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6,381 results for “spatial”
Microbial Observatory at North Temperate Lakes LTER High-resolution temporal and spatial dynamics of microbial community structure in freshwater bog lakes 2005 - 2009 original format (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-ntl/349/4. The abstract below was extracted from the Level 0 data package and is included for context: The North Temperate Lakes - Microbial Observatory seeks to study freshwater microbes over long time scales (10+ years). Observing microbial communities over multiple years using DNA sequencing allows in-depth assessment of diversity, variability, gene content, and seasonal/annual drivers of community composition. Combining information obtained from DNA sequencing with additional experiments, such as investigating the biochemical properties of specific compounds, gene expression, or nutrient concentrations, provides insight into the functions of microbial taxa. Our 16S rRNA gene amplicon datasets were collected from bog lakes in Vilas County, WI, and from Lake Mendota in Madison, WI. Ribosomal RNA gene amplicon sequencing of freshwater environmental DNA was performed on samples from Crystal Bog, North Sparkling Bog, West Sparkling Bog, Trout Bog, South Sparkling Bog, Hell’s Kitchen, and Mary Lake. These microbial time series are valuable both for microbial ecologists seeking to understand the properties of microbial communities and for ecologists seeking to better understand how microbes contribute to ecosystem functioning in freshwater.
LAGOS-US GEO v1.0: Data module of lake geospatial ecological context at multiple spatial and temporal scales in the conterminous U.S.
The LAGOS-US GEO data package is one of the core data modules of LAGOS-US, an extensible research-ready platform designed to study the 479,950 lakes and reservoirs larger than or equal to 1 ha in the conterminous US (48 states plus the District of Columbia). The GEO module contains data on the geospatial and temporal ecological setting (e.g., land use, terrain, soils, climate, hydrology, atmospheric deposition, and human influence) quantified at multiple spatial divisions (e.g., equidistant buffers around lakes, watersheds, hydrologic basins, political boundaries, and ecoregions) relevant to the LAGOS-US lake population defined in the LAGOS-US LOCUS module. The database design that supports the LAGOS-US research platform was created based on several important design features: lakes are the fundamental unit of consideration, all lakes in the spatial extent above the minimum size must be represented, and most information is connected to individual lakes. The design is modular, interoperable (the modules can be used with each other), and extensible (future database modules can be developed and used in the LAGOS-US research platform by others). Users are encouraged to use the other two core data modules that are part of the LAGOS-US platform: LOCUS (location, identifiers, and physical characteristics of lakes and their watersheds) and LIMNO (in situ lake physical, chemical, and biological measurements through time) that are each found in their own data packages.
R Code and Images for Developing a Spatial Concordance Coefficient at Harvard Forest 2010
Concordance correlation coefficients have been developed in a variety of different contexts. This problem has been widely addressed in a non-spatial context, but here we consider a coefficient that for a fixed spatial lag allows the comparison of two spatial sequences (e.g., images). We define a spatial concordance coefficient for second-order stationary processes.
Spatially Distributed Lake Mendota EXO Multi-Parameter Sonde Measurements Summer 2019
This data was collected over 9 sampling trips from June to August 2019. 35 grid boxes were generated over Lake Mendota. Before each sampling effort, sample point locations were randomized within each grid box. Surface measurements were taken with an EXO multi-parameter sonde at the 35 locations throughout Lake Mendota during each sampling trip. Measurements include temperature, conductivity, chlorophyll, phycocyanin, turbidity, dissolved organic material, ODO, pH, and pressure.
