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1,130 results for “Egypt”
Dataset: The Role of News Consumption on Influencers' Facebook Pages in Threat Perception and Political Conservatism During Times of COVID-19: A Comparative Study between the USA, Spain, and Egypt
<p>Este archivo ofrece los datos en bruto de una encuesta examina el impacto del consumo de noticias en las páginas de Facebook de los influencers en la motivación del conservadurismo político durante amenazas como el terrorismo o las pandemias. Muestra: N=1309, jóvenes de entre 18 y 35 años en Estados Unidos, España y Egipto. Trabajo de campo realizado entre el 10 de agosto de 2021 y el 5 de septiembre de 2021.</p> <p><span>Dataset correspondiente al proyecto El rol de la ciudadanía en la comunicación política digital CI-COMPOL (PID2020-119492GB-I00) financiado por MCIN/AEI/10.13039/501100011033/. IP: Andreu Casero-Ripollés, Departamento de Ciencias de la Comunicación, Universitat Jaume I de Castellón</span></p>
Coptic Monastic Heritage Archive (CMHA): Photographic Dataset of Monastic Settlement in Wadi Naqqat, Egypt
<p>This dataset was created as part of the Coptic Monastic Heritage Archive (CMHA) at the University of Ljubljana. It includes data and photographs of 14 monastic heritage sites in Wadi Naqqat (Eastern Desert, Egypt). Wadi Naqqat is located approximately 35 miles (55 km) west of the Red Sea town of Hurghada, in the broader region of ancient Mons Porphyrites, and dates to between the 4th and 6th centuries AD.</p> <p>The data was gathered through ground assessments conducted between 2018 and 2019 as part of the project “Endangered Hermitages: Documenting Coptic Monastic Heritage in Middle Egypt and the Eastern Desert”, led by Dr. Jan Ciglenečki (University of Ljubljana) and funded by the Antiquities Endowment Fund (AEF) of the American Research Center in Egypt (ARCE). Photographic documentation of the site was carried out by photographer Matjaž Kačičnik, using a 36-megapixel Nikon D810 digital camera, and by Dr. Jan Ciglenečki, using a 21-megapixel Canon EOS 5D Mark II digital camera. In 2024, this documentation was systematically integrated into the CMHA at the University of Ljubljana.</p> <p><span>The photographs include EXIF (GPS location, technical specs) and IPTC-IIM (e.g., Credits, Caption) and XMP metadata.</span></p>
Photographs of the article and additional photographs (Cairo, Egypt).
<p>Four photographs published in the paper :</p> <p>Vincent Battesti & Nicolas Puig, 2020 — « Towards a sonic ecology of urban life: Ethnography of sound perceptions in Cairo ». <em>The Senses & Society</em>, 15 (2), p. 170-191, doi: 10.1080/17458927.2020.1763606 — online: https://hal.archives-ouvertes.fr/hal-02890453</p> <p>… and extra pictures of Cairo (Egypt).</p>
Hassan #1 binaural recording in Darb al-Ahmar, Cairo (Egypt), 25-10-2011
<p>« Mics in the Ears » binaural experiment in Cairo (Egypt): Vincent Battesti & Nicolas Puig, social anthropologists, asked inhabitants of Cairo megapolis in Egypt to record the surrounding urban sounds during one of their daily journeys (without the researcher), equipped with binaural microphones and GPS device. Participants have recorded in different Cairo neighbourhoods, and are themselves from different generations, social and economic backgrounds, and different genders.</p> <p>The two sound files are one the raw sound recorded by one of them during this walk in a neighbourhood in Cairo (see name of the inhabitant and date and place of recording in the file name), and the other the description and comments he or she gave us a posteriori when listening to this previous raw sound he or she recorded. See <a href="https://vbat.org/article831">https://vbat.org/article831</a></p>
Hassan #2 Route binaural recording in Duwiqa, Cairo (Egypt), 28-09-2012
<p>« Mics in the Ears » binaural experiment in Cairo (Egypt): Vincent Battesti & Nicolas Puig, social anthropologists, asked inhabitants of Cairo megapolis in Egypt to record the surrounding urban sounds during one of their daily journeys (without the researcher), equipped with binaural microphones and GPS device. Participants have recorded in different Cairo neighbourhoods, and are themselves from different generations, social and economic backgrounds, and different genders.</p> <p>The two sound files are one the raw sound recorded by one of them during this walk in a neighbourhood in Cairo (see name of the inhabitant and date and place of recording in the file name), and the other the description and comments he or she gave us a posteriori when listening to this previous raw sound he or she recorded. See <a href="https://vbat.org/article831">https://vbat.org/article831</a></p>
