We show how to interoperate, semantically and inferentially, between the leading Semantic Web approaches to rules (RuleML Logic Programs) and ontologies (OWL/DAML+OIL Description Logic) via analyzing their expressive intersection. To do so, we define a new intermediate knowledge representation (KR) contained within this intersection: Description Logic Programs (DLP), and the closely related Description Horn Logic (DHL) which is an expressive fragment of first-order logic (FOL). DLP provides a significant degree of expressiveness, substantially greater than the RDFSchema fragment of Description Logic.We show how to perform DLP-fusion: the bidirectional translation of premises and inferences (including typical kinds of queries) from the DLP fragment of DL to LP, and vice versa from the DLP fragment of LP to DL. In particular, this translation enables one to "build rules on top of ontologies": it enables the rule KR to have access to DL ontological definitions for vocabulary primitives (e.g., predicates and individual constants) used by the rules. Conversely, the DLP-fusion technique likewise enables one to "build ontologies on top of rules": it enables ontological definitions to be supplemented by rules, or imported into DL from rules. It also enables available efficient LP inferencing algorithms/implementations to be exploited for reasoning over large-scale DL ontologies.

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Abstract. Rule languages and rule systems are widely used in business applications including computer-aided training, diagnostic fact finding, compliance monitoring, and process control. However, there is little interoperability between current rule-based systems. Interoperation is one of the main goals of the Semantic Web, and developing a language for sharing rules is often seen as a key step in reaching this goal. The Semantic Web Rule Language (SWRL) is an important first step in defining such a rule language. This paper describes the development of a configurable interoperation environment for SWRL built in Protégé-OWL, the most widely-used OWL development platform. This environment supports both a highly-interactive, full-featured editor for SWRL and a plugin mechanism for integrating third party rule engines. We have integrated the popular Jess rule engine into this environment, thus providing one of the first steps on the path to rule integration on the Web.

We address why, and especially how, to We argue that this new approach meets the overall requirements to a greater extent than any of the previous approaches, including than KIF, the leading previous declarative approach.We have implemented both aspects of our approach; a free alpha prototype called Common-

Abstract:SweetDeal is a rule-based approach to representation of business contracts that enables software agents to create, evaluate, negotiate, and execute contracts with substantial automation and modularity. It builds upon the situated courteous logic programs knowledge representation in RuleML, the emerging standard for Semantic Web XML rules.Here, we newly extend the SweetDeal approach by also incorporating process knowledge descriptions whose ontologies are represented in DAML+OIL (the close predecessor of W3C's OWL, the emerging standard for Semantic Web ontologies), thereby enabling more complex contracts with behavioral provisions, especially for handling exception conditions (e.g., late delivery or non-payment) that might arise during the execution of the contract. This provides a foundation for representing and automating deals about services -in particular, about Web Services, so as to help search, select, and compose them.We give a detailed application scenario of late delivery in manufacturing supply chain management (SCM). In doing so, we draw upon our new formalization of process ontology knowledge from the MIT Process Handbook, a large, previously-existing repository used by practical industrial process designers. Our system is the first to combine emerging Semantic Web standards for knowledge representation of rules (RuleML) with ontologies (DAML+OIL/OWL) with each other, and moreover for a practical e-business application domain, and further to do so with process knowledge. This also newly fleshes out the evolving concept of Semantic Web Services. A prototype (soon public) is running.--3

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In the winter, 2004 issue of AI Magazine, we reported Vulcan Inc.'s first step toward creating a question-answering system called "Digital Aristotle." The goal of that first step was to assess the state of the art in applied Knowledge Representation and Reasoning (KRR) by asking AI experts to represent 70 pages from the advanced placement (AP) chemistry syllabus and to deliver knowledge-based systems capable of answering questions from that syllabus. This paper reports the next step toward realizing a Digital Aristotle: we present the design and evaluation results for a system called AURA, which enables domain experts in physics, chemistry, and biology to author a knowledge base and that then allows a different set of users to ask novel questions against that knowledge base. These results represent a substantial advance over what we reported in 2004, both in the breadth of covered subjects and in the provision of sophisticated technologies in knowledge representation and reasoning, natural language processing, and question answering to domain experts and novice users.