Titlebook: Ontology-Driven Software Development; Jeff Z. Pan,Steffen Staab,Yuting Zhao Book 2013 Springer-Verlag Berlin Heidelberg 2013 description l

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Model-Driven Software Developmentsary to identify and analyse technologies applied in MDSD. We define basic concepts, such as model-driven engineering, metamodelling, model transformation and technological space, and describe the state-of-the-art implementations of these concepts.

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Ontology Languages and Description Logicstefacts and better handling of complexity, via ontology-based knowledge representation (KR) techniques and reasoning techniques. The term ontology originates from philosophy, where it refers to a unique description of the universe or ’things that are’. In modern information technology, especially in

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Case Studies for Marrying Ontology and Software Technologiese studies will be revisited in later chapters, in particular Chaps. 9 and 10. Many of the solutions are based on the scalable reasoning technologies to be introduced in Chap. 5. The rest of this chapter is organised as follows. Section. 4.1 shows which problems companies meet when they want to speci

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Scalable Ontology Reasoning Servicesoning, we refer readers to Chap. 3. As to be illustrated in Chaps. 9 and 10, reasoning services will be required to perform consistency checking and to derive implicit knowledge from the ontologies. Given the large number and volume of models, their complexity and the diversities of required reasoni

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Traceability exist among entities created or used during a software development process. Typically, these associations and dependencies are represented as traceability relationships between the artefacts or models to be traced. Today, traceability is recognised as being essential for various tasks related to so

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Metamodelling and Ontologies( ∗ )grating metamodelling and ontologies. On the one hand, there are metamodels for standard ontology languages, such as OWL 2. On the other hand, there have been efforts enriching standard ontology languages with metamodelling capabilities. Chapter 11 will provide further discussions on metamodelling o

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Ontology and Bridging Technologieshe ontology reasoning services introduced in Chaps. 3 and 5. We show how they can be used, as key-enabling technologies, to support bridging technologies for combining ModelWare technological spaces and OntologyWare technological spaces. ModelWare technological spaces provide modelling languages, wh

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Ontology Reasoning for Consistency-Preserving Structural ModellingSD infrastructure. We illustrate how the ontology services (see Chaps. 3 and 5 for details) summarised in Chap. 8 are employed to enable consistency-preserving structural modelling by providing means for the specification of consistency constraints, static semantics, or the derivation of suggestions

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