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2,195 results for “2005”
North Sea Wave Database (NSWD) 2005-2011
<p>North Sea Wave Database (NSWD)<br> The dataset contains each year of spectral metocean condition for Significant Wave Height (HSIGN) and wave energy period (TMM10), in meters and seconds.<br> Each variable has a year timestap which the data corresponds too i.e 1980. The latitudes and longitudes of the dataset have resolution of 0.025 degrees at each direction. Latitude starting coordinate is 50 degrees and Longitude 0.</p> <p>For more information on the process that developed the dataset, the methodogies followed, calibration, valdiation and sensitivity analysis, <br> see: </p> <p>Lavidas, G., & Polinder, H. (2019). North Sea Wave Database (NSWD) and the Need for Reliable Resource Data: A 38 Year Database for Metocean and Wave Energy Assessments. Atmosphere, 10(9), <a href="https://doi.org/10.3390/atmos10090551">https://doi.org/10.3390/atmos10090551 </a></p> <p>Lavidas, G., & Polinder, H. (2019). Wind effects in the parametrisation of physical characteristics for a nearshore wave model. Proceedings of the 13th European Wave and Tidal Energy Conference 1-6 September 2019, Naples, Italy.</p> <p>The dataset was produced by Dr George Lavidas during the WAVe Resource for Electrical Production (WAVREP, which received funding from the European Union's Horizon 2020 research & innovation programme under the Marie Sklodowska-Curie grant agreement No 787344.</p> <p>The dataset is accompanied by two publication that (i) present the calibration-validation and production (ii) analysis of the dataset.</p> <p>The official CORDIS website is https://cordis.europa.eu/project/id/787344<br> A list of outcomes for the NSWD and the WAVREP project is found at the researcher's page:<br> <a href="https://www.researchgate.net/project/WAVe-Resource-for-Electrical-Production-WAVREP ">https://www.researchgate.net/project/WAVe-Resource-for-Electrical-Production-WAVREP </a></p> <p>It can also be found at the official CORDIS website<br> <a href="https://cordis.europa.eu/project/id/787344">https://cordis.europa.eu/project/id/787344</a></p> <p>Sharing and Access information<br> Creative Commons Attribution (CC BY-SA). <br> The Creative Commons Attribution license allows others remix, tweak, and build upon your work, as long as they credit you and license their new creations under the identical terms.</p>
A long term hourly eddy covariance dataset of consistently processed CO2 and H2O Fluxes from the Tibetan Alpine Steppe at Nam Co (2005 - 2019)
<p>The data set contains nearly 15 years of eddy covariance data from an alpine steppe ecosystem on the central Tibetan Plateau. The data was processed following standardized quality control methods to allow for comparability between the different years of our record and with other data sets. To ensure meaningful estimates of ecosystem atmosphere exchange, careful application of the following correction procedures and analyses was necessary: (1) Due to the remote location, continuous maintenance of the eddy covariance (EC) system was not always possible, so that cleaning and calibration of the sensors was performed irregularly. Furthermore, the high proportion of bare soil and high wind speeds led to accumulation of dirt in the measurement path of the infrared gas analyzer (IRGA). The installation of the sensor in such a challenging environment resulted in a considerable drift in CO2 and H2O gas density measurements. If not accounted for, this concentration bias may distort the estimation of the carbon uptake. We applied a modified drift correction procedure following Fratini et al. (2014) which, instead of a linear interpolation between calibration dates, uses the CO2 concentration measurements from the Mt. Waliguan atmospheric observatory as reference time series. (2) We applied rigorous quality filtering of the calculated fluxes to retain only fluxes which represent actual physical processes. (3) During the long measurement period, there were several buildings constructed in the near vicinity of the EC system. We investigated the influence of these obstacles on the turbulent flow regime to identify fluxes with uncertain land cover contribution and