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.
1,989
datasets available to search
ShareScore release 0.7.1
Dataset results
1,989 results for “fires”
Monthly lake water quality data (May-September 2022) following the Greenwood Fire in northeastern Minnesota v1.0
<p>This repository contains lake water quality responses to the 2021 Greenwood Fire in Superior National Forest, Minnesota, USA (near Isabella, MN in northeastern MN). Thirty lakes (15 burned watershed, 15 control) were sampled monthly from May-September 2022 along various fire disturbance gradients (e.g., % watershed burned) and in relation to hydrologic connectivity (i.e., drainage vs. isolated lakes). Much of the non-water quality data we used came from published sources, which are described and referenced below. This repository also contains R code used to analyze and visualize data, as well as some output figures.</p>
Ukraine Fire Perimeters 2022
<p>The data set contains the fire perimeters for Ukraine for 2022 sourced from remote sensing data. The locations and dates of burning were detected using MODIS/VIIRS products on thermal anomalies. This information was used to select pre- and post-fire Copernicus Sentinel 2 L2A imagery. Satellite images were screened from clouds, cloud shadows and combined into median composite mosaics. The image mosaics were created using all available imagery within a 14-day time window before (pre-fire mosaic) and after (post-fire mosaic) each fire. Fire perimeters were visually delineated by comparing post and pre-fire image mosaics using a SWIR2–NIR–Red band combination. The spatial accuracy of fire perimeters corresponds to Sentinel 2 data at 20-m spatial resolution.</p> <p>Delineated fire perimeters were intersected with the Copernicus Dynamic Land Cover map at 100 m resolution (v.3.0.1) to extract burned areas of five land cover classes according to the following reclassification scheme of the original pixel values.</p> <table> <tbody> <tr> <td> <p><strong>Land cover class</strong></p> </td> <td> <p><strong>Original pixel values</strong></p> </td> </tr> <tr> <td> <p>Coniferous forest (LC_1)</p> </td> <td> <p>111</p> </td> </tr> <tr> <td> <p>Broadleaved forest (LC_2)</p> </td> <td> <p>112,113,114,115,116</p> </td> </tr> <tr> <td> <p>Other natural landscape (LC_3)</p> </td> <td> <p>121,124,125,126, 20,30,60,90</p> </td> </tr> <tr> <td> <p>Agricultural land (LC_4)</p> </td> <td> <p>40</p> </td> </tr> <tr> <td> <p>Settlement (LC_5)</p> </td> <td> <p>50</p> </td> </tr> </tbody> </table> <p><strong>MetaData</strong></p> <table> <tbody> <tr> <td> <p>Field name</p> </td> <td>Description</td> </tr> <tr> <td>id</td> <td>Unique identifier of each fire perimeter</td> </tr> <tr> <td>longitude</td> <td>Longitude referring to centroids of fire perimeters</td> </tr> <tr> <td>latitude</td> <td>Latitude referring to centroids of fire perimeters</td> </tr> <tr> <td>date</td> <td>Date of burning in the format DD.MM.YYYY</td> </tr> <tr> <td>year</td> <td>Year</td> </tr> <tr> <td>month</td> <td>Month</td> </tr> <tr> <td>day</td> <td>Day of the month</td> </tr> <tr> <td>week</td> <td>Week number in the year</td> </tr> <tr> <td>reg</td> <td>The capital city name of the Ukrainian regions (oblast) associated with each fire</td> </tr> <tr> <td>occupied</td> <td>A binary indicator variable referring to the locations of each fire within the Russian-occupied territory (1) or within the territory controlled by the Government of Ukraine (0) for a given date</td> </tr> <tr> <td>buff_30km</td> <td>A binary indicator variable referring to the location of each fire within a 30-km buffer zone on both sides of the front line. In contrast to a daily progression front line used to detect "occupied" territory, the buffer was calculated using the farthest position of a frontline towards territories controlled by the Government of Ukraine</td> </tr> <tr> <td>emerald</td> <td>A binary indicator variable referring to locations of each fire within the Emerald network</td> </tr> </tbody> </table> <p> Burned areas by land cover (LC) type (in hectares) within the fire perimeter according to the Copernicus Dynamic Land Cover map at 100 m resolution (v.3.0.1)</p> <table> <tbody> <tr> <td>LC_0</td> <td>N/A</td> </tr> <tr> <td>LC_1</td> <td>Coniferous forest</td> </tr> <tr> <td>LC_2</td> <td>Broadleaved forest </td> </tr> <tr> <td>LC_3</td> <td>Other natural landscape</td> </tr> <tr> <td>LC_4</td> <td>Agricultural land </td> </tr> <tr> <td>LC_5</td> <td>Settlement</td> </tr> </tbody> </table>
