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Ontologies and Model-Driven Architecture (MDA) are two modeling approaches being developed in parallel, but by different communities. They have common points and issues and can be brought closer together. Many authors have so far attempted to bridge gaps and have proposed several solutions. The result of these efforts is the recent OMG's initiative for defining an ontology development platform. In this chapter, we are giving an overview of the state-of-the-art research on the subject of applications of MDA standards for ontology development. The chapter is a result of our experience in developing the MDA-based ontology infrastructure as well as a series of tutorials we gave at many international conferences. The chapter tries to indicate the most important definition for both of the considered modeling approaches. Using those definitions, we depict their mutual similarities and differences. Then, we show the present solution pursuing to apply MDA standard to ontology development with the main stress on OMG's standardization efforts. [ABSTRACT FROM AUTHOR]

The paper presents the architecture and design of a description logics (DLs) reasoner based on the Model Driven Architecture (MDA) methodology. The architecture relies on OMG's description logics metamodel, tableau metamodel, and model transformations using a language for model transformation. We show an example of DLs knowledge base using UML notation in context of MDA. The idea can be easily applied to implementation of a first-order logic theorem prover. The paper does not discuss implementation details of reasoning algorithms and the reasoner performance. [ABSTRACT FROM AUTHOR]

This paper presents an approach to automatic annotation of learning objects' (LOs) content units that can be later assembled into new LOs personalized to the users' knowledge, preferences, and learning styles. Relying on a LO content structure ontology and some simple content-mining algorithms and heuristics, we manage to rather successfully determine the values of metadata elements aimed at annotating content units. Specifically, in this paper we present the specificities of generating metadata that describe the subject (based on a domain ontology) and the pedagogical role (based on an ontology of pedagogical roles) of a content unit. To test our approach we developed TANGRAM, an adaptive web-based educational environment for the domain of Intelligent Information system that enables on-the-fly assembly of personalized learning content out of existing content units. [ABSTRACT FROM AUTHOR]

This paper presents an ontology-based approach for automatic decomposition of learning objects (LOs) into reusable content units, and dynamic reassembly of such units into personalized learning content. To test our approach we developed TANGRAM, an integrated learning environment for the domain of Intelligent Information Systems. Relying on a number of ontologies, TANGRAM allows decomposition of LOs into smaller content units, which can be later assembled into new LOs personalized to the user's domain knowledge, preferences, and learning styles. The focus of the presentation is on the ontologies themselves, in the context of user modeling and personalization. Furthermore, the paper presents the algorithm we apply to dynamically assemble content units into personalized learning content. We also discuss our experiences with dynamic content generation and point out directions for future work. [ABSTRACT FROM AUTHOR]

The paper presents Ontology UML Profile (OUP); which, together with Ontology Definition Metamodel (ODM), enables the usage of Model Driven Architecture (MDA) standards in ontological engineering. Other similar metamodels and UML profiles are based on ontology representation languages, such as RDF(S), DAML+OIL, etc. However, none of these other solutions uses the recent W3C effort - The Web Ontology Language (OWL). In our approach, we firstly define the place of ODM and OUP in the context of the MDA four-layer architecture and identify the main OWL concepts. Then, to support ODM, we define OUP and describe its details. The proposed UML profile enables usage of the well-known UML notation in ontological engineering more extensively. We implemented an XSLT that transforms OUP ontologies into OWL in order to provide a suitable tool support. [ABSTRACT FROM AUTHOR]