Amazon Web Services and the National Aeronautics and Space Administration (NASA)
have entered into a Space Act Agreement to explore best practices around discovery,
access, and use of high-value NASA science datasets. Making analytics-optimized data
stores available to the science community will minimize the need for data wrangling
and preprocessing within the community, leading to a faster time to insight and quicker
innovation.
If you want to add a dataset or example of how to use a dataset to this registry, please follow the instructions on the Registry of Open Data on AWS GitHub repository.
Unless specifically stated in the applicable dataset documentation, datasets available through the Registry of Open Data on AWS are not provided and maintained by AWS. Datasets are provided and maintained by a variety of third parties under a variety of licenses. Please check dataset licenses and related documentation to determine if a dataset may be used for your application.
If you have a project using a listed dataset, please tell us about it. We may work with you to feature your project in a blog post.
agricultureair qualityanalyticsarchivesatmosphereclimateclimate modeldata assimilationdeep learningearth observationenergyenvironmentalforecastgeosciencegeospatialglobalhistoryimagingindustrymachine learningmachine translationmetadatameteorologicalmodelnetcdfopendapradiationsatellite imagerysolarstatisticssustainabilitytime series forecastingwaterweatherzarr
NASA's goal in Earth science is to observe, understand, and model the Earth system to discover how it is changing, to better predict change, and to understand the consequences for life on Earth. The Applied Sciences Program serves NASA and Society by expanding and accelerating the realization of societal and economic benefits from Earth science, information, and technology research and development.
The NASA Prediction Of Worldwide Energy Resources (POWER) Project, a NASA Applied Sciences program, improves the accessibility and usage NASA Earth Observations (EO) supporting community research in three focus areas: 1) renewable energy development, 2) building energy efficiency, and 3) agroclimatology applications. POWER can help communities be resilient amid observed climate variability through the easy access of solar and meteorological data via a verity of access methods.
The latest POWER version includes hourly-based source Analysis Ready Data (ARD), in addition to enhanced daily, monthly, annual, and climatology ARD. The daily time-series spans 40 years for meteorology available from 1981 and solar-based parameters start in 1984. The hourly source data are from Clouds and the Earth's Radiant Energy System (CERES) and Global Modeling and Assimilation Office (GMAO), spanning 20 years from 2001. The hourly data will provide users the ARD needed to model the energy performance of building systems, providing information directly amenable to decision support tools introducing the industry standard EPW (EnergyPlus Weather file).
POWER also provides parameters at daily, monthly, annual, and user-defined time periods, spanning from 1984 through to within a week of real time. Additionally, POWER provides are user-defined analytic capabilities, including custom climatologies and climatological-based reports for parameter anomalies, ASHRAE® compatible climate design condition statistics, and building climate zones.
The ARD and climate analytics will be readily accessible through POWER's integrated services suite, including the Data Access Viewer (DAV). The DAV has recently been improved to incorporate updated parameter groupings, new analytical capabilities, and the new data formats. POWER also provides a complete API (Application Programming Interface) that allows uses...
climateearth observationenvironmentalnatural resourceoceanssatellite imagerywaterweather
A global, gap-free, gridded, daily 1 km Sea Surface Temperature (SST) dataset created by merging multiple Level-2 satellite SST datasets. Those input datasets include the NASA Advanced Microwave Scanning Radiometer-EOS (AMSR-E), the JAXA Advanced Microwave Scanning Radiometer 2 (AMSR-2) on GCOM-W1, the Moderate Resolution Imaging Spectroradiometers (MODIS) on the NASA Aqua and Terra platforms, the US Navy microwave WindSat radiometer, the Advanced Very High Resolution Radiometer (AVHRR) on several NOAA satellites, and in situ SST observations from the NOAA iQuam project. Data are available fro...
climateCMIP5natural resourcesustainability
A collection of downscaled climate change projections, derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) [Taylor et al. 2012] and across the four greenhouse gas emissions scenarios known as Representative Concentration Pathways (RCPs) [Meinshausen et al. 2011]. The NASA Earth Exchange group maintains the NEX-DCP30 (CMIP5), NEX-GDDP (CMIP5), and LOCA (CMIP5).
machine learningNASA SMD AI
The v1 dataset includes AIA/HMI observations 2010-2018 and v2 includes AIA/HMI observations 2010-2020 in all 10 wavebands (94A, 131A, 171A, 193A, 211A, 304A, 335A, 1600A, 1700A, 4500A), with 512x512 resolution and 6 minutes cadence; HMI vector magnetic field observations in Bx, By, and Bz components, with 512x512 resolution and 12 minutes cadence; The EVE observations in 39 wavelengths from 2010-05-01 to 2014-05-26, with 10 seconds cadence.
