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Fundamentals of Database Systems

Seventh Edition

Chapter 3

Data Modeling Using the Entity-Relationship (E R) Model

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Learning Objectives (1 of 2)

3.1 Overview of Database Design Process

3.2 Example Database Application (COMPANY)

3.3 E R Model Concepts

3.3.1 Entities and Attributes

3.3.2 Entity Types, Value Sets, and Key Attributes

3.3.3 Relationships and Relationship Types

3.3.4 Weak Entity Types

3.3.5 Roles and Attributes in Relationship Types

Learning Objectives (2 of 2)

3.4 E R Diagrams - Notation

3.5 E R Diagram for COMPANY Schema

3.6 Alternative Notations – U M L class diagrams, others

3.7 Relationships of Higher Degree

Overview of Database Design Process (1 of 2)

Two main activities:

Database design

Applications design

Focus in this chapter on conceptual database design

To design the conceptual schema for a database application

Applications design focuses on the programs and interfaces that access the database

Generally considered part of software engineering

Overview of Database Design Process (2 of 2)

Figure 3.1 A simplified diagram to illustrate the main phases of database design.

Methodologies for Conceptual Design

Entity Relationship (E R) Diagrams (This Chapter)

Enhanced Entity Relationship (E E R) Diagrams (Chapter 4)

Use of Design Tools in industry for designing and documenting large scale designs

The U M L (Unified Modeling Language) Class Diagrams are popular in industry to document conceptual database designs

Example COMPANY Database (1 of 2)

We need to create a database schema design based on the following (simplified) requirements of the COMPANY Database:

The company is organized into DEPARTMENTs. Each department has a name, number and an employee who manages the department. We keep track of the start date of the department manager. A department may have several locations.

Each department controls a number of PROJECTs. Each project has a unique name, unique number and is located at a single location.

Example COMPANY Database (2 of 2)

The database will store each EMPLOYEE’s social security number, address, salary, sex, and birthdate.

Each employee works for one department but may work on several projects.

The D B will keep track of the number of hours per week that an employee currently works on each project.

It is required to keep track of the direct supervisor of each employee.

Each employee may have a number of DEPENDENTs.

For each dependent, the D B keeps a record of name, sex, birthdate, and relationship to the employee.

E R Model Concepts (1 of 2)

Entities and Attributes

Entity is a basic concept for the E R model. Entities are specific things or objects in the mini-world that are represented in the database.

For example the EMPLOYEE John Smith, the Research DEPARTMENT, the ProductX PROJECT

Attributes are properties used to describe an entity.

For example an EMPLOYEE entity may have the attributes Name, S S N, Address, Sex, BirthDate

E R Model Concepts (2 of 2)

A specific entity will have a value for each of its attributes.

For example a specific employee entity may have Name=‘John Smith’, S S N=‘123456789’, Address =‘731, Fondren, Houston, T X’, Sex=‘M’, BirthDate=‘09-JAN-55’

Each attribute has a value set (or data type) associated with it – e.g. integer, string, date, enumerated type, …

Types of Attributes (1 of 3)

Simple

Each entity has a single atomic value for the attribute. For example, S S N or Sex.

Composite

The attribute may be composed of several components. For example:

Address(Apt#, House#, Street, City, State, ZipCode, Country), or

Name(FirstName, MiddleName, LastName).

Composition may form a hierarchy where some components are themselves composite.

Types of Attributes (2 of 3)

Multi-valued

An entity may have multiple values for that attribute. For example, Color of a CAR or PreviousDegrees of a STUDENT.

Denoted as {Color} or {PreviousDegrees}.

In general, composite and multi-valued attributes may be nested arbitrarily to any number of levels, although this is rare.

For example, PreviousDegrees of a STUDENT is a composite multi-valued attribute denoted by

Types of Attributes (3 of 3)

Multiple PreviousDegrees values can exist

Each has four subcomponent attributes:

College, Year, Degree, Field

Example of a Composite Attribute

Figure 3.4 A hierarchy of composite attributes.

Entity Types and Key Attributes (1 of 2)

Entities with the same basic attributes are grouped or typed into an entity type.

