Analyzing the AIR language: a semantic web (production) rule language

Authors:
Ankesh Khandelwal;Jie Bao;Lalana Kagal;Ian Jacobi;Li Ding;James Hendler
Affiliations:
Rensselaer Polytechnic Institute, Troy, NY;Rensselaer Polytechnic Institute, Troy, NY;Massachusetts Institute of Technology, Cambridge, MA;Massachusetts Institute of Technology, Cambridge, MA;Rensselaer Polytechnic Institute, Troy, NY;Rensselaer Polytechnic Institute, Troy, NY
Venue:
RR'10 Proceedings of the Fourth international conference on Web reasoning and rule systems
Year:
2010

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Abstract

The Accountability In RDF (AIR) language is an N3-based, Semantic Web production rule language that supports nested activation of rules, negation, closed world reasoning, scoped contextualized reasoning, and explanation of inferred facts. Each AIR rule has unique identifier (typically an HTTP URI) that supports reuse of rule. In this paper we analyze the semantics of AIR language by: i) giving the declarative semantics that support the reasoning algorithm, ii) providing complexity of AIR inference; and iii) evaluating the expressiveness of language by encoding Logic Programs of different expressivities in AIR.