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The Semantic Application Design Language (SADL) combines advances in standardized declarative modeling languages based on formal logic with advances in domain-speci¯c language (DSL) development environments to create a controlled-English language that translates directly into the Web Ontology Language (OWL), the SPARQL graph query language, and a compatible if/then rule language. Models in the SADL language can be authored, tested, and maintained in an Eclipse-based integrated development environment (IDE). This environment o®ers semantic highlighting, statement completion, expression templates, hyperlinking of concepts to their de¯nition, model validation, automatic error correction, and other advanced authoring features to enhance the ease and productivity of the modeling environment. In addition, the SADL language o®ers the ability to build in validation tests and test suites that can be used for regression testing. Through common Eclipse functionality, the models can be easily placed under source code control, versioned, and managed throughout the life of the model. Di®erences between versions can be compared side-by-side. Finally, the SADL-IDE o®ers an explanation capability that is useful in understanding what was inferred by the reasoner/rule engine and why those conclusions were reached. Perhaps more importantly, explanation is available of why an expected inference failed to occur. The objective of the language and the IDE is to enable domain experts to play a more active and productive role in capturing their knowledge and making it available as computable artifacts useful for automation where appropriate and for decision support systems in applications that bene¯t from a collaborative human-computer approach. SADL is built entirely on open source code and most of SADL is itself released to open source. This paper explores the concepts behind the language and provides details and examples of the authoring and model lifecycle support facilities.

Abstract

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Formal ontology and rule-based approaches founded on semantic technologies have been proposed as powerful mechanisms to enable early manufacturability feedback. A fundamental unresolved problem in this context is that all manufacturing knowledge is encoded in unstructured text and there are no reliable methods to automatically convert it to formal ontologies and rules. It is impractical for engineers to write accurate domain rules in a structured semantic languages such as Web Ontology Language (OWL) or Semantic Application Design Language (SADL). Previous efforts in manufacturing research that have targeted extraction of OWL ontologies from text have focused on basic concept names and hierarchies. This paper presents a semantics-based framework for acquiring more complex manufacturing knowledge, primarily rules, in a semantically-usable form from unstructured English text such as those written in manufacturing handbooks. The approach starts with existing domain knowledge in the form of OWL ontologies and applies natural language processing techniques to extract dependencies between different words in the text that contains the rule. Domain-specific triples capturing each rule are then extracted from each dependency graph. Finally, new computer-interpretable rules are composed from the triples. The feasibility of the framework has been evaluated by automatically and accurately generating rules for manufacturability from a manufacturing handbook. The paper also documents the cases that result in ambiguous results. Analysis of the results shows that the proposed framework can be extended to extract domain ontologies which forms part of the ongoing work that also focuses on addressing challenges to automate different steps and improve the reliability of the system.