For example, the entity type EMPLOYEE and PROJECT.

An attribute of an entity type for which each entity must have a unique value is called a key attribute of the entity type.

For example, S S N of EMPLOYEE.

Entity Types and Key Attributes (2 of 2)

A key attribute may be composite.

VehicleTagNumber is a key of the CAR entity type with components (Number, State).

An entity type may have more than one key.

The CAR entity type may have two keys:

VehicleIdentificationNumber (popularly called V I N)

VehicleTagNumber (Number, State), aka license plate number.

Each key is underlined (Note: this is different from the relational schema where only one “primary key is underlined).

Entity Set

Each entity type will have a collection of entities stored in the database

Called the entity set or sometimes entity collection

Previous slide shows three CAR entity instances in the entity set for CAR

Same name (CAR) used to refer to both the entity type and the entity set

However, entity type and entity set may be given different names

Entity set is the current state of the entities of that type that are stored in the database

Value Sets (Domains) of Attributes

Each simple attribute is associated with a value set

E.g., Lastname has a value which is a character string of upto 15 characters, say

Date has a value consisting of M M-D D-Y Y Y Y where each letter is an integer

A value set specifies the set of values associated with an attribute

Attributes and Value Sets

Value sets are similar to data types in most programming languages – e.g., integer, character (n), real, bit

Mathematically, an attribute A for an entity type E whose value set is V is defined as a function

Where

indicates a power set (which means

all possible subsets) of V. The above definition covers simple and multivalued attributes.

We refer to the value of attribute A for entity e as

Displaying An Entity Type

In E R diagrams, an entity type is displayed in a rectangular box

Attributes are displayed in ovals

Each attribute is connected to its entity type

Components of a composite attribute are connected to the oval representing the composite attribute

Each key attribute is underlined

Multivalued attributes displayed in double ovals

See the full E R notation in advance on the next slide

Notation for E R Diagrams

Figure 3.14 Summary of the notation for E R diagrams.

Entity Type CAR with Two Keys and a Corresponding Entity Set

Figure 3.7 The CAR entity type with two key attributes, Registration and Vehicle_i d. (a) E R diagram notation. (b) Entity set with three entities.

Initial Conceptual Design of Entity Types for the COMPANY Database Schema

Based on the requirements, we can identify four initial entity types in the COMPANY database:

DEPARTMENT

PROJECT

EMPLOYEE

DEPENDENT

Their initial conceptual design is shown on the following slide

The initial attributes shown are derived from the requirements description

Initial Design of Entity Types: EMPLOYEE, DEPARTMENT, PROJECT, DEPENDENT

Figure 3.8 Preliminary design of entity types for the COMPANY database. Some of the shown attributes will be refined into relationships.

Refining the Initial Design by Introducing Relationships

The initial design is typically not complete

Some aspects in the requirements will be represented as relationships

E R model has three main concepts:

Entities (and their entity types and entity sets)

Attributes (simple, composite, multivalued)

Relationships (and their relationship types and relationship sets)

We introduce relationship concepts next

Relationships and Relationship Types

A relationship relates two or more distinct entities with a specific meaning.

For example, EMPLOYEE John Smith works on the ProductX Project, or EMPLOYEE Franklin Wong manages the Research DEPARTMENT.

Relationships of the same type are grouped or typed into a relationship type.

For example, the WORKS_ON relationship type in which EMPLOYEEs and PROJECTs participate, or the MANAGES relationship type in which EMPLOYEEs and DEPARTMENTs participate.

The degree of a relationship type is the number of participating entity types.

Both MANAGERS and WORKS_ON are binary relationships.

Relationship Instances of the WORKS_FOR N:1 relationship between EMPLOYEE and DEPARTMENT

Figure 3.9 Some instances in the WORKS_FOR relationship set, which represents a relationship type WORKS_FOR between EMPLOYEE and DEPARTMENT

Relationship Instances of the M:N WORKS_ON Relationship between EMPLOYEE and PROJECT

Figure 3.13 An M:N relationship, WORKS_ON.

