Mathematics – Logic
Scientific paper
Aug 2008
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2008aspc..394..723d&link_type=abstract
Astronomical Data Analysis Software and Systems ASP Conference Series, Vol. 394, Proceedings of the conference held 23-26 Septem
Mathematics
Logic
Scientific paper
A rule-based approach to data quality provides for efficient and extensible solutions in validating data sets. A working prototype proves that CLIPS, a trusted rules engine, can integrate with existing data processing libraries through PyCLIPS, resulting in a system which isolates data quality rules from programming logic to allow for parallel development and maintenance of rules and applications. The prototype demonstrates several benefits: developers can treat rules independently from application source code, a ruleset can accept new rules without modification of existing rules in the set, rules can provide value through conditional assertions which call on external tools, and even a very small rule set can point to real errors in telescope data. A rules engine which automates data quality validation with existing tool libraries could potentially lead to a substantial increase in operational availability even when faced with resource scarcity.
Duplain Ronald F.
Radziwill Nicole M.
Shelton Amy L.
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