setting up SARS-CoV-2-specific services. To avoid overlaps and ensure optimal use of resources, a scoping review was performed of European Union-supported SARS-CoV-2 research activities that overlap with COVRIN in terms of focus.</p> <p>This database is associated with OHEJP Deliverable report "D0.3.1: Scoping review of European Union-supported COVID-19 research activities" available at https://doi.org/10.5281/zenodo.5537781</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.