Relationship Type Versus Relationship Set (1 of 2)

Relationship Type:

Is the schema description of a relationship

Identifies the relationship name and the participating entity types

Also identifies certain relationship constraints

Relationship Set:

The current set of relationship instances represented in the database

The current state of a relationship type

Relationship Type Versus Relationship Set (2 of 2)

Previous figures displayed the relationship sets

Each instance in the set relates individual participating entities – one from each participating entity type

In E R diagrams, we represent the relationship type as follows:

Diamond-shaped box is used to display a relationship type

Connected to the participating entity types via straight lines

Note that the relationship type is not shown with an arrow. The name should be typically be readable from left to right and top to bottom.

Refining the Company Database Schema by Introducing Relationships

By examining the requirements, six relationship types are identified

All are binary relationships( degree 2)

Listed below with their participating entity types:

WORKS_FOR (between EMPLOYEE, DEPARTMENT)

MANAGES (also between EMPLOYEE, DEPARTMENT)

CONTROLS (between DEPARTMENT, PROJECT)

WORKS_ON (between EMPLOYEE, PROJECT)

SUPERVISION (between EMPLOYEE (as subordinate), EMPLOYEE (as supervisor))

DEPENDENTS_OF (between EMPLOYEE, DEPENDENT)

E R Diagram – Relationship Types Are: WORKS_FOR, MANAGES, WORKS_ON, CONTROLS, SUPERVISION, DEPENDENTS_OF

Figure 3.2 An E R schema diagram for the COMPANY database. The diagrammatic notation is introduced gradually throughout this chapter and is summarized in Figure 3.14 (see slide 51).

Discussion on Relationship Types

In the refined design, some attributes from the initial entity types are refined into relationships:

Manager of DEPARTMENT → MANAGES

Works_on of EMPLOYEE → WORKS_ON

Department of EMPLOYEE → WORKS_FOR

etc

In general, more than one relationship type can exist between the same participating entity types

MANAGES and WORKS_FOR are distinct relationship types between EMPLOYEE and DEPARTMENT

Different meanings and different relationship instances.

Constraints on Relationships

Constraints on Relationship Types

(Also known as ratio constraints)

Cardinality Ratio (specifies maximum participation)

One-to-one (1:1)

One-to-many (1:N) or Many-to-one (N:1)

Many-to-many (M:N)

Existence Dependency Constraint (specifies minimum participation) (also called participation constraint)

zero (optional participation, not existence-dependent)

one or more (mandatory participation, existence-dependent)

Many-To-One (N : 1) Relationship

Figure 3.9 Some instances in the WORKS_FOR relationship set, which represents a relationship type WORKS_FOR between EMPLOYEE and DEPARTMENT.

Many-To-Many (M : N) Relationship

Figure 3.13 An M:N relationship, WORKS_ON.

Recursive Relationship Type

A relationship type between the same participating entity type in distinct roles

Also called a self-referencing relationship type.

Example: the SUPERVISION relationship

EMPLOYEE participates twice in two distinct roles:

supervisor (or boss) role

supervisee (or subordinate) role

Each relationship instance relates two distinct EMPLOYEE entities:

One employee in supervisor role

One employee in supervisee role

Displaying a Recursive Relationship

In a recursive relationship type.

Both participations are same entity type in different roles.

For example, SUPERVISION relationships between EMPLOYEE (in role of supervisor or boss) and (another) EMPLOYEE (in role of subordinate or worker).

In following figure, first role participation labeled with 1 and second role participation labeled with 2.

In E R diagram, need to display role names to distinguish participations.

A Recursive Relationship Supervision`

Figure 3.11 A recursive relationship SUPERVISION between EMPLOYEE in the supervisor role (1) and EMPLOYEE in the subordinate role (2).

Recursive Relationship Type is: Supervision (Participation Role Names Are Shown)

Figure 3.2 An E R schema diagram for the COMPANY database. The diagrammatic notation is introduced gradually throughout this chapter and is summarized in Figure 3.14. (see slide 51)

Weak Entity Types (1 of 2)

An entity that does not have a key attribute and that is identification-dependent on another entity type.

