Abstract
Recently families of sets of dependencies treated as the Datalog extensions were discovered for which the interpretation of queries becomes tractable. Such families are intended for inference of new, unknown values in the process of query answering. This paper considers such decidable classes of dependencies as the assets for creation of new data models (called in the paper the value inventive data models) analogously to axiomatic extension of the canonical model kernel used so far for unification of structured and object data models aimed at heterogeneous database integration. The paper examines the decidable classes of dependencies reflecting the semantics of value inventive data models considering such classes to be the extensions of the canonical data model kernel. The issue of identifying of decidable subsets of the canonical model extension is considered.
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