BKM_DATS: Databázové systémy
6. Entity-Relationship Model
Vlastislav Dohnal
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Entity-Relationship Model
Modeling
E-R Diagram
Entity Sets and Relationships
Weak Entity Sets
Extended E-R Features
Design of the Bank Database
UML
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Entitně-relační model
◼ Konceptuální model používaný při vývoji IS
 Během analýzy požadavků
 Modeluje informace ukládané v DB
◼ Snadný pro porozumění
 Zákazník mu „rozumí“
DFD – půjčka v bance
BKM_DATS, Vlastislav Dohnal, FI MUNI, 2022 4
customer
Receipt
loan
req.
Process
loan
req.
Check
status
Loan application
Loanapplication
Confirmation
manager
Loans
History report
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Modeling
A database can be modeled as:
a collection of entities,
relationship among entities.
An entity is an object that exists and is distinguishable from other
objects.
Example: specific person, company, event, plant
Entities have attributes
Example: person has a name and address
An entity set is a set of entities of the same type that share the same
properties.
Example: set of all persons, companies, trees, holidays
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Entity Sets customer and loan
customer loan
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Relationship Sets
A relationship is an association among several entities
Example:
Hayes borrower A-102
customer entity relationship set loan entity
A relationship set is a mathematical relation among n  2 entities, each
taken from corresponding entity sets
R = {(e1, e2, … en) | e1  E1, e2  E2, …, en  En}
where (e1, e2, …, en) is a relationship
Example:
(Hayes, A-102)  borrower
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Relationship Set borrower
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Relationship Sets (Cont.)
An attribute can also be property of a relationship set.
For instance, the depositor relationship set between entity sets
customer and account may have the attribute access_date
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Mapping Cardinality Constraints
Express the number of entities to which another entity can be
associated via a relationship set.
Most useful in describing binary relationship sets.
For a binary relationship set the mapping cardinality must be one of
the following types:
One to one
One to many
Many to one
Many to many
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Mapping Cardinalities
One to one One to many
Note: Some elements in A and B may not be mapped to any
elements in the other set
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Mapping Cardinalities
Many to one Many to many
Note: Some elements in A and B may not be mapped to any
elements in the other set
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Attributes
An entity is represented by a set of attributes
= descriptive properties possessed by all members of an entity set.
Name – each attribute has its name unique within an entity
Domain – the set of permitted values for each attribute
Attribute type
Simple attribute – single value
Composite attribute – single value but structured
Multi-valued attribute – multiple values, can repeat
Example: phone_numbers
Derived attribute
Can be computed from other entity’s attributes
Example: age, given date_of_birth
Example:
customer = (customer_id, customer_name, customer_street, customer_city )
loan = (loan_number, amount )
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Composite Attributes
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E-R Diagram With Composite, Multivalued, and Derived Attributes
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Relationship Sets with Attributes
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Mapping Cardinality Constraints
We express cardinality constraints by drawing either
a directed line (→), signifying “one,” or
an undirected line (—), signifying “many,” between the relationship
set and the entity set.
One-to-one relationship:
A customer is associated with at most one loan via the relationship
borrower
A loan is associated with at most one customer via borrower
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One-To-Many Relationship
In the one-to-many relationship a loan is associated with at most one
customer via borrower, a customer is associated with several (including
zero) loans via borrower
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Many-To-One Relationships
In a many-to-one relationship, a loan is associated with several
(including zero) customers via borrower, a customer is associated with
at most one loan via borrower
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Many-To-Many Relationship
A customer is associated with several (possibly zero) loans via
borrower
A loan is associated with several (possibly zero) customers via
borrower
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Keys
Key = a subset of attributes of “special” interest
Search key
“Database / identification / unique” key
Referencing an entity
“Database key” (primary key constraint)
Defined for unique identification of each entity and/or relationship
A super key of an entity set is a set of one or more attributes whose
values uniquely determine each entity.
A candidate key of an entity set is a minimal super key
customer_id is a candidate key of customer
account_number is a candidate key of account
Although several candidate keys may exist, one of the candidate keys is
selected to be the primary key.
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Keys for Relationship Sets
The combination of primary keys of the participating entity sets forms a
super key of a relationship set.
(customer_id, account_number) is the super key of depositor
NOTE: this means a pair of entities can have at most one
relationship in a particular relationship set.
Example: if we wish to track all access_dates to each account by
each customer, we cannot assume a relationship for each
access. We may use a multivalued attribute.
Must consider the mapping cardinality of the relationship set when
deciding what the candidate keys are
Need to consider semantics of relationship set in selecting the primary
key in case of more than one candidate key
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E-R Diagram with a Ternary Relationship
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Cardinality Constraints on Ternary Relationship
We allow at most one arrow out of a ternary (or greater degree) relationship
to indicate a cardinality constraint
E.g., an arrow from works_on to job indicates an employee works at a
branch on at most one job.
If there is more than one arrow, there are two ways of defining the meaning.
