Incremental Reasoning on Streams and Rich Background Knowledge

  • Davide Francesco Barbieri
  • Daniele Braga
  • Stefano Ceri
  • Emanuele Della Valle
  • Michael Grossniklaus
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6088)


This article presents a technique for Stream Reasoning, consisting in incremental maintenance of materializations of ontological entailments in the presence of streaming information. Previous work, delivered in the context of deductive databases, describes the use of logic programming for the incremental maintenance of such entailments. Our contribution is a new technique that exploits the nature of streaming data in order to efficiently maintain materialized views of RDF triples, which can be used by a reasoner.

By adding expiration time information to each RDF triple, we show that it is possible to compute a new complete and correct materialization whenever a new window of streaming data arrives, by dropping explicit statements and entailments that are no longer valid, and then computing when the RDF triples inserted within the window will expire. We provide experimental evidence that our approach significantly reduces the time required to compute a new materialization at each window change, and opens up for several further optimizations.


Data Stream Logic Program Logic Programming Maintenance Program Expiration Time 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Davide Francesco Barbieri
    • 1
  • Daniele Braga
    • 1
  • Stefano Ceri
    • 1
  • Emanuele Della Valle
    • 1
  • Michael Grossniklaus
    • 1
  1. 1.Dipartimento di Elettronica e InformazionePolitecnico di MilanoMilanoItaly

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