Database Chapter 3

Chapter 3
Data Modeling Using the
Entity-Relationship (ER) Model
Copyright © 2004 Pearson Education, Inc.

Chapter 3-3Copyright © 2004 Pearson Education, Inc.
Elmasri/Navathe, Fundamentals of Database Systems, Fourth Edition
Chapter Outline
Example Database Application (COMPANY)
ER Model Concepts
– Entities and Attributes
– Entity Types, Value Sets, and Key Attributes
– Relationships and Relationship Types
– Weak Entity Types
– Roles and Attributes in Relationship Types
ER Diagrams - Notation
ER Diagram for COMPANY Schema
Alternative Notations – UML class diagrams, others

Example COMPANY
Database
Requirements of the Company (oversimplified for
illustrative purposes)
– 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.
– Each department controls a number of PROJECTs.
Each project has a name, number and is located at a
single location.

Example COMPANY Database
(Cont.)
–We store each EMPLOYEE’s social security number,
address, salary, sex, and birthdate. Each employee
works for one department but may work on several
projects. We keep track of the number of hours per
week that an employee currently works on each
project. We also keep track of the direct supervisor of
each employee.
–Each employee may have a number of
DEPENDENTs. For each dependent, we keep track
of their name, sex, birthdate, and relationship to
employee.

ER Model Concepts
Entities and Attributes
– Entities are specific objects or things 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 a Name, SSN, Address, Sex,
BirthDate
– A specific entity will have a value for each of its attributes. For
example a specific employee entity may have Name='John Smith',
SSN='123456789', Address ='731, Fondren, Houston, TX',
Sex='M', BirthDate='09-JAN-55‘
– Each attribute has a value set (or data type) associated with it –
e.g. integer, string, subrange, enumerated type, …

Types of Attributes (1)
Simple
– Each entity has a single atomic value for the attribute. For
example, SSN 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.
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}.

Types of Attributes (2)
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
{PreviousDegrees (College, Year, Degree, Field)}.

Entity Types and Key Attributes
Entities with the same basic attributes are grouped or typed
into an entity type. For example, the EMPLOYEE entity type
or the PROJECT entity type.
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, SSN of EMPLOYEE.
A key attribute may be composite. For example,
VehicleTagNumber is a key of the CAR entity type with
components (Number, State).
An entity type may have more than one key. For example, the
CAR entity type may have two keys:
– VehicleIdentificationNumber (popularly called VIN) and
– VehicleTagNumber (Number, State), also known as license_plate
number.

ENTITY SET corresponding to the
ENTITY TYPE CAR
car1
((ABC 123, TEXAS), TK629, Ford Mustang, convertible, 1999, (red, black))
car2
((ABC 123, NEW YORK), WP9872, Nissan 300ZX, 2-door, 2002, (blue))
car3
((VSY 720, TEXAS), TD729, Buick LeSabre, 4-door, 2003, (white, blue))
.
.
.
CAR
Registration(RegistrationNumber, State), VehicleID, Make, Model, Year, (Color)

SUMMARY OF ER-DIAGRAM
NOTATION FOR ER SCHEMASMeaning
ENTITY TYPE
WEAK ENTITY TYPE
RELATIONSHIP TYPE
IDENTIFYING RELATIONSHIP TYPE
ATTRIBUTE
KEY ATTRIBUTE
MULTIVALUED ATTRIBUTE
COMPOSITE ATTRIBUTE
DERIVED ATTRIBUTE
TOTAL PARTICIPATION OF E2 IN R
CARDINALITY RATIO 1:N FOR E1:E2 IN R
STRUCTURAL CONSTRAINT (min, max) ON PARTICIPATION
OF E IN R
Symbol
E1 R E2
E1 R E2
R
(min,max)
E
N

ER DIAGRAM – Entity Types are:
EMPLOYEE, DEPARTMENT, PROJECT, DEPENDENT

Relationships and Relationship
Types (1)
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 MANAGES and
WORKS_ON are binary relationships.

Example relationship instances of the WORKS_FOR
relationship between EMPLOYEE and DEPARTMENT
e1
e2
e3
e4
e5
e6
e7
EMPLOYEE
r1
r2
r3
r4
r5
r6
r7
WORKS_FOR
d1
d2
d3
DEPARTMENT

Example relationship instances of the WORKS_ON
relationship between EMPLOYEE and PROJECT
e1
e2
e3
e4
e5
e6
e7
r1
r2
r3
r4
r5
r6
r7
p1
p2
p3
r8
r9

Types (2)
More than one relationship type can exist with the same
participating entity types. For example, MANAGES and
WORKS_FOR are distinct relationships between
EMPLOYEE and DEPARTMENT, but with different
meanings and different relationship instances.