Forest disturbances in Europe mapped at high spatial detail and in near-real-time: Logging in protected Estonian forests
<p><strong>Data description</strong></p> <p>These datasets were generated for the Geostory "Forest disturbances in Europe mapped at high spatial detail and in near-real-time: Logging in protected Estonian forests" in the context of the Open Earth Monitor Cyberinfrastructure project.</p> <p>We used open source high-resolution Sentinel-1 satellite data to develop a wall-to-wall map of forest disturbances in the four-year period between the start of 2020 and end of 2023 in Estonia. First results are presented. The methodology is based on RADD-alerts developed for the pan-tropics (Reiche et al. 2021). Three years (2017-2019) of imagery was used as a historical period, and detections were generated for ~4 years (2020-2023). Winter images from November through March were not included as frozen conditions can introduce false detections. This will be addressed in the next version. Disclaimer: Disturbance maps have not been validated.</p> <p>Two additional layers are provided for visualization: a forest baseline layer (<em>forestcover</em>), masking out non-forest disturbance detections, was derived from Copernicus 10m 2018 forest cover density and GLAD 30m 2019 tree removal datasets, and a protected areas layer (<em>natura</em>), which displays the extent of Natura 2000 coverage in Estonia.</p> <p>'.SLD' files are provided for visualization (note: the <em>disturbance</em> .SLC file must be adjusted to contain appropriate time reference fields).</p> <p><strong>Naming Convention</strong></p> <p>To ensure consistency and ease of use across and within the projects, we follow the standard Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describes important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. For instance:</p> <ul> <li>disturbance_radd_c_10m_s_20200101_20200131_eu_epsg.3035_v20240222.tif</li> </ul> <p>with the following fields:</p> <ul> <li>Generic variable name: <strong>disturbance</strong></li> <li>Variable procedure combination i.e. method standard: <strong>radd</strong></li> <li>Position in the probability distribution / variable type: <strong>c</strong></li> <li>Spatial support: <strong>10m</strong></li> <li>Depth reference or depth interval e.g. below ("b"), above ("a") ground or at surface ("s"): <strong>s</strong></li> <li>Time reference begin time (YYYYMMDD): <strong>20200101</strong></li> <li>Time reference end time: <strong>20200131</strong></li> <li>Bounding box (2 letters max): <strong>eu </strong></li> <li>EPSG code: <strong>epsg.3035</strong></li> <li>Version code i.e. creation date: <strong>v20240222</strong></li> </ul> <p><strong>Source Data</strong></p> <p>Disturbance maps:</p> <p>Contains modified Copernicus Sentinel data [2017-2023] and Generated using European Union's EEA-10 Copernicus DEM; https://doi.org/10.5270/ESA-c5d3d65</p> <p>Forest baseline:</p> <p>Generated using European Union's Copernicus Land Monitoring Service information; https://doi.org/10.2909/486f77da-d605-423e-93a9-680760ab6791 and GLAD tree removal; https://doi.org/10.1016/j.rse.2023.113797</p> <p>Natura 2000: </p> <p>Generated using European Environmental Agency's Natura 2000 layers; https://sdi.eea.europa.eu/data/dae737fd-7ee1-4b0a-9eb7-1954eec00c65</p>
North Temperate Lakes LTER: Spatially Distributed Water Temperature (2004,2006) and Sediment Temperature (2006) of Lake Wingra
Profiles of water and sediment temperature were measured during the summer months in Lake Wingra, Dane County, WI, USA at several locations. During the months July through September, 2004, water temperature profiles were measured. For the months, June through August, 2006, sediment temperatures were measured along with the water temperature profiles. Sampling Frequency: 2 minutes and 4 minutes Number of sites: 3 sites each summer Instrument: http://www.microdaq.com/occ/u22/underwater_temperature_data_logger.php - Underwater Temperature Data Logger
North Temperate Lakes LTER: Spatial Variability of Wind Field at Lake Wingra (2004)
Wind speed and direction were measured at multiple locations around Lake Wingra. Two data tables are provided. The first has wind speed and direction measured at 7 sites around Lake Wingra, Dane County, WI, USA during the month of March, 2004 at a frequency of 10 minutes. The latter data table contains wind speed and direction measured at Vilas beach, Lake Wingra for the months July through September 2004 at a frequency of 2 minutes. Sampling Frequency: 2 minutes and 10 minutes Number of sites: 7 locations around Lake Wingra Instrument: http://www.campbellsci.com/03001-wind-sentry -- 03001-L R.M. Young Wind Sentry set
Fluxes project at North Temperate Lakes LTER: Spatial Metabolism Study 2007
