The Entity-Relationship Model
Chapter 2
1
Objectives

Overview of database design


Requirement analysis, conceptual design, logical design,
normalization, and physical design
The entity-relationship (ER) model

Basic constructs:
•
•
•

Advanced constructs:
•
•
•
•

Entities
Relationships
Attributes (of entities and relationships)
Constraints
Weak entities
ISA hierarchies
Aggregation
Conceptual design using the ER model
2
Overview of Database Design
Requirements analysis: Find out what users want to do with
the database




Conceptual design: Use the output of RA to develop a
high-level description of the data to be stored, along with
their constraints. Output of CD usually is an ER-diagram.



What data should be stored in the database?
What applications should be built on top of it?
What operations have critical performance requirements?
What are entities and relationships of the domain?
What are the integrity constraints (= business rules) that hold?
Logical design: Choose a DBMS and map the conceptual
schema (ER-diagram) into the data model of the DBMS.
Output of this step is the logical schema of the data.
3
Overview of Database Design (Cont’d)



Schema refinement: Analyze the logical schema, identify
potential problems in it, and fix these by refining the
logical schema using known normal forms.
Physical design: Consider expected workloads that the
database will support to further refine the design in
order to meet desired performance criteria. Output here
is the physical schema.
Application and security design: Consider aspects of the
design that go beyond the database itself. Complete
design methodologies such as UML are useful here:



What are the users and processes involved in the database
application?
What are the roles of the involved users?
What parts of the database are accessible to each role and what
must not?
4
Conceptual Database Design

Conceptual design: (ER Model is used at this stage.)





What are the entities and relationships in the
enterprise?
What information about these entities and
relationships should we store in the database?
Which integrity constraints (business rules) hold?
How to represent a database `schema’ in the ER
model ? pictorially (as ER diagrams) !
How to map an ER diagram into a relational schema?
5
ER Model Basics
ssn
name
lot
Employees



Entity: Real-world object distinguishable from other
objects. E.g., one employee.
Attribute: Construct describing an entity. E.g., the name
of an employee.
Entity Set: A collection of similar entities. E.g., all
employees.




All entities in an entity set have the same set of attributes.
(Exception: ISA hierarchies)
Each entity set has a key, i.e. a minimal set of attributes whose
values uniquely identify an entity in the entity set. Underlined !
Each attribute has a domain, i.e. a set of possible values
Entity set ~ rectangle; attribute ~ oval.
6
ER Model Basics (Cont’d.)
since
name
ssn
lot
Employees



dname
did
Works_In
budget
Departments
Relationship: Association among 2 or more entities. E.g.,
John works in the Pharmacy department.
Relationship Set: Collection of similar relationships.
 An n-ary relationship set R relates n entity sets E1 ... En;
each relationship in R involves entities e1 of E1, ..., en of
En.
Relationship Set ~ diamond.
7
name
ER Model Basics (Cont’d.)
name
Employees


dname
lot
did
Works_In
lot
Employees
since
ssn
ssn
budget
Departments
supervisor
subordinate
Reports_To
Descriptive attributes: Attributes of relationships.
A relationship set may relate non-distinct entity sets:


Related entities play different roles; e.g., emp1 reports to a
managing employee emp2. Role indicators emphasize this
difference in roles.
Unique names for attributes of the relationship set are obtained
by concatenating the indicator with the attributes of the entity set.
8
Key Constraints


Consider Works_In: An
employee can work in
many departments; a
dept can have many
employees.
In contrast, each dept
has at most one
manager; this is an
example of a key
constraint on Manages,
also called 1-to-many
relationship set. (See
arrow in figure)
since
name
ssn
dname
lot
Employees
1-to-1
1-to Many
did
Manages
Many-to-1
budget
Departments
Many-to-Many
9
Participation Constraints

Does every department have a manager?

If so, this is a participation constraint: the participation of
Departments in Manages is said to be total (vs. partial).
• (Every did value in Departments table must appear in a row
of the Manages table with a non-null ssn value!)
• Below: thick (thin) lines mean total (partial) participation.
since
name
ssn
dname
did
lot
Employees
Manages
budget
Departments
Works_In
since
10
Weak Entities

A weak entity can be identified uniquely only by considering the
primary key of another (identifying owner) entity.
 Owner entity set and weak entity set must participate in a one-tomany relationship set (one owner, many weak entities).
 Weak entity set must have total participation in this identifying
relationship set.
 Example below: employees holding insurance policies for their
dependents. The weak entity set and its identifying relationship
are indicated by drawing them with dark lines.
 A weak entity set has a partial key (indicated with dashed line).
name
ssn
lot
Employees
cost
Policy
pname
age
Dependents
11
name
ssn
ISA (`is a’) Hierarchies
As in C++, or other OO PLs,hourly_wages
attributes are inherited.
If we declare A ISA B, then every
A entity is also a B entity.



lot
Employees
hours_worked
ISA
contractid
Hourly_Emps
Contract_Emps
Overlap constraints: Are two classes allowed to overlap? E.g., can Joe be
both an Hourly_Emps and a Contract_Emps entity? (Allowed/disallowed)
Covering constraints: Do entities of subclasses contain all those in the
superclass? E.g., does every Employees entity also have to be an
Hourly_Emps or a Contract_Emps entity? (Yes/no)
Reasons for using ISA (by specialization/generalization):
 To add descriptive attributes specific to a subclass.
 To identify entities that participate in a relationship (See slide 17).
12
name
ssn
Aggregation

Employees
Used to model a
relationship
between entity sets
and relationship sets.


