Abstract
A desirable feature of scientific data systems is that suspect and bad data be identified before release to the user community. This is a challenging task within the NASA Earth Observing System (EOS), due to the large volume and the complexity of data produced and the near real time mode between data production and distribution. The EOS Data and Information System (EOSDIS) provides the computing and network facilities, to support the generation and archival of data products from EOS satellites. EOS Quality Assessment (QA) methodology integrates a) the automated detection of certain types of suspect data, b) the capability of EOSDIS to alert the instrument team scientists and processing facility personnel to suspect data, c) the extraction of this data from the archives for QA purposes and the subsequent storage of QA results within EOSDIS, and d) the organization, archival and display of all of these QA results ina user-friendly format for the user community. Development of EOS QA methodology is described through discussions of the organization of QA information within the EOSDIS database, the components of operational QA, suggestions of how users may exploit the provided QA parameters and the support EOSDIS will provide users in utilizing QA information.
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