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

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

54. Developing an E-R Diagram
The process of database design is an iterative rather than a linear or sequential process.
It usually begins with a general narrative of the organization’s operations and procedures.
The basic E-R model is graphically depicted and presented for review.
The process is repeated until the end users and designers agree that the E-R diagram is a fair representation of the organization’s activities and functions.

55. Developing an E-R Diagram
Tiny College Database (1)
Tiny College (TC) is divided into several schools. Each school is administered by a dean. A 1:1 relationship exists between DEAN and SCHOOL.
Each dean is a member of a group of administrators (ADMINISTRATOR). Deans also hold professorial rank and may teach a class (PROFESSOR). Administrators and professors are also Employees. (Figure 4.38)

57. Developing an E-R Diagram
Tiny College Database (2)
Each school is composed of several departments.
The smallest number of departments operated by a school is one, and the largest number of departments is indeterminate (N).
Each department belongs to only a single school.
Figure The First Tiny College ERD Segment

58. Developing an E-R Diagram
Tiny College Database (3)
Each department offers several courses.
Figure The Second Tiny College ERD Segment

59. Developing an E-R Diagram
Tiny College Database (4)
A department may offer several sections (classes) of the same course.
A 1:M relationship exists between COURSE and CLASS.
CLASS is optional to COURSE
Figure The Third Tiny College ERD Segment

60. Developing an E-R Diagram
Tiny College Database (5)
Each department has many professors assigned to it.
One of those professors chairs the department. Only one of the professors can chair the department.
DEPARTMENT is optional to PROFESSOR in the “chairs” relationship.
Figure The Fourth Tiny College ERD Segment

61. Developing an E-R Diagram
Tiny College Database (6)
Each professor may teach up to four classes, each one a section of a course.
A professor may also be on a research contract and teach no classes.
Figure The Fifth Tiny College ERD Segment

62. Developing an E-R Diagram
Tiny College Database (7)
A student may enroll in several classes, but (s)he takes each class only once during any given enrollment period.
Each student may enroll in up to six classes and each class may have up to 35 students in it.
STUDENT is optional to CLASS.
Figure The Sixth Tiny College ERD Segment

63. Developing an E-R Diagram
Tiny College Database (8)
Each department has several students whose major is offered by that department.
Each student has only a single major and associated with a single department.
Figure The Seventh Tiny College ERD Segment

64. Developing an E-R Diagram
Tiny College Database (9)
Each student has an advisor in his or her department; each advisor counsels several students.
An advisor is also a professor, but not all professors advise students.
Figure The Eighth Tiny College ERD Segment

65. Developing an E-R Diagram
Entities for the Tiny College Database
SCHOOL
DEPARMENT
EMPLOYEE
PROFESSOR
COURSE
CLASS
ENROLL (Bridge between STUDENT and CLASS)
STUDENT

66. Components of the E-R Model
Table 4.2

67. Figure 4.48

68. Developing an E-R Diagram
Converting an E-R Model into a Database Structure
A painter might paint many paintings. The cardinality is (1,N) in the relationship between PAINTER and PAINTING.
Each painting is painted by one (and only one) painter.
A painting might (or might not) be exhibited in a gallery; i.e., the GALLERY is optional to PAINTING.

69. Figure 4.49

70. Developing an E-R Diagram
Summary of Table Structures and Special Requirements for the ARTIST database
PAINTER(PRT_NUM, PRT_LASTNAME, PRT_FIRSTNAME, PRT_INITIAL, PTR_AREACODE, PRT_PHONE)
GALLERY(GAL_NUM, GAL_OWNER, GAL_AREACODE, GAL_PHONE, GAL_RATE)
PAINTING(PNTG_NUM, PNTG_TITLE, PNTG_PRICE, PTR_NUM, GAL_NUM)

71. A Data Dictionary for the ARTIST Database
Table 4.3

72. Developing an E-R Diagram
SQL Commands to Create the PAINTER Table
CREATE TABLE PAINTER ( PTR_NUM CHAR(4) NOT NULL UNIQUE, PRT_LASTNAME CHAR(15) NOT NULL, PTR_FIRSTNAME CHAR(15), PTR_INITIAL CHAR(1), PTR_AREACODE CHAR(3), PTR_PHONE CHAR(8), PRIMARY KEY(PTR_NUM));

