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.
275
datasets available to search
ShareScore release 0.9.0
Dataset results
275 results for “debris”
Coarse Woody Debris in Hemlock Removal Experiment at Harvard Forest since 2005
The woody detritus survey is designed to measure coarse woody detritus that includes snags, logs, and stumps, and to estimate fine woody detritus which includes smaller pieces of downed wood. To capture both standing and downed wood, we based our survey around two main types of methods, the line intercept method and the fixed radius plot method. Surveys have been completed for 2005, 2007, 2009, 2011, 2013, 2015, 2017, and 2021.
Mangrove Coast Collaborative Project, Post-hurricane Maria mangrove forest coarse woody debris data, Jobos Bay NERR, March 2022 - August 2022
This dataset describes the quality and size of coarse woody debris (downed woody debris > 7.5 cm in diameter) for each mangrove forest plot in Jobos Bay National Estuarine Research Reserve (NERR) assessed approximately 5 years after disturbance from Hurricane Maria (2017). Data was collected along three 20 m transects beginning at each plot center point and heading toward a randomly-selected azimuth. This dataset is associated with the Mangrove Coast Collaborative project (2020 - 2024).
Mangrove Coast Collaborative Project, Post-hurricane mangrove forest coarse woody debris data, Rookery Bay NERR, February 2022 - March 2023
This dataset describes the quality and size of coarse woody debris (downed woody debris > 7.5 cm in diameter) for each mangrove forest plot in Rookery Bay National Estuarine Research Reserve (NERR) assessed approximately 5 years after disturbance from Hurricane Irma (2017) and concurrent with Hurricane Ian (2022). Data was collected along three 20 m transects beginning at each plot center point and heading toward a randomly-selected azimuth. This dataset is associated with the Mangrove Coast Collaborative project (2020 - 2024).
Mangrove Coast Collaborative Project, Post-hurricane mangrove forest downed woody debris data, Rookery Bay NERR, February 2022 - March 2023
This dataset describes the quantity and size distribution of downed woody debris for each mangrove forest plot in Rookery Bay National Estuarine Research Reserve (NERR) assessed approximately 5 years after disturbance from Hurricane Irma (2017) and concurrent with Hurricane Ian (2022). Data was collected along three 20 m transects beginning at each plot center point and heading toward a randomly-selected azimuth. This dataset is associated with the Mangrove Coast Collaborative project (2020 - 2024).
Mangrove Coast Collaborative Project, Post-hurricane Maria mangrove forest downed woody debris data, Jobos Bay NERR, March 2022 - August 2022
This dataset describes the quantity and size distribution of downed woody debris for each mangrove forest plot in Jobos Bay National Estuarine Research Reserve (NERR) assessed approximately 5 years after disturbance from Hurricane Maria (2017). Data was collected along three 20 m transects beginning at each plot center point and heading toward a randomly-selected azimuth. This dataset is associated with the Mangrove Coast Collaborative project (2020 - 2024).
Forest tree, woody debris, root ingrowth, soil respiration and characterization data from long-term research plots for LTREB at the University of Michigan Biological Station
The NSF-funded project "LTREB: Drivers of temperate forest carbon storage from canopy closure through successional time" (2014-2024) supports research to meet the following goals: 1) elucidate mechanisms responsible for changes in C storage over decades to centuries; 2) link processes leading to persistence and resilience of forest C storage following disturbance; 3) quantify the effects of potential drivers such as forest structure, N availability, climate change, and atmospheric deposition on decadal and longer-term trajectories of C storage. Field activities for this research are conducted at the University of Michigan Biological Station (UMBS) on a pair of chronosequences and several old reference forests. Synthesis activities utilize data collected from these field sites in support of the LTREB project, as well as data synthesized from other sources (e.g., long-term UMBS plot data, AmeriFlux data, FIA data) all intended to address the core questions of the LTREB project. This dataset has been compiled and expanded over a series of versions, with new data types and observations appended periodically. Presently, the dataset includes observations from tree inventory censuses, woody debris sampling, fine root ingrowth cores, soil respiration measurements, and two sets of soil collections aimed at quantifying a range of physical, chemical, and biological properties of soil.