ER DIAGRAM – Relationship Types are:
WORKS_FOR, MANAGES, WORKS_ON, CONTROLS,
SUPERVISION, DEPENDENTS_OF

Weak Entity Types
An entity that does not have a key attribute
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 entity type
Example:
Suppose that a DEPENDENT entity is identified by the
dependent’s first name and birhtdate, and the specific
EMPLOYEE that the dependent is related to.
DEPENDENT is a weak entity type with EMPLOYEE as its
identifying entity type via the identifying relationship type
DEPENDENT_OF

Weak Entity Type is: DEPENDENT
Identifying Relationship is: DEPENDENTS_OF

Constraints on Relationships
Constraints on Relationship Types
– ( Also known as ratio constraints )
– Maximum Cardinality
 One-to-one (1:1)
 One-to-many (1:N) or Many-to-one (N:1)
 Many-to-many
– Minimum Cardinality (also called participation
constraint or existence dependency constraints)
 zero (optional participation, not existence-dependent)
 one or more (mandatory, existence-dependent)

Many-to-one (N:1) RELATIONSHIP
e1
e2
e3
e4
e5
e6
e7
EMPLOYEE
r1
r2
r3
r4
r5
r6
r7
WORKS_FOR
d1
d2
d3
DEPARTMENT

Many-to-many (M:N) RELATIONSHIP
e1
e2
e3
e4
e5
e6
e7
r1
r2
r3
r4
r5
r6
r7
p1
p2
p3
r8
r9

Types (3)
We can also have 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 ER diagram, need to display role names to distinguish
participations.

A RECURSIVE RELATIONSHIP
SUPERVISION
e1
e2
e3
e4
e5
e6
e7
EMPLOYEE
r1
r2
r3
r4
r5
r6
SUPERVISION
2
1
1
2
2
1
1
1
2
1
2
2
© The Benjamin/Cummings Publishing Company, Inc. 1994, Elmasri/Navathe, Fundamentals of Database Systems, Second Edition

Recursive Relationship Type is: SUPERVISION
(participation role names are shown)

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.

Attribute of a Relationship Type is:
Hours of WORKS_ON

Structural Constraints –
one way to express semantics
of relationships
Structural constraints on relationships:
Cardinality ratio (of a binary relationship): 1:1, 1:N, N:1,
or M:N
SHOWN BY PLACING APPROPRIATE NUMBER ON
THE LINK.
Participation constraint (on each participating entity
type): total (called existence dependency) or partial.
SHOWN BY DOUBLE LINING THE LINK
NOTE: These are easy to specify for Binary Relationship
Types.

Alternative (min, max) notation for relationship
structural constraints:
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
Must have min≤max, min≥0, max ≥1
Derived from the knowledge of mini-world constraints
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
relationship constraints
(1,1)(0,1)
(1,N)(1,1)

COMPANY ER Schema Diagram
using (min, max) notation

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
Higher-order relationships discussed further in Chapter 4

Data Modeling Tools
A number of popular tools that cover conceptual
modeling and mapping into relational schema
design. Examples: ERWin, S- Designer
(Enterprise Application Suite), ER- Studio, etc.
POSITIVES: serves as documentation of
application requirements, easy user
interface - mostly graphics editor support

Problems with Current
Modeling Tools
DIAGRAMMING
– Poor conceptual meaningful notation.
– To avoid the problem of layout algorithms and
aesthetics of diagrams, they prefer boxes and lines and
do nothing more than represent (primary-foreign key)
relationships among resulting tables.(a few exceptions)
METHODOLGY
– lack of built-in methodology support.
– poor tradeoff analysis or user-driven design preferences.
– poor design verification and suggestions for
improvement.

Some of the Currently Available Automated Database
Design Tools
COMPANY TOOL FUNCTIONALITY
Embarcadero
Technologies
ER Studio Database Modeling in ER and IDEF1X
DB Artisan Database administration and space and security
management
Oracle Developer 2000 and
Designer 2000
Database modeling, application development
Popkin Software System Architect 2001 Data modeling, object modeling, process modeling,
structured analysis/design
Platinum
Technology
Platinum Enterprice
Modeling Suite: Erwin,
BPWin, Paradigm Plus
Data, process, and business component modeling
Persistence Inc. Pwertier Mapping from O-O to relational model
Rational Rational Rose Modeling in UML and application generation in C++
and JAVA
Rogue Ware RW Metro Mapping from O-O to relational model
Resolution Ltd. Xcase Conceptual modeling up to code maintenance
Sybase Enterprise Application Suite Data modeling, business logic modeling
Visio Visio Enterprise Data modeling, design and reengineering Visual Basic
and Visual C++

ER DIAGRAM FOR A BANK
DATABASE
© The Benjamin/Cummings Publishing Company, Inc. 1994, Elmasri/Navathe, Fundamentals of Database Systems, Second Edition

PROBLEM with ER notation
THE ENTITY RELATIONSHIP MODEL IN
ITS ORIGINAL FORM DID NOT
SUPPORT THE SPECIALIZATION/
GENERALIZATION ABSTRACTIONS

Extended Entity-Relationship
(EER) Model
Incorporates Set-subset relationships
Incorporates Specialization/Generalization Hierarchies
NEXT CHAPTER ILLUSTRATES HOW THE ER
MODEL CAN BE EXTENDED WITH
- Set-subset relationships and
Specialization/Generalization Hierarchies and how to
display them in EER diagrams

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