BOWL: augmenting the semantic web with beliefs

Jin Song Dong, Yuzhang Feng, Yuan Fang Li*, Colin Keng Yan Tan, Bimlesh Wadhwa, Hai H. Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


As the Semantic Web is an open, complex and constantly evolving medium, it is the norm, but not exception that information at different sites is incomplete or inconsistent. This poses challenges for the engineering and development of agent systems on the Semantic Web, since autonomous software agents need to understand, process and aggregate this information. Ontology language OWL provides core language constructs to semantically markup resources on the Semantic Web, on which software agents interact and cooperate to accomplish complex tasks. However, as OWL was designed on top of (a subset of) classic predicate logic, it lacks the ability to reason about inconsistent or incomplete information. Belief-augmented Frames (BAF) is a frame-based logic system that associates with each frame a supporting and a refuting belief value. In this paper, we propose a new ontology language Belief-augmented OWL (BOWL) by integrating OWL DL and BAF to incorporate the notion of confidence. BOWL is paraconsistent, hence it can perform useful reasoning services in the presence of inconsistencies and incompleteness. We define the abstract syntax and semantics of BOWL by extending those of OWL. We have proposed reasoning algorithms for various reasoning tasks in the BOWL framework and we have implemented the algorithms using the constraint logic programming framework. One example in the sensor fusion domain is presented to demonstrate the application of BOWL.

Original languageEnglish
Pages (from-to)203-215
Number of pages13
JournalInnovations in Systems and Software Engineering
Issue number3
Early online date31 Mar 2015
Publication statusPublished - Sept 2015

Bibliographical note



  • OWL
  • probabilistic ontology language
  • semantic web


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