Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
18,820
datasets available to search
ShareScore release 0.9.0
Dataset results
18,820 results for “northing”
Water Body Checklists 2019: North Atlantic Species List
Species checklists created using effechecka and modified polygons from IHO. The polygons were reduced in resolution.<p></p>List of species collected from the North Atlantic Ocean region using effechecka and a modified polygon from the International Hydrographic Association.
National Checklists 2019: North America 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>List of species from North America inferred from individual country lists that were derived from effechecka and modified geonames polygons
National Checklists 2019: North Korean 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 North Korea collected using effechecka and geonames polygons
National Checklists 2019: North America 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>List of species from North America inferred from individual country lists that were derived from effechecka and modified geonames polygons
Water Body Checklists: North Sea Species List
Species checklists created using effechecka and modified polygons from IHO. The polygons were reduced in resolution.<p></p>List of species collected from the North Sea using effechecka and a modified polygon from the International Hydrographic Association. A filter was applied (based on data from WoRMS) to remove all non-marine taxa.
Water Body Checklists: North Atlantic Species List
Species checklists created using effechecka and modified polygons from IHO. The polygons were reduced in resolution.<p></p>List of species collected from the North Atlantic Ocean region using effechecka and a modified polygon from the International Hydrographic Association.
Water Body Checklists: North Pacific Species List
Species checklists created using effechecka and modified polygons from IHO. The polygons were reduced in resolution.<p></p>List of species collected from the North Pacific Ocean region using effechecka and a modified polygon from the International Hydrographic Association.
Spreadsheet template for Body Size Data for North American Orthopteroid Insects
<p>Body size data for orthopteroid insects extracted from:</p> <p>Vickery, V.R., Kevan, D.K.McE., 1985. The insects and arachnids of Canada, Part 14. The Grasshoppers, Crickets, and Related Insects of Canada and Adjecent Regions. Research Branch Agriculture Canada Publication 1777:1-918.</p>
Body Size Data for North American Spiders
<p>Body size data for North American spiders extracted from The Insects and Arachnids of Canada: <br><br>Dondale, C. D. & Redner, J. H. (1978). The insects and arachnids of Canada, Part 5. The crab spiders of Canada and Alaska, Araneae: Philodromidae and Thomisidae. Research Branch Agriculture Canada Publication 1663: 1-255. <br><br>Dondale, C. D. & Redner, J. H. (1982). The insects and arachnids of Canada, Part 9. The sac spiders of Canada and Alaska, Araneae: Clubionidae and Anyphaenidae. Research Branch Agriculture Canada Publication 1724: 1-194. <br><br>Dondale, C. D. & Redner, J. H. (1990). The insects and arachnids of Canada, Part 17. The wolf spiders, nurseryweb spiders, and lynx spiders of Canada and Alaska, Araneae: Lycosidae, Pisauridae, and Oxyopidae. Research Branch Agriculture Canada Publication 1856: 1-383. <br><br>Platnick, N. I. & Dondale, C. D. (1992). The insects and arachnids of Canada, Part 19. The ground spiders of Canada and Alaska (Araneae: Gnaphosidae). Research Branch Agriculture Canada Publication 1875: 1-297.</p>
Spreadsheet Template for Body Size Data for North American Hemiptera
