This paper targets on parallel XML document partitioning strategies to process XML queries in parallel. To describe the problem of XML data partitioning, a concept, intermediary node, is presented in this paper. By a set of intermediary nodes, an XML data tree can be partitioned into a root-tree and a set of sub-trees. While the root-tree is duplicated over all the nodes, the set of the sub-trees can be evenly partitioned over all the nodes based on the workload of user queries. For the same XML data tree, there are a number of intermediary nodes sets, and different intermediary nodes sets will generate different partitions. It can be evaluated if a partitioning is good based on the workload of user queries. It is obviously an NP hard problem to choose an optimal partitioning. To solve this problem, this paper proposes a set of heuristic rules. Based on the idea described above, this paper designs and implements an XML data partitioning algorithm, WIN, and the extensive experimental results show that its speedup and scaleup performances outperform the existing strategies.