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4,283 results for “Database”
Titanium Alloys Database for Medical Applications
<p>The new 2.0 version (12.7.2023) includes the following modifications: 247 biocompatible Ti alloys; the table shows only literature data; a Jupyter notebook provides the calculated data.</p> <p>In this database, 238 titanium alloys were collected, almost entirely of biocompatible alloying elements. The primary motivation behind creating such a database is to establish a foundation for designing new alloys using machine learning methods. The database can assist researchers, engineers, and biomedical professionals in developing titanium alloys for various medical applications, thereby improving health outcomes and driving advancements in biomaterials and biomedical engineering.</p> <p>For more information read the paper at: <a href="https://doi.org/10.30544/MMD5"> https://doi.org/10.30544/MMD5 </a></p> <p>NOTE: To avoid misunderstandings, please cite both the database and the published article when citing this database.</p> <p>We invite other authors to contribute to the updating of this database (send at least 20 new alloys to appear as co-author)</p>
LAGOS-NE-LIMNO v1.087.3: A module for LAGOS-NE, a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of U.S. Lakes: 1925-2013
This data package, LAGOS-NE-LIMNO v1.087.3, is 1 of 5 data packages associated with the LAGOS-NE database-- the LAke multi-scaled GeOSpatial and temporal database. With this release, only this data package is being updated and users are expected to use prior releases of the other types of data. Please see the attached additional documentation for a full description of the changes that have been made for this new release.The data packages that make up LAGOS-NE include the following information on lakes and reservoirs in 17 lake-rich states in the Northeastern and upper Midwestern U.S. (1) LAGOS-NE-LOCUS v1.01: lake location and physical characteristics for all lakes greater than one hectare. (2) LAGOS-NE-GEO v1.05: ecological context (i.e., the land use, geologic, climatic, and hydrologic setting of lakes) for all lakes and for all spatial resolutions, also called ‘zones’ (i.e., ecoregions, states, counties). These geospatial data were created by processing national-scale and publicly-accessible datasets to quantify numerous metrics at multiple spatial resolutions. (3) LAGOS-NE-LIMNO v1.087.3: in-situ measurements of lake water quality from the past three decades for approximately 2,600-12,000 lakes, depending on the variable. This module was created by harmonizing 87 water quality datasets from federal, state, tribal, and non-profit agencies, university researchers, and citizen scientists. This module includes variables that are most commonly measured by state agencies and researchers for studying eutrophication. For each water quality data value, we also include metadata related to the sampling program, methods, qualifiers with data flags from the original program (qual, not standardized for LAGOS-NE), censor codes from our quality control procedures (censorcode, standardized for LAGOS-NE), and the date of each sample. (4) LAGOS-NE-GIS v1.0: the GIS data layers for lakes, wetlands, and streams, as well as the spatial resolutions that were used to create the LAGOS-N
International Soil Carbon Network version 3 Database (ISCN3)
The ISCN is an international scientific community devoted to the advancement of soil carbon research. The ISCN manages an open-access, community-driven soil carbon database. This is version 3-1 of the ISCN Database, released in December 2015. It gathers 38 separate data set contributions, totaling 67,112 sites with data from 71,198 soil profiles and 431,324 soil layers. For more information about the ISCN, its scientific community and resources, data policies and partner networks visit: http://iscn.fluxdata.org/. For information about processes used to construct the DB: https://iscn.fluxdata.org/data/data-information/.
Limno-STOICH a comprehensive database linking the elemental content of organisms with inland, aquatic habitats (2025-12-11)
The Limnology Stoichiometric Traits of Organisms In their Chemical Habitats (Limno-STOICH) contains >51,000 observations of organismal elemental content fro >3,100 rivers, lakes, wetlands, and other aquatic ecosystem sites on seven continents. The data are derived from 190+ sources including author contributed collections, novel NEON-related data, and published datasets. The database also includes extensive spatial and temporal metadata to link elemental stoichiometry with ecosystem type, trophic status, etc., and information on organismal data (body size, taxonomic classifications, stable isotope composition) and water physicochemical parameters, as available. Users are encouraged to read the associated manuscript (Corman et al.) for further information.