Tree Growth and Coarse Woody Debris in Regenerating Forests at Harvard Forest since 2008
This project is a field-based study to measure sequestration of atmospheric carbon dioxide in a regenerating New England forest. This study established long-term biometric plots suitable for measuring changes in carbon storage through time in three forest stands: an early-20th-century conifer plantation, a naturally regenerating former conifer plantation harvested in the 1990s, and a conifer plantation scheduled for harvest next winter. The first three years of this project determined the initial carbon budget of these forest stands, measured carbon fluxes into and out of these stands, and laid the groundwork for future investigations. Subsequent years will investigate larger-scale questions, such as how successional patterns affect carbon sequestration, and how these patterns change with stand age. The work also addresses how forestry practices influence carbon sequestration, and provide guidance for how forest management could enhance terrestrial carbon uptake in the future.
Coarse Woody Debris in the Clearcut Site at Harvard Forest 2010
The woody debris survey was designed to quantify the baseline amount of woody debris within the clearcut site, including coarse and fine woody debris and stumps. Coarse woody debris and stumps were measured using the plot method, while fine woody debris was measured using the line intercept method. Our woody debris survey methods are detailed below. An initial or baseline survey was completed in 2010.
Respiration of Coarse Woody Debris in the Clearcut Site at Harvard Forest in 2011
This study explored the effects of log position and microclimate variability on the rates of coarse woody debris (CWD) respiration. The rates of respiration of downed Norway spruce (Picea abies) logs were repeatedly measured in-situ using an LI-6200 gas analyzer. Treatments included native logs in the clearcut site, native logs in a neighboring mature spruce stand, and logs transferred from the clearcut site to the mature spruce stand.
North Temperate Lakes LTER Northern Highland Lake District Coarse Woody Debris Logs
Coarse woody debris (CWD) is an important, but often neglected, component of lake ecosystems. It is ecologically valuable because it creates littoral habitat complexity but it is susceptible to manipulation by riparian process, in particular removal by property owners. The objective of this study is to determine the spatial scales at which human and environmental factors contribute to coarse woody debris input and output dynamics. Coarse woody debris, boat docks, and riparian trees (with the potential of becoming CWD) around the five lakes of the NTL-LTER site (Trout Lake, Allequash Lake (north basin), Sparkling Lake, Crystal Lake, and Big Muskellunge Lake) were measured in 1996 and 1997. CWD was defined as logs: greater than 2 m length, greater than 15 cm diameter, mostly submersed in lake, less than 25 m from shore, and less than 2 m water depth. Locations were determined as average of greater than 30 dGPS positions. Numbered aluminum tags were attached to each log to facilitate the long-term study of CWD. Return visits to Sparkling and Trout Lakes in 1997 found some tags had been removed by ice or vandals. Heavier tags were attached to these logs. The 1997 re-survey and tag check was not complete.
North Temperate Lakes LTER Northern Highland Lake District Coarse Woody Debris Trees
Coarse woody debris (CWD) is an important, but often neglected, component of lake ecosystems. It is ecologically valuable because it creates littoral habitat complexity but it is susceptible to manipulation by riparian process, in particular removal by property owners. The objective of this study is to determine the spatial scales at which human and environmental factors contribute to coarse woody debris input and output dynamics. Coarse woody debris, boat docks, and riparian trees (with the potential of becoming CWD) around the five lakes of the NTL-LTER site (Trout Lake, Allequash Lake (north basin), Sparkling Lake, Crystal Lake, and Big Muskellunge Lake) were measured in 1996 and 1997. Riparian trees with the potential of becoming CWD were measured in Feb. 1997. Locations were determined by differential GPS (greater than 10 points per tree) and diameters were measured as diameter-at-breast-height (dbh) using a "cruising stick" according to the Scribner 78 scale (Philip 1994). Substantial snow cover made nominal "breast height" approximately 200 cm. The entire shores of Crystal and Sparkling Lakes were sampled. Shorelines on the other lakes were selected to represent developed and undeveloped conditions. Approximately 31 percent% (19/61 km) of the total shoreline of the five lakes was surveyed.