<p>Body size data for North American Hemiptera extracted from The Insects and Arachnids of Canada:</p> <p>Hamilton, K.G.A., 1982. The insects and arachnids of Canada, Part 10. The Spittlebugs of Canada. Homoptera: Cercpidae. Research Branch Agriculture Canada Publication 1740:1-102.</p> <p>Kelton, L.A., 1978. The insects and arachnids of Canada, Part 4. The Anthocoridae of Canada and Alaska: Heteroptera, Anthocoridae. Research Branch Agriculture Canada Publication 1639:1-101.</p> <p>Kelton, L.A., 1980. The insects and arachnids of Canada, Part 8. The plant bugs of the prairie provinces of Canada (Heteroptera: Miridae). Research Branch Agriculture Canada Publication 1703:1-408.</p> <p>Matsuda, R., 1977. The insects and arachnids of Canada, Part 3. The Aradidae of Canada: Hemiptera: Aradidae. Research Branch Agriculture Canada Publication 1634:1-116.</p>
Spreadsheet Template for Body Length Data for North American Beetles
<p>Body size data for North American beetles extracted from The Insects and Arachnids of Canada:</p> <p>Anderson, R.S., Peck, S.B., 1985. The insects and arachnids of Canada, Part 13. The Carrion Beetles of Canada and Alaska: Coleoptera: Silphidae and Agyrtidae. Research Branch Agriculture Canada Publication 1778: 1-121.</p> <p>Bright, D.E., 1976. The insects and arachnids of Canada, Part 2. The bark beetles of Canada and Alaska: Coleoptera: Scolytidae. Research Branch Agriculture Canada Publication 1576: 1-241. </p> <p>Bright, D.E., 1987. The insects and arachnids of Canada, Part 15. The Metallic Wood-boring Beetles of Canada and Alaska. Coleoptera: Buprestidae. Research Branch Agriculture Canada Publication 1810: 1-335.</p> <p>Bright, D.E., 1993. The insects and arachnids of Canada, Part 21. The Weevils of Canada and Alaska: Volume 1. Coleoptera: Curculionoidea, excluding Scolytidae and Curculionidae. Research Branch Agriculture Canada Publication 1882: 1-217.</p>
Macroscopic, histological and stereological image dataset of Megrim (Lepidorhombus whiffiagonis) ovaries from the ICES Celtic Seas, south of Greater North sea or Bay of Biscay Ecoregions
<p><strong>Contents: </strong></p> <p>This dataset contains the macroscopic and histological images of the ovaries of 202 Megrim (female, <em>Lepidorhombus whiffiagonis</em>, Walbaum, 1792) collected from the ICES Celtic Seas, south Greater North sea or Bay of Biscay Ecoregions (Eco) in November 2019 (n=25; Eco=7h & 7j), November 2020 (n=14, Eco=7h & 7j), December 2020 (n=1, Eco=7h), May 2021 (n=15, Eco=7h & 7g), June 2021 (n=15, Eco=7h), July 2021 (n=15, Eco=7h & 7e), October 2021 (n=15, Eco=7g & 7f), October 2021 (n=6, Eco=8a & 8b & 8c), November 2021 (n=6, Eco=8a & 8b), November 2021 (n=15, Eco=7j), December 2021 (n=15, Eco=7e & 7g), January 2022 (n=15, Eco=7f), February 2022 (n=15, Eco=7g), March 2022 (n=15, Eco=7g) and May 2022 (n=15, Eco=7g).</p> <p> </p> <p><strong>Images:</strong></p> <ul> <li><strong>Macroscopic_pictures.zip: </strong>archive in zip format of 549 pictures (.JPG; 2Mo-8Mo; JPG; 350pp) from 202 female megrim dissected during this study. Each photo was taken with a digital camera (no flash). For each individual, up to three pictures were taken when possible (Le Meleder <em>et al.</em>, 2022) with : <ul> <li>one picture of the entire fish with its abdominal cavity open with the ovaries in view</li> <li>one picture of the whole fish with the ovaries outside of the abdominal cavity</li> <li>one picture of the ovaries</li> <li>the name of the picture is the same as the fish's ID number.</li> </ul> </li> <li><strong>Histology_slides.zip :</strong> archive in zip format containing the ovarian histological slides digitized using an Aperio CS (Scan Scope Console software, v.10.2.0.2352), x20 lens. The whole slide images (.svs) are of the 461 histological slides acquired during this study. </li> </ul> <p> </p> <p><strong>Data:</strong></p> <ul> <li><strong>Readings.zip :</strong> archive in zip format containing the stereology reading results of the ovarian histological slides. In this folder, three directories are available. <ul> <li><strong>Calibration</strong> : Reading results of 3 different agents, with the first and last readings, as well as the QuPath scripts used.