Program parallelization requires mapping computation and data to processing elements. Navigational programming (NavP), based on the principle of migrating computations, offers a different approach than the conventional solutions that use a SPMD model. This paper focuses on data distribution for NavP. We introduce the navigational trace graph (NTG), a mathematical structure that captures the alignment and distribution preferences of a sequential program. Graph partitioning is applied to NTGs to obtain data distribution solutions. The major advantage is that our methodology can focus exclusively on reducing communication overhead first and later determine the actual computation partition and parallelization, because NavP computations migrate freely across partitions. This is in stark contrast to SPMD, where the data partitioning imposes hard constraints on the threads because they are stationary. We present experimental results to demonstrate the effectiveness of our approach.