Salma binaural recording, Wast al-Balad, Cairo (Egypt), 26-09-2012
<p>« Mics in the Ears » binaural experiment in Cairo (Egypt): Vincent Battesti & Nicolas Puig, social anthropologists, asked inhabitants of Cairo megapolis in Egypt to record the surrounding urban sounds during one of their daily journeys (without the researcher), equipped with binaural microphones and GPS device. Participants have recorded in different Cairo neighbourhoods, and are themselves from different generations, social and economic backgrounds, and different genders.</p> <p>The two sound files are one the raw sound recorded by one of them during this walk in a neighbourhood in Cairo (see name of the inhabitant and date and place of recording in the file name), and the other the description and comments he or she gave us a posteriori when listening to this previous raw sound he or she recorded. See <a href="https://vbat.org/article831">https://vbat.org/article831</a></p>
Samir binaural recording in Bashtil, Cairo (Egypt), 28-09-2012
<p>« Mics in the Ears » binaural experiment in Cairo (Egypt): Vincent Battesti & Nicolas Puig, social anthropologists, asked inhabitants of Cairo megapolis in Egypt to record the surrounding urban sounds during one of their daily journeys (without the researcher), equipped with binaural microphones and GPS device. Participants have recorded in different Cairo neighbourhoods, and are themselves from different generations, social and economic backgrounds, and different genders.</p> <p>The two sound files are one the raw sound recorded by one of them during this walk in a neighbourhood in Cairo (see name of the inhabitant and date and place of recording in the file name), and the other the description and comments he or she gave us a posteriori when listening to this previous raw sound he or she recorded. See <a href="https://vbat.org/article831">https://vbat.org/article831</a></p>
Shady binaural recording in Wast al-Balad, Cairo (Egypt), 26-09-2012
<p>« Mics in the Ears » binaural experiment in Cairo (Egypt): Vincent Battesti & Nicolas Puig, social anthropologists, asked inhabitants of Cairo megapolis in Egypt to record the surrounding urban sounds during one of their daily journeys (without the researcher), equipped with binaural microphones and GPS device. Participants have recorded in different Cairo neighbourhoods, and are themselves from different generations, social and economic backgrounds, and different genders.</p> <p>The two sound files are one the raw sound recorded by one of them during this walk in a neighbourhood in Cairo (see name of the inhabitant and date and place of recording in the file name), and the other the description and comments he or she gave us a posteriori when listening to this previous raw sound he or she recorded. See <a href="https://vbat.org/article831">https://vbat.org/article831</a></p>
Least cost network data for ancient camel transportation in the Eastern desert of Egypt - Desert Networks HiSoMA CNRS
<p>This repository contains the data necessary for the realization of a least cost network for camel transport during antiquity (Ptolemaic and Roman period) in the Egyptian eastern desert. The details of the network construction and data processing can be found in the the associated paper and datapaper.</p> <p>Study paper:<br> Manière, L., Crépy, M., Redon, B. (2020) Building a Model to reconstruct the Hellenistic and Roman Road Networks of the Eastern desert of Egypt, a Semi-Empirical Approach Based on Modern Travelers’ Itineraries. DOI : <a href="http://doi.org/10.5334/jcaa.67">http://doi.org/10.5334/jcaa.67</a></p> <p>Datapaper:<br> Manière, L., Crépy, M., Redon, B. (2020) Geospatial data from the “Modelling the Hellenistic and Roman Road Networks of the Eastern desert of Egypt, a Semi-Empirical Approach Based on Modern Travelers’ Itineraries” paper. DOI : <a href="http://doi.org/10.5334/joad.71">http://doi.org/10.5334/joad.71</a></p>
National Checklists 2017: Egypt Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details<p></p>A list of species from Egypt collected using effechecka and geonames polygons
National Checklists 2019: Egypt Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details.<p></p>A list of species from Egypt collected using effechecka and geonames polygons
FIG. 4. — CUWM 53 in New Amphicyonids (Mammalia, Carnivora) from Moghra, Early Miocene, Egypt
FIG. 4. — CUWM 53, Moghra, Early Miocene, Amphicyon giganteus (Schinz, 1825): A, lingual view; B, occlusal view; C, labial view. Scale bar: 100 mm.
