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SeaBASS, the publicly shared archive of in situ oceanographic and atmospheric data maintained by the NASA Ocean Biology Processing Group (OBPG). High quality in situ measurements are prerequisite for satellite data product validation, algorithm development, and many climate-related inquiries. As such, the NASA Ocean Biology Processing Group (OBPG) maintains a local repository of in situ oceanographic and atmospheric data to support their regular scientific analyses. The SeaWiFS Project originally developed this system, SeaBASS, to catalog radiometric and phytoplankton pigment data used their calibration and validation activities. To facilitate the assembly of a global data set, SeaBASS was expanded with oceanographic and atmospheric data collected by participants in the SIMBIOS Program, under NASA Research Announcements NRA-96 and NRA-99, which has aided considerably in minimizing spatial bias and maximizing data acquisition rates. Archived data include measurements of apparent and inherent optical properties, phytoplankton pigment concentrations, and other related oceanographic and atmospheric data, such as water temperature, salinity, stimulated fluorescence, and aerosol optical thickness. Data are collected using a number of different instrument packages, such as profilers, buoys, and hand-held instruments, and manufacturers on a variety of platforms, including ships and moorings.
SESAR, the System for Earth Sample Registration, is a global registry for specimens (rocks, sediments, minerals, fossils, fluids, gas) and related sampling features from our natural environment. SESAR's objective is to overcome the problem of ambiguous sample naming in the Earth Sciences. SESAR maintains a database of sample records that are contributed by its users. Each sample that is registered with SESAR is assigned an International Geo Sample Number IGSN to ensure its global unique identification.
The UCI Machine Learning Repository is a collection of databases, domain theories, and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms. It is used by students, educators, and researchers all over the world as a primary source of machine learning data sets. As an indication of the impact of the archive, it has been cited over 1000 times.
The NSIDC Distributed Active Archive Center (DAAC) processes, archives, documents, and distributes data from NASA's past and current Earth Observing System (EOS) satellites and field measurement programs. The NSIDC DAAC focuses on the study of the cryosphere. The NSIDC DAAC is one of NASA's Earth Observing System Data and Information System (EOSDIS) Data Centers.