air qualityatmosphereearth observationenvironmentalgeospatialsatellite imagery
NO2 tropospheric column density, screened for CloudFraction < 30% global daily composite at 0.25 degree resolution for the temporal range of 2004 to May 2020. Original archive data in HDF5 has been processed into a Cloud-Optimized GeoTiff (COG) format. Quality Assurance - This data has been validated by the NASA Science Team at Goddard Space Flight Center.Cautionary Note: https://airquality.gsfc.nasa.gov/caution-interpretation.
cogplanetarysatellite imagerystac
These data are infrared image mosaics, tiled to the Mars quadrangle, generated using Thermal Emission Imaging System (THEMIS) images from the 2001 Mars Odyssey orbiter mission. The mosaic is generated at the full resolution of the THEMIS infrared dataset, which is approximately 100 meters/pixel. The mosaic was absolutely photogrammetrically controlled to an improved Viking MDIM network that was develop by the USGS Astrogeology processing group using the Integrated Software for Imagers and Spectrometers. Image-to-image alignment precision is subpixel (i.e., <100m). These 8-bit, qualitative d...
cogplanetarysatellite imagerystac
The Solid State Imager (SSI) on NASA's Galileo spacecraft acquired more than 500 images of Jupiter's moon, Europa. These images vary from relatively low-resolution hemispherical imaging, to high-resolution targeted images that cover a small portion of the surface. Here we provide a set of 92 image mosaics generated from minimally processed, projected Galileo images with photogrammetrically improved locations on Europa's surface.
These images provide users with nearly the entire Galileo Europa imaging dataset at its native resolution and with improved relative image locations. The S...
cogplanetarysatellite imagerystac
The Solid State Imager (SSI) on NASA's Galileo spacecraft acquired more than 500 images of Jupiter's moon, Europa. These images vary from relatively low-resolution hemispherical imaging, to high-resolution targeted images that cover a small portion of the surface. Here we provide a set of 481 minimally processed, projected Galileo images with photogrammetrically improved locations on Europa's surface. These individual images were subsequently used as input into a set of 92 observation mosaics.
These images provide users with nearly the entire Galileo Europa imaging dataset at its native resolution and with improved relative image locations. The Solid State Imager on NASA's Galileo spacecraft provided the only moderate- to high-resolution images of Jupiter's moon, Europa. Unfortunately, uncertainty in the position and pointing of the spacecraft, as well as the position and orientation of Europa, when the images were acquired resulted in significant errors in image locations on the surface. The result of these errors is that images acquired during different Galileo orbits, or even at different times during the same orbit, are significantly misaligned (errors of up to 100 km on the surface).
The dataset provides a set of individual images that can be used for scientific analysis...
astronomymachine learningNASA SMD AI
The SOHO/LASCO data set (prepared for the challenge hosted in Topcoder) provided here comes from the instrument’s C2 telescope and comprises approximately 36,000 images spread across 2,950 comet observations. The human eye is a very sensitive tool and it is the only tool currently used to reliably detect new comets in SOHO data - particularly comets that are very faint and embedded in the instrument background noise. Bright comets can be easily detected in the LASCO data by relatively simple automated algorithms, but the majority of comets observed by the instrument are extremely faint, noise-...
fluorescence imagingGeneLabgeneticgenetic mapsmicroscopyNASA SMD AI
Fluorescence microscopy images of individual nuclei from mouse fibroblast cells, irradiated with Fe particles or X-rays with fluorescent foci indicating 53BP1 positivity, a marker of DNA damage. These are maximum intensity projections of 9-layer microscopy Z-stacks.
gene expressionGeneLabgeneticgenetic mapsNASA SMD AIspace biology
RNA sequencing data from spaceflown and control mouse liver samples, sourced from NASA GeneLab and augmented with generative adversarial network.
chemistryfluid dynamicsmaterials sciencephysicsspace biology
NASA's Physical Sciences Research Program, along with its predecessors, has conducted significant fundamental and applied research in the physical sciences. The International Space Station (ISS) is an orbiting laboratory that provides an ideal facility to conduct long-duration experiments in the near absence of gravity and allows continuous and interactive research similar to Earth-based laboratories. This enables scientists to pursue innovations and discoveries not currently achievable by other means. NASA's Physical Sciences Research Program also benefits from collaborations with several of the ISS international partners—Europe, Russia, Japan, and Canada—and foreign governments with space programs, such as France, Germany and Italy.