Analysis of EV Fires from Accesible Public Domain Data
<p>The incidents of EV fires have been collated from publicly accessible data, aiming to offer insights into potential EV fires in the future. The dataset also includes causes as determined from the reports analyzed.</p>
Fire Season Multi-Resolution Database
<p>In the realm of wildfire research and analysis, the need for comprehensive and adaptable datasets has never been more critical. To address this imperative, we introduce the "Fire Season Multi-Resolution Database." This meticulously curated dataset represents a significant advancement in the realm of wildfire data, offering a versatile, multi-resolution approach to understanding the intricate dynamics of fire seasons.</p> <p>The Fire Season Multi-Resolution Database is a set of geospatial earth grids, thoughtfully designed to accommodate diverse research needs by providing information at varying levels of detail. Within each grid, a wealth of data is embedded, concerning fire seasons and their comprehensive characterizations at every individual pixel.</p> <p>Within each pixel of these multi-resolution grids, a set of nine variables about their respective fire seasons can be found.<br> </p> <ul> <li> FsOrNot (int): a binary variable (0,1) that contains information whether a pixel has a fire season or not </li> <li> MainStart (int): Starting month of the fire season </li> <li> MainEnd (int) : Ending month of the fire season </li> <li> SecondStart (int): Start month of a possible secondary fire seasson (if it is bimodal) </li> <li> SecondEnd (int) : End month of the secondary fire seasson </li> <li> Length (int): Months that lasts the fire season </li> <li> C (float): Seasonal concentration of the fire seasson </li> <li> P (float): Seasonal phase or timming of the fire season </li> <li> FBA (float): Fraction of Burneable Area </li> </ul> <p> </p> <p>Github used to build these files: </p> <p>https://github.com/delatorre96/Development-of-a-multi-resolution-fire-season-database-on-a-global-scale</p> <p>Finally, the sources of information used to build this dataset is the Copernicus project, specifically the web page: https://cds.climate.copernicus.eu/cdsapp#!/dataset/satellite-fire-burned-area?tab=overview. This dataset has been constructed with the aim of enhancing wildfire research and aiding in the development of effective wildfire management and mitigation strategies. </p>
Forest fire assessement training dataset (2022-07-18 fire at Maclas - France)
<p>This dataset has been created to train Univ. Eiffel personnels on raster data handling with QGIS.</p><p>It provides the following elements:</p><ul><li>Geopackage database with the following layers:<ul><li>QGIS project</li><li>Extract from the SENTINEL-2 2022-06-11 B8A band</li><li>Extract from the SENTINEL-2 2022-06-11 B12 band</li><li>Extract from the SENTINEL-2 2022-07-21 B8A band</li><li>Extract from the SENTINEL-2 2022-07-21 B12 band</li><li>Reclassified delta NBR raster layer</li><li>Delta NBR vector layer</li><li>Studied area bounding box</li></ul></li><li>Intermediate results:<ul><li>pre-event NBR raster file</li><li>post-event NBR raster file</li><li>Delta NBR raster file</li><li>Delta NBR raster file multiplied by 1000 (for easier reclassification)</li></ul></li></ul><p>Data sources IDs from opensearch-theia.cnes.fr-sentinel2-l2a catalogue :</p><ul><li>SENTINEL2B_20220721-104826-811_L2A_T31TFL_D</li><li>SENTINEL2B_20220611-104824-395_L2A_T31TFL_D</li></ul><p> </p>
Young forests and fire: Using lidar-imagery fusion to explore fuels and burn severity in a subalpine forest reburn, Grand Teton National Park, Wyoming.
