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4,404 results for “Digitization”
2-round Delphi study on digital technologies in vegetable farming in Switzerland
<p>This dataset contains survey data including the codebook for a 2-round Delphi study we conducted in Switzerland in autumn 2020. Selected experts were asked to describe the future of digital technologies in vegetable farming in Switzerland.</p>
Corpus de revistas Proyecto Digitization and Analysis of Cultural Transfers in Colombian Literary Magazines (1892–1950)
<p>Coprpus de revistas Proyecto Digitization and Analysis of Cultural Transfers in Colombian Literary Magazines (1892–1950)</p>
Digital Elevation Models of Tweedsmuir Glacier 1950-2018
<p>This dataset contains digital elevation models (DEMs) of Tweedsmuir Glacier, British Columbia, Canada between 1950 and 2018. DEMs from 1950, 1969, 1974, and 1987 were created using Structure-from-Motion photogrammetry in Agisoft Metashape by Meghan A. Sharp. DEMs from 2000, 2007, 2010, and 2018 were acquired from open-source satellite sources (see "Amplification of Surface Topography during Surges of Tweedsmuir Glacier" for sources). All DEMs have been co-registered to ArcticDEM (Porter et al., 2018) using Shean et al (2016)'s open-source tool <em>demcoreg</em>.</p> <p> </p>
Digital Approaches to Analyzing and Translating Emotion: What Is Love?
<p>This repository contains the data used for and created during the research for the article "Digital Approaches to Analyzing and Translating Emotion: What Is Love?" in Karen Sonik and Ulrike Steinert (eds.),<em> The Routledge Handbook of Emotions in the Ancient Near East</em> (London: Routledge, 2022), pp. 88–116, <a href="https://doi.org/10.4324/9780367822873-6">https://doi.org/10.4324/9780367822873-6</a>.</p> <p><strong>Lists/</strong> contains various lists used for and created while analyzing love words in Akkadian.</p> <p><strong>Networks and figures/</strong> contains the networks and figures produced during our research.</p> <p><strong>Oracc data/</strong> contains the raw data extracted from the Oracc texts.</p> <p><strong>PMI and fastText results/</strong> contains the results produced with PMI and fastText.</p> <p><strong>Texts/</strong> contains the text file used for producing the results with PMI and fastText.</p> <p>We gratefully acknowledge that our research has been funded by the Academy of Finland (decision numbers 298647, 312051, and 330727). Our research data originates from the Open Richly Annotated Cuneiform Corpus (Oracc). We thank Oracc for their efforts in making linguistically annotated cuneiform texts available online. We are indebted to everyone who has been involved in creating this research data, including the authors of the original publications and the researchers who have made the data Oracc-compatible and enriched it through lemmatizations and by adding other metadata (for a list of projects and their contributors, see the file OraccCredits.txt). In the context of this article and dataset, we want to acknowledge the work of the Munich Open-access Cuneiform Corpus Initiative (PIs Karen Radner and Jamie Novotny), the Royal Inscriptions of the Neo-Assyrian Period project (PI Grant Frame), and the Akkadian Love Literature project (Nathan Wasserman and Yigal Bloch) in particular.</p>
Measurements in October 2021 using a digital magnetic variation station at the Simeiz-Katsiveli geodynamic test site
<p>Measured by the digital magnetic variation station at the Simeiz-Katsiveli test site during the period October 07–21, 2021.</p>
Shape from Shading Digital Elevation Model for Oxia Planum Candidate Landing Site
