Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Partnerships and Cooperations
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Section: New Results

A Quotient Framework for Summarizing RDF Graphs

RDF is the data model of choice for Semantic Web applications. RDF graphs are often large and heterogeneous, thus users may have a hard time determining whether a graph is useful for a certain application. We consider answering such questions by inspecting a graph summary, a compact structure conveying as much information as possible about the input graph. A summary is representative of a graph if it represents both its explicit and implicit triples, the latter resulting from RDF Schema constraints. To ensure representativeness, we defined a novel RDF-specific summarization framework based on RDF node equivalence and graph quotients; our framework can be instantiated with many different RDF node equivalence relations. We have shown that our summaries are representative, and establish a sufficient condition on the RDF equivalence relation to ensure that a graph can be efficiently summarized, without materializing its implicit triples. We illustrate our framework on bisimulation equivalence relations between graph nodes, and demonstrate the performance benefits of our efficient summarization method through a set of experiments. These results appeared in [17] and are extended in [20], [19].