exclude them from subsequent computations. (4) We calculated the de-facto standard correction for instrument surface heating during cold conditions (hereafter called sensor self heating correction) following Burba et al. (2008) and a revision of the original method following Frank and Massman (2020). (5) Subsequently, we applied the traditional and widely used gap filling procedure following Reichstein et al. (2005) to provide a more complete overview of the annual net ecosystem CO2 exchange. (6) We estimated the flux uncertainty by calculating the random flux error (RE) following Finkelstein and Sims (2001) and by using the standard deviation of the fluxes used for gap filling (NEE_fsd) as a measure for spatial and temporal variation.</p> <p>References:</p> <ol> <li>Burba, G. G., McDermitt, D. K., Grelle, A., Anderson, D., and XU, L. (2008). Addressing the influence of instrument surface heat exchange on the measurements of CO2 flux from open-path gas analyzers, Global Change Biology, 14, 1854-1876, <a href="https://doi.org/10.1111/j.1365-2486.2008.01606.x">https://doi.org/10.1111/j.1365-2486.2008.01606.x</a>.</li> <li>Finkelstein, P. L. and Sims, P. F. (2001). Sampling error in eddy correlation flux measurements, J. Geophys. Res. Atmos., 106, 3503–3509, doi:10.1029/2000JD900731.</li> <li>Frank, J. M. and Massman, W. J.: A new perspective on the open-path infrared gas analyzer self-heating correction, Agricultural and Forest Meteorology, 290, 107986, doi:10.1016/j.agrformet.2020.107986, 2020.</li> <li>Fratini, G., McDermitt, D. K., and Papale, D. (2004). Eddy-covariance flux errors due to biases in gas concentration measurements: origins, quantification and correction, Biogeosciences, 11, 1037-1051, <a href="https://doi.org/10.5194/bg-11-1037-2014">https://doi.org/10.5194/bg-11-1037-2014</a>.</li> <li>Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M., Berbigier, P., Bernhofer, C., Buchmann, N., Gilmanov, T., Granier, A., Grunwald, T., Havrankova, K., Ilvesniemi, H., Janous, D., Knohl, A., Laurila, T., Lohila, A., Loustau, D., Matteucci, G., Meyers, T., Miglietta, F., Ourcival, J.-m., Pumpanen, J., Rambal, S., Rotenberg, E., Sanz, M., Tenhunen, J., Seufert, G., Vaccari, F., Vesala, T., Yakir, D., and valentini, R. (20050. On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm, Global Change Biology, 11, 1424-1439, <a href="https://doi.org/10.1111/j.1365-2486.2005.001002.x">https://doi.org/10.1111/j.1365-2486.2005.001002.x</a>.</li> </ol>
International and EU funding in the eastern neighbourhood (2005-2022). REDEMOS Dataset 3.2
<p>International, EU and EU Member States’ funding for democracy, human rights, gender equality, the rule of law and good governance in the Eastern Neighbourhood, between 2005 and 2022.</p>
Tree-covered and intact forest landscapes BC1000, 1995, 2000, 2005, 2010, 2013, 2016 at 250 m
<p>Based on the <a href="http://www.unep-wcmc.org/resources-and-data/generalised-original-and-current-forest">UNEP historic forest cover map</a>, ESA land cover time series and <a href="http://www.intactforests.org/data.ifl.html">intact forest landscape (IFL 2000, 2013 and 2016) data</a>. Processing steps are described in detail <strong><a href="https://gitlab.com/openlandmap/global-layers/tree/master/soil/LDN">here</a></strong>. Antartica is not included.</p> <p>To access and visualize maps use: <a href="http://www.openlandmap.org/">OpenLandMap.org</a></p> <p>If you discover a bug, artifact or inconsistency in the maps, or if you have a question please use some of the following channels:</p> <ul> <li>Technical issues and questions about the code: <a href="https://gitlab.com/openlandmap/global-layers/issues">https://gitlab.com/openlandmap/global-layers/issues</a> </li> <li>General questions and comments: <a href="https://disqus.com/home/forums/landgis/">https://disqus.com/home/forums/landgis/</a></li> </ul> <p>All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention:</p> <ul> <li>ldg = theme: land degradation,</li> <li>forest.cover = variable: forest / tree cover,</li> <li>esacci.ifl = determination method: combination of ESA land cover and IFL maps,</li> <li>c = factor,</li> <li>250m = spatial resolution / block support: 250 m,</li> <li>s0..0cm = vertical reference: land surface,</li> <li>1995 = time reference: year 1995,</li> <li>v0.1 = version number: 0.1,</li> </ul>