Anticipating fire behavior as climate change and fire activity accelerate is an increasingly pressing management challenge in fire-prone landscapes. In subalpine forests adapted to infrequent, stand-replacing fire, self-limitation of burn severity in short-interval fire is incompletely understood. Spatially explicit fuels data can support assessments of landscape-scale fire risk and fuels feedbacks on burn severity. For a about 1,450 km2 largely forested landscape in the US Northern Rocky Mountains, we used airborne lidar and imagery to predict and map canopy and surface fuels. In a fire that burned mature ( greater than 125-year-old) and also reburned young (~30-year-old) subalpine forest, we then asked: (1) How do pre-fire fuels and burn severity compare between young and mature forests that burned under similar fire weather conditions? (2) How well do pre-fire fuels and forest structure predict burn severity under extreme versus moderate fire weather? Lidar-imagery fusion predicted fuel characteristics with high accuracy across forest and shrubland vegetation (R2 from 0.65-0.95). Young post-fire forests had abundant, densely packed canopy fuels, and both young and mature forests had similar canopy fuel loads and coarse wood biomass. Under similar weather conditions, young and mature forests burned at similar severity. Overall, fuels were weak predictors of burn severity and, surprisingly, better predicted severity under extreme (R2LMM(m) = 0.27) rather than moderate (R2LMM(m) = 0.15) fire weather. Our findings are relevant for subalpine landscapes increasingly dominated by young lodgepole pine (Pinus contorta var. latifolia) forests vulnerable to short-interval fire and provide a benchmark to assess how fuels influence burn severity in future fires. Fire managers should continually reassess fuels and update expectations about fire behavior as landscapes change. Although recovering post-fire forests can limit fire spread and severity for a period of time, our resu
Long-term response of wetland plant communities to management intensity, grazing abandonment, and prescribed fire
Isolated, seasonal wetlands within agricultural landscapes are important ecosystems. However, they are currently experiencing direct and indirect effects of agricultural management surrounding them. Because wetlands provide important ecosystem services, it is crucial to determine how these factors affect ecological communities. Here, we studied the long-term effects of land use intensification, cattle grazing, prescribed fires, and their interactions on wetland plant diversity, community dynamics, and functional diversity. To do this, we used vegetation and trait data from a 14-year-old experiment on 40 seasonal wetlands located within semi-natural and intensively managed pastures in Florida. These wetlands were allocated different grazing and prescribed fire treatments (grazed vs. ungrazed; burned vs. unburned). Our results showed that wetlands within intensively managed pastures have lower native plant diversity, floristic quality, evenness, higher non-native species diversity, and exhibited the most resource-acquisitive traits. Wetlands embedded in intensively managed pastures were also characterized by lower species turnover over time. We found that 14 years of cattle exclusion reduced species diversity in both pasture management intensities and had no effect on floristic quality. Fenced wetlands exhibited lower functional diversity and experienced a higher rate of community change both due to an increase in tall, clonal, and palatable grasses. The effects of prescribed fires were often dependent on grazing treatment. For instance, prescribed fires increased functional diversity in fenced wetlands but not in grazed wetlands. Our study suggests that cattle exclusion and prescribed fires are not enough to restore wetlands in intensively managed pastures and further highlights the importance of not converting semi-natural pastures to intensively managed pastures. Our study also suggests that grazing levels applied in semi-natural pastures maintained high plant dive
Less fuel for the next fire? Short-interval fire delays forest recovery and interacting drivers amplify effects, Greater Yellowstone Ecosystem, Montana and Wyoming, USA
As 21st-century climate and disturbance dynamics depart from historical baselines, ecosystem resilience is uncertain. Multiple drivers are changing simultaneously, and interactions among drivers could amplify ecosystem vulnerability to change. We explored how interacting drivers affected post-fire recovery of subalpine forests, which Subalpine forests in Greater Yellowstone (Northern Rocky Mountains, USA) were historically resilient to infrequent (100-300 year), severe fire., in Greater Yellowstone (Northern Rocky Mountains, USA). We sampled paired short- (< 30 year) and long- (> 125 year) interval post-fire plots most recently last burned between 1988 and 2018 to address two questions: (1) How do short-interval fire, climate, topography, and distance to unburned live forest edge and other factors (topography, distance to live edge) interact to affect post-fire forest recoveryregeneration? (2) How do forest biomass and fuels vary following