AUG 12, 2014 5:00am ET

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Ontologies versus Data Models


Data models have been with us since Ted Codd described normalization in 1970 and Peter Chen published his paper on entity relationship diagrams in 1976. Ontology as a discipline in philosophy can trace its roots to ancient Greece. As applied to data management, it is much more recent than data modeling and has only appeared in the past few years. But just what is the difference between ontologies and data models? If they are both about data, do they not boil down to the same thing?

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Comments (4)
Great article as usual!

Ontologies should always be used in the design of data and databases but unfortunately the tools, database design methodologies, the books and training of designers have not adopted this technique.

Creating ontologies also exposes the many varied "realties" of how individuals, departments and organizations perceive objects such a customer. When ontologies (there are always multiple ontologies in a business) are created these multiple realties become evident and add complexity to designing a database.

A database design without developing ontologies represents a singular reality that at best serves a single purpose (e.g. transaction processing) or serves the needs of s single department such as finance or sales. This is why we have multiple databases and numerous spreadsheets in organizations. Each department and ultimately each individual creates their own representation of customer or product and thus their own reality.

Reverse engineering ontologies from databases and spreadsheets is an interesting experience that can help an organization better understand their data. But few are willing or able to take the time to do this so they create yet another database.

Posted by Richard O | Tuesday, August 12 2014 at 10:43AM ET
Great article on the relationship, and hierarchy of data models and ontologies. I've usually thought of ontologies as "what you know", so seeing Malcolm's breakdown of the ontology into datasets, so organizations can make better use of what they know in an automated solution is quite helpful. I might add though that the epistemology (how do you know it) of that information is also relevant. Keeping track of the original source of the information will assist in the data architecture, and reduce risks of data duplication that often sneak into data modelling.
Posted by Edan P | Wednesday, August 13 2014 at 5:38PM ET
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