Data movement is a key concept in parallel computing. Given that data movement is generally slower than data processing, it is important to guarantee an efficient use of the communication facilities of the hardware. The MPI communication protocol is the most common model to allocate and move data in High Performance Computing. MPI is a very expressive model but is also a very low-level one. More high-level models such as the PGAS (Partitioned Global Address Space) model allow easier abstraction but limit expressivity.In this paper we present an extension of the PGAS model to include more expressivity while conserving the abstract representations of the model. Specifically, we use the concept of data shape to represent data distribution and use a generalized concept of function to move and process data.