In a significant class of sensor-network applications, the identities of the reporting sensors are an essential part of the reported information. For instance, in environmental monitoring, the goal is to reconstruct physical quantities over space and time; these quantities are sampled by the sensors, and the source identity associated with each measurement is necessary for the spatial and temporal reconstruction. In many practical scenarios, source identities constitute the bulk of the communicated data, whereas the message itself can be as small as a single bit. In these scenarios, the traditional network-protocol paradigm of separately specifying the source identity and the message in distinct fields leads to inefficient communication. In this paper, we re-examine this traditional data separation and propose a scheme for joint identity-message encoding; we use this scheme to design a new efficient collection protocol for identity-aware sensor networks. Compared to conventional data collection, our protocol reduces the amount of traffic in the network at least by a factor of two (up to an order of magnitude, in lossy environments), while its performance scales better with network complexity; we show these results both through theoretical analysis and extensive simulations.