FIG. 2. — CUWM 55 in New Amphicyonids (Mammalia, Carnivora) from Moghra, Early Miocene, Egypt
FIG. 2. — CUWM 55, Moghra, Early Miocene. Holotype of Cynelos anubisi n. sp.: A, lingual view; B, occlusal view; C, labial view. Scale bar: 100 mm.
FIG. 15 in The exploitation of molluscs and other invertebrates in Alexandria (Egypt) from the Hellenistic period to Late Antiquity: food, usage, and trade
FIG. 15. — Spider conch (Lambis sp. Röding, 1798) shell from: A, Fouad site; and B, Theater Diana, probably used as a container. Inner side at the top and outer side at the bottom. Scale bar: 10 mm.
FIG. 14 in The exploitation of molluscs and other invertebrates in Alexandria (Egypt) from the Hellenistic period to Late Antiquity: food, usage, and trade
FIG. 14. — Indo-Pacificmolluscshells: A, Chicoreusramosus Linnaeus, 1758; B, Tridacna maxima (Röding, 1798). Scale bars: 10 mm.
Cats from Egypt
<p>Ancient Egyptian culture is known for its devotion to the cat. Here an image which is showing some "cats" (mummies and statuettes) exhibited at the Egyptian Museum of Torino. </p>
Hassan #1 Arabic and French transcripts of description and comments on his recording in Darb al-Ahmar, Cairo (Egypt), 25-10-2011
<p>« Mics in the Ears » binaural experiment in Cairo (Egypt): Vincent Battesti & Nicolas Puig, social anthropologists, asked inhabitants of Cairo megapolis in Egypt to record the surrounding urban sounds during one of their daily journeys (without the researcher), equipped with binaural microphones and GPS device. Participants have recorded in different Cairo neighbourhoods, and are themselves from different generations, social and economic backgrounds, and different genders.</p> <p>These text files (pdf and Word) are the transcripts (original in Arabic and translation in French) of the audio file of the description and comments one of them gave us a posteriori when listening to his/her own route he/she recorded with binaural mics. See https://vbat.org/article831</p>
qdgc Egypt
<p>QDGC tables delivered in geopackage file<br> - - - - - - - - - - - - - - - - - - - - - -<br> QDGC represents a way of making (almost) equal area squares covering a specific area to represent specific qualities of the area covered. The squares themselves are based on the degree squares covering earth. Around the equator we have 360 longitudinal lines , and from the north to the south pole we have 180 latitudinal lines. Together this gives us 64800 segments or tiles covering earth.<br> <br> <br> Within each geopackage file you will find a number of tables with these names:<br> <br> <br> -tbl_qdgc_01<br> -tbl_qdgc_02<br> -tbl_qdgc_03<br> -tbl_qdgc_04<br> -tbl_qdgc_05<br> -etc<br> <br> <br> The attributes for each table are:<br> <br> <br> qdgc Unique Quarter Degree Grid Cell reference string<br> area_reference Country<br> level_qdgc QDGC level<br> cellsize degrees decimal degree for the longitudal and latitudal length of the cell<br> lon_center Longitude center of the cell<br> lat_center Latitudal center of the cell<br> area_km2 Calculated area for the cell<br> geom Geometry<br> <br> <br> Metadata<br> --------<br> Geodata GCS_WGS_1984<br> Datum: D_WGS_1984<br> Prime Meridian: 0<br> <br> <br> Areas are calculated with different versions of Albers Equal Area Conic using the PostGIS function st_area. For the African continent I have used Africa Albers Equal Area Conic which will look like this:<br> - st_area(st_transform(geom, 102022))/1000000)<br> <br> <br> Licensing<br> ---------<br> Creative Commons Attribution 4.0 International<br> <br> <br> Conditions<br> ----------<br> Delivered to the user as-is. No guarantees. If you find errors, please tell me and I will try to fix it.