An important pathway to solve several computer vision problems may be through qualitative vision. Progress in qualitative vision has been very limited due to the difficulties in modeling and analyzing qualitativeness. In this paper, we consider the issue of representing shape in the qualitative sense. A robust representation is important to enable the fusion of qualitative information that is obtained from different sources. We begin with the simple scheme of storing relative positions in space. This representation is compact and can be updated easily. Probabilistic, relaxation-based schemes for fusion are possible. However, we show that this representation is not unique. In particular, we show that two objects with different qualitative shapes could have the same representation. We indicate how the representation can be augmented to overcome this difficulty. We point out the need to identify minimum information requirements for representation and other tasks.