A peer to peer system easily provides a way to aggregate information distributed in the network. Anyhow, while collecting data it is quite natural for a source peer to associate different degrees of reliability to the portion of data provided by its neighbor peers. This paper investigates the data exchange problem among distributed independent sources and concentrates on the task of using dynamic preferences to drive the integration process in the case of conflicting information. Previous works in the literature are
in the sense that preferences between conflicting sets of atoms, that a peer can import, only depends on the priorities associated to the source peers at design time. These approaches do not allow to model concepts such as
“import tuples from the peer having the highest upload speed if they conflict”
“among conflicting values import the most recent ones”
. In this paper it is supposed the existence of a special peer, called
. It contains information about the peers in the network, is accessible from each peer of the system and is used to enhance preference mechanism. The framework, here proposed, ensures dynamism by allowing to select among different scenarios looking at the properties of data provided by the peers: this is done by
establishing priorities among mapping rules.