This paper presents a sample translation addressing the diversity of existing learning object metadata standards. Specifically, the bidirectional translation is between CanCore metadata and Weighted Object-Oriented RuleML, and is accomplished using XSLT. The overall aim of these translators is to demonstrate that interoperability is not precluded by lack of consensus among groups interested in ...

We show the first detailed realistic e-business application scenario that uses and exploits capabilities of the SweetRules V2.1 toolset for e-contracting using the SweetDeal approach. SweetRules is a uniquely powerful integrated set of tools for semantic web rules and ontologies. SweetDeal is a rule-based approach to representation of business contracts that enables software agents to create, e...

In F-logic and RIF, objects (frames) are de ned entirely separately from function and predicate applications. In POSL and RuleML, these fundamental notions are integrated by permitting applications with optional object identi ers and, orthogonally, arguments that are positional or slotted. The resulting positional-slotted, object-applicative (psoa) terms are given a novel formalization, reducin...

Our work is part of the heterogeneous data integration, with the definition of a structural and semantic mediation model. Our aim is to propose architecture for the heterogeneous sources metadata mediation, represented by XML, RDF and RuleML models, providing to the user the metadata transparency. This, by including data structures, of natures fundamentally different, and allowing the decomposi...

This paper presents a context mediation based approach for achieving interoperability among semantically heterogeneous learning objects and learners. The presented work is focused on building a common ontology for the domain of learning objects participating in data exchange. An ontological graph is proposed as a knowledge representation of the ontology, and methods for manipulating ontologies ...

An approach to building ontologies that assists in achieving interoperability among semantically heterogeneous learning objects and learners is presented. Current work focuses on building ontologies of learning objects, particularly course outlines. The ontology is implemented using the Rule Markup Language (RuleML), an XML-based standard. A RuleML representation allows the ontology to be flexi...

In Positional-Slotted Object-Applicative (PSOA) RuleML, a predicate application (atom) can have an Object IDentifier (OID) and descriptors that may be positional arguments (tuples) or attributevalue pairs (slots). PSOA RuleML 1.0 extends earlier versions by explicitly specifying for each descriptor whether it is to be interpreted under the perspective of the predicate in whose scope it occurs. ...

RuleML and SWRL are closely related rule markup languages that are growing in popularity particularly within the Semantic Web community. Both are based on XML and as such are more amenable to computer processing than human generation and interpretation. Even so it is possible to read and write RuleML and SWRL rules manually using a text editor. Due to certain constraints imposed within SWRL, ho...

Rule Responder is a rule-based multi-agent framework in which agents run platform-specific rule engines as distributed inference services. They communicate with each other using Reaction RuleML as the common rule interchange format, e.g. for question answering or execution of mobile rule code in distributed problem solving, concurrent processing workflows and distributed event/action processing...