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
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2011
paper Ontological Requirements for Annotation and Navigation of Philosophical Resources
Synthese, Volume 182, Number 2, Springer, Jan 2011.
2010
2009
paper PhiloSURFical: An Ontological Approach To Support Philosophy Learning
Semantic Web Technologies for e-Learning, Oct 2009. D. Dicheva, R. Mizoguchi, J. Greer (Eds.), vol. 4 The Future of Learning, IOS Press
paper Ontological Requirement for Supporting Smart Navigation of Philosophical Resources
PhD Thesis, Milton Keynes, UK, The Open University, Jul 2009.
2007
paper Supporting Philosophers’ Work through the Semantic Web: Ontological Issues
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.