FedS: Towards traversing federated RDF graphs

Abstract

Traversing paths within a graph is a well-studied problem and highly intractable especially with large-scale graphs. In case of multiple graphs, the standard practice is to merge distinct graphs in a centralised way to evaluate the existence of paths between given entities (or nodes). In the biomedical domain counting and retrieving the number of paths (or edges) that connect two biological entities is a highly desirable feature expected from graph databases. Therefore, non-standard solutions exist that count and retrieve paths from a single graph database. From the standard perspective, SPARQL 1.1 provides the navigational feature called Property Paths (PP) which is limited only to a single RDF graph where path existence can be evaluated between pair of nodes. In this paper, we propose a federated approach – called FedS – that retrieves paths from multiple RDF triple stores. Our key idea is to partially delegate computational load to a set of federated RDF triple stores in a peer-to-peer manner thus reducing the computational burden on a centralised query processing server. In our preliminary investigation, we evaluate FedS against the state-of-the-art approaches that provide the path counting feature over single RDF graph. We compare FedS against these approaches in terms of performance (overall path retrieval time) and result completeness, i.e., number of paths retrieved.