A weak entity must participate in an identifying relationship type with an owner or identifying entity type

Entities are identified by the combination of:

A partial key of the weak entity type

The particular entity they are related to in the identifying relationship type

Weak Entity Types (2 of 2)

Example:

A DEPENDENT entity is identified by the dependent’s first name, and the specific EMPLOYEE with whom the DEPENDENT is related

Name of DEPENDENT is the partial key

DEPENDENT is a weak entity type

EMPLOYEE is its identifying entity type via the identifying relationship type DEPENDENT_OF

Attributes of Relationship Types

A relationship type can have attributes:

For example, HoursPerWeek of WORKS_ON

Its value for each relationship instance describes the number of hours per week that an EMPLOYEE works on a PROJECT.

A value of HoursPerWeek depends on a particular (employee, project) combination

Most relationship attributes are used with M:N relationships

In 1:N relationships, they can be transferred to the entity type on the N-side of the relationship

Example Attribute of a Relationship Type: Hours of WORKS_ON

Figure 3.2 An E R schema diagram for the COMPANY database. The diagrammatic notation is introduced gradually throughout this chapter and is summarized in Figure 3.14. (see slide 51)

Notation for Constraints on Relationships

Cardinality ratio (of a binary relationship): 1:1, 1:N, N:1, or M:N

Shown by placing appropriate numbers on the relationship edges.

Participation constraint (on each participating entity type): total (called existence dependency) or partial.

Total shown by double line, partial by single line.

Note: These are easy to specify for Binary Relationship Types.

Alternative (Min, Max) Notation for Relationship Structural Constraints: (1 of 2)

Specified on each participation of an entity type E in a relationship type R

Specifies that each entity e in E participates in at least min and at most max relationship instances in R

Default(no constraint): min=0, max=n (signifying no limit)

Must have

Derived from the knowledge of mini-world constraints

Alternative (Min, Max) Notation for Relationship Structural Constraints: (2 of 2)

Examples:

A department has exactly one manager and an employee can manage at most one department.

Specify (0,1) for participation of EMPLOYEE in MANAGES

Specify (1,1) for participation of DEPARTMENT in MANAGES

An employee can work for exactly one department but a department can have any number of employees.

Specify (1,1) for participation of EMPLOYEE in WORKS_FOR

Specify (0,n) for participation of DEPARTMENT in WORKS_FOR

The (Min,Max) Notation for Relationship Constraints

Read the min, max numbers next to the entity type and looking away from the entity type

Company E R Schema Diagram Using (Min, Max) Notation

Figure 3.15 E R diagrams for the company schema, with structural constraints specified using (min, max) notation and role names.

Alternative Diagrammatic Notation

E R diagrams is one popular example for displaying database schemas

Many other notations exist in the literature and in various database design and modeling tools

Appendix A illustrates some of the alternative notations that have been used

U M L class diagrams is representative of another way of displaying E R concepts that is used in several commercial design tools

Summary of Notation for E R Diagrams

Figure 3.14 Summary of the notation for E R diagrams.

U M L Class Diagrams

Represent classes (similar to entity types) as large rounded boxes with three sections:

Top section includes entity type (class) name

Second section includes attributes

Third section includes class operations (operations are not in basic E R model)

Relationships (called associations) represented as lines connecting the classes

Other U M L terminology also differs from E R terminology

Used in database design and object-oriented software design

U M L has many other types of diagrams for software design

U M L Class Diagram for Company Database Schema

Figure 3.16 The COMPANY conceptual schema in U M L class diagram notation.

Other Alternative Diagrammatic Notations

Figure A.1 Alternative notations. (a) Symbols for entity type/class, attribute, and relationship. (b) Displaying attributes. (c) Displaying cardinality ratios. (d) Various (min, max) notations. (e) Notations for displaying specialization/generalization.

