Getting back to the ontological work..

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



  • Why use OWL? by Adam Pease (clear presentation of the advantages of OWL over XML)
  • Interdisciplinary Ontology Forum in Japan – InterOntology10
  • The research prototype of Europeana’s semantic search engine.
  • Hozo (a nice ontology editor) online ontology viewer
  • OWLSight – owl ontology browser (online)