A review and comparison of rule languages and rule-based inference engines for the Semantic Web

Abstract

With the Semantic Web data standards defined, more applications demand inference engines in providing support for intelligent processing of the Semantic Web data. Rule-based inference engines or rule-based reasoners are used in many domains such as supporting clinical decision support system, e-commerce recommender system, access control mechanism. In order to allow rule reuse and interoperation, several rule languages have been designed for the Web. In this paper, we review and compare some rule languages designed for the Web including FOL-RuleML, SWRL, Notation3, Jena rules and RIF. Some of the comparison criteria include rule expressiveness, syntax, production operations, and built-in functions. In addition, we review and compare some free and public domain rule-based reasoners including Jena inference engine, EYE, OWLIM-lite, BaseVISor and FuXi. Some of the comparison criteria include inference algorithms, supported programming languages, RDFS/OWL reasoning, rule languages and functions. The review and comparison results will provide some guideline for researchers and developers in choosing the rule languages and systems that match the application requirements.