SweetJess: Translating DAMLRuleML to JESS

We describe the design of SweetJess, our new system for Semantic Web rules in Jess. The SweetJess approach makes four main new contributions. First, we show how to translate from rules in the Situated Courteous Logic Programs (SCLP) knowledge representation, syntactically encoded in RuleML, into Jess rules, and likewise to translate from a broad but restricted case of Jess rules into SCLP RuleML. SCLP is expressively powerful and features prioritized conflict handling and procedural attachments. The translation applies to a broad but restricted case in each direction, and preserves semantic equivalence – i.e., for a given rulebase, the same conclusions are entailed. Second, we give an architecture to perform (a broad case of) SCLP RuleML inferencing using the Jess rule engine. Third, rather straightforwardly, we have developed a DAML+OIL ontology for (SCLP) RuleML itself. The resulting syntax for RuleML is called “DamlRuleML”; the DAML+OIL is simply used as “syntactic sugar” for encoding of RuleML. Fourth, our translation newly enables bidirectional inter-operability, via RuleML, between Jess — a “reactive” rule system — and multiple other heterogeneous rule systems, including Prologs and relational database systems (“derivational” rule systems), for which translation to RuleML has already been shown and among which there are several existing translation tools (e.g., our SweetRules system). It thereby moves a discernible step closer to the Semantic Web’s vision of wide knowledge sharing and integration among intelligent applications, e.g., where rules are already often deployed for e-business policies and workflow. Prototyping of SweetJess is in progress. We intend to make the implementation publicly available.