Data from a lake spatial metabolism study by Matthew C. Van de Bogert for his Phd project, "Aquatic ecosystem carbon cycling: From individual lakes to the landscape." The goal of this study was to capture the spatial heterogeneity of within-lake processes in effort to make robust estimates of daily metabolism metrics such as gross primary production (GPP), respiration (R), and net ecosystem production (NEP). In pursuing this goal, multiple sondes were placed at different locations and depths within two stratified Northern Temperate Lakes, Sparkling Lake (n=35 sondes) and Peter Lake (n=27 sondes), located in the Northern Highlands Lake District of Wisconsin and the Upper Peninsula of Michigan, respectively.Dissolved oxygen and temperature measurements were made every 10 minutes over a 10 day period for each lake in July and August of 2007. Dissolved oxygen measurements were corrected for drift. In addition, conductivity, temperature compensated specific conductivity, pH, and oxidation reduction potential were measured by a subset of sondes in each lake. Two data tables list the spatial information regarding sonde placement in each lake, and a single data table lists information about the sondes (manufacturer, model, serial number etc.). Documentation:Van de Bogert, M.C., 2011. Aquatic ecosystem carbon cycling: From individual lakes to the landscape. ProQuest Dissertations and Theses. The University of Wisconsin - Madison, United States -- Wisconsin, p. 156. Also see Van de Bogert, M.C., Bade, D.L., Carpenter, S.R., Cole, J.J., Pace, M.L., Hanson, P.C., Langman, O.C., 2012. Spatial heterogeneity strongly affects estimates of ecosystem metabolism in two north temperate lakes. Limnology and Oceanography 57, 1689-1700.
WSC 2006: Spatial interactions among ecosystem services in the Yahara Watershed
Understanding spatial distributions, synergies and tradeoffs of multiple ecosystem services (benefits people derive from ecosystems) remains challenging. We analyzed the supply of 10 ecosystem services for 2006 across a large urbanizing agricultural watershed in the Upper Midwest of the United States, and asked: (i) Where are areas of high and low supply of individual ecosystem services, and are these areas spatially concordant across services? (ii) Where on the landscape are the strongest tradeoffs and synergies among ecosystem services located? (iii) For ecosystem service pairs that experience tradeoffs, what distinguishes locations that are win win exceptions from other locations? Spatial patterns of high supply for multiple ecosystem services often were not coincident locations where six or more services were produced at high levels (upper 20th percentile) occupied only 3.3 percent of the landscape. Most relationships among ecosystem services were synergies, but tradeoffs occurred between crop production and water quality. Ecosystem services related to water quality and quantity separated into three different groups, indicating that management to sustain freshwater services along with other ecosystem services will not be simple. Despite overall tradeoffs between crop production and water quality, some locations were positive for both, suggesting that tradeoffs are not inevitable everywhere and might be ameliorated in some locations. Overall, we found that different areas of the landscape supplied different suites of ecosystem services, and their lack of spatial concordance suggests the importance of managing over large areas to sustain multiple ecosystem services. Documentation: Refer to the supporting information of the follwing paper for full details on data sources, methods and accuracy assessment: Qiu, Jiangxiao, and Monica G. Turner. "Spatial interactions among ecosystem services in an urbanizing agricultural watershed." Proceedings of the National Academy
Microbial Observatory at North Temperate Lakes LTER Spatial and temporal cyanobacterial population dynamics in Lake Mendota 2009 - 2011
Toxic cyanobacterial blooms threaten freshwaters worldwide but have proven difficult to predict because the mechanisms of bloom formation and toxin production are unknown, especially on weekly time scales. Water quality management continues to focus on aggregated metrics, such as chlorophyll and total nutrients, which may not be sufficient to explain complex community changes and functions such as toxin production. For example, nitrogen (N) speciation and cycling play an important role, on daily time scales, in shaping cyanobacterial communities because declining N has been shown to select for N fixers. In addition, subsequent N pulses from N2 fixation may stimulate and sustain toxic cyanobacterial growth. Herein, we describe how rapid early summer declines in N followed by bursts of N fixation have shaped cyanobacterial communities in a eutrophic lake (Lake Mendota, Wisconsin, USA), possibly driving toxic Microcystis blooms throughout the growing season. On weekly time scales in 2010 and *2011, we monitored the cyanobacterial community in a eutrophic lake using the phycocyanin intergenic spacer (PC-IGS) region to determine population dynamics. In parallel, we measured microcystin concentrations, N2 fixation rates, and potential environmental drivers that contribute to structuring the community.
