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This paper describes a platform that helps industrial domain experts to preserve the connection between textual sources and formalized business rules by using lexicalized ontologies both for links and for storage of the conceptual knowledge. Business Rules Management Systems (BRMSs) are used to update and query business rules of an automotive use case. They rely strongly on domain ontologies, which model the business knowledge and provide a conceptual vocabulary for the formalization of the rules that are expressed in written policies. We show that lexicalized ontologies are a key component of such BRMSs and how such knowledge can be encoded. Our proposed solution supports domain experts in the automotive industry in understanding and maintaining their business rules by presenting the relevant source documents that were used to create the ontological concepts. The use case is based on a car development scenario that models the connection between car testing scenarios, e.g., safety tests, and the methods and tools used to analyze and prepare these tests. The intended solution has been developed in the ONTORULE project and is still work in progress.

International audienceKnowledge acquisition is a key issue in the business rule methodology. As Natural Language (NL) policies and regulations are often important or even contractual sources of knowledge, we propose a framework for acquisition and maintenance of business rules based on NL texts. It enables business experts to author the specification of rule applications without the help of knowledge engineers. This framework has been created as part of the ONTORULE project, which is defining an integrated platform for acquisition, maintenance and execution of business-oriented knowledge bases combining ontologies and rules. Our framework relies on a data structure, called "index", encompassing and connecting the source text, the ontology and a textual representation of rules. Textual rules are as close to the Structured English representation of SBVR as possible for business users in charge of rule elicitation. The index relies on W3C technologies, which makes the tools interoperable and enable semantic search. We show that such an index structure supports the parallel maintenance of policy documents and knowledge bases (acquisition, consistency check and update). Two detailed examples with preliminary results are provided, one from air travel and the other from the automotive industry

Abstract:Ontologies that have been built from texts can be associated with lexical information that is crucial for the semantic annotation of texts and all semantic search tasks. However, the entire pocess of building ontologies from texts cannot be fully automated and it is important to guide the knowledge engineer during the building process. This paper presents an enriched version of TERMINAE, which is a text-based methodology for ontology design. It combines a fact-based approach of modeling with the more traditional concept-centric one. We show that named entities can be used to enrich an existing ontology and to bootstrap the acquisition process. In other words, named entities are used for the conceptualisation of ontologies and not only for their population. This approach is illustrated on two use-cases based on policy documents and evaluated by measuring the Precision and Recall of the resulting ontologies with respect to pre-existing ontologies independently built by domain experts.