Analyzing the AIR Language: A Semantic Web (Production) Rules Language

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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.


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TAMI LogoTransparent and Accountable Datamining Initiative (TAMI)
Principal Investigator: Deborah L. McGuinness and Jim Hendler
Description: The TAMI Project is creating technical, legal, and policy foundations for transparency and accountability in large-scale aggregation and inferencing across heterogeneous information systems.