In fulfillment of the Open Science model, NASA's Physical Sciences Research Program is pleased to offer the PSI data repository for physical science experiments performed in reduced-gravity environments such as the ISS, Space Shuttle flights, and Free-flyers. PSI also includes data from some related ground-based studies. The PSI system is accessible and open to the public. This provides the opportunity for researchers to data mine results from prior flight investigations, expanding on the research performed. This approach will allow numerous ground-based investigations to be conducted fro...
geospatialsatellite imagery
The Terra Basic Fusion dataset is a fused dataset of the original Level 1 radiances from the five Terra instruments. They have been fully validate to contain the original Terra instrument Level 1 data. Each Level 1 Terra Basic Fusion file contains one full Terra orbit of data and is typically 15 – 40 GB in size, depending on how much data was collected for that orbit. It contains instrument radiance in physical units; radiance quality indicator; geolocation for each IFOV at its native resolution; sun-view geometry; bservation time; and other attributes/metadata. It is stored in HDF5, conformed to CF conventions, and accessible by netCDF-4 enhanced models. It’s naming convention follows: TERRA_BF_L1B_OXXXX_YYYYMMDDHHMMSS_F000_V000.h5. A concise description of the dataset, along with links to complete documentation and available software tools, can be found on the Terra Fusion project page: https://terrafusion.web.illinois.edu.Terra is the flagship satellite of NASA’s Earth Observing System (EOS). It was launched into orbit on December 18, 1999 and carries five instruments. These are the Moderate-resolution Imaging Spectroradiometer (MODIS), the Multi-angle Imaging SpectroRadiometer (MISR), the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), the Clouds and Earth’s Radiant Energy System (CERES), and the Measurements of Pollution in the Troposphere (MOPITT).The Terra Basic Fusion dataset is an easy-to-access record of the Level 1 radiances for instruments on...
analyticsarchivesdeep learningmachine learningNASA SMD AIplanetary
NASA missions like the Curiosity and Perseverance rovers carry a rich array of instruments suited to collect data and build evidence towards answering if Mars ever had livable environmental conditions. These rovers can collect rock and soil samples and can take measurements that can be used to determine their chemical makeup.
Because communication between rovers and Earth is severely constrained, with limited transfer rates and short daily communication windows, scientists have a limited time to analyze the data and make difficult inferences about the chemistry in order to prioritize the next operations and send those instructions back to the rover.
This project aimed at building a model to automatically analyze gas chromatography mass spectrometry (GCMS) data collected for Mars exploration in order to help the scientists in their analysis of understanding the past habitability of Mars.
More information are available at https://mars.nasa.gov/msl/spacecraft/instruments/sam/ and the data from Mars are available and described at https://pds-geosciences.wustl.edu/missions/msl/sam.htm.
We request that you cite th...
analyticsarchivesdeep learningmachine learningNASA SMD AIplanetary
NASA missions like the Curiosity and Perseverance rovers carry a rich array of instruments suited to collect data and build evidence towards answering if Mars ever had livable environmental conditions. These rovers can collect rock and soil samples and can take measurements that can be used to determine their chemical makeup.
Because communication between rovers and Earth is severely constrained, with limited transfer rates and short daily communication windows, scientists have a limited time to analyze the data and make difficult inferences about the chemistry in order to prioritize the next operations and send those instructions back to the rover.
This project aimed at building a model to automatically analyze evolved gas analysis mass spectrometry (EGA-MS) data collected for Mars exploration in order to help the scientists in their analysis of understanding the past habitability of Mars.
More information are available at https://mars.nasa.gov/msl/spacecraft/instruments/sam/ and the data from Mars are available and described at https://pds-geosciences.wustl.edu/missions/msl/sam.htm.
We request that you ci...
air temperatureclimateclimate modelclimate projectionsCMIP6cogearth observationenvironmentalglobalmodelNASA Center for Climate Simulation (NCCS)near-surface relative humiditynear-surface specific humiditynetcdfprecipitation
The NEX-GDDP-CMIP6 dataset is comprised of global downscaled climate scenarios derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 6 (CMIP6) and across two of the four "Tier 1" greenhouse gas emissions scenarios known as Shared Socioeconomic Pathways (SSPs). The CMIP6 GCM runs were developed in support of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR6). This dataset includes downscaled projections from ScenarioMIP model runs for which daily scenarios were produced and distributed...