short- versus long-interval severe fires? Mean post-fire live stem density was an order of magnitude lower following short- versus long-interval fires (3,240 versus 28,741 stems ha-1, respectively). Differences between paired plots increased with greater climate water deficit normal (ρ = 0.67) and were amplified at longer distances to live forest edge. Surprisingly, warmer-drier climate was associated with higher seedling densities even after short-interval fire, likely relating to regional variation in serotiny of lodgepole pine (Pinus contorta var. latifolia). Unlike conifers, density of aspen (Populus tremuloides), a deciduous resprouter, increased with short- versus long-interval fire (mean 384 versus 62 stems ha-1, respectively). Live biomass and canopy fuels remained low nearly 30 years after short-interval fire, in contrast to rapid recovery after long-interval fire, suggesting that future burn severity may be reduced for several decades following reburns. Short-interval plots also had half as much dead woody biomass compar
Plant abundance data from the 2016 Chimney Tops 2 Fire in Gatlinburg, TN
We surveyed understory plant communities during the second growing season (2018) after the 2016 fire at sites in WUI near Gatlinburg (hereafter “exurban”) and in GSMNP (hereafter "natural"). We chose sites based on dominant forest vegetation type (available for GSMNP) and elevation to minimize the potential confounding effects of these variables. We used stratified random sampling in ESRI ArcMap to select 18 sites, nine in natural locations and nine in exurban locations; within the location type we randomly selected sites to represent fire severity categories, three no burn, three low/medium burn, and three high burn. In the field, we randomly selected two 1x1 m permanent plots to survey and identify each individual plant in the understory to at least genus level, and to count the number of individuals for each taxon. We generated taxa lists and count of individuals per taxa by aggregating plot level records by month. Individuals that could not be identified to at least genus level due to immature characteristics or herbivore damage were assigned observational taxonomic unit numbers (OTUs).
Peeking under the canopy: anomalously short fire-return intervals alter subalpine forest understory plant communities
Changing climate and fire regimes are profoundly affecting temperate coniferous forests, driving greatly reduced tree cover postfire. However, whether similar changes are present in the understory of these forests remains less well-understood. We sampled understory plant communities in 20 plot pairs across Greater Yellowstone (Wyoming, USA) in July and August 2021, with each including one plot burned at short (<30 year) fire-return interval and one plot burned in the same most recent fire but not burned previously for >125 years. We also included 11 plot pairs meeting our definition of short- and long-interval fire that were sampled 12 years after the 1988 Yellowstone fires in summer 2000. We also used previously collected published and unpublished data to compare understory communities following recent (2016) short-interval fires to those following the previous long-interval fire in the same general area. In each plot, percent cover of understory plant species was estimated in 0.25-m2 quadrats, and species richness determined via a whole-plot sweep. Understory plant community cover, richness, and diversity did not differ by interval class, but species able to persist in drier conditions and in lower vegetation zones became more abundant following shot interval fire. Further, previously distinct understory communities following long-interval fire in two regions of Greater Yellowstone became slightly more similar following recent short-interval fire. Dissimilarity between plot pairs increased with greater historical snowfall and decreased with time since fire and postfire winter snowfall. These changes to understory plant communities may continue with ongoing shifts in climate and fire across temperate and boreal forests.
Snag-fall patterns following stand-replacing fire vary with stem characteristics and topography in subalpine forests of Greater Yellowstone
We assessed the stem- and landscape-level drivers of snag persistence and snag-fall mode within the area burned as stand-replacing fire in the 1988 Yellowstone Fires in Yellowstone National Park, Wyoming, USA. Snags were sampled 14-15 years postfire (n = 131) and again in a separate set of plots 34 years postfire (n = 55). Stem characteristics such as species identity (e.g., lodgepole pine, whitebark pine, Engelmann spruce, subalpine fir, and Douglas-fir), diameter at breast height, whether the tree was alive or dead at the time of fire, and the mode of snag-fall (snapping or uprooting) were measured and used to explain patterns of snag persistence and modes of snag-fall. In addition, plot-level environmental variables (e.g., slope, aspect, elevation, stand density) were measured and related to the proportion of stems still standing as snags at 14-15 and 34 years postfire. Data collection is complete and is part of a forthcoming manuscript in revision at Forest Ecology and Management.
