There is a new trend to use Datalog-style rule-based languages to specify modern distributed applications, notably on the Web. We introduce here such a language for a distributed data model where peers exchange messages (i.e. logical facts) as well as rules. The model is formally defined and its interest for distributed data management is illustrated through a variety of examples. A contribution of our work is a study of the impact on expressiveness of "delegations" (the installation of rules by a peer in some other peer) and explicit timestamps. We also validate the semantics of our model by showing that under certain natural conditions, our semantics converges to the same semantics as the centralized system with the same rules. Indeed, we show this is even true when updates are considered.
Conjunctive regular path queries are an expressive extension of the well-known class of conjunctive queries. Such queries have been extensively studied in the (graph) database community, since they support a controlled form of recursion and enable sophisticated path navigation. Somewhat surprisingly, there has been little work aimed at using such queries in the context of description logic (DL) knowledge bases, particularly for the lightweight DLs that are considered best suited for data-intensive applications. This paper aims to bridge this gap by providing algorithms and tight complexity bounds for answering two-way conjunctive regular path queries over DL knowledge bases formulated in lightweight DLs of the DL-Lite and EL families. Our results demonstrate that in data complexity, the cost of moving to this richer query language is as low as one could wish for: the problem is NL-complete for DL-Lite and P-complete for EL. The combined complexity of query answering increases from NP- to PSpace-complete, but for two-way regular path queries (without conjunction), we show that query answering is tractable even with respect to combined complexity. Our results reveal two-way conjunctive regular path queries as a promising language for querying data enriched by ontologies formulated in DLs of the DL-Lite and EL families or the corresponding OWL 2 QL and EL profiles.
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