73. Developing an E-R Diagram
SQL Commands to Create the GALLERY Table
CREATE TABLE GALLERY ( GAL_NUM CHAR(4) NOT NULL UNIQUE, GAL_OWNER CHAR(35), GAL_AREACODE CHAR(3) NOT NULL, GAL_PHONE CHAR(8) NOT NULL,
GAL_RATE NUMBER(4,2), PRIMARY KEY(GAL_NUM));

74. Developing an E-R Diagram
SQL Commands to Create the PAINTING Table
CREATE TABLE PAINTING ( PNTG_NUM CHAR(4) NOT NULL UNIQUE, PNTG_TITLE CHAR(35), PNTG_PRICE NUMBER(9,2), PTR_NUM CHAR(4) NOT NULL, GAL_NUM CHAR(4), PRIMARY KEY(PNTG_NUM) FOREIGN KEY(PTR_NUM) RERERENCES PAINTER ON DELETE RESTRICT ON UPDATE CASCADE, FOREIGN KEY(GAL_NUM) REFERENCES GALLERY ON DELETE RESTRICT ON UPDATE CASCADE);

75. Developing an E-R Diagram
General Rules Governing Relationships among Tables
1. All primary keys must be defined as NOT NULL.
2. Define all foreign keys to conform to the following requirements for binary relationships.
1:M Relationship
Weak Entity
M:N Relationship
1:1 Relationship

76. Developing an E-R Diagram
1:M Relationships
Create the foreign key by putting the primary key of the “one” (parent) in the table of the “many” (dependent).
Foreign Key Rules:

77. Developing an E-R Diagram
Weak Entity
Put the key of the parent table (strong entity) in the weak entity.
The weak entity relationship conforms to the same rules as the 1:M relationship, except foreign key restrictions:
NOT NULL
ON DELETE CASCADE
ON UPDATE CASCADE
M:N Relationship
Convert the M:N relationship to a composite (bridge) entity consisting of (at least) the parent tables’ primary keys.

78. Developing an E-R Diagram
1:1 Relationships
If both entities are in mandatory participation in the relationship and they do not participate in other relationships, it is most likely that the two entities should be part of the same entity.

79. Developing an E-R Diagram
CASE 1: M:N, Both Sides MANDATORY
Figure Entity Relationships, M:N, Both Sides Mandatory

80. Developing an E-R Diagram
CASE 2: M:N, Both Sides OPTIONAL
Figure Entity Relationships, M:N, Both Sides Optional

81. Developing an E-R Diagram
CASE 3: M:N, One Side OPTIONAL
Figure Entity Relationships, M:N, One Side Optional

82. Developing an E-R Diagram
CASE 4: 1:M, Both Sides MANDATORY
Figure Entity Relationships, 1:M, Both Sides Mandatory

83. Developing an E-R Diagram
CASE 5: 1:M, Both Sides OPTIONAL
Figure Entity Relationships, 1:M, Both Sides Optional

84. Developing an E-R Diagram
CASE 6: 1:M, Many Side OPTIONAL, One Side MANDATORY
Figure Entity Relationships, 1:M, Many Side Optional, One Side Mandatory

85. Developing an E-R Diagram
CASE 7: 1:M, One Side OPTIONAL, One Side MANDATORY
Figure Entity Relationships, 1:M, One Side Optional, Many Side Mandatory

86. Developing an E-R Diagram
CASE 8: 1:1, Both Sides MANDATORY
Figure Entity Relationships, 1:1, Both Sides Mandatory

87. Developing an E-R Diagram
CASE 9: 1:1, Both Sides OPTIONAL
Figure Entity Relationships, 1:1, Both Sides Optional

88. Developing an E-R Diagram
CASE 10: 1:1, One Side OPTIONAL, One Side MANDATORY
Figure Entity Relationships, 1:1, One Side Optional, One Side Mandatory

89. Developing an E-R Diagram
CASE 11: Weak Entity (Foreign key located in weak entity)
Figure Entity Relationships, Weak Entity

90. Developing an E-R Diagram
CASE 12: Multivalued Attributes
Figure Entity Relationships, Multivalued Attributes

92. The Chen Representation of the Invoicing Problem
Figure 4.63

93. The Crow’s Foot Representation of the Invoicing Problem
Figure 4.64

94. Figure 4.65 The Rein85 Representation of the Invoicing Problem

95. The IDEF1X Representation of the Invoicing Problem
Figure 4.66

96. The Challenge of Database Design: Conflicting Goals
Design standards (design elegance)
Processing speed
Information requirements
Design Considerations
Logical requirements and design conventions
End user requirements; e.g., performance, security, shared access, data integrity
Processing requirements
Operational requirements
Documentation