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Title: R-DEVICE: A Deductive RDF Rule Language
Author(s): N. Bassiliades, I. Vlahavas.
Availability: Click here to download the PDF (Acrobat Reader) file (16 pages).
Keywords: RDF, Deductive Rules, Production Rules, RuleML.
Appeared in: Third International Workshop on Rules and Rule Markup Languages for the Semantic Web (RuleML 2004), G. Antoniou, H. Boley (Ed.), Springer-Verlag, LNCS 3323, pp. 65-80, Hiroshima, Japan, 8 Nov. 2004, 2004.
Abstract: In this paper we present R-DEVICE, a deductive rule language for reasoning about RDF metadata. R-DEVICE includes features such as normal and generalized path expressions, stratified negation, aggregate, grouping, and sorting, functions. The rule language supports a second-order syntax, where variables can range over classes and properties. Users can define views which are materialized and incrementally maintained by translating deductive rules into a couple of CLIPS production rules. Users can choose between an OPS5/CLIPS-like or a RuleML-like syntax. R-DEVICE is based on a OO RDF data model, different than the established graph model, which maps resources to objects and encapsulates properties inside resource objects, as traditional OO attributes. In this way, less joins are required to access the properties of a single resource resulting in better inferencing/querying performance. The descriptive semantics of RDF may call for dynamic re-definitions of resource classes and objects, which are handled by R-DEVICE effectively.
See also : R-DEVICE


        This paper has been cited by the following:

1 R. Angles, C. Gutierrez, "Querying RDF Data from a Graph Database Perspective", 2nd. European Semantic Web Conference (ESWC2005), May 2005, Heraklion, Greece. Lecture Notes in Computer Science, Volume 3532 / 2005, pp. 346-360.
2 Smart, Paul R (2007) Rule-Based Intelligence on the Semantic Web: Implications for Military Capabilities, Technical Report, University of Southampton, Faculty of Physical and Applied Science, Electronics and Computer Science, Web & Internet Science, http://eprints.soton.ac.uk/id/eprint/264912.
3 R. Rubino, An Implementation of Temporal Defeasible Logic for Legal Reasoning, PhD Thesis, Centro Interdipartimentale di Ricerca in Storia del Diritto, Filosofia e Sociologia del Diritto e Informatica Giuridica, University of Bolognia, 2009.
4 Duy Hoang Pham, Efficient Representation and Effective Reasoning for Multi-Agent Systems, PhD thesis, School of Information Technology and Electrical Engineering, University Of Queensland, Australia, April 2010.
5 Bry Francois, Furche Tim, Ley Clemens, Marnette Bruno, Linse Benedikt, Schaffert Sebastian, Datalog Relaunched: Simulation Unification and Value Invention, Proceedings of the Datalog 2.0 Workshop, 2011.


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