Peer-to-peer (P2P) systems research has gained considerable attention recently with the increasing popularity of file sharing applications. Since these applications are used for sharing huge amounts of data, it is very important to efficiently locate the data of interest in such systems. However, these systems usually do not provide efficient search techniques. Existing systems offer only keyword search functionality through a centralized index or by query flooding. In this paper, we propose a scheme based on ref erence vectors for sharing multi-dimensional data in P2P systems. This scheme effectively supports a larger set of query operations (such as k-NN queries and content-based similarity search) than current systems, which generally support only exact key lookups and keyword searches. The basic idea is to store multiple replicas of an object's index at different peers based on the distances between the object's feature vector and the reference vectors. Later, when a query is posed, the system identifies the peers that are likely to store the index information about relevant objects using reference vectors. Thus the system is able to return accurate results by contacting a small fraction of the participating peers.