<br> <br> <br> Thankyou<br> --------<br> The work has over the years been supported and receicved advice and moral support from many organisations and stakeholders. Here are some of them:<br> - Tanzania Wildlife Research Institute<br> - Dept of Biology, NTNU, Norway<br> - Norwegian Environment Agency<br> - Eivin Røskaft, Steven Prager, Howard Frederick, Julian Blanc, Honori Maliti, Paul Ramsey<br> <br> <br> References<br> ----------<br> * http://en.wikipedia.org/wiki/QDGC<br> * http://www.mindland.com/wp/projects/quarter-degree-grid-cells/about-qdgc/<br> * http://en.wikipedia.org/wiki/Lambert_azimuthal_equal-area_projection<br> * http://www.safe.com<br> <br> <br> <br> <br> Ragnvald Larsen<br> Trondheim 20th of January, 2021<br> <br> <br> ragnvald@mindland.com<br> www.mindland.com</p>
Infrastructure Climate Resilience Assessment Data Starter Kit for Egypt
<p> This starter data kit collects extracts from global, open datasets relating to climate hazards and infrastructure systems. </p> <p> These extracts are derived from global datasets which have been clipped to the national scale (or subnational, in cases where national boundaries have been split, generally to separate outlying islands or non-contiguous regions), using Natural Earth (2023) boundaries, and is not meant to express an opinion about borders, territory or sovereignty. </p> <p> Human-induced climate change is increasing the frequency and severity of climate and weather extremes. This is causing widespread, adverse impacts to societies, economies and infrastructures. Climate risk analysis is essential to inform policy decisions aimed at reducing risk. Yet, access to data is often a barrier, particularly in low and middle-income countries. Data are often scattered, hard to find, in formats that are difficult to use or requiring considerable technical expertise. Nevertheless, there are global, open datasets which provide some information about climate hazards, society, infrastructure and the economy. This "data starter kit" aims to kickstart the process and act as a starting point for further model development and scenario analysis. </p> <p>Hazards:</p> <ul> <li>coastal and river flooding (Ward et al, 2020; Baugh et al, 2024)</li> <li>extreme heat and drought (Russell et al 2023, derived from Lange et al, 2020)</li> <li>tropical cyclone wind speeds (Russell 2022, derived from Bloemendaal et al 2020 and Bloemendaal et al 2022)</li> </ul> <p>Exposure:</p> <ul> <li>population (Schiavina et al, 2023)</li> <li>built-up area (Pesaresi et al, 2023)</li> <li>roads (OpenStreetMap, 2025)</li> <li>railways (OpenStreetMap, 2025)</li> <li>power plants (Global Energy Observatory et al, 2018)</li> <li>power transmission lines (Arderne et al, 2020)</li> </ul> <p>Contextual information:</p> <ul> <li>elevation (European Union and ESA, 2021)</li> <li>land-use and land cover (Copernicus Climate Change Service and Climate Data Store, 2019)</li> <li>administrative boundaries from geoBoundaries (Runfola et al., 2020)</li> </ul> <p> The spatial intersection of hazard and exposure datasets is a first step to analyse vulnerability and risk to infrastructure and people. </p> <p> To learn more about related concepts, there is a free short course available through the Open University on <a href="https://www.open.edu/openlearncreate/course/view.php?id=12278">Infrastructure and Climate Resilience</a>. This <a href="https://opsis.eci.ox.ac.uk/courses/2-infra-for-resil/">overview of the course</a> has