Spatial variability in water chemistry of four Wisconsin aquatic ecosystems - High speed limnology Environmental Science and Technology datasets
Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. We developed a new sensor platform to continuously samples surface water at a range of speeds (0 to > 45 km hr-1) resulting in high-density, meso-scale spatial data. Here, we archive data associated with an Environmental Science and Technology publication. Data include a single spatial survey of the following aquatic ecosystems: Lake Mendota, Allequash Creek, Pool 8 of the Upper Mississippi River, and Trout Bog. Data have been provided in three formats (raw, hydraulic-corrected, and tau-corrected).
Cascade project at North Temperate Lakes LTER - High-resolution spatial analysis of CASCADE lakes during experimental nutrient enrichment 2015 - 2016
This dataset contains high-resolution spatio-temporal water quality data from two experimental lakes during a whole-ecosystem experiment. Through gradual nutrient addition, we induced a cyanobacteria bloom in an experimental lake (Peter Lake) while leaving a nearby reference lake (Paul Lake) as a control. Peter and Paul Lakes (Gogebic county, MI USA), were sampled using the FLAMe platform (Crawford et al. 2015) multiple times during the summers of 2015 and 2016. In 2015 nutrient additions to Peter Lake began on 1 June, and ceased on 29 June, Paul Lake was left unmanipulated. In 2016 no nutrients were added to either lake. Measurements were taken using a YSI EXO2 probe and a Garmin echoMap 50s. Sensor- data were collected continuously at 1 Hz and linked via timestamp to create spatially explicit data for each lake. Crawford, J. T., L. C. Loken, N. J. Casson, C. Smith, A. G. Stone, and L. A. Winslow. 2015. High-speed limnology: Using advanced sensors to investigate spatial variability in biogeochemistry and hydrology. Environmental Science & Technology 49:442–450.
Microbial Observatory at North Temperate Lakes LTER High-resolution temporal and spatial dynamics of microbial community structure in freshwater bog lakes 2005 - 2009 original format
The North Temperate Lakes - Microbial Observatory seeks to study freshwater microbes over long time scales (10+ years). Observing microbial communities over multiple years using DNA sequencing allows in-depth assessment of diversity, variability, gene content, and seasonal/annual drivers of community composition. Combining information obtained from DNA sequencing with additional experiments, such as investigating the biochemical properties of specific compounds, gene expression, or nutrient concentrations, provides insight into the functions of microbial taxa. Our 16S rRNA gene amplicon datasets were collected from bog lakes in Vilas County, WI, and from Lake Mendota in Madison, WI. Ribosomal RNA gene amplicon sequencing of freshwater environmental DNA was performed on samples from Crystal Bog, North Sparkling Bog, West Sparkling Bog, Trout Bog, South Sparkling Bog, Hell’s Kitchen, and Mary Lake. These microbial time series are valuable both for microbial ecologists seeking to understand the properties of microbial communities and for ecologists seeking to better understand how microbes contribute to ecosystem functioning in freshwater.
Mississippi River spatial water chemistry Environmental Research Letters datasets
We mapped surface water chemistry along the entire length of the Upper Mississippi River (UMR) to understand spatial patterns in nitrate sources and processing. We used a sensor-based and boat-mounted sensing platform to continuously measure underway water chemistry. Measurements were linked with global positioning systems (GPS) to create maps of surface water chemistry. Here, we archive data associated with an Environmental Research Letters publication (Loken et al. 2018). Data include a single spatial survey of the entire length of the UMR (Minneapolis, Minnesota to Cairo, Illinois) in August 2015 and repeat surveys in Navigation Pool 8 (located near La Crosse, WI). Data have been provided in three formats (raw, hydraulic-corrected, and tau-corrected). Additionally, we archive laboratory chemistry data from water samples collected during the project. Sites include a range of main channel, backwaters, and tributaries. Water chemistry samples were analyzed at the North Temperate Lakes - Long Term Ecological Research facility and linked with underway sensor measurements.
