E-R diagrams

Report
Entity-Relationship (E-R) modeling:
constructing a conceptual schema
(Chapter 5)
Due to course constraints I have to defer
other modeling issues (normalization in
chapters 3 and 4) until later in the
semester.
Entity
a thing you need to model.
It is analogous to a class in object oriented
design.
Fields of an entity are called attributes.
An entity instance is an occurrence of a
particular entity.
It is analogous to an object. However, there
is no encapsulation in the OO sense.
One or more attributes is usually an
identifier, which uniquely identifies an
entity.
It is also called a key, though the term
identifier is used in the data model and
key is used when creating tables.
Semantics.
Design issue:
Many designers like to keep each
identifier and primary key dataless
This means that it contains no
information about the entity. This way,
they never change.
Ex. IDs, account numbers, etc.
Advantageous if there’s an index or hash
function that uses the keys since a
changing key would change the internal
structure.
Also useful since a key value sometimes
exists in other records that are related to
the entity with the given key.
These would need to change also.
A relationship defines how two or more
entities are connected according the rules
in the reality you are modeling.
Some guidelines
A relationship should be named and welldefined.
Do not simply state there is a relationship
between two entities.
Articulate what the relationship
represents.
Example:
there is a relationship between a student
entity and a course entity.
So?
Does it represent courses for which the
student has registered?
Does it represent courses dropped?
Does it represent courses needed for a
major?
Does it represent courses on a transcript?
Spell it out!!
Degree of a relationship is the number of
entities involved.
Most are degree 2 (binary relationships)
but some are more.
A ternary relationship involves 3 entities.
Example: p. 148.
Can you think of more?
Cardinality is the number of entity
instances in a relationship.
Maximum cardinality is the maximum
number of instances in a relationship.
For example, the relationship between a
sports team and its players has a
maximum cardinality defined by rules of
the sport.
Three types of maximum cardinality
1-1 relationship between A and B
For each instance of type A there is no more
than one instance of type B, and vice-versa.
Notation and example: p. 149
Some possible examples:
Employee
1:1
fleet vehicle
Project
employee (defined by
who is project leader and assumes each
employee leads no more than one
project.)
1:1
Employee
1:1
computer
1-many relationship between A and B
For each instance of type A there may be
many instances of type B; however, for each
instance of type B there is no more than one
instance of type A.
Notation and example: p. 149.
Other possible examples:
Course
sections
1:N
Departments
1:N
project
(participation)
employees
1:N
Employee
employees
1:N
computer
May actually specify a maximum
number.
Example: Team-players. Number depends on
the sport.
Sometimes the term parent applies to the
entity on the “one side” and child applies
to the entity on the “many side”.
Many-many relationship between A and
B
For each instance of type A there may be
many instances of type B, and vice-versa.
Notation: p. 149
More examples follow
Students
courses (could have
several meanings)
Authors
books
Movies
actors;
advisors
students;
artist
songs
Major
courses
N:M
N:M
N:M
N:M
N:M
N:M
These are sometimes called HAS-A
relationships.
A team has players; a student has courses;
etc.
Minimum cardinality
May specify a minimum number of
instances.
Can specify whether an instance is
mandatory or optional.
Examples: p. 150. Can you think of more?
A crow’s foot notation (page 152-153)
often used to provide a visual of the
relationships.
We’ll use this notation in subsequent
diagrams
Weak entity
Cannot exist unless another type of entity
exists
Employeedependent (dependent is
weak)
building  room (room is weak)
course  section (section is weak)
book has more
ID-dependent entity
special type of weak entity in which the
ID contains the ID of another entity
EX: Rooms on campus have an ID such
as MAC 122 (Building ID and room
number).
Other examples on page 154
All ID-dependent entities are weak
A weak entity may not be ID-dependent
(example p.155)
Shown in diagram using solid lines (ex.
P.154)
If the parent entity is removed, so must
all child entities.
Dashed lines represent non-identifying
relationships
Strong entity
existence does not depend on another
entity.
Ex: Students, employees, departments,
computer, building, etc.
Difference between strong and weak not
always clear.
Subject to variances in interpretation of
the mode.
Kroenke lists possible tests on page 156
and 160
Example:
One-to-many relationship between a
pharmaceutical company and a drug.
One-to-many relationship between an
employee and a dependent.
Dependent does not exist w/o the
employee.
Drug does not exist w/o the
pharmaceutical company
Are drug and dependent both weak?
If the employee is removed the
dependent disappears.
If the pharmaceutical company
disappears, the drug may be
assigned to another company.