<p>This data set contains the calibrated and map-projected HiRISE image ESP_037558_1985 and the matching Shape from Shading DEM using the method described in Hess et al., (2019a), and in more detail in Hess et al. (2022). The SfS DTM was part of the EPSC abstract Hess et al., (2019b). When using the data please reference Hess et al. (2022) for the method.</p> <p>ESP_037558_1985_30cm_o.cub: Image data in radiances, ISIS cube file, Equirectangular map projection at 0.25 m/pixel resolution.</p> <p>ESP_037558_1985_30cm_DEM.cub: Digital Elevation Model (DEM) with heights in meter, ISIS cube file, Equirectangular map projection at 0.25 m/pixel resolution.</p> <p>Cube files can be converted to other data formats using gdal (https://gdal.org/) or directly loaded in, e.g., ArcGIS or QGIS.</p> <p> </p> <p>Hess, M., Wohlfarth, K., Grumpe, A., Wöhler, C., Ruesch, O., and Wu, B.: ATMOSPHERICALLY COMPENSATED SHAPE FROM SHADING ON THE MARTIAN SURFACE: TOWARDS THE PERFECT DIGITAL TERRAIN MODEL OF MARS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W13, 1405–1411, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1405-2019, 2019a.</p> <p>Hess, Marcel. "High Resolution Digital Terrain Model for the Landing Site of the Rosalind Franklin (ExoMars) Rover." Proc. European Planetary Science Congress, EPSC-DPS2019-1533-4, Geneva, Switzerland, 2019b.</p> <p>Hess, M.; Tenthoff, M.; Wohlfarth, K.; Wöhler, C. Atmospheric Correction for High-Resolution Shape from Shading on Mars. <em>J. Imaging</em> <strong>2022</strong>, <em>8</em>, 158. https://doi.org/10.3390/jimaging8060158</p>
High-resolution digital topography and layer attitude measurements over Juventae Chasma (Valles Marineris, Mars)
<p>Stereo-derived topography over mounds in Juventae Chasma (Valles Marineris, Mars), including derived measurements (ASCII .csv and .xls). File naming in measurements follows the numbering of NASA MRO HiRiSE stereo pairs.</p> <p>Please note for all DTMs</p> <p>Format: GeoTiff<br> Projection: Equirectangular<br> Datum: Mars 2000 Sphere</p> <p>Bit depth: 32bit</p> <p>Spatial resolution: 1m/pixel</p> <p>HiRise images avalable at:https://hirise.lpl.arizona.edu/<br> (use one of the image numbers listed below in the search box)</p> <p>Stereo pairs:</p> <p>HiRISE 1 (PSP_002590_1765_RED-PSP_002946_1765_RED-DEM_cyli.tif)<br> PSP_002590_1765<br> PSP_002946_1765</p> <p><br> HiRISE 2 (PSP_006915_1760_RED-PSP_007060_1760_RED-DEM_cyli.tif)<br> PSP_006915_1760<br> PSP_007060_1760</p> <p>HiRISE 3 (ESP_015934_1760_RED-ESP_016646_1760_RED-DEM_cyli.tif)<br> ESP_016646_1760<br> ESP_015934_1760</p> <p>HiRISE 4 (ESP_020470_1755_RED-ESP_014378_1755_RED-DEM_cyli.tif)<br> ESP_020470_1755<br> ESP_014378_1755</p> <p>HiRISE 5 (PSP_002379_1755_RED-PSP_002023_1755_RED-DEM_cyli.tif)<br> PSP_002379_1755<br> PSP_002023_1755</p> <p>HiRISE 6 (ESP_016567_1755_RED-ESP_017279_1755_RED-DEM_cyli.tif)<br> ESP_016567_1755<br> ESP_017279_1755</p> <p>HiRISE 7 (PSP_003790_1755_RED-PSP_004291_1755_RED-DEM_cyli.tif)<br> PSP_003790_1755<br> PSP_004291_1755</p> <p>HiRISE 8 (ESP_016145_1775_RED-ESP_017424_1775_RED-DEM_cyli.tif)<br> ESP_016145_1775<br> ESP_017424_1775</p> <p>HiRISE 9 (PSP_008708_1780_RED-PSP_008998_1780_RED-DEM_cyli.tif)<br> PSP_008708_1780<br> PSP_008998_1780</p> <p>HiRISE 10 (ESP_011688_1760_RED-ESP_019613_1760_RED-DEM_cyli.tif)<br> ESP_019613_1760<br> ESP_011688_1760</p>
Digital government HRM literature review
<p>Digital government HRM index</p> <p> </p> <p>Data collected and processed as part of the ODDEA (Overcoming Digital Divide Between Europe and Southeast Asia) EU research project (<em>Project ID: HORIZON MSCA-SE 101086381)</em></p>
Digitization Workflow: Talk with Joana Meier
<p>Jane Haller, a sociologist, digital project manager, and president of the Digitales Schaudepot, is in conversation with Joana Meier. Joana holds a BA in Sociology and English Literature, is a Master's student in Digital Humanities, and works in museum education and digitization.</p> <ul> <li>As a Digital Humanities Master’s student and museum education expert, talking about experimenting and hands on exercises with the digital</li> <li>What does "curating data stories" mean from a technical and academic perspective?</li> </ul> <p>As a winning project of the Dariah Theme Call 2022-2024 on Workflows, we evaluated a showcase project called “<a href="https://curiositas.digitalesschaudepot.ch/en/">curiositas5.0</a>”, initiated by the <a href="https://www.digitalesschaudepot.ch/">Digitales Schaudepot Association</a> (DSD) it is intended to assist in planning projects and, above all, avoiding unwanted missteps. Keep in mind that each project is distinct and may necessitate alternative measures. </p> <p>To capture voices from the community and provide insight into the different working methods, expertise, and backgrounds of the people collaborating on the curiositas5.0 project, we conducted 3 interviews.</p> <p> </p> <p> </p>