</li> <li><strong>Homogeneity</strong> : Reading results for 102 histological slides used to check the cellular homogeneity inter- and intra-gonad. These 102 slides belong to 17 fish, with three histological samples taken in the anterior (1), median (2) and posterior (3) sections of the left (G) and right (D) ovaries. A QuPath folder is also present, containing the scripts used.</li> <li><strong>Total </strong>: Reading results for 202 ovarian histological slides of the median position of either the left or right ovary. One median slide was read per sampled fish. A QuPath folder is also present, containing the scripts used.</li> </ul> </li> <li><strong>Macro_WHI_read_me.txt</strong> : a text file (.txt) listing the acronyms used in the <strong>Macro_WHI.xlsx</strong> file, as well as their meaning.</li> <li><strong>Macro_WHI.xlsx</strong> : Excel file (.xlsx) containing measurements of macroscopic parameters for all 202 fish sampled during this study. The information contained in this table is as follows: <ul> <li>Fish_id: identification of the fish. This id is identical to the name given to the pictures of the full ovaries (<strong>Macroscopic_pictures_Data</strong>)</li> <li>ICES _Division: International Council for the Exploration of the Sea (ICES) division where the fish was sampled in the Food and agricultural Organization of the United nations (FAO) fishing area 27</li> <li>ICES_statistical_rectangle : Statistical rectangle where the fish was sampled within the FAO fishing area 27</li> <li>Date: date the fish was caught (dd/mm/yyyy)</li> <li>Total_fish_length: total length of the fish (cm)</li> <li>Ungutted_fish_weight: total weight of the fish (g)</li> <li>Otolith_ID: unique identification number given to each sampled fish through the Imagine (Ellebode <em>et al.</em>, 2022) software used by IFREMER</li> <li>Parasite: presence (Y) or absence (N) of parasite in or on the fish</li> <li>age: age (in years) of the fish after analysis of the fish's otolith. The IFREMER laboratory of Boulogne-sur-Mer (FRANCE) executed this analysis</li> <li>Visual_maturity : visually estimated maturity, after observation macroscopic criteria of the fish's gonad with the naked eye, following the WKASMSF (ICES, 2018) scale</li> <li>Liver_weight: liver weight (g)</li> <li>Droite_gonad_weight : gonad weight (g) of right ovary</li> <li>Gauche_gonad_weight : gonad weight (g) of left ovary</li> <li>Sections: number of cross sections sampled for the individual</li> </ul> </li> <li><strong>Stereo_WHI_read_me.txt</strong> : a text file (.txt) listing the acronyms used in the <strong>Stereo_WHI.csv</strong> file, as well as their meaning.</li> <li><strong>Stereo_WHI.csv</strong> : a text data file (.csv) of the stereology count results of 287 slides read during this study. Among these slides, 102 were read to test the homogeneity distribution of different cell types found throughout each ovary (17 fish with 6 histological sections : a median, an anterior and a posterior histological section, for both ovaries), slides were read by multiple agents for calibration purposes (see <strong>Calibration</strong> folder for reading results of the 3 agents). Finally, 202 median histological ovarian slides were read. The information contained in this table is as follows: <ul> <li>cell_type: structure identified for one sample point (for the abbreviations, see Heude-Berthelin <em>et al.</em> 2023)</li> <li>idpt: identification number of the sampling point</li> <li>id: unique complex identification number of the sampling point generated by combining the x and y coordinates</li> <li>x: x coordinate of the sampling point</li> <li>y: y coordinate of the sampling point</li> <li>reading: Indicates if the reading data was used to test cellular homogeneity (Homogeneity) or to the sexual maturity phase</li> <li>slideid: identification number of the digitized histological slide that was used for the stereological count. Shares the same 12 first characters with <strong>Fish_id</strong></li> </ul> </li> </ul> <p> </p> <p><strong>Contact :</strong></p> <p>This