Relationships of Higher Degree

Relationship types of degree 2 are called binary

Relationship types of degree 3 are called ternary and of degree n are called n-ary

In general, an n-ary relationship is not equivalent to n binary relationships

Constraints are harder to specify for higher-degree relationships (n > 2) than for binary relationships

Discussion of N-Ary Relationships (n > 2) (1 of 2)

In general, 3 binary relationships can represent different information than a single ternary relationship (see Figure 3.17a and b on next slide)

If needed, the binary and n-ary relationships can all be included in the schema design (see Figure 3.17a and b, where all relationships convey different meanings)

In some cases, a ternary relationship can be represented as a weak entity if the data model allows a weak entity type to have multiple identifying relationships (and hence multiple owner entity types) (see Figure 3.17c)

Example of a Ternary Relationship

Figure 3.17 Ternary relationship types. (a) The SUPPLY relationship. (b) Three binary relationships not equivalent to SUPPLY. (c) SUPPLY represented as a weak entity type.

Discussion of N-Ary Relationships (n > 2) (2 of 2)

If a particular binary relationship can be derived from a higher-degree relationship at all times, then it is redundant

For example, the TAUGHT_DURING binary relationship in Figure 3.18 (see next slide) can be derived from the ternary relationship OFFERS (based on the meaning of the relationships)

Another Example of a Ternary Relationship

Figure 3.18 Another example of ternary versus binary relationship types.

Displaying Constraints on Higher-Degree Relationships

The (min, max) constraints can be displayed on the edges – however, they do not fully describe the constraints

Displaying a 1, M, or N indicates additional constraints

An M or N indicates no constraint

A 1 indicates that an entity can participate in at most one relationship instance that has a particular combination of the other participating entities

In general, both (min, max) and 1, M, or N are needed to describe fully the constraints

Overall, the constraint specification is difficult and possibly ambiguous when we consider relationships of a degree higher than two.

Another Example: A University Database

To keep track of the enrollments in classes and student grades, another database is to be designed.

It keeps track of the COLLEGEs, DEPARTMENTs within each college, the COURSEs offered by departments, and SECTIONs of courses, INSTRUCTORS who teach the sections etc.

These entity types and the relationships among these entity types are shown on the next slide in Figure 3.20.

University Database Conceptual Schema

Chapter Summary

E R Model Concepts: Entities, attributes, relationships

Constraints in the E R model

Using E R in step-by-step mode conceptual schema design for the COMPANY database

E R Diagrams - Notation

Alternative Notations – U M L class diagrams, others

Binary Relationship types and those of higher degree.

Data Modeling Tools (Additional Material )

A number of popular tools that cover conceptual modeling and mapping into relational schema design.

Examples: E R Win, S- Designer (Enterprise Application Suite), E R- Studio, etc.

Positives:

Serves as documentation of application requirements, easy user interface - mostly graphics editor support

Negatives:

Most tools lack a proper distinct notation for relationships with relationship attributes

Mostly represent a relational design in a diagrammatic form rather than a conceptual E R-based design

Some of the Automated Database Design Tools

Company	Tool	Functionality
Embarcadero Technologies	E R Studio	Database Modeling in E R and I D E F 1 X
Embarcadero Technologies	D B Artisan	Database administration, space and security management
Oracle	Developer 2000/Designer 2000	Database modeling, application development
Popkin Software	System Architect 2001	Data modeling, object modeling, process modeling, structured analysis/design
Platinum (Computer Associates)	Enterprise Modeling Suite: Erwin, B P Win, Paradigm Plus	Data, process, and business component modeling
Persistence Inc.	Pwertier	Mapping from O-O to relational model
Rational (I B M)	Rational Rose	U M L Modeling & application generation in C++/JAVA
Resolution Ltd.	Xcase	Conceptual modeling up to code maintenance
Sybase	Enterprise Application Suite	Data modeling, business logic modeling
Visio	Visio Enterprise	Data modeling, design/reengineering Visual Basic/C++

(Note: Not All May Be on the Market Now)

Extended Entity-Relationship (E E R) Model (in the Next Chapter)

The entity relationship model in its original form did not support the specialization and generalization abstractions

Next chapter illustrates how the E R model can be extended with

Type-subtype and set-subset relationships

Specialization/Generalization Hierarchies

Notation to display them in E E R diagrams

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