Argues that the drug is strong.
Creating an E-R diagram using Visio:
Open Microsoft Office Visio.
Select Software and Database under
template categories.
Select Database Model Diagram as a
template.
Press the Create button.
Drag and drop one or more entity images
to your worksheet.
Double click on the icon and, through the
properties pane below the worksheet, you
can give it a name and define its fields.
Drag and drop a relationship icon to the
worksheet.
Connect each end to an entity.
To get the “crow’s foot” format
select Display Options in the database tab
Select the Relationship tab
check the Crow’s feet checkbox.
Double click the relationship icon
select miscellaneous under categories
Select the appropriate cardinality.
NOTE: Visio does not allow the
specification of a many-to-many
relationship.
Does a poor job as a modeling tool.
However, we will see later that ALL
many-to-many relationships can be
implemented via two one-to-many
relationships
Probably best to NOT use visio for true
data modeling diagrams.
But OK for defining relationships among
tables and for this course.
Ternary relationships.
Doctor – Patients – Drugs
Relationship below does not convey all
necessary information
patient
n:m
prescription
drug
doctor
n:m
prescribes
drug
A specific drug given to a patient must
have been prescribed by a doctor.
Would need
patient
doctor
drugs
Building a data model:
Interview the users of data. Find out how
they operate!!
Look at existing forms, reports, files,
lists, etc.
Determine entities. Look for key words
such as order, appointment, product,
customer, etc.
Specify relationships.
Examine all combinations of entities or
examine documents obtained from previous
steps.
Determine what attribute (identifier)
uniquely determines an entity.
Determine attributes.
Ask whether an attribute should be its own
entity.
Salesperson has a region: should region be
just an attribute or a separate entity?
Data models should reflect reality.
Problem is one person’s reality may be
different than another’s.
See book for examples.
In Class example: Design a data model
for a university database.
Using Patterns to design relationships.
Asking users what the maximum cardinality is
won’t work
they won’t know what you’re talking about.
You can show them a prototype form or report
to learn how many entity objects relate to
another.
Ex. Show a course form to a user that shows
one instructor.
The user will likely let you know if other
instructors should be shown.
Figure 5-15a on p. 159
Suggests a 1-1 relationship between
strong entities member and locker
Data model in Figure 5-16
Figure 5-17 on p. 160
Suggests a one-to-many between
company and department
Figure 5-18 shows the model
Figures 5-19a and 5-19b on p. 161
The form and report suggest a many-tomany relationship between company and
part
Data model in Figure 5.20
Association pattern:
Consider a n:m relationship connecting
students and courses (transcript).
Where is the grade stored?
It is not part of the student entity
It is not part of the course entity.
The data model should show a 3rd entity
(transcript?) containing the grade
This is analogous to the example from
figures 5.21 & 5.22 on p. 162-163
Student
Courses
transcripts
Multivalued attribute pattern
when is an attribute not an attribute
Consider a customer entity.
Is the phone number an attribute?
If just one number, store as an attribute.
If multiple numbers, might be a problem
since arrays or lists can not be attribute
types in a relation.
May create an ID-dependent entity,
PHONE, connected to the customer.
If just two numbers max, might create a
primary and secondary phone number
attribute of the customer.
Archetype/Instance pattern
One entity represents an instance of
another.
Prints of a painting
Copies of a book
Sections of a course
Line Item Pattern
Multiple instances of an entity used to
describe another entity
Ex: Line items to describe an order
Recursive relationships – may be 1:1,
1:n, or n:m
A course and it’s prerequisites (n:m).
A course may have multiple prerequisites
and may be a prerequisite for multiple other
courses.
Manufacturing (Bill of Materials).
Products consists of parts, some of which are
composed of other parts.
Parts may be included in other parts (p. 173)
Basic ER modeling
Define strong and weak entities.
Define relationships and categorize as
1:1, 1:n, or n:m
The rest allows you to refine for better
accuracy.
Subtype entities
Similar to inheritance.
A subtype entity isa special case of
another entity (supertype).
Ex. Distinction of male and female
patients for medical tests.
Ex. Distinction of different types of
employees.
Diagram notation on page 156 and
158.
Discriminator: supertype attribute that
determines the subtype.
Ex: patient gender or employee
classification.
May not always exist.
Examples on page 156
An exclusive subtype means the
supertype relates to at most one
subtype.
An inclusive subtype means the
supertype can relate to more than one
subtype.
Ex. A patient is male or female, not
both.
An employee might be a team leader,
programmer, analyst, or all.

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