dataset was established under the MATO (MATurité Objectif des poissons par l'histologie quantitative) project, during the PhD of Carine Sauger (October 2021-2023), financed by France Fillière Pêche (FFP/2020/AM/MF/109), under the supervision of IFREMER (Institut Français de Recherche pour l'Exploitation de la Mer) and BOREA (Biologie des Organismes et Ecosystèmes Aquatiques), and with the collaboration of a research facility from the University of Caen-Normandie : CMABIO3 (Centre de Microscopie Appliquée à la Biologie). For any enquiries, please contact: carine.sauger@gmail.com or laurent.dubroca@ifremer.fr</p>
Two-wave Post-Disaster Survey on Climate Change Attitudes: Texas after Hurricane Harvey and the 2021 North American Winter Storms
<p><strong>Overview</strong></p> <p>This repository contains data needed to reproduce the analysis results from Chen et al. 2024. "Disaster Experience Mitigates the Partisan Divide on Climate Change: Evidence from Texas," <em>Global Environmental Change</em>. It is a study about climate change attitudes and experience with climate disasters across U.S. partisan groups. For details about the data, please see the published paper. Results reproduction code is available at <a href="https://github.com/tedhchen/floodStorm" target="_blank" rel="noopener">https://github.com/tedhchen/floodStorm</a>.</p> <p> </p> <p><strong>Data Set Details</strong></p> <p>`texas_climate_attitudes.csv` contains data from two waves of surveys of Democrats and Republicans living in Texas, with the following groups of variables.</p> <ul> <li>climate change attitudes</li> <li>self-reported exposure to climate disasters</li> <li>scientific information treatment condition and checks</li> <li>political leaning</li> <li>sociodemographics and residential location</li> <li>survey administration details</li> </ul> <p>`outage2021_data.RData` contains power outage data for counties and cities in Texas during Feb. 2020 and Feb. 2021.</p> <p>`outage2021_data_multithreshold.RData` contains power outage data for counties and cities in Texas during Feb. 2020 and Feb. 2021, aggregated to the county level based on different thresholds of uncertainty about which cities people live in.</p> <p>`gtrends_archive.RData` contains Google Trends data for "hurricane", "astros", and "power", in Texas between 2017 and 2021.</p> <p> </p> <p><strong>References</strong></p> <p>Please reference the original study when using this data set.</p> <p>Ted Hsuan Yun Chen, Christopher J. Fariss, Hwayong Shin, Xu Xu. 2024. "Disaster Experience Mitigates the Partisan Divide on Climate Change: Evidence from Texas." <em>Global Environmental Change</em>. <a href="https://doi.org/10.1016/j.gloenvcha.2024.102918" target="_blank" rel="noopener">doi:10.1016/j.gloenvcha.2024.102918</a>.</p>
The North Pacific Eukaryotic Gene Catalog: clustered nucleotide metatranscripts and read counts
<p>This data continues with the development of the NPEGC Trinity <em>de novo</em> metatranscriptome assemblies from the protein data repository of <a href="../doi/10.5281/zenodo.10472589">The North Pacific Eukaryotic Gene Catalog</a>. The nucleotide sequences corresponding to the NPEGC cluster representatives are collected together in these repository files:<br><br><em>NPac.G1PA.bf100.id99.nt.fasta.gz</em><br><em>NPac.G2PA.bf100.id99.nt.fasta.gz</em><br><em>NPac.G3PA.bf100.id99.nt.fasta.gz</em><br><em>NPac.G3PA_diel.bf100.id99.nt.fasta.gz</em><br><em>NPac.D1PA.bf100.id99.nt.fasta.gz</em><br><br>A full description of this data is published in Scientific Data, available here: <a href="https://www.nature.com/articles/s41597-024-04005-5" target="_blank" rel="noopener">The North Pacific Eukaryotic Gene Catalog of metatranscriptome assemblies and annotations</a>. Please cite this publication if your research uses this data:<br><br>Groussman, R. D., Coesel, S. N., Durham, B. P., Schatz, M. J., & Armbrust, E. V. (2024). The North Pacific Eukaryotic Gene Catalog of metatranscriptome assemblies and annotations. <em>Scientific Data</em>, <em>11</em>(1), 1161.