Data for: Sparse subalpine forest recovery pathways, plant communities, and carbon stocks 34 years after stand-replacing fire (Greater Yellowstone Ecosystem, Wyoming, USA; 2022)
We assessed postfire forest recovery pathways, stem densities, understory plant communities, and carbon stocks across 55 plots in areas exhibiting sparse and reduced forest recovery 34 years after the 1988 Yellowstone Fires in the Greater Yellowstone Ecosystem, Wyoming, USA. Recovery pathways were identified using plot-level frequency distributions of tree ages and correlated with potentially important biotic and abiotic variables (e.g., elevation, seed source distance). Species- and age-specific stem densities were similarly regressed across environmental factors to determine variability in forest recovery across the sampled landscape. Understory plant communities were sampled in 0.25m-square quadrats and environmental drivers of individual species occurrence and whole compositional shifts were determined. Finally, carbon stock sizes were derived from field measures of tree characteristics, understory cover, and soil combined with regionally derived allometric equations. Data collection is complete and is part of a forthcoming manuscript at Ecological Monographs.
Data for: Reburning before recovery: Effects of short-interval fire on subalpine forest nitrogen stocks and fluxes
In forests adapted to infrequent (>100-yr) stand-replacing fires, novel short-interval (<30-yr) fires have started to burn young forests before they recover from previous burns. Postfire tree regeneration is reduced, plant communities shift, soils are hotter and drier, but effects on biogeochemical cycling are unresolved. This study focused on how postfire nitrogen (N) stocks, N availability and N fixation varied in lodgepole pine (Pinus contorta var. latifolia) forests burned at long and short intervals in Grand Teton National Park (Wyoming, USA). This data package includes our field data from 2021 and 2022, along with laboratory analyses of foliar and litter chemistry, resin-sorbed N, and field measurements of N fixation. The data included here were also used to compute aboveground N stocks. Our study found that short-interval fires reduced and repartitioned aboveground N stocks, but soil N stocks were unaffected. Results indicate that these shifts in N pools and fluxes suggest reburns can markedly alter N cycling in subalpine forests. The citation for the publication associated with these data is: Turner, M. G., R. E. Heumann, N. G. Kiel, J. A. Warren, and C. C. Cleveland. Reburning before recovery: Effects of short-interval fire on subalpine forest nitrogen stocks and fluxes. Ecosystems (In press)
Demographic measures of Liatris ohlingerae (Asteraceae) in 20 populations across multiple habitats and time-since-fire intervals in south central Florida from 1997-2017
Demographic data were collected on 2,858 tagged individually marked plants annually from 1997 to 2017 in 20 populations across three sites on the southern end of the Lake Wales Ridge in south central Florida, USA. Our goal was to understand demographic responses including recruitment, survival, reproduction and mortality of individuals across populations, habitat types and fire-return-intervals. Habitats include rosemary scrub, scrubby flatwoods and human created sandy roadsides. Populations spanned three sites including Archbold Biological Station (18 populations), Florida Forest Service Arbuckle Tract of the Lake Wales Ridge State Forest (1 population), and Florida Fish and Wildlife Conservation Commission Gould Road property (1 population). Annual demographic measures include survival (including plant dormancy), stage, measures of size, reproductive effort and herbivory. Plots were surveyed annually during flowering in August for previously marked plants and searched for newly recruited putative seedlings or previously missed larger adults. This landscape is managed with periodic prescribed fire impacting some populations with additional post-burn censuses completed after the burn. In addition, damage following three hurricanes in 2004 were recorded. Plants were followed through their lifecycle and after four years of no aboveground growth, plants were assumed dead and tags removed from the field.