more details. </p> <p> These Python libraries may be a useful place to start analysis of the data in the packages produced by this workflow: </p> <ul> <li> <a href="https://github.com/tomalrussell/snkit"><code>snkit</code></a> helps clean network data </li> <li> <a href="https://github.com/nismod/snail"><code>nismod-snail</code></a> is designed to help implement infrastructure exposure, damage and risk calculations </li> </ul> <p> The <a href="https://github.com/nismod/open-gira"><code>open-gira</code></a> repository contains a larger workflow for global-scale open-data infrastructure risk and resilience analysis. </p> <p> For a more developed example, some of these datasets were key inputs to a regional climate risk assessment of current and future flooding risks to transport networks in East Africa, which has a related online visualisation tool at <a href="https://east-africa.infrastructureresilience.org/">https://east-africa.infrastructureresilience.org/</a> and is described in detail in Hickford et al (2023). </p> <p><strong>References</strong></p> <ul> <li> Arderne, Christopher, Nicolas, Claire, Zorn, Conrad, & Koks, Elco E. (2020). Data from: Predictive mapping of the global power system using open data [Dataset]. In Nature Scientific Data (1.1.1, Vol. 7, Number Article 19). Zenodo. DOI: <a href="https://doi.org/10.5281/zenodo.3628142">10.5281/zenodo.3628142</a> </li> <li> Baugh, Calum; Colonese, Juan; D'Angelo, Claudia; Dottori, Francesco; Neal, Jeffrey; Prudhomme, Christel; Salamon, Peter (2024): Global river flood hazard maps. European Commission, Joint Research Centre (JRC) [Dataset] PID: <a href="http://data.europa.eu/89h/jrc-floods-floodmapgl_rp50y-tif">data.europa.eu/89h/jrc-floods-floodmapgl_rp50y-tif</a> </li> <li> Bloemendaal, Nadia; de Moel, H. (Hans); Muis, S; Haigh, I.D. (Ivan); Aerts, J.C.J.H. (Jeroen) (2020): STORM tropical cyclone wind speed return periods. 4TU.ResearchData. [Dataset]. DOI: <a href="https://doi.org/10.4121/12705164.v3">10.4121/12705164.v3</a> </li> <li> Bloemendaal, Nadia; de Moel, Hans; Dullaart, Job; Haarsma, R.J. (Reindert); Haigh, I.D. (Ivan); Martinez, Andrew B.; et al. (2022): STORM climate change tropical cyclone wind speed return periods. 4TU.ResearchData. [Dataset]. DOI: <a href="https://doi.org/10.4121/14510817.v3">10.4121/14510817.v3</a> </li> <li> Copernicus Climate Change Service, Climate Data Store, (2019): Land cover classification gridded maps from 1992 to present derived from satellite observation. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: <a href="https://doi.org/10.24381/cds.006f2c9a">10.24381/cds.006f2c9a</a> (Accessed on 09-AUG-2024) </li> <li> Copernicus DEM - Global Digital Elevation Model (2021) DOI: <a href="https://doi.org/10.5270/ESA-c5d3d65">10.5270/ESA-c5d3d65</a> (produced using Copernicus WorldDEM™-90 © DLR e.V. 2010-2014 and © Airbus Defence and Space GmbH 2014-2018 provided under COPERNICUS by the European Union and ESA; all rights reserved) </li> <li> Global Energy Observatory, Google, KTH Royal Institute of Technology in Stockholm, Enipedia, World Resources Institute. (2018) Global Power Plant Database. Published on Resource Watch and Google Earth Engine; <a href="http://resourcewatch.org/">resourcewatch.org/</a> </li> <li> Hickford et al (2023) Decision support systems for resilient strategic transport networks in low-income countries – Final Report. Available online: <a