Towards Rule-Based Minimization of RDF Graphs under Constraints

The Resource Description Framework (RDF) is a cornerstone of the Semantic Web. Due to its few and elementary language constructs, RDF data can become large and contain redundant information. So far, techniques for eliminating redundancy rely on the generic notion of lean graphs. We propose a user-specific minimization technique based on Datalog rules, enabling a user to specify the structures in an RDF graph that are not relevant for an application and therefore are deleted, while still by means of the rules retaining the possibility to reconstruct the deleted data. We set this scenario on top of constraints to ensure data consistency, i.e. if an RDF graph satisfies some constraints before minimization, these constraints must be also satisfied afterwards. The problem is decidable but already for a restricted case intractable. In addition we give a fragment of the minimization problem which can be solved in polynomial time.

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