North Temperate Lakes LTER Northern Highland Lake District Coarse Woody Debris Shoreline Development Index
Coarse woody debris (CWD) is an important, but often neglected, component of lake ecosystems. It is ecologically valuable because it creates littoral habitat complexity but it is susceptible to manipulation by riparian process, in particular removal by property owners. The objective of this study is to determine the spatial scales at which human and environmental factors contribute to coarse woody debris input and output dynamics. Coarse woody debris, boat docks, and riparian trees (with the potential of becoming CWD) around the five lakes of the NTL-LTER site (Trout Lake, Allequash Lake (north basin), Sparkling Lake, Crystal Lake, and Big Muskellunge Lake) were measured in 1996 and 1997. Shorelines were characterized using a qualitative shoreline development index (SDI). The index included: (1) developed and devoid of riparian trees (i.e. lawn, boat launch), (2) few widely spaced trees, (3) some riparian trees and some understory, (4) substantial forest cover, and (5) undeveloped and heavily forested. All 5 lakes were surveyed in June/July 1996. Endpoint positions were determined by greater than 30 dGPS points. Shoreline data were subsequently divided into 10 m segments.
North Temperate Lakes LTER Northern Highland Lake District Coarse Woody Debris Docks
Coarse woody debris (CWD) is an important, but often neglected, component of lake ecosystems. It is ecologically valuable because it creates littoral habitat complexity but it is susceptible to manipulation by riparian process, in particular removal by property owners. The objective of this study is to determine the spatial scales at which human and environmental factors contribute to coarse woody debris input and output dynamics. Coarse woody debris, boat docks, and riparian trees (with the potential of becoming CWD) around the five lakes of the NTL-LTER site (Trout Lake, Allequash Lake (north basin), Sparkling Lake, Crystal Lake, and Big Muskellunge Lake) were measured in 1996 and 1997. Boat docks were located on all 5 lakes. Docks were verified in 1997 using digital orthophotos. GPS positions were adjusted to coincide with the photos. Many of the docks were photographed with a digital camera.
Supraglacial features of debris covered glaciers in the Himalaya from Landsat-8 spectral umixing and Pleiades
<p>This dataset contains the spectral unmixing output files for the debris covered glacier surfaces based on Landsat-8 OLI imagery and Pleiades imagery of 2015. Files are provided for two domains, the Khumbu reference region of Nepal and the greater Himalaya region (76.3 to 92.6° W and 26.3 to 34.2° N), which covers covering most area from Himachal/Jammu and Kashmir border to Bhutan Himalaya. </p> <ul> <li>Landsat surface reflectance : Himalaya_L8_6S_surface_reflectance_scenes_2015 .zip <ul> <li>Contains surface reflectance images of Landsat-8 OLI scenes mostly from 2015 (two images are from 2014 and 2016 due to clouds in 2015) </li> <li>Collection 1 Level 1 (L1TP)</li> <li>Atmospherically and topographically corrected using the ARCSI routine, supplied in .kea format. These can be converted to GeoTifs using the GDAL command.</li> <li>Naming structure: LS8_yyyymmdd_latYYlongXXXX_rRRpPPP_vmsk_topshad_rad_srefdem_stdsref.kea</li> <li>Projection is UTM (zones depending on the image), from the original Landsat L1TP files</li> <li>The file naming convention, which is a standard output from ARCSI routine, include the image date ("yyyy" = year, mm = "month", "dd" = day), latitude ("YY") and longitude ("XXXX") of the image center, path/row ("PPP" = path, "RRR" = row), and the output products generated by ARCSI ("rad" = radiation, "topshad" = topographic shadows, "srefdem" indicates the use of elevation data, "stdsref" = standardized surface reflectance)</li> </ul> </li> <li>Fractional maps for the Khumbu: LS8_20150930_r41p140_frac_files. zip <ul> <li>Raster format (GeoTiffs) </li> <li>Non-normalized fractional water, light and dark debris and vegetation maps for the Khumbu reference image (Sept 30, 2015, path 140 row 40)</li> <li>Output from the linear mixing model routine used to produce binary maps of surfaces with values ranging from 0 to 1 (0% to 100% pixel coverage)</li> </ul> </li> <li>Binary surface maps for the Himalaya: Himalaya_L8_raw_binary_surface_maps.zip <ul> <li>Vector