Columbia River spatial water chemistry
We mapped surface water chemistry along a ~600 km segment of the Columbia River. We used a sensor-based and boat-mounted sensing platform to continuously measure underway water chemistry. Measurements were linked with global positioning systems (GPS) to create maps of surface water chemistry. Data were collected over 6 days in July 2018 and include a single longitudinal survey of the Columbia River. Data have been provided in three formats (raw, hydraulic-corrected, and tau-corrected). Additionally, we archive laboratory chemistry data from water samples collected during the project. Sites include a range of main channel, backwaters, and tributaries. Water chemistry samples were analyzed at the North Temperate Lakes - Long Term Ecological Research facility and linked with underway sensor measurements.
Spatial surface water chemistry of Lake Mendota with FLAMe: 2014-2016
We mapped surface water chemistry in Lake Mendota 39 times between 2014 and 2016. We used a sensor-based and boat-mounted sensing platform to continuously measure underway water chemistry. Measurements were linked with global positioning systems (GPS) to create maps of surface water chemistry. Data have been provided in three formats (raw, hydraulic-corrected, and tau-corrected). Dataset is used for the publication, "Large spatial and temporal variability of carbon dioxide and methane in a eutrophic lake", https://doi.org/10.1029/2019JG005186
Spatial heterogeneity of within-stream methane concentrations North Temperate Lakes LTER, 2014
Streams, rivers, and other freshwater features may be significant sources of CH4 to the atmosphere. However, high spatial and temporal variabilities hinder our ability to understand the underlying processes of CH4 production and delivery to streams and also challenge the use of scaling approaches across large areas. We studied a stream having high geomorphic variability to assess the underlying scale of CH4 spatial variability and to examine whether the physical structure of a stream can explain the variation in surface CH4. A combination of high-resolution CH4 mapping, a survey of groundwater CH4 concentrations, quantitative analysis of methanogen DNA, and sediment CH4 production potentials illustrates the spatial and geomorphic controls on CH4 emissions to the atmosphere.
Cascade Project at North Temperate Lakes LTER – High-resolution Spatial Data for Whole Lake Experiments 2018 - 2019
Spatial measurements of water quality from Peter and Paul lakes in 2018 and 2019. In 2019, inorganic nitrogen and phosphorus were added to Peter Lake daily to cause an algal bloom while Paul Lake was an unmanipulated reference lake. In 2018, both lakes were sampled 1 time per week, while in 2019 lakes were sampled three times per week. Measurements were taken using the FLAMe sampling platform (Crawford et al. 2015, Environmental Science and Technology 49:442-450), which was driven in a grid pattern and recorded GPS coordinates and water measurements at 1Hz to create high resolution spatial maps.