A Comprehensive Global Aquatic N2O Emission Database (GANED): Unravelling N2O Emission Patterns from Different Water Bodies, 1980-2023
The Global Aquatic Nitrous Oxide Emission Database (GANED) is a comprehensive synthesis of empirical observations of N2O concentration measurements and flux records, spanning the period 1980-2023. GANED advances N2O research by providing the first global systematic emission mechanisms among the different aquatic system types, including rivers, streams, estuaries, reservoirs, ponds, lakes, open seas and coastal areas. The N2O data in GANED is further interconnected with biogeochemical metadata on dissolved oxygen, dissolved organic carbon, ammonium, nitrate, nitrite, total nitrogen, water temperature, salinity and pH, along with site data (latitude, longitude, codes of channel type, depth, surface area, elevation). The dataset explains the discrepancy that emission of N2O in aquatic bodies is determined mainly by substrate availability, and not by climatic factors, and reveals the systematic biases of concentration-only measurements, which can result in an underestimation of fluxes in effluent water of dynamically changing aquatic waters. Consequently, GANED constitutes a crucial transition “where” emissions occur to understanding “why” they differ across systems, and thus enabling targeted mitigation interventions. GANED includes 5130 records of N2O concentration and 7386 flux measurements from 3,002 unique sites, most of which are resolved to the daily time scale.
ClimHyrdoDB Archive: Meteorologic and hydrologic observations from LTER and USFS sites, 2001-2020 - orignal database format
This dataset is an archive of the ClimHydroDB database, which was actively used from early 2001 to mid 2020. The database contained contributions from 62 contributors (primarily from the LTER Network and US Forest Service) and 672 research sites. Data records total approximately 16 million (raw) or 1.6 million (aggregated) for 22 meteorologic or hydrologic variables. This archive contains the 23 core tables of the ClimHydroDB database as text tables of comma separated values, plus the database entity relationship diagram (ERD), User Guide, database table descriptions (DDL, SQL script), and a zip file of related documents and presentations. Database design: At last upgrade, the database was implemented in Microsoft SQL Server 2008 (see DDL for more information). Database tables are primarily in a key-value pair arrangement, with controlled input for many fields, and extensive cross referencing. This design allows many types of descriptors to be assigned, e.g., for the types of activities taking place at research stations, or for physical parameters to describe a research area itself. The EML metadata for tables holding controlled vocabularies are described using the string “List of …”. Cross reference tables are described in metadata as such, including the parent table names. Database history: To facilitate intersite research within the LTER network, site data managers developed a system to provide climatic summaries dynamically, called ClimDB. Later funding from the U. S. Forest Service allowed the original database to be expanded to include hydrologic variables, and the combined database was renamed ClimHydroDB in 2003. The database also harvested real-time streamflow data from USGS gauging stations, using code developed by the Georgia Coastal Ecosystem LTER. As of 2021, the ClimHydroDB content is available as data packages from individual contributing sites, each containing identically formatted text tables in the ODM 1.1 format, for integration with CUAHSI tools
Six decades (1959-2022) of water quality in the upper San Francisco Estuary: an integrated database of 16 discrete monitoring surveys in the Sacramento San Joaquin Delta, Suisun Bay, Suisun Marsh, and San Francisco Bay
The upper San Francisco Estuary (SFE) is simultaneously a central hub of water delivery in California and home to commercially important and endangered fishes, such as Chinook Salmon, Green Sturgeon, and Delta and Longfin Smelt. Extensive ecological monitoring has been conducted for over 50 years, mainly under the auspices of the Interagency Ecological Program for the San Francisco Estuary (https://iep.ca.gov/). We integrated water quality data from 16 boat-based long-term monitoring surveys in the upper SFE. This integrated dataset includes measurements of temperature (surface and bottom), conductivity (surface), salinity (surface), Secchi depth, qualitative concentration of the toxic alga Microcystis (surface), Chlorophyll-a concentration (surface), nutrients (surface), and other parameters from 1959 - 2022. The component surveys range in sampling frequency from thrice weekly to monthly and range in duration from 5 – 60 years. Most component surveys sample at fixed stations, but the Enhanced Delta Smelt Monitoring survey uses random sites and some stations (with “EZ” in the station name) of the Environmental Monitoring Program follow the salinity field. It is highly recommended to inspect the documentation of the component surveys for more information on their methods.
Database of Geographic Information: Change in groundwater level, Central Arizona-Phoenix, 1985-2000
Change in Level of Groundwater in central Arizona-Phoenix, 1985-2000. This file shows spatial changes in groundwater levels for two separate time periods: 1985-1989 and 1996-2000. This is a spatial data object with a Coordinate Reference System (CRS) of EPSG:3479 NAD83(NSRS2007) / Arizona Central (ft); https://www.spatialreference.org/ref/epsg/3479/). The coordinate reference system (CRS) associated with these data when they were constructed initially was misrepresented in early versions (<= knb-lter-cap.101.8) of this dataset. The CAP LTER has attempted to assign a CRS based on reasonable values but the accuracy of the identified CRS cannot be certain.