E.g., a ternary relationship R between A, B and C with arrows to B and C
could mean
1. each A entity is associated with a unique entity from B and C or
2. each pair of entities from (A, B) is associated with a unique C entity,
and each pair (A, C) is associated with a unique B
Each alternative has been used in different formalisms
To avoid confusion, we outlaw more than one arrow
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Roles
Entity sets of a relationship need not be distinct
The labels “manager” and “worker” are called roles; they specify how
employee entities interact via the works_for relationship set.
Roles are indicated in E-R diagrams by labeling the lines that connect
diamonds to rectangles.
Role labels are optional, and are used to clarify semantics of the
relationship
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Participation of an Entity Set in a Relationship Set
Total participation (indicated by double line)
every entity in the entity set participates in at least one relationship
in the relationship set
E.g., participation of loan in borrower is total
every loan must have a customer associated to it via borrower
Partial participation (default)
some entities may not participate in any relationship in the
relationship set
Example: participation of customer in borrower is partial
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Existence Dependencies
If the existence of entity x depends on the existence of entity y, then x
is said to be existence dependent on y.
y is a dominant entity (in example below, loan)
x is a subordinate entity (in example below, payment)
If a loan entity is deleted, then all its associated payment entities must
also be deleted.
loan-payment paymentloan
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Weak Entity Sets (Cont.)
We depict a weak entity set by double rectangles.
We underline the discriminator of a weak entity set with a dashed line.
payment_number – discriminator of the payment entity set
So, it can represent the order of individual payments of a loan.
Primary key for payment is (loan_number, payment_number)
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More Weak Entity Set Examples
In a university, a course is a regular entity set and a course_offering can
be modeled as a weak entity set.
The discriminator of course_offering is semester (including year)
and section_number (if there is more than one section)
If we modeled course_offering as a regular entity, we would add
course_id as an attribute.
Then the relationship to course would be also implicit in the
course_offering.course_id attribute.
course course_offering
course_id
title
credits semester
section_number
time_schedule
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Design Issues
Use of entity sets vs. attributes
Choice mainly depends on the structure of the enterprise being
modeled, and on the semantics associated with the attribute in
question.
Use of entity sets vs. relationship sets
Possible guideline is to designate a relationship set to describe an
action that occurs between entities
Binary versus n-ary relationship sets
Although it is possible to replace any nonbinary (n-ary, for n > 2)
relationship set by a number of distinct binary relationship sets, an
n-ary relationship set shows more clearly that several entities
participate in a single relationship.
Placement of relationship attributes
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Binary Vs. Non-Binary Relationships
Some relationships that appear to be non-binary may be better
represented using binary relationships
E.g. A ternary relationship parents, relating a child to his/her
father and mother, is best replaced by two binary relationships,
father and mother
Using two binary relationships allows partial information (e.g.
only mother being know)
But there are some relationships that are naturally non-binary
Example: works_on
father
parents
mother
child
father
parent
child
mother
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Extended E-R Features: Specialization
A top-down design process
We designate subgroupings within an entity set that are distinctive
from other entities in the set.
These subgroupings become lower-level entity sets
can have attributes or participate in relationships
but do not apply to the higher-level entity set.
Depicted by a triangle component labeled ISA
E.g., customer “is a” person.
Inheritance
a lower-level entity set inherits all the attributes and
relationship participation of the higher-level entity set to which it is
linked.
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Specialization Example
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Aggregation
Consider the ternary relationship works_on, which we saw earlier
Suppose we want to record managers for some tasks performed by an
employee at a branch
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Aggregation (Cont.)
Relationship sets works_on and manages represent overlapping
information
Every manages relationship corresponds to a works_on
relationship
However, some works_on relationships may not correspond to
any manages relationships
So, we can’t discard the works_on relationship
Eliminate this redundancy via aggregation
Treat a relationship as an abstract entity
Allows relationships between relationships
Abstraction of relationship into new entity
Without introducing redundancy, the following diagram represents:
An employee works on a particular job at a particular branch
An employee, branch, job combination may have an associated
manager
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E-R Diagram With Aggregation
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E-R Design Decisions
Already discussed:
The use of an attribute or entity set to represent an object.
Whether a real-world concept is best expressed by an entity set
or a relationship set.
The use of a ternary relationship versus a set of binary
relationships.
The use of a regular (strong) or weak entity set.
The use of specialization/generalization
contributes to modularity in the design.
The use of aggregation
can treat the aggregate entity sets as a single unit without
concern for the details of its internal structure.
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E-R Diagram for a Banking Enterprise
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Summary of Symbols Used in E-R Notation
Chen E-R Notation
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Alternative E-R Notations
https://www.softwareideas.net/erd-relation-arrows
Case
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UML
UML: Unified Modeling Language
UML has many components to graphically model different aspects of an
entire software system
Supported techniques
data modeling (entity relationship diagrams)
business modeling (workflows)
object modeling
component modeling
UML Class Diagrams correspond to E-R Diagram
but there are several differences.
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Summary of UML Class Diagram Notation
Chen notation UML notation
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UML Class Diagram Notation (Cont.)
* Note the reversal notation of numeric relationship cardinality constraints in UML
* Generalization can use merged or separate arrows independent of disjoint/overlapping
overlapping
disjoint
Chen notation UML notation