ECCO Iter22 Global Ocean State Estimate - 1 January 2004 to 30 April 2005
<p>Time series of global ocean temperature, salinity, and sound speed derived from the “Estimating the Circulation and Climate of the Ocean" (ECCO) program Iter22 state estimates. The sound speed fields were computed for simulation of acoustic propagation over basin scales or longer in a realistic oceanic environment. These estimates were computed in 2010 by the JPL-MIT-SIO ECCO program. <br>Original link: http://ecco2.jpl.nasa.gov/data9/cube/iter22/lat_lon/quart_80S_80N/THETA/ , now defunct.</p> <p>The solution is mesoscale permitting. The solution was obtained on a cube sphere grid between 80S and 80N with 18-km horizontal grid spacing and 50 vertical levels (Menemenlis et al., 2005, NASA supercomputer improves prospects for ocean <br>climate research, Eos Trans., AGU 86, 89, 95–96.). State estimates were averaged over a 3-day interval. File 003 is averaged over 2004/1/1 -- 2004/1/3. Three-day-mean temperature and salinity profiles from the iter22 solution were provided on 1/4 degree <br>grid for the period 1 January 2004 to 30 April 2005. There are 162 snapshots at 3-day intervals. </p> <p>Depths were decimated to the standard 33 depths of the World Ocean Atlas to 5500 m. YearDay 1 is 1 January 1992. The number of the filename indicates the yearday in 2004. In situ temperature was computed from model potential temperature. Sound speed was computed using the Del Grosso sound speed equation. Original model profiles descended only to the model sea floor. Temperature, salinity and sound speed were filled in on a uniform grid using nearest neighbor to 5500 m depth. Values on a regular grid make life easier. Product documented in Dushaw and Menemenlis, 2014, Antipodal acoustic thermometry: 1960, 2004, Deep Sea Research Part I: Oceanographic Research Papers, 86, 1–20, https://doi.org/10.1016/j.dsr.824 2013.12.008.</p> <p>Each snapshot is stored as a netcdf 4 file. Latitude, Longitude, Depth, and YearDay variables given separately in sspgrid.nc . <br>N.B.: Values in the files are stored as 32-bit or 16-bit integers to save disk space:</p> <p>Sound Speed: saved as "round( (c-1000)*1000 )", so to get actual c: c=1000. + double(c)/1000. <br>Sound speed is stored to 3 decimal places as a 32-bit integer.</p> <p>Temperature: saved as "round( (T-10)*1000 )", so to get actual T: T=10. + double(T)/1000. <br>Temperature is stored to 3 decimal places as a 16-bit integer. Note that abyssal temperature can sometimes be negative.</p> <p>Salinity: saved as "round( (S-10)*1000 )", so to get actual S: S=10. + double(S)/1000. <br>Salinity is stored to 3 decimal places as a 16-bit integer.</p> <p>Data directory also has two matlab routines: get_section.m and dist.m. get_section.m shows how to load the files, compute the physical variable from the stored value, and compute a section of ssp, T, or S. dist.m is a utility for computing geodesics; it relies on R. Pawlowitz's m_map package which can be downloaded freely from his University of Vancouver web page.</p> <p>$ md5sum *tgz <br>53ca3621f422b89c599c92fbab71d2fc S_ecco_iter22.tgz (2.99 GB)<br>a9e9109b6dae7355bf2fa0926d436d9a ssp_ecco_iter22.tgz (6.09 GB)<br>0cb8d1c2cdee4c7377353dff722ece34 T_ecco_iter22.tgz (4.33 GB)</p>
Inter-Chemical Correlation results for the study: NHANES20052006 (NHANES Survey 2005-2006)
Title: NHANES Survey 2005-2006 <br>Species: Homo sapiens <br>Number of samples: 9582 <br>Number of named analytes: 319 <br>Datasource url: https://wwwn.cdc.gov/nchs/nhanes/search/datapage.aspx?Component=Laboratory <br>
MSG SEVIRI NDVI dataset for the Horn of Africa 2005-2023
<p>Dataset related to the paper "A high temporal resolution NDVI time series to monitor drought events in the Horn of Africa". The dataset does not contain the bias correction explained in the paper but be can easily applied using the provided formula. The dataset is for the countries Kenya, Ethiopia, Djibouti and Somalia.</p>
Sacramento-San Joaquin Bay-Delta Continuous (15 Minute) water quality monitoring data collected by the Continuous Environmental Monitoring Program, DWR, 2005- ongoing.
