Guotong Xie

Model-driven ontology engineering

W3C’s Semantic Web provides a common framework that allows data to be shared and reused across application and enterprise. As the Semantic Web shapes the future of the Web, it becomes more and more important in software engineering and enterprise application development. While existing ontology engineering tools provide a stack of ontology management support and are used successfully in certain domains, there still remains a gap between the ontology engineering tools and the traditional software engineering. For several decades, software engineering has been established on different modeling languages and methodologies such as Unified Modeling Language (UML). The differences in modeling languages and methodologies cause difficulties in enterprise application development involving the Semantic Web technologies. The existing ontology engineering tools provide only an ad hoc approach to bridging this gap with limited functionality and performance. The primary objective of our work is to bridge this gap between two different, but complementary engineering disciplines with a systematic approach. Our approach leverages Model-Driven Architecture (MDA) and Ontology Definition Metamodel (ODM), which enable model transformation. This approach allows seamlessly supporting existing models in UML and other languages in Semantic Web-based software development. In addition, it allows exploiting the availability and features of UML tools for creation of vocabularies and ontologies. Furthermore, MDA enables code generation and facilitates software tool development. This paper presents an MDA-based system for ontology engineering. In addition, it presents the entire stack of individual components of the developed ontology engineering tool.

Supporting Ontology-Based Dynamic Property and Classification in WebSphere Metadata Server

Metadata management is an important aspect of todays enterprise information systems. Metadata management systems are growing from toolspecific repositories to enterprise-wide metadata repositories. In this context, one challenge is the management of the evolving metadata whose schema or meta-model itself may evolve, e.g., dynamically-added properties, which are often hard to predict upfront at the initial meta-model design time; another challenge is to organize the metadata by semantically-rich classification schemes. In this paper, we present a practical system which provides support for users to dynamically manage semantically-rich properties and classifications in the IBM WebSphere Metadata Server (MDS) by integrating an OWL ontology repository. To enable the smooth acceptance of Semantic Web technologies for developers of commercial software which must run 24 hours/day, 7 days/week, the system is designed to consist of integrated modeling paradigms, with an integrated query language and runtime repository. Specifically, we propose the modeling of dynamic properties on structured metadata as OWL properties and the modeling of classification schemes as OWL ontologies for metadata classification. We present a natural extension to OQL (Object Query Language)-like query language to embrace dynamic properties and metadata classification. We also observe that hybrid storage, i.e., horizontal tables for structured metadata and vertical triple tables for dynamic properties and classification, is suitable for the storage and query processing of co-existing structured metadata and semantic metadata. We believe that our study and experience are not specific to MDS, but are valuable for the community trying to apply Semantic Web technologies to the structured data management area.