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A distributed system for approximate query answering on sensor network data is proposed, where a suitable compression technique is exploited to represent data and support query answering. Each node of the system stores either detailed or summarized sensor readings. Query answers are computed by identifying the set of nodes that contain (either compressed or not) data involved in the query, and eventually partitioning the query in a set of sub-queries to be evaluated at different nodes. Queries are partitioned according to a cost model aiming at making the evaluation efficient and guaranteeing the desired degree of accuracy of query answers.