In this paper, we propose a framework that facilitates the use of heterogeneous data sources to represent a plan state. The traditional planners use monolithic predicate based schema for plan state representation where the world state is described as a set of predicates that are currently true. However, this approach is not efficient because, firstly, in reality, the world state can be obtained by aggregating information from different modular sources represented through multiple knowledge representation techniques and secondly, the performance of a planner can be affected when the size of state is enormously large. To overcome the stated limitations, we redefine the notion of a plan state and represent it as the combination of state predicates as well as the references to non-predicate data sources like databases, ontologies etc. The main challenge of our work is to handle plan state representation using distributed heterogeneous data sources, without altering planning algorithm in concern. Though we have based our idea around HTN planning, the approach is applicable to other planners, without any additional overhead.