format (ArcGIS shapefiles)</li> <li>Raw, unprocessed binary maps of ponds, vegetation debris, ice and clouds over the debris covered glacier tongues in the Himalaya around the year 2015 (binary files) </li> <li>Derived from tresholding the fractional maps using a variable threshold (see publication)</li> <li>Maps in this pre-release version have not been manually corrected for misclassified areas due to confusion of classes, and the ice and cloud classes are not highly accurate</li> <li>These are not the final coverages of these surfaces over the domain and should not be used as such</li> <li>The supraglacial pond maps will undergo manual corrections and the datasets will be updated on this page</li> </ul> </li> <li>Dataset for analysis, glacier-by-glacier: Himalaya_SDC_LS_for_analysis_gt1km2_with_frac_and_debris_attributes.txt <ul> <li>original data from the SupraGlacial Debris Cover dataset (Sherler et al 2018)</li> <li>updated with the preliminary fractional cover of each surface (in %) on a glacier-by-glacier basis</li> <li>contains only debris covered tongues >1 km2 </li> <li>debris covered attributes were calculated from the ALOS Global Digital Surface Model (AW3D30 DEM) for each debris covered tongue <ul> <li>DC_area_km2 = recalculated debris covered area</li> <li>DCmin = minimum debris cover elevation (meters)</li> <li>DCmax = maximum debris cover elevation (meters)</li> <li>DCrange = altitudinal range (meters)</li> <li>DCmed = median elevation (meters)</li> <li>SLmean = mean slope (degrees)</li> <li>SLrange = slope range (degrees)</li> <li>SLmin = min slope (degrees)</li> <li>SLmax = max slope (degrees)</li> </ul> </li> </ul> </li> </ul>
DebDaB: A database of supraglacial debris thickness and physical properties
<p><strong>DebDaB: A database of supraglacial debris thickness and physical properties</strong></p> <p>DebdaB is a database of measured and reported physical properties and thickness of supraglacial debris that is openly available and open to community submissions.</p> <p>The majority of the database (90%) is compiled from 172 sources in the literature, and the remaining 10% has not been published before. DebDaB contains 8,286 data entries for supraglacial debris thickness, of which 1,852 entries also include sub-debris ablation rates, 167 data entries of thermal conductivity of debris, 157 of aerodynamic surface roughness length, 77 of debris albedo, 56 of debris emissivity and 37 of debris porosity. The data are distributed over 83 glaciers in 13 regions in the Global Terrestrial Network for Glaciers. </p> <p>This is version 2 of the dataset, corresponding to the revised version of the database after peer-review of its accompanying "Data descriptor manuscript" submitted for publication to the scientific journal "Earth System Science Data (ESSD)" from Copernicus Publications. The preprint is available at <a href="https://doi.org/10.5194/essd-2024-559">https://doi.org/10.5194/essd-2024-559 </a></p> <p>DebDaB version 2 consists of the following files:</p> <ul> <li>DebDaB_v2.zip : The actual DebDaB database, provided as a navigable Open Document Spreadsheet (.ods) with spreadsheet tabs for each of the debris properties. Additionally, the database is also provided as separate .csv files for each debris property, and as a GeoPackage (.gpkg). </li> <li>Readme_files.zip: A .txt file for each of the debris property tabs, describing all the fields in each tab. </li> <li>Templates_for_data_submission.zip: Templates (.csv files and additionally .xlsx files) for data submission for each of the debris properties in DebDaB. Data submissiosn to DebDaB should be sent to debriscoveredglaciers@ista.ac.at. </li> <li>DebDaB_data_sources.pdf: List of DebDaB sources from published literature. </li> <li>DebDaB_data_sources.bib: BibTeX list of DebDaB sources from published literature. </li> <li>Manuscript_codes.zip: The codes to download and process the data to generate the figures for data descriptor manuscript on ESSD.