The EER model was developed in the 1980s by database researchers including Ramez Elmasri and Shamkant Navathe to address the limitations of the basic ER model when modeling complex databases in domains such as engineering design, manufacturing systems (CAD/CAM), telecommunications networks, geographic information systems (GIS), and complex software applications.
Overview
The EER model extends the basic ER model by adding support for more complex data relationships and semantic information. While the traditional ER model effectively represents entities, attributes, and relationships, it lacks the ability to model hierarchies, inheritance, and classification structures that are common in real-world databases.
The EER model retains all concepts from the basic ER model—including entities, attributes, relationships, keys, and cardinality constraints, while adding new constructs to handle:
Subclass and superclass relationships: Enabling classification hierarchies
Specialization and generalization: Top-down and bottom-up abstraction mechanisms
Attribute and relationship inheritance: Automatic propagation of properties to subclasses
Union types (categories): Entities that can belong to multiple distinct superclasses
Constraints on hierarchies: Rules governing membership in specialization hierarchies
These enhancements make the EER model particularly suitable for modeling complex enterprise databases, object-oriented applications, and systems requiring sophisticated classification schemes.
Key concepts and features
Subclass and superclass
A subclass (or subtype) is an entity type that has distinct attributes or relationships in addition to those inherited from another entity type, called the superclass (or supertype). The subclass is a subset of the superclass, meaning every instance of a subclass is also an instance of its superclass.
Example: In a university database,
Person might be a superclass with subclasses
Student
Professor
Staff
Each subclass inherits common attributes like
Name
Address
DateOfBirth
from Person, while having specific attributes such as
StudentID
Major
Student
Rank
Department
for Professor.
Formally, if S is a subclass of C (the superclass), then:
S ⊆ C (every member of S is also a member of C)
S inherits all attributes and relationships of C
S may have additional specific attributes and relationships
Specialization
Specialization is a top-down conceptual refinement process where a higher-level entity type (superclass) is subdivided into lower-level, more specialized entity types (subclasses) based on distinguishing characteristics. It emphasizes differences among entities within the superclass.
Process:
Start with a general entity type
Identify distinguishing characteristics
Define subclasses based on these characteristics
Assign specific attributes and relationships to each subclass
Example: Starting with an Employee entity, specialization might identify distinct types based on job function:
Employee (superclass) specializes into:
Secretary (with attribute TypingSpeed)
Engineer (with attribute EngineeringType)
Technician (with attribute TechGrade)
Specialization can be:
Attribute-defined: Based on a specific attribute value (e.g., EmployeeType)
User-defined: Not based on any specific attribute condition
Generalization
Generalization is a bottom-up abstraction process where multiple entity types with common characteristics are combined into a higher-level, generalized entity type (superclass). It emphasizes similarities among entities.
Process:
Identify entity types with common attributes
Extract common attributes into a new superclass
Establish subclass relationships
Retain specialized attributes in subclasses
Example: Separate entities Car, Truck, and Motorcycle can be generalized into a superclass Vehicle containing common attributes like VehicleID, Color, Year, and Manufacturer, while specific attributes remain with subclasses.
Specialization and generalization are inverse processes: specialization creates subclasses from a superclass, while generalization creates a superclass from existing entity types.
Attribute and relationship inheritance
Inheritance is a fundamental principle of the EER model where subclasses automatically inherit all attributes and relationships from their superclass(es). This promotes data consistency and reduces redundancy in the model.
Types of inheritance:
Single inheritance: A subclass inherits from exactly one superclass.
Example: Student inherits from Person
Multiple inheritance: A subclass inherits from multiple superclasses, acquiring attributes and relationships from all parents.
Example: TeachingAssistant might inherit from both Student and Employee
Inheritance properties:
Transitive: If C is a subclass of B, and B is a subclass of A, then C inherits from both B and A
Additive: Subclasses can define additional attributes and relationships beyond inherited ones
Overriding: Generally not supported in EER (unlike object-oriented models)
Union types and categories
A union type (or category) represents a subclass that is a subset of the UNION of two or more distinct superclasses. Unlike regular subclasses that inherit from a single superclass, a category can have instances from multiple different entity types.
Characteristics:
An instance of a category must belong to exactly one of the superclasses
The category inherits attributes common to all superclasses
Each instance maintains its identity in the originating superclass
Notation: Represented by a circle with the union symbol (∪) connected to all superclasses, with an arc and subset symbol (⊂) connecting to the category.
Example: In a vehicle registration database, an Owner category can be defined as a subset of PERSON ∪ BANK ∪ COMPANY. Each vehicle owner is either a person, a bank, or a company, but not multiple types simultaneously. The Owner category would have a relationship Owns with the Vehicle entity.
Formal definition: If category T is defined on superclasses S1, S2, ..., Sn, then:
T ⊆ S1 ∪ S2 ∪ ... ∪ Sn
For each instance t ∈ T, t ∈ Si for exactly one i
Aggregation
Aggregation is an abstraction concept that treats a relationship as a higher-level entity, allowing relationships to participate in other relationships. This is useful when modeling complex scenarios where relationships themselves have attributes or participate in additional relationships.
Example: In a project management system:
Employees work on Projects (relationship: WorksOn)
For each work assignment, specific Machinery is required
The aggregation treats the entire WorksOn relationship as an entity that can be related to Machinery
This allows modeling: "Employee E working on Project P requires Machinery M" without creating artificial intermediate entities.
Tools
Numerous tools support EER diagram creation, ranging from specialized database design software to general-purpose diagramming applications.
↑Elmasri, Ramez; Navathe, Shamkant B. (2011). "Chapters 8 and 9". Fundamentals of Database Systems (6thed.). Boston: Pearson/Addison Wesley. ISBN978-0-136-08620-8.
Further reading
Textbooks discussing EER and implementation using purely relational databases:
Elmasri, Ramez; Navathe, Shamkant B. (2011). Fundamentals of Database Systems (6thed.). Pearson/Addison Wesley. Chapters 8 and 9. ISBN978-0-136-08620-8.
Coronel, Carlos; Morris, Steven; Rob, Peter (2011). Database Systems: Design, Implementation, and Management (9thed.). Cengage Learning. Chapter 5. ISBN978-0-538-46968-5.
Connolly, Thomas M.; Begg, Carolyn E. (2005). Database Systems: A Practical Approach to Design, Implementation, and Management (4thed.). Addison-Wesley. Chapters 12 and 16. ISBN978-0-321-21025-8.
Booklet discussing EER and implementation using object-oriented and object–relational databases:
Dietrich, Suzanne W.; Urban, Susan D. (2011). Fundamentals of Object Databases: Object-Oriented and Object–Relational Design. Morgan & Claypool Publishers. ISBN978-1-60845-476-1.
Textbook discussing implementation in relational and object–relational databases:
Teorey, Toby J.; Yang, Dongqing; Fry, James P. (1986). "A logical design methodology for relational databases using the extended entity–relationship model". ACM Computing Surveys. 18 (2): 197–222. doi:10.1145/7474.7475.
Sikha Bagui (2006). "Extended Entity Relationship Modeling". In Laura C. Rivero; Jorge H. Doorn; Viviana E. Ferraggine (eds.). Encyclopedia of Database Technologies and Applications. Idea Group Inc (IGI). pp.233–239. ISBN978-1-59140-795-9.
External links
- Slides for chapter 8 from Fundamentals of Database Systems by Elmasri and Navathe (Pearson, 2011)