  The ability to efficiently find relevant subgraphs and paths in a large graph
to a given query is important in many applications including scientific data
analysis, social networks, and business intelligence. Currently, there is
little support and no efficient approaches for expressing and executing such
queries. This paper proposes a data model and a query language to address this
problem. The contributions include supporting the construction and selection
of: (i) folder nodes, representing a set of related entities, and (ii) path
nodes, representing a set of paths in which a path is the transitive
relationship of two or more entities in the graph. Folders and paths can be
stored and used for future queries. We introduce FPSPARQL which is an extension
of the SPARQL supporting folder and path nodes. We have implemented a query
engine that supports FPSPARQL and the evaluation results shows its viability
and efficiency for querying large graph datasets.