Aggregation: Allows
to treat a relationship
set as an entity set
for purposes of
participation in
(other) relationships.
Notation: dashed box
indicating that a
relationship set
participates in
another relationship
set.
lot
Monitors
since
started_on
pid
pbudget
Projects
until
dname
did
Sponsors
budget
Departments
* Aggregation vs. ternary relationship:
-- Monitors is a distinct relationship,
with a descriptive attribute.
-- Also, can say that each sponsorship
is monitored by at most one employee.
13
Conceptual Design Using the ER Model

Design choices:




Should a concept be modeled as an entity or an
attribute?
Should a concept be modeled as an entity or a
relationship?
Identifying relationships: Binary or ternary?
Aggregation?
Constraints in the ER Model:


A lot of data semantics can (and should) be captured.
But some constraints cannot be captured in ER
diagrams.
14
Entity vs. Attribute
Should address be an attribute of Employees or an
entity (connected to Employees by a relationship)?
 Depends upon the use we want to make of address
information, and the semantics of the data:

• If we have several addresses per employee, address
must be an entity (since attributes cannot be setvalued).
• If the structure (city, street, etc.) is important, e.g., we
want to retrieve employees in a given city, address
must be modeled as an entity (since attribute values
are atomic).
15
Entity vs. Attribute (Contd.)
from
name



ssn
lot
Works_In4 does not
allow an employee to
work in a department
Employees
for two or more periods.
Similar to the problem of
wanting to record several
addresses for an employee:
We want to record several
values of the descriptive
name
attributes for each instance of
ssn
this relationship.
Accomplish this by
Employees
introducing new entity set
Duration.
to
dname
did
Works_In4
budget
Departments
dname
lot
from
did
Works_In4
Duration
budget
Departments
to
16
Entity vs. Relationship



Should an attribute be
descriptive or not?
First ER diagram depicts
the situation where a
manager gets a separate
discretionary budget for
each dept.
What if a manager gets a
discretionary budget that
covers all managed depts?


Redundancy: dbudget
stored for each dept
managed by manager.
Misleading: Suggests
dbudget associated with
department-mgr
combination.
since
name
ssn
dbudget
lot
Employees
dname
did
budget
Departments
Manages2
name
ssn
lot
dname
since
did
Employees
ISA
Managers
Manages2
dbudget
budget
Departments
This fixes the
problem!
17
Binary vs. Ternary Relationships
name
ssn
pname
lot
Employees
age
Dependents
Covers
Bad design for the additional requirements
Policies
policyid

cost
This ER diagram expresses the following requirements :
 An employee can own several policies.
 Each policy can be owned by several employees.
 Each dependent can be covered by several policies.

The ER diagram doesn’t express the following requirements:
 A policy cannot be covered jointly by 2 or more employees.
 Every policy must be covered by some employee.
 Dependents is a weak entity set with partial key “pname” and identified by
the primary key of Policies.

Which constraints would capture the additional requirements?
18
Binary vs. Ternary Relationships (Cont’d)


Solution: instead of Covers, introduce two binary relationships,
Purchaser and Beneficiary.
Then add the following constraints:
 Key constraint on Policies with respect to Purchaser
 Total participation constraint on Policies with respect to Purchaser
 Appropriate constraints on the weak entity set Dependents

What if we only add a key constraint on Policies wrt to Covers?
name
pname
ssn
lot
age
Dependents
Employees
Purchaser
Beneficiary
Better design
policyid
Policies
cost
19
Binary vs. Ternary Relationships (Contd.)
Previous example illustrated a case when two
binary relationships were better than one ternary
relationship.
 An example in the other direction: a ternary
relation Contracts relates entity sets Parts,
Departments and Suppliers, and has descriptive
attribute qty. No combination of binary
relationships is an adequate substitute:



S “can-supply” P, D “needs” P, and D “deals-with” S
does not imply that D has agreed to buy P from S.
How do we record qty? Impossible to represent it
cleanly with these binary relations.
20
Summary of Conceptual Design

Conceptual design follows requirements analysis,


Yields a high-level description of data to be stored
ER model popular for conceptual design


Constructs are expressive, close to the way people think
about their applications.
It is a semantic model !
Basic constructs are: entities, relationships, and
attributes (of entities and relationships).
 Some additional constructs are: weak entities, ISA
hierarchies, and aggregation.
 There are many variations of ER model in the
literature.

21
Summary of ER (Contd.)

Several kinds of integrity constraints can be expressed
in the ER model: key constraints, participation
constraints, and overlap/covering constraints for ISA
hierarchies. Some foreign key constraints are also
implicit in the definition of a relationship set.


Some constraints (notably, functional dependencies) cannot be
expressed in the ER model.
Constraints play an important role in determining the best
database design for an enterprise.
22
Summary of ER (Contd.)

ER design is subjective. There are often many ways
to model a given scenario! Analyzing alternatives
can be tricky, especially for a large enterprise.
Common choices include:

Entity vs. attribute, entity vs. relationship, binary or nary relationship, whether or not to use ISA hierarchies,
and whether or not to use aggregation.
23