<br><br>These nucleotide sequences have been sourced from the Zenodo repository for raw assemblies: <a href="../records/7332796">The North Pacific Eukaryotic Gene Catalog: Raw assemblies from Gradients 1, 2 and 3</a></p> <p>Key processing steps are sampled below with links to the detailed code on the main github code repository: <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog">https://github.com/armbrustlab/NPac_euk_gene_catalog</a></p> <p><br>Code used to build the kallisto indices and map the short reads against indices with kallisto are online in the code repository here: <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog/blob/main/scripts/nt_data/NPEGC.nt_kallisto_counts.sh">NPEGC.nt_kallisto_counts.sh</a><br><br>There are two main steps:<br>1. Generate the kallisto index on the sets of clustered nucleotide metatranscripts<br>2. Map the short reads from environmental samples back to the assembly index</p> <p>As generated above, kallisto generates separate results files for each of the sample files. Even after compression, the total size of the tarballed kallisto output results directories are prohibitively large (>50GB). We use the code in this template R script to join together the 'est_count' estimated count values for the tens of millions of protein sequences in each project metatranscriptome, along with length.</p> <p>The code in this template script was used for each project: <a href="https://github.com/armbrustlab/NPac_euk_gene_catalog/blob/main/scripts/nt_data/aggregate_kallisto_counts.R">aggregate_kallisto_counts.R</a><br>The output count files for each project are Gzip-compressed and uploaded to the NPEGC nucleotide data repository here: </p> <p><em>G1PA.raw.est_counts.csv.gz</em><br><em>G2PA.raw.est_counts.csv.gz</em><br><em>G3PA.raw.est_counts.csv.gz</em><br><em>G3PA_diel.raw.est_counts.csv.gz</em><br><em>D1PA.raw.est_counts.csv.gz</em></p>
Diel-regulated transcriptional cascades of microbial eukaryotes in the North Pacific Subtropical Gyre
<p>Trinity <em>de novo </em>assemblies of 24 poly-A+ selected, combined-replicate metatranscriptomes from HOE-Legacy 2 cruise KM1513 (Jul 24 - Aug 6, 2015). KM1513 cruise information, plots, and associated environmental data for the HOE Legacy II cruise can be found online at <a href="http://hahana.soest.hawaii.edu/hoelegacy/hoelegacy.html">http://hahana.soest.hawaii.edu/hoelegacy/hoelegacy.html</a>. Raw metatranscriptome short-read sequence data is available in the NCBI Sequence Read Archive under BioProject ID PRJNA492142. Code associated with this project is available on Github (<a href="https://github.com/armbrustlab/diel_eukaryotes">https://github.com/armbrustlab/diel_eukaryotes</a>).</p> <p> </p> <p> </p>
Landslide Susceptibility in the North Tanganyika-Kivu Rift Region
<p>The map is derived from the ensemble landslide susceptibility model as presented in the paper entitled "The added value of a regional landslide susceptibility assessment: The western branch of the East African Rift". This work was published in Geomorphology (https://doi.org/10.1016/j.geomorph.2019.106886). Refer to this paper when using this map.</p> <p>The map covers parts of the eastern DRC, Rwanda, and Burundi.</p> <p>The map is provided in .tif format and displays values between 0 (low susceptibility) and 1000 (high susceptibility). The coordinate reference system is EPSG:4326 - WGS84.</p>
Potential tree species distributions from the Last Glacial Maximum in North America
<p>Modern tree distributions modeled under current climate and predicted to past climate.</p> <p>Values of '2' represent presence.</p> <p>The column mark is current presence, while _20000 is 20 ka, _14000 is 14 ka, _13000 is 13 ka, etc.</p> <p>For quick download, the .dbf for each species can be joined to the shapefile (us_can_ecosub). Alternatively, download and use the zipped folder of shapefiles (glac_shapes)..</p>
TAN1808 bathymetry (north)
