Data Models: A Semantic Approach for Database Systems (MIT Press series in computer science)

This book deals with two issues which are of considerable interest within database management today: the development of semantic data models, and equivalence properties of data models. Semantic data models ease the expression of a particular application to a database system. An understanding of data model equivalence is necessary for accessing a single database using different data models and for transferring data and programs from one database system to another.

In addition to explaining previous work in these areas, Data Models presents new research results. This is done with a balance of definitions, examples, discussion, and theorems.

Two semantic data models are presented: the semantic relation data model and the semantic graph data model. These data models are related in form to two popular data models: the relational data model and the network data model.

The equivalence properties of the two semantic data models are explored in a general framework useful for understanding equivalence properties of any data models. Significantly, the derivations of equivalent update operations are considered in detail.

Data Models can be used to advantage by practitioners as well as researchers. For designers of database systems, especially shared or distributed systems, it provides a framework for understanding important aspects of such systems and points out specific problems which must be addressed in the system design. Data Models can help users of database systems understand their current systems as well as understand what database systems of the future will look like.

Data Models is appropriate as a supplemental text on database management at the advanced undergraduate and graduate levels. Instructors will appreciate this book as a fine example of applying formal techniques to a relevant research area.