Inconsistency tolerance in P2P data integration: An epistemic logic approach

We study peer-to-peer image data integration, where each peer models an autonomous system that exports data in terms of its own schema, and data interoperation is achieved by means of mappings among the peer schemas, rather than through a unique global schema. We propose a multi-modal epistemic logical formalization based on the idea that each peer is conceived as a rational agent that exchanges knowledge/belief with other peers, thus nicely modeling the modular structure of the system. We then address the issue of dealing with possible inconsistencies, and distinguish between two types of inconsistencies, called local and P2P, respectively. We define a nonmonotonic extension of our logic that is able to reason on the beliefs of peers under both local and P2P inconsistency tolerance. Tolerance to local inconsistency essentially means that the presence of inconsistency within one peer does not affect the consistency of the whole system. Tolerance to P2P inconsistency means being able to resolve inconsistencies arising from the interaction between peers. We study query answering in the new nonmonotonic logic, with the main goal of establishing its decidability and its computational complexity. Indeed, we show that, under reasonable assumptions on peer schemas, query answering is decidable, and is coNP-complete with respect to data complexity, i.e., the size of the data stored at the peers.