Global Data Management

Decentralized data management has been addressed during the years by means of several technical solutions, ranging from distributed DBMSs, to mediatorbased data integration systems. Recently, such an issue has been investigated in the context of Peer-to-Peer (P2P) architectures. In this chapter we focus on P2P data integration systems, which are characterized by various autonomous peers, each peer being essentially an autonomous information system that holds data and is linked to other peers by means of P2P mappings. P2P data integration does not rely on the notion of global schema, as in traditional mediator-based data integration. Rather, it computes answers to users’ queries, posed to any peer of the system, on the basis of both local data and the P2P mappings, thus overcoming the main drawbacks of centralized mediator-based data integration systems and providing the foundations of effective data management in virtual organizations. In this chapter we first survey the most significant approaches proposed in the literature for both mediator-based data integration and P2P data management. Then, we focus on advanced schema-based P2P systems for which the aim is semantic integration of data, and analyze the commonly adopted approach of interpreting such systems using a first-order semantics. We show some weaknesses of this approach, and compare it with an alternative approach, based on multi-modal epistemic semantics, which reflects the idea that each peer is conceived as a rational agent that exchanges knowledge/belief with other peers. We consider several central properties of P2P data integration systems: modularity, generality, and decidability. We argue that the approach based on epistemic logic is superior with respect to all the