World Bank Digitalization Database ODDEA Project
<p><span>Data collected and processed as part of the ODDEA (Overcoming Digital Divide Between Europe and Southeast Asia) EU research project (<em>Project ID: HORIZON MSCA-SE 101086381). It consists of </em>8 ICT indicators for 266 countries and country groups for 2012 – 2022 period. Excel files with metadata compacted in zip file. </span></p>
Annotated Data in Spanish for Toxicity and Insults in Digital Social Networks
<p>This repository contains data sets and materials for a gold standard elaboration on toxicity and incivility in the digital sphere based on human coding to benchmark algorithmic classification tasks with transformers and LLMs. <strong>The labelling progress is 62%</strong>.</p> <p>We are labelling two samples of novel datasets of political digital interactions on Twitter (rebranded as X). The first set comprises almost 5 million data points from three Latin American protest events: (a) protests against the coronavirus and judicial reform measures in Argentina during August 2020; (b) protests against education budget cuts in Brazil in May 2019; and (c) the social outburst in Chile stemming from protests against the underground fare hike in October 2019. We are focusing on interactions in Spanish to elaborate a gold standard for digital interactions in this language, therefore, we prioritise Argentinian and Chilean data. The second set contains more than 31 million messages and more than 9 million interactions between 2010 and 2022, covering the election of members of the first Constitutional Convention in Chile, the drafting process and the referendum in which the proposal was rejected.</p> <p>This project is generously funded by the <strong>OpenAI Academic Programme</strong>, <strong>2024 FAE-UDP Research Grant</strong>, and partially by the <strong>St Hilda's College Muriel Wise Fund at the University of Oxford</strong>. The <a href="https://training-datalab.com/"><strong>Training Data Lab</strong></a> research group also logistically supports this project.</p>
Digital Repository of Ireland Member Digitisation Workflows for 2D Image Files: Survey Questions and Dataset
<p>The Digital Repository of Ireland (DRI) issued a survey to its membership, <strong>DRI Member Digitisation Workflows for 2D Images</strong>, which ran from December 7, 2023–January 31, 2024. The survey was conducted to improve the DRI’s understanding of the technical processes and metadata workflows that our members use to digitise and share images in the Repository, in order to better tailor our support for this work and deliver the most complete information about digital images files available to our users. </p> <p>The survey informed the actions taken in WorldFAIR Project WP13 deliverable <a href="https://doi.org/10.5281/zenodo.10850009" target="_blank" rel="noopener">13.3 Implementing and Testing the Cultural Heritage Image Sharing Recommendations: DRI Case Study Report</a>. The data will inform ongoing work at DRI aimed at improving the transparency of technical information associated with digital assets accessed through the Repository.</p> <p>Read more about the Cultural Heritage Image Sharing Case Study DRI on our website: <a href="https://dri.ie/the-worldfair-project/">https://dri.ie/the-worldfair-project/</a>. </p> <p>Summary: DRI is Ireland's national repository for the arts, humanities, and social sciences data, and operates on a membership scheme. There were 20 respondents to the survey, giving us a response rate of about 35% of DRI's membership. Representation from professional fields of work across the cultural heritage sector was captured in the results (note that some institutions gave multiple responses): 17 Archives, 12 Libraries, 5 Museums and 11 Higher Education Institutions. </p>
