The rise of ubiquitous sensing enables the harvesting of massive amounts of data from the physical world. This data is often used to drive the behavior of devices, but when presented to users, it is most commonly visualized quantitatively, as graphs and charts. Another approach for the representation of sensor network data presents the data within a rich, virtual environment. By freely exploring such environments, users gain a vivid, multi-modal, and experiential perspective into large, multi-dimensional datasets. We present a variety of approaches to manifesting data in “avatar landscape”, including landscapes generated off live video, representing sensor history in the appearance and behavior of animals, or tinting frames in correspondence with temperature.