A minimal-model based horizontal fragmentation algorithm for disjunctive deductive databases

Disjunctive deductive databases (DDDBs) capture indefinite information, i.e., imprecise or partial knowledge of the real world, and are more general than definite deductive databases that can only represent unconditionally true facts. Formal approaches for fragmenting a DDDB, with a view to distribute the DDDB and then design a query optimization strategy for the distributed DDDB, are lacking. We present a formal approach for fragmenting a DDDB based on the minimal-model semantics. Fragments generated by the proposed algorithm facilitate query evaluation against the DDDB in a distributed system