Information Modeling and Relational Databases: From Conceptual Analysis to Logical Design

Chapter 1: Introduction

1.1 Information Modeling

Do you remember the news flashes back in September 1999 when NASA s Mars Climate Orbiter was lost in space? Apparently, errors in its course settings caused the $125 million craft to burn up in the Martian atmosphere. Embarrassingly, the likely cause of this demise was the failure to make a simple conversion from the U.S. customary system of measurement to metric units. One team worked in customary units and sent its data to a second team working in metric, but no conversion was made. If I tell you that I weigh 180, do I need to go on a drastic diet? No if I mean 180 lb, but yes if I mean 180 kg. Data by itself is not enough what we really need is information, the meaning or semantics behind the data. Since computers lack common sense, we need to pay especial attention to semantics when we use computers to model some aspect of reality.

This book provides a modern introduction to database systems, with the emphasis on information modeling. At its heart is a very high level semantic approach that is fact-oriented in nature. If you model databases using either traditional or object-oriented approaches, you ll find that fact orientation lifts your thinking to a higher level, illuminating your current way of doing things. Even if you re a programmer rather than a database modeler, this semantic approach provides a natural and powerful way to design your data structures.

A database is basically a collection...

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