Data people are often critical of their clients for the haphazard way they use language, especially across departments. But what about us? What is your definition for "conceptual data model"? How is that different from each of your colleagues' definitions? What about "logical data model"? "Physical data model"? This presentation describes various kinds of data models common in the industry, and attampts to provide a coherent set of definitions for each. It is based on a combination of history and your presenter's ideas of the logical way to approach the problem. This will not revolutionize the industry, but it is to be hoped that it will at least stimulate conversations.

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