Identified Charcoal Hearths from "Slope Analysis of 'Digital Elevation Model for Blue Mountain Charcoal Research Project'"
<p>This is a GeoJSON file that lists all of the potential charcoal hearths along the Blue Mountain of eastern Pennsylvania. For a detailed description of how this data was produced, please see:</p> <p>Carter, Benjamin. (2018, May 29). Description of Methods for Identifying Charcoal Hearths along the Blue Mountain of Pennsylvania. (Version 0.1.0). Zenodo. http://doi.org/10.5281/zenodo.1255101</p> <p>These hearths were identified using this data:</p> <p>Carter, Benjamin. (2018). Slope Analysis of "Digital Elevation Model for Blue Mountain Charcoal Research Project" (Version 0.1.0). Zenodo. http://doi.org/10.5281/zenodo.1252977</p> <p>The above is derived from:</p> <p>Carter, Benjamin P. (2018). Digital Elevation Model for Blue Mountain Charcoal Research Project (Version 0.1.0). Zenodo. http://doi.org/10.5281/zenodo.1252441</p> <p> </p>
Abstracts from the Digital Humanities Conference 2005-2018
<p>Plain-text versions of the <a href="http://adho.org/conference">Digital Humanities Conference</a>s' books of abstracts (2005-2018).<br> </p>
The Key to the City: Using Digital Tools to Understand Tablet Provenience
<p>These files are those used in the keyness analysis for unprovenienced "Diyala" texts against tablets from Tutub, Eshnunna, Tell Suleimah, Kish and Girsu. Each site has two files: the cleaned atf used to generate a word list, and the word list giving the frequency of each word (based on the lemmatized version of words in the Lemma List and incomplete words in the Stopword List).</p>
Digital models of test objects captured by RFSAT Ltd using 3D photogrammetry
<p>This data set contains a number of digital models produced via 3D photogrammetric scanning as part of the SCAN4RECO project, funded by the European Horizon'2020 program. Scanning and processing of models was done with Pix4D Mapper and Autodesk ReMake software from images captured with Canon 5DS camera in 50 Megapixel image resolution. Example objects include Byzantine icons painted on wood, oil paintings on canvas and painted Venetian carnival paper masks.</p> <p>Second version of the data set includes historical icons of Saint DImitrios and Saint Archangel Michael, an icon of Saint Mary painted specially for testing SCAN4RECO technologies, as well as models of an original high-relief sculpture from OPD and of its 3D printed copy (made by Fraunhofer-IGD and hand painted by RFSAT)..</p> <p>Selected models can be also seen in the SCAN4RECO Virtual Museum developed by CERTH-ITI:<br> http://scan4reco.eu/scan4reco/content/scan4reco-virtual-museum</p>
Metadata, Title Pages, and Network Graph of the Digitized Content of the Berlin State Library (146,000 items)
<p>The data set has been downloaded via the OAI-PMH endpoint of the Berlin State Library/Staatsbibliothek zu Berlin’s Digitized Collections (<a href="https://digital.staatsbibliothek-berlin.de/oai">https://digital.staatsbibliothek-berlin.de/oai</a>) on March 1<sup>st</sup> 2019 and converted into common tabular formats on the basis of the provided Dublin Core metadata. It contains 146,000 records.</p> <p>In addition to the bibliographic metadata, representative images of the works have been downloaded, resized to a 512 pixel maximum thumbnail image and saved in JPEG format. The image data is split into title pages and first pages. Title pages have been derived from structural metadata created by scan operators and librarians. If this information was not available, first pages of the media have been downloaded. In case of multi-volume media, title pages are not available.</p> <p>In total, 141,206 images title/first pages are available.</p> <p> </p> <p>Furthermore, the tabular data has been cleaned and extended with geo-spatial coordinates provided by the OpenStreetMap project (<a href="https://www.openstreetmap.org">https://www.openstreetmap.org</a>). The actual data processing steps are summarized in the next section. For the sake of transparency and reproducibility, the original data taken from the OAI-PMH endpoint is still present in the table.