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An ontology-based methodology for supporting knowledge-intensive multi-discipline engineering processes
| Content Provider | CiteSeerX |
|---|---|
| Author | Moser, Thomas Mordinyi, Richard Biffl, Stefan |
| Abstract | Software-intensive systems in business IT and industrial automa-tion have become increasingly complex due to the need for more flexible system re-configuration, business and engineering pro-cesses. Systems and software engineering projects depend on the cooperation of experts from heterogeneous engineering disciplines using tools that were not designed to cooperate seamlessly. Current multi-discipline engineering is often ad hoc and fragile, making the evolution of tools and re-use of integration solutions across projects unnecessarily inefficient and risky. This paper describes an ontology-based methodology, the so-called Engineering Knowledge Base (EKB), for engineering envi-ronment integration in multi-disciplinary engineering projects. The EKB stores explicit engineering knowledge to support access to and management of engineering models across tools and disciplines by providing a) data integration based on mappings between local and domain-level engineering concepts; b) transformations between lo-cal engineering concepts; and c) advanced applications built on these foundations, e.g., end-to-end analyses. As a result experts from different organizations may use their well-known tools and data models, and can access data from other tools in their syntax. The methodology has been evaluated in an industrial application domain and initial evaluation results indicate an effort reduction for re-use in new engineering projects and finding defects earlier in the engineering process. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Ontology-based Methodology Knowledge-intensive Multi-discipline Engineering Process Access Data Well-known Tool Lo-cal Engineering Concept Flexible System Re-configuration End-to-end Analysis Initial Evaluation Result Engineering Envi-ronment Integration Current Multi-discipline Engineering New Engineering Project Domain-level Engineering Concept Different Organization Engineering Process Ad Hoc Ekb Store Engineering Pro-cesses Software-intensive System Result Expert Software Engineering Project Engineering Knowledge Engineering Model Heterogeneous Engineering Discipline Integration Solution Data Model Multi-disciplinary Engineering Project Industrial Application Domain Industrial Automa-tion So-called Engineering Knowledge Base Effort Reduction Data Integration |
| Content Type | Text |
| Resource Type | Article |
