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On Computing Deltas of RDF/S Knowledge Bases

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Published:01 July 2011Publication History
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Abstract

The ability to compute the differences that exist between two RDF/S Knowledge Bases (KB) is an important step to cope with the evolving nature of the Semantic Web (SW). In particular, RDF/S deltas can be employed to reduce the amount of data that need to be exchanged and managed over the network in order to build SW synchronization and versioning services. By considering deltas as sets of change operations, in this article we introduce various RDF/S differential functions which take into account inferred knowledge from an RDF/S knowledge base. We first study their correctness in transforming a source to a target RDF/S knowledge base in conjunction with the semantics of the employed change operations (i.e., with or without side-effects on inferred knowledge). Then we formally analyze desired properties of RDF/S deltas such as size minimality, semantic identity, redundancy elimination, reversibility, and composability, as well as identify those RDF/S differential functions that satisfy them. Subsequently, we experimentally evaluate the computing time and size of the produced deltas over real and synthetic RDF/S knowledge bases.

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      • Published in

        cover image ACM Transactions on the Web
        ACM Transactions on the Web  Volume 5, Issue 3
        July 2011
        177 pages
        ISSN:1559-1131
        EISSN:1559-114X
        DOI:10.1145/1993053
        Issue’s Table of Contents

        Copyright © 2011 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 1 July 2011
        • Accepted: 1 November 2010
        • Revised: 1 July 2010
        • Received: 1 September 2008
        Published in tweb Volume 5, Issue 3

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