A Global database of methane concentrations and atmospheric fluxes for streams and rivers
This dataset, referred to as MethDB, is a collation of publicly available values of methane (CH4) concentrations and atmospheric fluxes for world streams and rivers, along with supporting information on location, geographic, physical, and chemical conditions of the study sites. The data set is composed of four linked tables, corresponding to the data sources (Papers_MethDB), the study sites (Sites_MethDB), concentrations (Concentrations_MethDB), and influx/efflux rates (Fluxes_MethDB). Information was extracted from journal articles, government reports, book chapters, and similar sources that were acquired before 15 September 2015. Concentrations and fluxes were converted to a standard unit (micromoles per liter for concentration and millimoles per square meter per day for flux) and both the author-reported and converted data are included in the database. MethDB was assembled as part of a larger synthesis effort on stream and river CH4 dynamics, and assembled data were used to identify large-scale patterns and potential drivers of fluvial CH4 and to generate an updated global-scale estimate of CH4 emissions from world rivers.
Wisconsin Lake Plants - multi source database of lake plant abundance 1930 - 2004
This data set provides sampling-point by sampling-point macrophyte data for lakes sampled by a number of agencies in Wisconsin. The relational tables in this dataset were originally used to generate plant community tables. This dataset contains detailed and recent data from approximately the 1970s onward. Sampling timing and intensity varied. Table DATSOUR contains sources of data for tables AQUAPLT2 and LAKEHAB. Table AQUAPLT2 gives an estimate of plant density at each sample point. Table MAXDEPLNG has initial lake parameters derived from data in AQUAPLT2 and LAKEHAB Table LAKEHAB contains habitat characteristics at macrophyte sampling locations. Table PLTNAME has species information for plants in tables AQUAPLT2 and LAKESPEC. Table LAKES contains information for lakes included in this dataset. Table COUNTY contains information associated with the counties where the lakes in the AQUAPLT2 dataset and the LAKESPEC dataset are located. . Sampling Frequency: varies Number of sites: 1938
SBC LTER: Reef: Historical Kelp Database for giant kelp (Macrocystis pyrifera) biomass in California and Mexico
ISP Alginates (formerly Kelco Co.) has collected information on the abundance of giant kelp (Macrocystis pyrifera) in California and Mexico from routine aerial surveys since 1957. The standard protocol consists of an observer visually estimating the amount of harvestable giant kelp biomass within designated kelp beds from a small fixed-wing aircraft. Observations were recorded on paper data sheets in the field and archived in notebooks housed at ISP Alginates. With cooperation from ISP Alginates, the SBCLTER converted ISP Alginates long-term records of giant kelp biomass into a digital format. The database consists of a data table containing kelp biomass, a catalog of maps. The format ISP Alginates used to report kelp abundance data changed periodically over the course of the collecting period. These details, pus descriptions of designated kelp beds are described in the protocol document.
An isotropic EPI database for rat brain resting-state fMRI
Open the record for dataset details and reuse information.
Reference Windfarm database CNk4 90
<p>Dataset for TotalControl reference windfarm database simulation of a conventionally neutral boundary layer flow with 90 degree inflow wind direction angle (Casename CNk4 90)</p> <p>Included Python files for loading and visualizing the data. Use the plot_*.py files.</p> <p>Further information, including description of the case and dataset can be found in the deliverable report at: </p> <p><a href="https://cordis.europa.eu/project/id/727680/results">https://cordis.europa.eu/project/id/727680/results</a></p> <p>"Database for reference wind farms part 2: windfarm simulations"</p>
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>
North Sea Wave Database (NSWD) 1989-1997
<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>
North Sea Wave Database (NSWD) 2012-2017
<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>
Salzburg Database of Polygonal Data
<p>The Salzburg Database is a repository of polygonal areas of various classes and sizes, with and without holes.</p>
Open Database of Spatial Room Impulse Responses at Detmold University of Music
