Database Reference
In-Depth Information
Chapter II
Comparing Metamodels
for ER, ORM and
UML Data Models
Terry Halpin, Northface University, USA
ABSTRACT
This chapter provides metamodels for some of the main database modeling notations used
in industry. Two Entity Relationship (ER) notations (Information Engineering and
Entity Relationship (ER) notations ( Barker
ER) are examined in detail, as well as Object Role Modeling (ORM) conceptual schema
diagrams. The discussion of optionality, cardinality and multiplicity is widened to include
Unifi ed Modeling Language (UML) class diagrams. Issues addressed in the metamodel
analysis include the normalization impact of non-derived constraints on derived associations,
the infl uence of orthogonality on language transparency, and trade-offs between simplicity
and expressibility. To facilitate comparison, the same modeling notation is used to display
each metamodel. For this purpose, ORM is used because of its greater expressibility and
clarity.
INTRODUCTION
To ensure the correctness and completeness of an information system being developed,
requirements analysis should precede its design and implementation. The analysis phase
leads to a conceptual schema that specifi es the structure of the universe of discourse (applica-
tion domain). This conceptual structure should be capable of being readily understood and
validated by the domain expert, without requiring this subject matter expert to understand
technical aspects of the internal structure used to actually implement the application. Once
validated, the conceptual schema can be mapped to logical/physical/external schemas using
procedures that are partly or fully automatable.