href="https://transport-links.com/hvt-publications/final-report-decision-support-systems-for-resilient-strategic-transport-networks-in-low-income-countries">https://transport-links.com/hvt-publications/final-report-decision-support-systems-for-resilient-strategic-transport-networks-in-low-income-countries</a> </li> <li> Lange, S., Volkholz, J., Geiger, T., Zhao, F., Vega, I., Veldkamp, T., et al. (2020). Projecting exposure to extreme climate impact events across six event categories and three spatial scales. Earth's Future, 8, e2020EF001616. DOI: <a href="https://doi.org/10.1029/2020EF001616">10.1029/2020EF001616</a> </li> <li> Natural Earth (2023) Admin 0 Map Units, v5.1.1. [Dataset] Available online: <a href="https://www.naturalearthdata.com/downloads/10m-cultural-vectors/10m-admin-0-details/">www.naturalearthdata.com/downloads/10m-cultural-vectors/10m-admin-0-details</a> </li> <li> OpenStreetMap contributors, Russell T., Thomas F., nismod/datapkg contributors (2025) Road and Rail networks derived from OpenStreetMap. [Dataset] Available at <a href="https://global.infrastructureresilience.org">global.infrastructureresilience.org</a> </li> <li> Pesaresi M., Politis P. (2023): GHS-BUILT-S R2023A - GHS built-up surface grid, derived from Sentinel2 composite and Landsat, multitemporal (1975-2030) European Commission, Joint Research Centre (JRC) PID: <a href="http://data.europa.eu/89h/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea">data.europa.eu/89h/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea</a>, doi:10.2905/9F06F36F-4B11-47EC-ABB0-4F8B7B1D72EA </li> <li> Runfola D, Anderson A, Baier H, Crittenden M, Dowker E, Fuhrig S, et al. (2020) geoBoundaries: A global database of political administrative boundaries. PLoS ONE 15(4): e0231866. DOI: <a href="https://doi.org/10.1371/journal.pone.0231866">10.1371/journal.pone.0231866</a>. </li> <li> Russell, T., Nicholas, C., & Bernhofen, M. (2023). Annual probability of extreme heat and drought events, derived from Lange et al 2020 (Version 2) [Dataset]. Zenodo. DOI: <a href="https://doi.org/10.5281/zenodo.8147088">10.5281/zenodo.8147088</a> </li> <li> Schiavina M., Freire S., Carioli A., MacManus K. (2023): GHS-POP R2023A - GHS population grid multitemporal (1975-2030). European Commission, Joint Research Centre (JRC) PID: <a href="http://data.europa.eu/89h/2ff68a52-5b5b-4a22-8f40-c41da8332cfe">data.europa.eu/89h/2ff68a52-5b5b-4a22-8f40-c41da8332cfe</a>, doi:10.2905/2FF68A52-5B5B-4A22-8F40-C41DA8332CFE </li> <li> Ward, P.J., H.C. Winsemius, S. Kuzma, M.F.P. Bierkens, A. Bouwman, H. de Moel, A. Díaz Loaiza, et al. (2020) Aqueduct Floods Methodology. Technical Note. Washington, D.C.: World Resources Institute. Available online at: <a href="https://www.wri.org/publication/aqueduct-floods-methodology">www.wri.org/publication/aqueduct-floods-methodology</a>. </li> </ul>
Fig. (10-17): (10) Dichrogaster aestivalis, fore wing; (11) C. armator, areolet of fore wing; (12) Mesostenus sp., areolet of fore wing; (13) Venturia canescens, ovipositor; (14) Barichneumon sp.; ventral aspect of metasoma; (15) Ctenichneumon sp., ventral aspect of metasoma; (16) Exochus castaniventris, frontal view of head; (17) Diplazon laetatorius, frontal view of head. in Ichneumonidae from the Suez Canal region Egypt (Hymenoptera, Ichneumonoidea)
Fig. (10-17): (10) Dichrogaster aestivalis, fore wing; (11) C. armator, areolet of fore wing; (12) Mesostenus sp., areolet of fore wing; (13) Venturia canescens, ovipositor; (14) Barichneumon sp.; ventral aspect of metasoma; (15) Ctenichneumon sp., ventral aspect of metasoma; (16) Exochus castaniventris, frontal view of head; (17) Diplazon laetatorius, frontal view of head.
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.