The NPP Community Collaborative Calibration and Validation Data Management System

Characterization, calibration, verification and validation of instruments' sensor and derived environmental parameters for the NPOESS Preparatory Program (NPP) will be accomplished using a partnership among industry, academia and the US Government. Two distinct facets of the work are the prime contractor's verification activities focused on contractual performance specifications and the Government's validation activities focused on the suitability of the data products for use in operational and decision support applications. These efforts are complementary and are designed as a managed collaboration. The management of data associated with the activity is likewise a coordinated use of a group of interoperable systems. The Government Resource for Algorithm Verification, Independent Testing, and Evaluation (GRAVITE) is a multifunction coordinating Information Technology resource for the acquisition, routine processing and distribution among the team of relevant data product resources. Within GRAVITE is Northrop Grumman's contribution to the combined resource called the NPOESS Science Investigator-led Processing System (NSIPS). GRAVITE also includes components that are the machine-to-machine interface to NASA's NPP Science Data Segment and for long-term preservation of the Calibration record to NOAA's Comprehensive Large-array Storage System (CLASS). A set of projects on NOAA's agency-wide CasaNOSA collaborative development environment is also used. These projects include a comprehensive pre-launch instrument test data repository, a technical library of instrument and algorithm documentation, and an active repository for both the operational algorithm code and for modified versions proposed by the Collaborative Team. CasaNOSA serves also as the collection point for findings from the calibration and validation activities, including not only recommended code changes, and specific non-conformance or bug reports but also reports on the performance of the sensors and products and updates to lookup tables, etc. Additionally, individually focused calibration and validation efforts will use the Investigator Computing Facilities at their home institutions to analyze sensor and algorithm performance.

This presentation will describe the data management principles that drive the inclusion of different systems within the data management system design. These principles include data policy for access, distribution, quality assessment, provenance and archive and principles for open sharing within the team, control of research configuration and full documentation of findings.