</li> </ul> <p>The data descriptor manuscript is in open review stage at: <a href="https://essd.copernicus.org/preprints/essd-2024-559/">https://essd.copernicus.org/preprints/essd-2024-559/ </a></p> <p><strong>DebDaB is open to new data submissions</strong>, and therefore future data submissions of previously unpublished data to DebDaB will entail co-authorship on the DebDaB database on Zenodo. </p> <p>According to the authors’ understanding of FAIR principles, authors of published literature and published data, that:</p> <ul> <li>Correct existing data within DebDaB, in case of errors</li> <li>Send the raw data from digitised figures</li> <li>Submit additional data that was previously unavailable (for example, accurate coordinates or additional data or metadata which is not already available)</li> </ul> <div>will have the right to be added as co-authors on the database in Zenodo. The authors are working to reevaluate their policies to conform to changes or unusual circumstances in authorship contributions, and are happy to involve eager people in the core team.</div> <div> </div> <div><strong>How to submit data: </strong>Please use the templates provided in the database files for data submissions and send it to debriscoveredglaciers@ista.ac.at. Authors who submit data will be asked to fill in a form regarding authorship contributions. </div> <p><strong>Important note on citations:</strong> DebDaB data users must cite the data descriptor manuscript (Fontrodona-Bach et al. 2025), the DebDaB zenodo repository<br>(Groeneveld et al., 2025), <strong>and the original data sources</strong> when using the database, given that DebDaB is mostly<br>a compilation of previously published data. To facilitate the citations of original data sources, each of the data entries in DebDaB contains the corresponding<br>original reference and corresponding DOI.</p> <p><strong>Manuscript citation:</strong> Fontrodona-Bach, A., Groeneveld, L., Miles, E., McCarthy, M., Shaw, T., Melo Velasco, V., and Pellicciotti, F.: DebDaB: A database of supraglacial debris thickness and physical properties, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2024-559, in review, 2025.</p> <p><strong>Zenodo citation:</strong> Groeneveld, L., Fontrodona-Bach, A., Miles, E., McCarthy, M., Melo Velasco, V., Shaw, T., Pellicciotti, F., Bauder, A., Buri, P., Kneib, M., Kumar, A., Mishra, A., & Petersen, L. (2025). DebDaB: A database of supraglacial debris thickness and physical properties (Version v2) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.14514803" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.</a><a href="https://doi.org/10.5281/zenodo.14224835" target="_blank" rel="noopener">14224835</a></p> <p><strong>Original data sources citation:</strong> See <em>DebDaB_data_sources.pdf</em> or <em>DebDaB_data_sources.bib</em></p> <p>The authors acknowledge the Debris-Covered Glaciers Working Group (DCGWG) from the International Association of Cryospheric Sciences (IACS) for setting the stage and drawing together the debris-covered glaciers community to focus on broader needs transcending a specific research topic, and starting the zenodo community on debris-covered glaciers, where this database is hosted. </p> <p><strong>Author contributions: </strong>The following spreadsheet states the contribution of each of the co-authors on the database: <br><a href="https://docs.google.com/spreadsheets/d/1nTieH_ZkwqnUpHQMYn7bygEcV5RzX4DJuqZ_qd-_PzE/edit?usp=sharing" target="_blank" rel="noopener">Author contributions statement (click here)</a></p> <p>A description of what each contribution field means is below:</p> <ul> <li><em>Conceptualisation:</em> This refers to the original idea and shaping of the database and is therefore closed.</li> <li><em>Data curation:</em> The data managers of DebDaB. Primarily the quality checks and curation done to all the collected published and unpublished data. It may also include authors who have compiled a lot of measurements from sources the authors did not have, and merged them into DebDaB, or if someone else takes on the role of ingesting/homogenizing data in the future.</li> <li><em>Data collection: </em>Field measurements as well as scouring past literature that the authors have missed, digitising sources, or advocating for old missing data sources to be entered into DebDaB.</li> <li><em>Formal analysis:</em> In the case of methods being applied to derive debris property values from other measurements, such as the case for surface roughness and thermal conductivity.</li> <li><em>Supervision/funding: </em>This refers to funding provided for the generation of DebDaB itself, but also funding for the data collection (measurements). </li> </ul>
Database - Bridge clogging and debris - July 2021 flood