<p>This repository contains an open source database of Spatial Room Impulse Responses (SRIR) captured at three different performance spaces of the Detmold University of Music. It includes the following rooms: </p> <ul> <li>Detmold Konzerthaus (medium sized concert hall, ~600 seats).</li> <li>Brahmssaal (small music chamber room, ~100 seats).</li> <li>Detmold Sommertheater (theater, ~300 seats).</li> </ul> <p>The collection contains approximately 600 multichannel RIRs corresponding to several source and receiver configurations. For each room we include measurement positions on stage and at the audience area captured with both an artificial head and an open microphone array compatible with the Spatial Decomposition Method (SDM).</p> <p>The Detmold Konzerthaus holds a large scale Wave Field Synthesis system and a Room Acoustic Enhancement System. SRIRs of an ensemble of focused sources on stage and with conditions of increased artificial reverberation are also included.</p> <p>If you use this dataset for your research, please cite our work:</p> <p>Amengual Gari, S. V.; Sahin, B.; Eddy, D; Kob, M.: <strong>"Open Database of Spatial Room Impulse Responses at Detmold University of Music"</strong>, <em>149th Convention of the Audio Engineering Society, </em>2020.</p> <p> </p> <p>The database is organized in 3 sets:</p> <p><strong>- Set A: </strong></p> <p>Source: Single Source measurements.</p> <p>Receiver: Open Array and Dummy Head.</p> <p>Rooms: BS, DST, KH</p> <p>Special configurations: Artificial reverberation, music stand on stage</p> <p><strong>- Set B: </strong></p> <p>Source: Loudspeaker and WFS orchestra</p> <p>Receiver: Open Array.</p> <p>Rooms: KH</p> <p><strong>- Set C:</strong></p> <p>Source: Loudspeaker orchestra</p> <p>Receiver: Dummy Head and Omni8 array</p> <p>Rooms: KH</p> <p> </p> <p>Further details on the measurement procedure and acoustical analysis of the RIRs can be found in the following publications:</p> <p><strong>Set A</strong></p> <p>Amengual Gari, S. V., Investigations on the Influence of Acoustics on Live Music Performance using Virtual Acoustic Methods, Ph.D. thesis, 2017.</p> <p>Amengual Garí, S. V.; Kob, M: "Investigating the impact of a music stand on stage using spatial impulse responses". 142nd Convention of the Audio Engineering Society, Berlin, May 2017.</p> <p><strong>Set B</strong></p> <p>Amengual Garí, S. V.; Pätynen, J.; Lokki, T.: "Physical and perceptual comparison of real and focused sound sources in a concert hall". Journal of the Audio Engineering Society, vol. 64 (12), pp. 1014-1025, December 2016.</p> <p><strong>Set C</strong></p> <p>Sahin, B., ““Investigation of the Detmold Concert Hall auditorium acoustics by comparing preference ratings and objective measurements.”, M.Sc. Thesis, 2017.</p> <p>Sahin, B., Amengual, S. V., and Kob, M., “Investigating listeners’ preferences in Detmold Concert Hall by comparing sensory evaluation and objective measurements,” Proc. 43th DAGA, Kiel, 2017.<br> </p>
River Surface Reflectance Database (RiverSR)
<p><strong>RiverSR database (River Surface Reflectance) v1.1.0</strong></p> <p>This database contains Landsat 5, 7, and 8 Level 1 Collection 1 surface reflectance from all rivers in the contiguous USA that are ~60 meters wide or greater. The surface reflectance values across bands (red, green, blue, nir, swir1, swir1) represent the median reflectance of pixels detected as water within each Landsat scene that are within the boundaries of each reach represented by NHDPlusV2 centerlines. Surface reflectance is therefore geo-referenced to river center lines with network topology (NHDPlusV2) for quick geospatial analysis.</p> <p><strong>Files:</strong></p> <p>1) Metadata (riverSR_v1.1_metadata.docx): Description of all data files associated with this repository. </p> <p>2) Surface reflectance database (riverSR_usa_v1.1.feather). Feather files are text files readable in R and python with the feather package and this table is joinable to nhdplusv2_modified_v1.0.shp based on the "ID" column and to the original NHDplusV2 flowlines with the "COMID" column.</p> <p>3) Shapefile of river centerlines to which the reflectance data can be attached (nhdplusv2_modified_v1.0.shp).</p> <p>4) Shapefile of the reach polygons associated with each nhdplusv2_modified reach. (nhdplusv2_polygons.shp).</p> <p>5) The reach IDs of original and new NHDplusV2 centerlines. (COMID_ID.csv).</p> <p> </p> <p> </p> <p> </p>
Composite Beams Database
<p>1. <a href="https://zenodo.org/api/files/a457c2ad-d898-4726-b65e-6a635e0ed6af/Composite_Beams_Database_v1.0.xlsx">Composite Beam Database v1.0</a></p> <p>A database of composite steel beams that are part of moment-resisting frames is provided. The database consists of 97 tests conducted over the last 30 years. The collection and metadata methodology are thoroughly presented in El Jisr et al. (2019). </p> <p>Each column in the spreadsheet is defined in the "Definitions" tab along with accompanying figures in the "Figures" tab. The database includes details of the composite slab (dimensions, material strength, shear studs) as well as the calculation of the plastic moment resistance and elastic stiffness of the sections as per European, US and Japanese provisions. A comparison between the code-based and test values is also shown. Furthermore, the database includes the plastic deformation capacity of the sections based on the first cycle envelope.</p> <p>2.<a href="https://zenodo.org/api/files/a457c2ad-d898-4726-b65e-6a635e0ed6af/Digitized_Moment_Rotation_Data_v1.0.zip">Digitized Moment Rotation Data v1.0</a></p> <p>Full digitized histories of the moment-chord rotation of the composite beams are provided.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.