Recent work in building data-centric sensor networks treats a sensor network as a pool of information. Sensor nodes generate, store, and retrieve information as both data producers and consumers. The intensive demand of data exchange within the network leads previous approaches with sensor-to-sink transmission model inefficient. In-network data storage schemes, such as geographical hash table (GHT) and double-rulings, have been accordingly proposed to structure the information storage among the network so as to facilitate the consumers to efficiently discover and retrieve data. Under those approaches, however, each sensor node needs to publish and retrieve data from different routes calculated every time, introducing unnecessary computation and communication overhead. This paper proposes anew approach that stores and queries data through bouncing tracks. Sensors are able to publish replica of generated data along their bouncing tracks and successfully retrieve data from other sensors along the same tracks, which largely simplifies data exchange and improves efficiency. The strengths of this design also include distance-bounded data retrieval. We conducted extensive simulations and the results show that this approach outperforms existing designs, including rumor routing and double-rulings, in terms of communication efficiency and cost.