The Enhanced E-R Model

Objectives

• Define terms
• Understand use of supertype/subtype relationships
• Understand use of specialization and generalization techniques
• Specify completeness and disjointness constraints
• Develop supertype/subtype hierarchies for realistic business situations
• Develop entity clusters
• Explain universal (packaged) data model
• Describe special features of data modeling project using packaged data model

 

 

 

Supertypes and Subtypes

• Enhanced ER model: extends original ER model with new modeling constructs
• Subtype: A subgrouping of the entities in an entity type that has attributes distinct from those in other subgroupings
• Supertype: A generic entity type that has a relationship with one or more subtypes
• Attribute Inheritance:
• Subtype entities inherit values of all attributes of the supertype
• An instance of a subtype is also an instance of the supertype

 

 

 

Relationships and Subtypes

• Relationships at the supertype level indicate that all subtypes will participate in the relationship
• The instances of a subtype may participate in a relationship unique to that subtype. In this situation, the relationship is shown at the subtype level

 

 

 

Generalization and Specialization

• Generalization: The process of defining a more general entity type from a set of more specialized entity types. BOTTOM-UP
• Specialization: The process of defining one or more subtypes of the supertype and forming supertype/subtype relationships. TOP-DOWN

 

 

 

Constraints in Supertype/ Completeness Constraint

• Completeness Constraints: Whether an instance of a supertype must also be a member of at least one subtype
• Total Specialization Rule: Yes (double line)
• Partial Specialization Rule: No (single line)

 

 

 

Constraints in Supertype/ Disjointness constraint

• Disjointness Constraints: Whether an instance of a supertype may simultaneously be a member of two (or more) subtypes
• Disjoint Rule: An instance of the supertype can be only ONE of the subtypes
• Overlap Rule: An instance of the supertype could be more than one of the subtypes

 

 

 

Constraints in Supertype/ Subtype Discriminators

• Subtype Discriminator: An attribute of the supertype whose values determine the target subtype(s)
• Disjoint – a simple attribute with alternative values to indicate the possible subtypes
• Overlapping – a composite attribute whose subparts pertain to different subtypes. Each subpart contains a Boolean value to indicate whether or not the instance belongs to the associated subtype

 

 

 

Entity Clusters

• EER diagrams are difficult to read when there are too many entities and relationships
• Solution: Group entities and relationships into entity clusters
• Entity cluster: Set of one or more entity types and associated relationships grouped into a single abstract entity type

 

 

 

Packaged Data Models

• Predefined data models
• Could be universal or industry-specific
• Universal data model = a generic or template data model that can be reused as a starting point for a data modeling project (also called a “pattern”)

 

 

 

Advantages of Packaged Data Models

• Use proven model components
• Save time and cost
• Less likelihood of data model errors
• Easier to evolve and modify over time
• Aid in requirements determination
• Easier to read
• Supertype/subtype hierarchies promote reuse
• Many-to-many relationships enhance model flexibility
• Vendor-supplied data model fosters integration with vendor’s applications
• Universal models support inter-organizational systems