The Continuous Environmental Monitoring Program (CEMP) plays an instrumental role in overseeing real-time water quality in the Sacramento-San Joaquin Delta (the Delta) and Suisun Bay. The program harnesses wireless telemetry to transmit crucial data to the California Data Exchange Center (CDEC), making high-resolution environmental data pertaining to the Delta and Suisun Bay publicly accessible. The extensive dataset captures information at 15-minute intervals from 15 monitoring stations, utilizing YSI 6600 and YSI EXO sondes to obtain standalone water quality measurements. This extensive dataset informs the operations of the California State Water Project, ensuring it adheres to mandated water quality standards set by Water Right Decision 1641. This data compilation incorporates all information since the transition to YSI multiparameter sondes in 2005. It is important to note that the commencement dates and subsequent upgrades vary between stations, leading to slight discrepancies in the dataset's date ranges. Since its inception in the mid-1980s, CEMP has progressively expanded its monitoring capabilities, consistently augmenting the number of monitoring locations and the array of water quality parameters assessed. Its commitment to utilizing the most advanced water quality monitoring technology reaffirms its position as an environmental monitoring leader in the Delta and Suisun Bay. Today, the program oversees 15 water quality stations that reliably capture data every 15 minutes, each day of the year, transmitting this data in real-time. The core tenents of CEMP: • to obtain consistent and accurate data in real-time at established monitoring stations • to provide data necessary to achieve compliance with salinity, flow, and dissolved oxygen standards • to perform data analyses for further understanding of estuarine ecology • to report information to other government agencies, as well as the public, for the purpose of management and conservation of the upper San F
Hourly water chemistry measurements at the mouth of West Falmouth Harbor, MA, USA from 2005 to 2019 and 2023
West Falmouth Harbor (West Falmouth, MA, USA) has been experiencing a dramatic increase in nitrogen loading from an upgradient municipal wastewater treatment facility since the early 2000s. As part of a long-term study into the effects of this nitrogen enrichment, we have been measuring water chemistry at the mouth of the harbor to calculate exchange between the harbor and adjacent coastal waters of Buzzards Bay. Water samples were taken hourly over 24- to 48-hour periods during several periods in 2005-2009, 2014, 2017, 2019, and 2023. Data from 2005-2009 were collected year-round; samples from 2014 and later were collected during June through August. Samples were processed for ammonium, phosphate, nitrate + nitrite, total nitrogen, and total phosphorus unless otherwise notated. During some sampling years, additional samples were run for silicate, chlorophyll, total dissolved nitrogen, total dissolved phosphorus, dissolved organic carbon, particulate organic carbon, and particulate organic nitrogen. Salinity is reported for all samples. Samples were collected with an ISCO autosampler and stored on ice until analysis. Full analysis details and quality control methods are available in Hayn et al. 2014 (doi: 10.1007/s12237-013-9699-8) and Hayn 2025 (doi: 10.7298/btm6-ba76).
