An Efficient Constraint Planning Algorithm for Distributed Bio-Ontologies*

The data of Semantic Web exist in machine readable format called RDF, in order to promote data exchange on the web based on their semantics. Due to the nature of biological data, bio-ontologies tend to be very large, distributed, and interconnected. Thus, maintaining constraints and enforcing data consistency become very challenging. In previous study, we conducted a pioneer study and presented a framework for checking global constraints and ensuring integrity on data that span multiple ontologies. As an update is issued to a single site, global constraints that can be potentially violated are broken down into sub constraints that only involve a very small subset of ontologies. The checking of sub constraints runs effectively in parallel and returns results about each subset. The collection of these results determines the violation of global constraints. In this work, we present an efficient constraint planning algorithm for distributed bio-ontologies. This algorithm serves as the key part of the global constraint checking framework. This algorithm takes a number of distributed but interconnected bio-ontologies and a set of global constraints expressed in logic programming as inputs, and produces a set of sub-constraints in Semantic Web query language SPARQL for constraint checking. An working example is presented at the end.