In DataRing ANR project, data should be replicated to improve availability despite peers’ failures and to improve performance of mass collaboration. Since the data can be updated in parallel by different peers, data reconciliation must be supported. Finally, more advanced data management capabilities (e.g. replication and caching) could be provided and increase significantly the scope of social networks (e.g. enable large-scale collaboration of social participants).

To help locate replicated data that is cached at different collaborating peers, we propose a form of indexing based on recommendation. The main idea is to recommend high quality contents related to query topics from friends (or friends of friends), who are interest and active in topics related to the query. Thus, we propose P2Prec, a recommendation service for P2P content sharing systems that exploits users’ social data. To manage users’ social data, we rely on Friend-Of-A-Friend (FOAF) descriptions. P2Prec has a hybrid P2P architecture to work on top of any P2P content sharing system. It combines efficient DHT indexing to manage the users’ FOAF files with gossip robustness to disseminate the topics of expertise between friends.

It is implemented in java using the Shared-Data Overlay Network (SON) infrastructure which is the basis for the DataRing architecture.