Nitrogen and carbon concentrations and stable isotope ratios (δ¹⁵N and δ¹³C) in European moss samples, 2005-2006
This dataset contains nitrogen (N) and carbon (C) concentrations and stable isotope ratios (δ¹⁵N and δ¹³C) measured in moss samples collected across Europe within the framework of the ICP Vegetation programme (International Cooperative Programme on Effects of Air Pollution on Natural Vegetation and Crops, UNECE LRTAP Convention). Moss surveys are conducted every five years and the data presented here correspond specifically to the first sampling campaign, carried out in 2005/2006. During the 2005/2006 European moss survey, approximately 3,000 moss samples were collected at non-urban and semi-natural sites across 16 European countries following a standardized biomonitoring protocol. The dataset used in this study comprises a subset of 1,022 moss samples (approximately 35 % of the total survey), provided by 12 European countries, which were selected for the determination of nitrogen and carbon concentrations and their corresponding stable isotope signatures (δ¹⁵N and δ¹³C). Moss samples collected by each participating country were sent to the Integrated Environmental Quality Laboratory (LICA), Institute for Biodiversity and Environment (BIOMA - University of Navarra), where all chemical and isotopic analyses were subsequently performed under uniform analytical conditions. In addition, this dataset incorporates moss data from Sweden, Croatia and Macedonia for the same sampling year, which were not included in the official ICP Vegetation 2005/2006 dataset. The European moss biomonitoring network was established to provide a complementary, high spatial resolution and time-integrated measure of atmospheric deposition of nitrogen and other pollutants within terrestrial ecosystems. The approach is based on the ability of ectohydric mosses to accumulate nutrients and trace elements directly from wet and dry atmospheric deposition, enabling dense spatial sampling across large geographical areas. This biomonitoring framework supports the assessment of spatial patterns of atmos
Aphid Collection Tower Site at KBS at the Kellogg Biological Station, Hickory Corners, MI (2005 to 2013) (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-kbs/49/25. The abstract below was extracted from the Level 0 data package and is included for context: Survey of migration of soybean aphid and other aphids of economic interest in 10 midwestern States. Aphids are collected using a suction trap. original data source http://lter.kbs.msu.edu/datasets/52
Gloeotrichia echinulata density at four nearshore sites in Lake Sunapee, NH, USA from 2005-2016
Surface densities of Gloeotrichia echinulata, a filamentous colonial cyanobacterium, were collected at four nearshore sites in Lake Sunapee, NH, USA from 2005-2016. Lake Sunapee is a large (1667 hectare surface area), oligotrophic, north temperate lake used for drinking water and recreation with a primarily forested watershed and a moderately-developed shoreline. Samples were collected approximately weekly at Herrick Cove South and Newbury mid-July to September in 2005 and at Herrick Cove South late June to mid-September in 2006. Data collection at Herrick Cove South, Newbury, South of the Fells, and Sunapee Harbor occurred from mid-June to mid-September in 2007-2008 and from May to October in 2009-2016.
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.
Water-quality monitoring in Tempe Town Lake, Tempe, Arizona, USA (2005-2021)
Constructed in 1997, the Tempe Town Lake is a small man-made reservoir that transforms a section of the typically-dry Salt River bed into a 224-acre lake in the heart of Tempe, Arizona. To accommodate the river when it flows, the lake features hydraulically-operated steel gates that allow water to pass through the system unimpeded. The lake has been a remarkable success as a community amenity and as a driver of economic growth in the area around the lake. The lake provides an ideal model system for the many artificial lakes constructed in arid-land cities owing to management decisions, such as draining, that affect their operation and ecology. At the same time, dramatic shifts in hydrology and chemistry when the lake is transformed to a flowing river and back into a lake during and after floods, provide opportunities to study the system's dynamic evolution to new limnological steady states. The CAP LTER has been measuring water quality, including temperature, pH, conductivity, and dissolved oxygen, dissolved organic carbon (DOC), and total dissolved nitrogen (TDN), in the lake since 2005.
