Towards a Data-driven Ontology Engineering Framework presented at the 16th International Conference on Computers in Education in Taipei, Taiwan, October 27-31, 2008

Abstract

The dynamic nature of ontology requires a new methodology to discover the evolving semantics of a particular conceptualization and maintain the novelty of specific ontology with minimal human intervention. This paper posits a conceptual framework that supports a data-driven, iterative, and self-correcting ontology engineering methodology for developing application-oriented and light-weight ontology. The method is being tested and implemented in a work-in-progress intelligent educational system (IES) project that serves an agent-based and ontology-driven academic advising system.