Assuming P<GI<NP, the creation and verification of a digital signature of an arbitrary RDF graph cannot be done in polynomial time.

The Resource Description Framework (RDF) describes graphs of statements about resources. This paper explores the equality of two RDF graphs in light of the graph isomorphism literature. We consider anonymous resources as unlabelled vertices in a graph, and show that the standard graph isomorphism

Abstract. In this paper a method for Partial RDF Encryption (PRE) is proposed in which sensitive data in an RDF-graph is encrypted for a set of recipients while all non-sensitive data remain publicly readable. The result is an RDF-compliant self-describing graph containing encrypted data

thematic view of a given RDF dataset, making it easier to target the rel-evant resources and properties. Our approach combines a density-based graph clustering algorithm with semantic criteria in order to identify clusters, each one corresponding to a theme. Prior to clustering, the ini-tial RDF graph

The Resource Description Framework (RDF) is a graph-based data model promoted by the W3C as the standard for Semantic Web applications. Its associated query language is SPARQL. RDF graphs are often large and varied, produced

The Semantic Web can be thought of as one large “universal” RDF graph distributed across many Web pages. Since the graph is an unwieldy view, we usually work with online RDF documents. This is natural and appropriate for most tasks

Abstract not found

This paper describes a node-centric technique for visualizing Resource Description Framework (RDF) graphs. Nodes of interest are discovered by searching over literals. Subgraphs for display are constructed by using the area around selected nodes. Wider views are created by sorting

and processing RDF graphs is often a difficult task and methods to reduce the size while keeping as much of its structural in-formation become attractive. In this paper we study bisimu-lation as a means to reduce the size of RDF graphs according to structural equivalence. We study two bisimulation algo

in RDF graphs. For dealing with SWRL/RDF rules, we regard ‘Implies’ as an OWL class, and extract all ‘Implies’ rules from an RDF database that represents a SWRL knowledge base. Each ‘Implies ’ rule is grounded through mappings built into the semantic conditions of the model theory. Based on the fixpoint