Efficient Data Sharing Over Large-Scale Distributed Communities
Source: North Dakota State University
Data sharing in large-scale Peer Data Management Systems (PDMS) is challenging due to the excessive number of data sites, their autonomous nature, and the heterogeneity of their schema. Existing PDMS query applications have difficulty to simultaneously achieve high recall rate and scalability. In this paper, the authors propose an ontology-based sharing framework to improve the quality of data sharing and querying over large-scale distributed communities. In particular, they add a semantic layer to the PDMSs, which alleviates the semantic heterogeneity and assists the system to adjust its topology, so that semantically related data sources can be connected.