</p> <p> </p> <p>To conclude with, various graphs in GML file format are available that can be loaded directly into graph analysis tools such as Gephi (<a href="https://gephi.org/">https://gephi.org/</a>).</p> <p> </p> <p>The implementation of the data processing steps (incl. graph creation) are available as a Jupyter notebook provided at <a href="https://github.com/elektrobohemian/SBBrowse2018/blob/master/DataProcessing.ipynb">https://github.com/elektrobohemian/SBBrowse2018/blob/master/DataProcessing.ipynb</a>.</p> <p> </p> <p>Tabular Metadata</p> <p> </p> <p>The metadata is available in Excel (cleanedData.xlsx) and CSV (cleanedData.csv) file formats with equal content.</p> <p>The table contains the following columns. Italique columns have not been processed.</p> <p>· <em>title</em> The title of the medium</p> <p>· <em>creator</em> Its creator (family name, first name)</p> <p>· <em>subject</em> A collection’s name as provided by the library</p> <p>· <em>type</em> The type of medium</p> <p>· <em>format</em> A MIME type for full metadata download</p> <p>· <em>identifier</em> An additional identifier (most often the PPN)</p> <p>· <em>language</em> A 3-letter language code of the medium</p> <p>· <em>date</em> The date of creation/publication or a time span</p> <p>· <em>relation</em> A relation to a project or collection a medium has been digitized for.</p> <p>· <em>coverage</em> The location of publication or origin (ranging from cities to continents)</p> <p>· <em>publisher</em> The publisher of the medium.</p> <p>· <em>rights</em> Copyright information.</p> <p>· <em>PPN</em> The unique identifier that can be used to find more information about the current medium in all information systems of Berlin State Library/Staatsbibliothek zu Berlin.</p> <p>· spatialClean In case of multiple entries in coverage, only the first place of origin has been extracted. Additionally, characters such as question marks, brackets, or the like have been removed. The entries have been normalized regarding whitespaces and writing variants with the help of regular expressions.</p> <p>· dateClean As the original date may contain various format variants to indicate unclear creation dates (e.g., time spans or question marks), this field contains a mapping to a certain point in time.</p> <p>· spatialCluster The cluster ID determined with the help of the Jaro-Winkler distance on the spatialClean string. This step is needed because the spatialClean fields still contain a huge amount of orthographic variants and latinizations of geographic names.</p> <p>· spatialClusterName A verbal cluster name (controlled manually).</p> <p>· latitude The latitude provided by OpenStreetMap of the spatialClusterName if the location could be found.</p> <p>· longitude The longitude provided by OpenStreetMap of the spatialClusterName if the location could be found.</p> <p>· century A century derived from the date.</p> <p>· textCluster A text cluster ID on the basis of a k-means clustering relying on the title field with a vocabulary size of 125,000 using the tf*idf model and k=5,000.</p> <p>· creatorCluster A text cluster ID based on the creator field with k=20,000.</p> <p>· titleImage The path to the first/title page relative to the img/ subdirectory or None in case of a multi-volume work.</p> <p>Other Data</p> <p> </p> <p><em>graphs.zip</em></p> <p> </p> <p>Various pre-computed graphs.</p> <p><em> </em></p> <p><em>img.zip</em></p> <p> </p> <p>First and title pages in JPEG format.</p> <p> </p> <p><em>json.zip</em></p> <p> </p> <p>JSON files for each record in the following format:</p> <p> </p> <p>ppn "PPN57346250X"</p> <p>dateClean "1625"</p> <p>title "M. Georgii Gutkii, Gymnasii Berlinensis Rectoris Habitus Primorum Principiorum, Seu Intelligentia; Annexae Sunt Appendicis loco Disputationes super eodem habitu tum in Academia Wittebergensi, tum in Gymnasio Berlinensi ventilatae"</p> <p>creator "Gutke, Georg"</p> <p>spatialClusterName "Berlin"</p> <p>spatialClean "Berolini"</p> <p>spatialRaw "Berolini"</p> <p>mediatype "monograph"</p> <p>subject "Historische Drucke"</p> <p>publisher "Kallius"</p> <p>lat "52.5170365"</p> <p>lng "13.3888599"</p> <p>textCluster "45"</p> <p>creatorCluster "5040"</p> <p>titleImage "titlepages/PPN57346250X.jpg"</p>