Post-Tubbs Fire Chaparral Floristic Survey at Pepperwood Preserve in the California Coast Ranges 2018-2019
The Dwight Center for Conservation Science at Pepperwood is an ecological institute dedicated to educating, engaging, and inspiring our community through habitat preservation, science-based conservation, leading-edge research, and interdisciplinary educational programs. Our mission is to steward the life and landscapes of the 3,200-acre Pepperwood Preserve and to advance science-based conservation of ecosystems throughout our region and beyond. Following the October 2017 Tubbs Fire, Pepperwood hired Nomad Ecology, LLC, to implement Nomad Ecology's post-fire research program at Pepperwood. Specifically, Nomad Ecology conducted a two-year study of post-fire plant diversity and succession in chaparral at the preserve. Species richness and ecological dynamics are not well understood in these post-fire areas (especially in northern California) despite high interest from land managers, ecologists, and botanists. Documentation of the post-fire flora and the sensitive species that are part of this fleeting diversity is essential to understanding the full range of natural resources associated with chaparral ecosystems, and thus key to developing conservation goals specific to Pepperwood. This study documented the burn severity and diversity and abundance of the fleeting post-Tubbs Fire flora in spring 2018 and 2019 using species ocular cover estimates across ten 50-meter belt transects in four different soil types: rhyolite, fluvial and lacustrine deposits, andesite, and serpentinite.
Conifer seed delivery after the Berry Fire Grand Teton National Park, USA, 2018
These data were collected by NS Gill, TJ Hoecker, and MG Turner in Grand Teton National Park from July-October 2018. The dataset represents seed delivery and surrounding forest structure and demographics following the 2016 Berry Fire, used to examine the relationship between fire regime change and conifer seed delivery in Pinus contorta var. latifolia forests. Stand structure and cone abundance were quantified at 21 sites positioned at the edges of the burned area in 50-m transects. Seed delivery was measured in seed traps placed at distance intervals running out to 100 m into burned patches from the live forest edge over a period of three months. Pinus contorta, Picea engelmannii, and Abies lasiocarpa seeds were collected. Five meteorological stations were deployed throughout the study area. Wind speed and direction data were attributed to transects from the nearest of these deployed meteorological stations.
Dendrochronology study of fire history, Andrews Experimental Forest and central western Cascades, Oregon, 1482-1952
Fire history is documented for an 11,000 hectare (27,110 acre) area in the western Oregon Cascades , including H. J. Andrews Experimental Forest. Fire scar and tree origin data were collected mainly from stumps at 359 sites. Thirty-five fire events are mapped from 1482 to 1952. Mean fire return intervals are derived from data at individual sites, about 5 hectares in size, rather than from the corrected master fire chronology.
Fire history database of the western United States, 1994
To create a database of existing published and unpublished tree-ring reconstructions of fire regimes in forested areas, before circa 1900, west of 100 W longitude in the continental United States, exclusive of Alaska. The studies included in the database are restricted to tree-ring reconstructions of fire history and the information extracted includes citations to the data sources, site information, estimated fire regimes, and information on individual fire events (when readily available). Fire regimes vary greatly across short distances in the western United States, so that a reconstruction of fire history over a small area may not represent the history of a larger area. Therefore, we extracted information on the size of the study area and the amount of fire evidence (number of trees scarred and/or number of tree origin dates) used in computing the fire regimes to allow the user to gauge the applicability of each reconstruction to larger areas.
Spot fire locations (1991), Andrews Experimental Forest
1991 Spot Fire Locations for the HJ Andrews Experimental Forest. This data documents the locations of fires during the 1991 fire season. There is little additional information about the fires and suppression efforts.
Fire history reconstruction (1482 - 1952), Andrews Experimental Forest and vicinity
Fire History - H J Andrews and Vicinity (1482 - 1952) individual fires and fire frequency. Fire history studies by Peter Teensma provide the base information for this layer. Individual fire episodes were manuscripted onto HJA base maps and digitized. Fire episodes were maintained in thirty one separate polygon coverages, until Arc/Info Version 7 provided the region feature class to accomodate overlapping polygons. REGIONPOLY was used to create regions for each fire episode and then the 31 episode regions were combined using UNION. The field "AGE" = 0 means that a fire occured in the polygon. AGE = 1 means that fire was absent
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.