<pre>Processed multibeam bathymetry data acquired during the TAN1808 research voyage using Kongsberg EM302 multibeam echosounder on the RV Tangaroa. Data are gridded to 25 m. </pre> <p>File Type: Geotiff</p> <p>Coordinate Reference System: EPSG:2193 - NZGD2000 / New Zealand Transverse Mercator 2000 (units: m)</p> <p>Extent: Southwest: 1755587.5, 5333687.5 : Northeast 1927537.5, 5452337.5</p> <p>Pixels: 6878 (width) by 4746 (height)</p> <p>Pixel Size: 25 m</p> <p>Data loading and viewing: Loadable with standard GIS software, like the free open source software QGIS</p>
Ocean drifters from oil-on-water exercise in North Sea (Frigg oil field) June 2019
<p>Ocean drifters from oil-on-water exercise in North Sea (Frigg oil field) June 2019. Described in more detail in Brekke, C., Espeseth, M. M., Dagestad, K.-F., Röhrs, J., Hole, L. R., & Reigber, A. (2021). Integrated analysis of multisensor datasets and oil drift simulations - a free-floating oil experiment in the open ocean. Journal of Geophysical Research: Oceans, 126, e2020JC016499. https://doi.org/10.1029/2020JC016499</p> <p>Work is funded by grant no. 237906 (CIRFA) of the Norwegian Research Council.</p>
Historical digital elevation models (DEMs) and orthoimage mosaics for North American Glacier Aerial Photography (NAGAP) program, version 1.0
<p>This data archive contains digital elevation models (DEMs) and orthoimages generated from scanned historical aerial photographs from the North American Glacier Aerial Photography program available from the NSF Arctic Data Center (ADC, arcticdata.io). </p> <p>The scanned images were preprocessed using the <a href="https://github.com/friedrichknuth/hipp">Historical Image Pre-Processing</a> v0.1 software. Photogrammetric processing was performed with the <a href="https://github.com/friedrichknuth/hsfm">Historical Structure from Motion</a> v0.1 software. </p> <p>All DEM and orthoimage products are provided in the UTM Zone 10N (EPSG:32610) projected coordinate system. Elevation values are in meters above the WGS84 ellipsoid. </p> <p>See <a href="https://www.sciencedirect.com/science/article/pii/S0034425722004850">manuscript</a> and <a href="https://ars.els-cdn.com/content/image/1-s2.0-S0034425722004850-mmc1.pdf">supplement</a> for processing details and further dataset description.</p> <p>This release contains data products for two study sites in Washington state, USA:</p> <p><strong>Mount Baker</strong><br> 1970-09-09<br> 1970-09-29<br> 1974-08-10<br> 1977-09-27<br> 1979-10-06<br> 1987-08-21<br> 1990-09-05<br> 1991-09-09<br> 1992-09-15<br> 1992-09-18</p> <p><strong>South Cascade</strong><br> 1967-09-21<br> 1970-09-29<br> 1974-08-10<br> 1977-10-03<br> 1979-08-20<br> 1979-10-06<br> 1984-08-14<br> 1986-09-05<br> 1987-08-21<br> 1990-09-05<br> 1991-09-09<br> 1992-07-28<br> 1992-09-15<br> 1992-09-18<br> 1992-10-06<br> 1994-09-06<br> 1996-09-10<br> 1997-09-23</p> <p>The 00_thumbnails.jpg provides a quicklook overview at both sites.</p> <p><strong>The DEM and ortho file names are structured as follows:</strong><br> hsfm_NAGAP_[site-name]_[date]_[type].tif</p> <p><strong>For example:</strong><br> hsfm_NAGAP_south-cascade_19670921_ortho.tif</p> <p><strong>Where:</strong><br> [site-name] = Either mount-baker or south-cascade<br> [date] = Image acquisition date in YYYYMMDD format<br> [type] = File type</p> <p><strong>For each DEM and ortho pair, we provide the following:</strong><br> _1m_dem.tif = Digital elevation model posted at 1 m resolution <br> _ortho.tif = Orthoimage mosaic posted at the median image ground sample distance, rounded up to the nearest second decimal place.<br> _metadata.tar.gz = Metadata tarball containing:<br> _ortho_footprints.geojson = Orthoimage mosaic footprint polygons provided in GeoJSON format (EPSG:4326)<br> _dem_footprints.geojson = DEM footprint polygons provided in GeoJSON format (EPSG:4326)<br> _cameras.csv = Image file names, positions, and orientations</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.