Extracted Illustrations of the Berlin State Library's Digitized Collections (part 1 of 4)
<p>The dataset consists of various illustrations extracted from 26,233 historical books and other media offered in the Berlin State Library's Digitized Collections. The media objects are older than 1920.</p> <p>Version 1.0 contains of 594,890 extracted illustrations in total.</p> <p>The extraction of illustrations is driven by the coordinates given by the ABBYY FineReader OCR engine (in ALTO XML) . The extracted illustrations have not been resized but compressed and saved in JPEG format.</p> <p>Pre-trained models in order to separate color scales, hand-written signatures, library stamps or the like from interesting content are available under: <a href="https://github.com/elektrobohemian/imi-unicorns">https://github.com/elektrobohemian/imi-unicorns</a>.</p> <p>The extracts for each media object are stored in separated sub-folders and tar files named after the PPN (a unique ID used in the library) to facilitate further processing. Additional metadata can be obtained with help of the PPN as described here: <a href="https://github.com/elektrobohemian/StabiHacks/blob/master/ppn-howto.md">https://github.com/elektrobohemian/StabiHacks/blob/master/ppn-howto.md</a> .</p> <p>The dataset is published as a set of ZIP files, each fitting on a Blu Ray disc. <strong>After decompression, the contents will consume ca. 166 GB.</strong></p> <p><em>Change Log for Version</em></p> <ol> <li>original dataset</li> <li>added color histograms (RGB, separated by channel) in JSON and Python pickle format as extracted by the <a href="https://pillow.readthedocs.io/en/stable/">Pillow</a> package (see https://github.com/elektrobohemian/StabiHacks/tree/master/image-tools)</li> </ol> <p><strong>This is part 1 of 4. The following datasets contain the other ZIP files (8 files in total):</strong></p> <ul> <li><a href="https://doi.org/10.5281/zenodo.2598145">https://doi.org/10.5281/zenodo.2598145</a></li> <li><a href="https://doi.org/10.5281/zenodo.2598261">https://doi.org/10.5281/zenodo.2598261</a></li> <li><a href="https://doi.org/10.5281/zenodo.2598270">https://doi.org/10.5281/zenodo.2598270</a></li> </ul> <p> </p>
OCR fulltexts of the Digital Collections of the Berlin State Library (DC-SBB)
<p>The digital collections of the SBB contain 153,942 digitized works from the time period of 1470 to 1945.</p> <p>At the time of publication, 28,909 works have been OCR-processed resulting in 4,988,099 full-text pages.<br> For each page with OCR text, the language has been determined by <em>langid </em>(Lui/Baldwin 2012).</p> <p>corpus-entropy.pkl entropy rate per document page</p> <p>corpus-language.pkl language per document page</p> <p>corpus.zip fulltext corpus (extracts to .txt format)</p> <p>de_corpus.zip German sub-corpus (extracts to .txt format)</p> <p>selection_de.pkl Selection list of German documents</p> <p>xml2csv_alto.csv fulltext corpus per document page (incl.OCR word confidences)</p> <p> </p> <p><em>Sources</em></p> <p>Marco Lui and Timothy Baldwin. 2012. Langid.py:</p> <p>An off-the-shelf language identification tool. In Proceedings of the ACL 2012 System Demonstrations,</p> <p>ACL ’12, pages 25–30, Stroudsburg, PA, USA. Association for Computational Linguistics</p>
MA Digital Cultures Dissertation Dataset 2019
<p>This project contains the data, code, and files for my Master dissertation for the MA Digital Cultures at UCC 2018/19. I complied a data set from the Union List of Artist Names (ULAN) online repository (http://www.getty.edu/research/tools/vocabularies/ulan/) with SSMS and created a data visualization with Gephi. The thesis can be found at https://ckdigitalarts.com/dissertation-documentation/.</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.