1. Chapter 4 Entity Relationship (E-R) Modeling
Database Systems: Design, Implementation, and Management
4th Edition
Peter Rob & Carlos Coronel

2. Basic Modeling Concepts
Database design is both art and science.
A data model is the relatively simple representation, usually graphic, of complex real-world data structures. It represents data structures and their characteristics, relations, constraints, and transformations.
The database designer usually employs data models as communications tools to facilitate the interaction among the designer, the applications programmer, and the end user.
A good database is the foundation for good applications.

3. Figure 4.1 Four Modified (ANSI/SPARC) Data Abstraction Models

4. Data Models: Degrees of Data Abstraction
The Conceptual Model
The conceptual model represents a global view of the data. It is an enterprise-wide representation of data as viewed by high-level managers.
Entity-Relationship (E-R) model is the most widely used conceptual model.
The conceptual model forms the basis for the conceptual schema.
The conceptual schema is the visual representation of the conceptual model.
The conceptual model is independent of both software (software independence) and hardware (hardware independence).

5. Tiny College Entities
Figure 4.2

6. A Conceptual Schema for Tiny College
Figure 4.3

7. Data Models: Degrees of Data Abstraction
The Internal Model
The internal model adapts the conceptual model to a specific DBMS.
The internal model is software-dependent.
Development of the internal model is especially important to hierarchical and network database models.

8. Figure 4.4

9. Data Models: Degrees of Data Abstraction
The External Model
The external model is the end user’s view of the data environment.
Each external model is then represented by its own external schema.
CREATE VIEW CLASS_VIEW AS SELECT (CLASS_ID, CLASS_NAME, PROF_NAME, CLASS_TIME, ROOM_ID) FROM CLASS, PROFESSOR, ROOM WHERE CLASS.PROF_ID = PROFESSOR.PROF_ID AND CLASS.ROOM_ID = ROOM.ROOM_ID;

10. Figure 4.5
The External Models
for Tiny College

11. Data Models: Degrees of Data Abstraction
The External Model
Advantages of Using External Schemas
It makes application program development much simpler.
It facilitates the designer’s task by making it easier to identify specific data required to support each business unit’s operations.
It makes the designer’s job easier by providing feedback about the conceptual model’s adequacy.
It helps to ensure security constraints in the database design.

12. Data Models: Degrees of Data Abstraction
The Physical Model
The physical model operates at the lowest level of abstraction, describing the way data is saved on storage media such as disks or tapes.
It requires the definition of both the physical storage devices and the access methods required to reach the data within those storage devices.
The physical model is both software and hardware-dependent.
It requires detailed knowledge of hardware and software used to implement the database design.

13. The Entity Relationship (E-R) Model
E-R model is commonly used to:
Translate different views of data among managers, users, and programmers to fit into a common framework.
Define data processing and constraint requirements to help us meet the different views.
Help implement the database.

14. The Entity Relationship (E-R) Model
E-R Model Components
Entities
In E-R models an entity refers to the entity set.
An entity is represented by a rectangle containing the entity’s name.
Attributes
Attributes are represented by ovals and are connected to the entity with a line.
Each oval contains the name of the attribute it represents.
Attributes have a domain -- the attribute’s set of possible values.
Attributes may share a domain.
Primary keys are underlined.
Relationships

15. The Attributes of the STUDENT Entity
Figure 4.6

16. Basic E-R Model Entity Presentation
Figure 4.7

17. The CLASS Table (Entity) Components and Contents
Figure 4.8

18. The Entity Relationship (E-R) Model
Classes of Attributes
A simple attribute cannot be subdivided.
Examples: Age, Sex, and Marital status
A composite attribute can be further subdivided to yield additional attributes.
Examples:
ADDRESS Street, City, State, Zip
PHONE NUMBER  Area code, Exchange number

19. The Entity Relationship (E-R) Model
Classes of Attributes
A single-valued attribute can have only a single value.
Examples:
A person can have only one social security number.
A manufactured part can have only one serial number.
Multivalued attributes can have many values.
A person may have several college degrees.
A household may have several phones with different numbers
Multivalued attributes are shown by a double line connecting to the entity.