Temperatures,salinities, and dissolved oxygen levels in the Shark River Slough, Everglades National Park (FCE LTER) , from May 2005 to May 2014
This dataset provides information on the environmental conditions in the Shark River Slough including dissolved oxygen, water temperature, and salinity. Data suggest that environmental parameters vary spatially and temporally within the system, especially during transition periods between the wet and dry seasons.
Water flow velocity data, Shark River Slough (SRS) near Black Hammock island, Everglades National Park (FCE LTER), South Florida from October 2003 to August 2005
Water velocity data measured every 5 or 15 minutes in Shark River Slough beside Black Hammock tree island, Everglades National Park using Sontek Agronaut water flow sampler.
Water flow velocity data, Shark River Slough (SRS) near Satinleaf Island, Everglades National Park (FCE LTER) from July 2003 to December 2005
Water velocity data measured every 5 or 15 minutes in Shark River Slough near Satinleaf tree island, Everglades National Park, using Sontek Agronaut water flow sampler.
Relative Abundance of Soft Algae From the Comprehensive Everglades Restoration Plan (CERP) Study (FCE), Florida, USA, September 2005 to November 2011
Relative soft algae data collected between September 2005 and November 2011 "The Comprehensive Everglades Restoration Plan (CERP) focuses on “getting the water right” in the south Florida ecosystem—getting the right amount of water of the right quality to the right places at the right time" (USACE & DoI, 2015. Central and Southern Florida Project Comprehensive Everglades Restoration Plan) in the Everglades ecosystems. To inform CERP, since February 2005 we have been investigating the spatio-temporal variations of distribution, biomass and diversity of algae (key aquatic primary producers) in periphyton mats in relation to hydrology, nutrients and pH, and other environmental conditions.
Periphyton Abundance and Structural Traits, Diatom Taxa Relative Abundance, and Associated Environmental Data from Samples Collected from the Greater Everglades, Florida, USA from September 2005 - ongoing
This data package contains benthic algae (periphyton) and environmental data collected annually during the wet season between 2005 and 2021 from sites distributed throughout the greater Everglades ecosystem. This project is part of the Comprehensive Everglades Restoration Program's Monitoring and Assessment Plan (CERP MAP) intended to document baseline variability in periphyton attributes for assessing the effectiveness of restoration projects. A total of 200 primary sampling units (PSU) of 800 m x 800 m are nested in 32 landscape units (LSU) and each year, random coordinates are 'drawn' within each PSU and one draw is visited in each sampleable PSU. Sampled periphyton is processed for aggregate structural traits (i.e., biomass, chlorophyll-a, organic content, and phosphorus concentration) and for diatom taxa. For diatoms, slides are prepared, and at least 500 frustules are enumerated and identified to the lowest possible taxonomic resolution per slide. Taxon abundances are then relativized to the total count. These data accompany environmental and spatial data for each sampled draw. In addition to the CERP MAP data, this dataset also includes data on the same variables collected from up to 21 primary sampling units in the Broward County Water Preserve Area beginning in 2020. The data in this package replace and supersede those in package knb-lter-fce.1210 (https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-fce&identifier=1210).
Fall 2005 crab population monitoring: mid-marsh and creek bank abundance based on crab hole counts at GCE marsh, monitoring sites 1-9
This data set is the Fall 2005 estimate of crab densities at the GCE-LTER marsh sites used for population monitoring. Crab abundance was determined by counting the number of crab holes within a 625 cm^2 quadrat and converting the counts to number per square meter. Counts were made in the mid-marsh and creek bank zones (n = 4 per zone) at GCE sites 1 through 9. Site 10 was not sampled (see anomalies below). This method does not differentiate which species made a particular hole and therefore only estimates total crab abundance. Plugged holes were excluded from the counts. Mean density across all sites and zones was 226 m^-2 (+/- 181 s.d.)
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.