Physics
Scientific paper
Dec 2010
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010agufmsm31a1851b&link_type=abstract
American Geophysical Union, Fall Meeting 2010, abstract #SM31A-1851
Physics
[1910] Informatics / Data Assimilation, Integration And Fusion, [1978] Informatics / Software Re-Use, [1982] Informatics / Standards, [2794] Magnetospheric Physics / Instruments And Techniques
Scientific paper
The Heliolib uniform data model is a powerful and flexible approach to filling an important need of the virtual observatory community (see "Uniform Access to Heliophysics Time Series Data", SM19), but its usefulness does not stop there. We present an implementation of the Heliolib uniform data model as part of the science data pipeline for the JUNO/JEDI and New Horizons/PEPSSI instruments. JUNO/JEDI, New Horizons/PEPSSI and other upcoming instruments use the multimission telemetry processing framework Conduit to unpack the raw telemetry data into internal data structures which can be written out as science data products. It is useful during integration and testing on the ground or in flight, to be able to load these data structures directly into the final science analysis software. The JEDI science team analysis software, MIDL, uses Heliolib. Thus, since the telemetry data structures can be easily adapted to Heliolib data structures, the "wrapped" telemetry data is then automatically supported as fully described science data types, available for instrument team scientists to analyze even during early stages of instrument integration and testing. This allows the science team to potentially spot and correct errors much more efficiently than waiting until they are analyzing flight data, when discovered errors may require complex and expensive reprogramming of the instrument in flight. Examples from JEDI and PEPSSI team experiences will be described. The "wrapped" telemetry data can also be ingested into any other system that uses the Heliolib model. As an example, we present a simple spreadsheet style viewer for Heliolib "ITable" data.
Brown Lawrence E.
Haggerty Dennis K.
Hill Matthew E.
Mauk Barry H.
Vandegriff Jon D.
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