This paper is a contribution to semantic data management in P2P systems. It is based on the previous works of the sameauthors in which a declarative semantics for P2P systems is defined: under this semantics, only facts not making thelocal databases inconsistent are imported (Weak Models) and the Maximal Weak Models are those in which peers importmaximal sets of facts not violating integrity constraints. The proposal, presented in this paper, stems from the following twoobservations: (i) the Maximal Weak Model Semantics ensures that locally consistent P2P systems always admit a maximalweak model, but fails for locally inconsistent P2P systems; (ii) the self-esteem degree of a peer should impact on theinteraction with other peers in the system so that driving the integration process. From the above-mentioned observationsa more general framework is presented. Our proposal is able to manage local inconsistencies and allows to model a peerintegration process driven by the self-esteem degree of each peer. Different self-esteem degrees could be considered; in thispaper we focus our attention on three different scenarios in which a generic peer can declare an high, low or medium selfesteemdegree, stating respectively that it trusts its own knowledge more, less or equally with respect to the knowledge thatcan be provided from the rest of the system. Three different basic semantics are proposed, High, Low, Medium Self-EsteemSemantics and results about the computational complexity of P2P logic queries are investigated by considering brave andcautions reasoning. The paper also presents an extension of the basic framework of the Self-Esteem Semantics that modelsa finer-grained self-esteem concept and allows each peer to exhibit different levels of self-esteem each of them defined withrespect to a subset of its mapping rules.
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