<p><span>This dataset documents 71 floating debris accumulations at bridges following an extreme hydrological event that hit Belgium and Germany in July 2021. Data were collected from various sources including public authorities’ documents, public online database, post event pictures and field visits. The dataset covers bridge geometry, flood conditions and debris accumulation. In particular, it systematically details deposits dimensions and classifies deposits components, which contain a significant portion of man-made objects, in addition to driftwood. </span></p> <p><span>The dataset is stored in a single CSV file, with semicolon separator. The file contains 72 lines and 63 columns. First line contains the label of the columns parameters. Each of the 71 following lines contains the data of one bridge and corresponding accumulation. </span></p> <p><span>A data descriptor is under review in Nature Scientfic Data: <br>Erpicum S., Poppema D., Burghardt L., Benet L., Wüthrich D., Klopries E., Dewals B., (submitted) A dataset of floating debris accumulation at bridges after July 2021 Flood in Germany and Belgium, Nature Scientific Data<br></span></p>
Data and Models from the study entitled, "Large-area automatic detection of shoreline stranded marine debris using deep learning"
<p>This repository contains data and models used in the study entitled, "Large-area automatic detection of shoreline stranded marine debris using deep learning". This study can be accessed as an open access publication at the following location: https://doi.org/10.1016/j.jag.2023.103515.</p> <p>The data set is comprised of 1,587 images (512 pixels x 512 pixels) which contains 10,703 individual bounding box labels of marine debris objects. The imagery was collected over the State of Hawai'i in 2015 at 2 centimeter resolution (ground spacing distance).</p> <p>The classification scheme consists of 8 labeled classes: unidentified object, processed wood, metal, vessel, net/cloth, buoy, tire, and line fragments.</p>
Fish and crayfish density and count data for Peeks Creek, Macon County, NC, USA 2005-2014, 2019, and 2022 following a catastrophic debris flow, as well as six reference streams
We followed the process of recovery of the fish and crayfish assemblage in Peeks Creek, a high-gradient second order stream in the Little Tennessee River watershed of North Carolina, after a debris flow devastated the channel and its riparian zone. After 15 years, the fish assemblage had recovered, and the channel and riparian zone had stabilized. Of the three major components of the fish assemblage, Rainbow Trout (Oncorhynchus mykiss (Walbaum)), a strong swimmer, reappeared in year 1. Longnose Dace (Rhinichthys cataractae (Valenciennes in Cuvier and Valenciennes)) reappeared in year 3. Mottled Sculpin (Cottus bairdii Girard), a weak swimmer, did not become established until year 6 and only resumed expected abundance in year 9. Appalachian Brook Crayfish (Cambarus bartonii cavatus Hay) numbers recovered quickly, though only one individual was found the year following the debris flow. Unassisted natural recovery occurred after a costly engineered restoration project had been rejected and arguably represents the preferable solution. However, recovery of the fish assemblage may not have been achieved if the stream flowed directly into an impoundment or low gradient river that lacked the source of species for recolonization, or if the stream had been located above a barrier to upstream movement.
Fine woody debris inventory data from reference stands and inventory plots in the Pacific Northwest, 1992 to 2000
These data provide an inventory of the mass of downed fine woody debris stored within various forest types. This data is used to determine total organic matter, carbon, and nutrient stores in forests.
Fire Self-Limitation (FiSL) Experiment: Quantifying Wildfire Carbon Combustion Losses in boreal Deciduous and Mixed Forests in Interior Alaska and the Boreal Cordillera VII: Coarse and Fine Woody Debris Inventory 2022
This dataset contains characteristics of coarse woody debris and snags collected in the field for plots in 8 fire scars in Interior Alaska and the Yukon. Data was collected in the summer of 2022. Fire scars sampled included Shovel Creek (2019), Aggie Creek (2015), Hess Creek (2019), Baker (2015), Munson Creek (2021), Isom Creek (2020), 2019MA014 (2019), and 2019BC005 (2019).
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.