In recent years, the amount of structured RDF data available on the Web has been increasing rapidly. Efficient query processing that can scale to large amounts of RDF data has become an important topic. Significant efforts have been dedicated to the development of solutions for RDF data management. Along this line of research, the authors elaborate on a novel data partitioning strategy, which leverages the structure of the underlying data. This structure is represented in form of a parameterized structure index they propose for Resource Description Framework (RDF) data graphs called PIG.