Point locations for spatial and morphological analyses of barchans in swarms
<div>This dataset contains the long-lat coordinates of seven points on ~6000 barchans located in six swarms.</div> <div> </div> <div>Four of the locations are on Earth (three in the Tarfaya region of the Western Sahara, one in Mauritania).</div> <div>The other two swarms are from high latitudes of the northern hemisphere of Mars.</div> <div> </div> <div>In each location between 850 and 1112 barchans were measured.</div> <div> </div> <div>The measurements were carried out manually by Dominic T Robson and Andreas CW Baas according to the method described in</div> <div>Robson, D. T., Annibale, A., & Baas, A. C.W. (2022). Reproducing size distributions of swarms of barchan dunes on Mars and Earth using a mean-field model. Physica A: Statistical Mechanics and its Applications, 606, 128042.</div> <div> </div> <div>The included metadata file lists the copyrights and dates (DD/MM/YYYY) for the imagery used, all imagery was accessed through Google Earth. </div> <div> </div> <div>The metadata file also includes descriptions of the format of the data. The data themselves are provided in separate comma delimited files for each location. Only the bedforms identified as barchans are included although other bedforms in the locations were also measured (see Robson et al. Physica A (2022)).</div> <div> </div> <div>Using the seven points recorded for each dune it is possible to calculate:</div> <div>Body length</div> <div>Total length</div> <div>Horn lengths</div> <div>Total width</div> <div>Horn-to-horn width</div> <div>Port flank width</div> <div>Starboard flank width</div> <div>Slipface length</div> <div>Dune orientation</div> <div> </div> <div>The area of the polygons formed by the points also provides an estimate for the basal area of the dune though it is not a perfect match.</div> <div> </div> <div>We hope that these data will be of use to those seeking to study the morphology, size, asymmetry, and spatial distribution of barchans in swarms.</div> <div> </div> <div>Dominic T Robson and Andreas CW Baas.</div>
Antarctic Ecosystem Inventory: Spatial data for Ice-free lands v1.0
<p>This is Antarctica’s first comprehensive ecosystem map of ice-free lands. The data comprise a spatially explicit 3-tiered hierarchical ecosystem classification with nine Major Environment Types (tier 1), 33 Habitat Complexes (tier 2) and 269 Bioregional Ecosystem Types (tier 3). These Bioregional Ecosystem Types are aligned with ‘level 4’ of the IUCN Global Ecosystem Typology (Keith et al. 2022). </p> <p><br>The spatial data are available in raster format (TIF) at 100 m resolution in the Polar Stereographic Projected Coordinate System (GCS_WGS_1984) for all known ice-free areas south from latitude -57.330551 decimal degrees South (pdf map shows extent of ice-free areas in relation to terrestrial ice and ice shelves). A value attribute table (VAT) provides text fields containing codes and full names for each unit in each level of the classification hierarchy and the spatial extent of tier 3 units in hectares.</p> <p><br>Methods of development, source data and uses of the inventory are detailed by Tóth et al. (2025a). Descriptive profiles for tier 1 and 2 units are available in Tóth et al. (2025b).</p> <p><br>References<br>Keith, D.A., Ferrer-Paris, J.R., Nicholson, E., Bishop, M.J., Polidoro, B.A., Ramirez-Llodra, E., Tozer, M.G., Nel, J.L., Nally, R. Mac, Gregr, E.J., Watermeyer, K.E., Essl, F., Faber-Langendoen, D., Franklin, J., Lehmann, C.E.R., Etter, A., Roux, D.J., Stark, J.S., Rowland, J.A., Brummitt, N.A., Fernandez-Arcaya, U.C., Suthers, I.M., Wiser, S.K., Donohue, I., Jackson, L.J., Pennington, R.T., Iliffe, T.M., Gerovasileiou, V., Giller, P., Robson, B.J., Pettorelli, N., Andrade, A., Lindgaard, A., Tahvanainen, T., Terauds, A., Chadwick, M.A., Murray, N.J., Moat, J., Pliscoff, P., Zager, I. & Kingsford, R.T. (2022) A function-based typology for Earth’s ecosystems. Nature 610, 513–518. [doi: 10.1038/s41586-022-05318-4].<br>Tóth, A.B., Terauds, A., Chown, S.L., Hughes, K.A., Convey, P., Hodgson, D.A., Cowan, D.A., Gibson, J., Leihy, R.I., Murray, N.J., Robinson, S.A., Shaw, J.D., Stark, J.S., Stevens, M.I., van den Hoff, J., Wasley, J. and Keith D.A. (2025a). A dataset of Antarctic ecosystems in ice-free lands: classification, descriptions, and maps. Scientific Data 12, 133. [https://doi.org/10.1038/s41597-025-04424-y] <br>Tóth, A.B., Terauds, A., Chown, S.L., Hughes, K.A., Convey, P., Hodgson, D.A., Cowan, D.A., Gibson, J., Leihy, R.I., Murray, N.J., Robinson, S.A., Shaw, J.D., Stark, J.S., Stevens, M.I., van den Hoff, J., Wasley, J. & Keith D.A. (2025b). Antarctic Ecosystem Inventory: Descriptive profiles for ice-free lands v1.0. DOI: 110.5281/zenodo.14625890. Australian Antarctic Data Centre.</p>
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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.