Learning the differences between ontologies and conceptual schemas through ontology-driven information systems

Frederico Fonseca, James Martin

Research output: Contribution to journalReview articlepeer-review

60 Scopus citations


In the traditional systems modeling approach, the modeler is required to capture a user's view of some domain in a formal conceptual schema. The designer's conceptualization may or may not match with the user's conceptualization. One of the reasons for these conflicts is the lack of an initial agreement among users and modelers concerning the concepts belonging to the domain. Such an agreement could be facilitated by means of an ontology. If the ontology is previously constructed and formalized so that it can be shared by the modeler and the user in the development process, such conflicts would be less likely to happen. Following up on that, a number of investigators have suggested that those working on information systems should make use of commonly held, formally defined ontologies that would constrain and direct the design, development, and use of information systems - thus avoiding the above mentioned difficulties. Whether ontologies represent a significant advance from the more traditional conceptual schemas has been challenged by some researchers. We review and summarize some major themes of this complex discussion. While recognizing the commonalities and historical continuities between conceptual schemas and ontologies, we think that there is an important emerging distinction that should not be obscured and should guide future developments. In particular, we propose that the notions of conceptual schemas and ontologies be distinguished so as to play essentially different roles for the developers and users of information systems. We first suggest that ontologies and conceptual schemas belong to two different epistemic levels. They have different objects and are created with different objectives. Our proposal is that ontologies should deal with general assumptions concerning the explanatory invariants of a domain - those that provide a framework enabling understanding and explanation of data across all domains inviting explanation and understanding.

Original languageEnglish (US)
Pages (from-to)129-142
Number of pages14
JournalJournal of the Association for Information Systems
Issue number2
StatePublished - 2007

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications


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