20. The Entity Relationship (E-R) Model
Multivalued Attribute in Relational DBMS
The relational DBMS cannot implement multivalued attributes.
Possible courses of action for the designer
Within the original entity, create several new attributes, one for each of the original multivalued attribute’s components (Figure 4.9).
Create a new entity composed of the original multivalued attribute’s components (Figure 4.10).
Table 4.1

21. Splitting the Multivalued Attributes into New Attributes
Figure 4.9

22. Figure 4.10 A New Entity Set Composed of Multivalued
Attribute’s Components
Figure 4.10

23. The Entity Relationship (E-R) Model
A derived attribute is not physically stored within the database; instead, it is derived by using an algorithm.
Example: AGE can be derived from the data of birth and the current date.
Figure A Derived Attribute

24. The Entity Relationship (E-R) Model
Relationships
A relationship is an association between entities.
Relationships are represented by diamond-shaped symbols.
Figure An Entity Relationship

25. The Entity Relationship (E-R) Model
A relationship’s degree indicates the number of associated entities or participants.
A unary relationship exists when an association is maintained within a single entity.
A binary relationship exists when two entities are associated.
A ternary relationship exists when three entities are associated.

26. The Implementation of a Ternary Relationship
Figure 4.14

27. The Entity Relationship (E-R) Model
Connectivity
The term connectivity is used to describe the relationship classification (e.g., one-to-one, one-to-many, and many-to-many).
Figure Connectivity in an ERD

28. The Entity Relationship (E-R) Model
Cardinality
Cardinality expresses the specific number of entity occurrences associated with one occurrence of the related entity.
Figure 4.16 Cardinality in an ERD

29. Figure 4.17

30. Existence Dependency Figure 4.18
If an entity’s existence depends on the existence of one or more other entities, it is said to be existence-dependent.
Figure 4.18

31. The Entity Relationship (E-R) Model
Relationship Participation
The participation is optional if one entity occurrence does not require a corresponding entity occurrence in a particular relationship.
An optional entity is shown by a small circle on the side of the optional entity.
Figure An ERD With An Optional Entity

32. Figure 4.20 CLASS is Optional to COURSE
Figure COURSE and CLASS in a Mandatory Relationship

33. The Entity Relationship (E-R) Model
Weak Entities
A weak entity is an entity that
Is existence-dependent and
Has a primary key that is partially or totally derived from the parent entity in the relationship.
The existence of a weak entity is indicated by a double rectangle. (Figure 4.22)
The weak entity inherits all or part of its primary key from its strong counterpart.

34. A Weak Entity in an ERD
Figure 4.22

35. Figure 4.23 An Illustration of the Weak Relationship Between
DEPENDENT and EMPLOYEE
Figure 4.23

36. The Entity Relationship (E-R) Model
Recursive Entities
A recursive entity is one in which a relationship can exist between occurrences of the same entity set.
A recursive entity is found within a unary relationship.
Figure An E-R Representation of Recursive Relationships

37. Figure 4.25
Figure 4.26

38. The Implementation of the M:N Recursive
“PART Contains PART” Relationship
Figure 4.27

39. Figure 4.28 Implementation of the M:N “COURSE Requires COURSE”
Recursive Relationship
Figure 4.28

40. Figure 4.29 Implementation of the 1:M “EMPLOYEE Manages EMPLOYEE”
Recursive Relationship
Figure 4.29

41. The Entity Relationship (E-R) Model
Composite Entities
A composite entity is composed of the primary keys of each of the entities to be connected.
The composite entity serves as a bridge between the related entities.
The composite entity may contain additional attributes.

42. Converting the M:N Relationship Into Two 1:M Relationships
Figure 4.30

43. The M:N Relationship Between STUDENT and CLASS
Figure 4.31

44. A Composite Entity in the ERD
Figure 4.32

45. The Entity Relationship (E-R) Model
Entity Supertypes and Subtypes
Figure Nulls Created by Unique Attributes

46. The Entity Relationship (E-R) Model
Entity Supertypes and Subtypes
The generalization hierarchy depicts the parent- child relationship.
The supertype contains the shared attributes, while the subtype contains the unique attributes.
A subtype entity inherits its attributes and its relationships from the supertype entity.

47. A Generalization Hierarchy
Figure 4.34

48. The Entity Relationship (E-R) Model
Entity Supertypes and Subtypes
The supertype entity set is usually related to several unique and disjointed (nonoverlapping) subtype entity sets.
The supertype and its subtype(s) maintain a 1:1 relationship.

49. The EMPLOYEE/PILOT Supertype/Subtype Relationship
Figure 4.35

50. The Entity Relationship (E-R) Model
Entity Supertypes and Subtypes
The generalization hierarchy depicts the parent- child relationship. (Figure 4.34)
The supertype contains the shared attributes, while the subtype contains the unique attributes.
The supertype entity set is usually related to several unique and disjointed (nonoverlapping) subtype entity sets.
The supertype and its subtype(s) maintain a 1:1 relationship.

51. A Generalization Hierarchy With Overlapping Subtypes
Figure 4.36

52. Figure 4.37