I'll be working in Osaka for three months on ontologizing a couple of datasets with the help of Riichiro Mizoguchi. This means that I'll have enough time to revise various notions about ontology engineering during this period. Here's a first and fundamental one, regarding the difference between ontologies and data models:
The difference between ontologies and data models does not lie in the language being used: you can deﬁne an ontology in a basic ER language (although you will be hampered in what you can say); similarly, you can write a data model with OWL. Writing something in OWL does not make it an ontology! The key difference is not the language the intended use. A data model is a model of the information in some restricted well-delimited application domain, whereas an ontology is intended to provide a set of shared concepts for multiple users and applications. To put it simply: data models live in a relatively small closed world; ontologies are meant for an open, distributed world (hence their importance for the Web).
Schreiber. Knowledge Engineering. Handbook of Knowledge Representation (2007) pp. 929-946
Cite this blog post:
Digital Humanities 2011 , Stanford, USA, Jun 2011.
Synthese, Volume 182, Number 2, Springer, Jan 2011.
Semantic Web Technologies for e-Learning, Oct 2009. D. Dicheva, R. Mizoguchi, J. Greer (Eds.), vol. 4 The Future of Learning, IOS Press
PhD Thesis, Milton Keynes, UK, The Open University, Jul 2009.
Fifth International Workshop on Ontologies and Semantic Web for E-Learning (SWEL-07), held in conjunction with AIED-07, Marina Del Rey, California, USA, Jul 2007.