1. IS6125 Database Analysis and Design Lecture 4: Conceptual Data Modelling 2: ER Modelling and Beyond the Presentation Layer
Rob Gleasure

2. IS6125
Today’s session
Applying the ER Modelling Grammar to the Conceptual Modelling Process
The Presentation Layer ER Model
The Coarse-Granular Design-Specific ER Model
The Fine-Granular Design-Specific ER Model
An exercise

3. Applying the ER Modelling Grammar to the Conceptual Modelling Process
An ER model can be used for two main reasons
To act as a tool for communication between designers and end-users
To guide the design of the eventual database
These roles are met by different types of ERDs and constraint specifications
The communication role is met by the Presentation Layer
The database design role is met by the Design-Specific ER model

4. The Presentation Layer ER Model
The Presentation Layer Model is
Technology-independent
Human-focused in terms of communication
Simple, where possible
Heuristic-based rather than scientific
Iterative/recursive

5. Applying the ER Modelling Grammar to the Conceptual Modelling Process
Presentation Layer ER model/schema
Design-Specific ER Model/schema
Coarse-granular ER Model/schema
Fine-granular ER Model/schema

6. The Presentation Layer ER Model
Last week we spoke about several aspects of ER Modelling at the presentation layer
Image from Data Modeling and Database Design, By Narayan Umanath, Richard Scamell

7. The Presentation Layer ER Model
Also cardinality - note that there are several forms of notation, the one we have been using is Chen’s ‘look across’ numbered notation
Exactly 1
0 or 1
1 or more
0 or many 1 1 n n

8. The Presentation Layer ER Model
Chen’s notation uses the diamond for relationships and can be a very intuitive way to create ERDs
Is entered through
Building
Ground-floor entrance 1 n

9. The Presentation Layer ER Model
We can also describe co-dependencies between relationships using three types of arcs
Exclusive (one can only exist when the other does not)
Customer
Valet
service n 1
Reserves
Reserves n
Rental car n

10. The Presentation Layer ER Model
Inclusive (one can only exist when the other does also)
Staff
member
Valet
service 1 1
Books
valet
Reserves 1
Rental car n

11. The Presentation Layer ER Model
Noninclusive (one or both must exist)
Staff
member
Customer 1 n
Provides
map
Provides
map 1
Rental car n

12. The Synthesis Approach to Generate an Initial Set of Entity Types and Attributes
List all discernable data elements and treat them as attributes
Group these attributes based on apparent commonalities
Designate each cluster of attributes as an entity type
Review leftover data elements and investigate the possibility that some of them serve as links among the entity types previously identified
Designate these links as relationship types

13. The Analysis Approach to Generate an Initial Set of Entity Types and Attributes
Begin by searching for things that can be labelled by singular nouns and call these things entity types
Gather properties that appear to belong to individual entity types and label them as attributes of a particular entity type
Be sensitive throughout the process to the identification of relationships among the various entity types

14. Rounding Off Initial Modelling
When this is done
Gather business rules that can’t be captured in the ERD into a list of Semantic Integrity Constraints, a supplement to the ERD
Repeat last two steps (as many times as necessary) until all aspects of the story (i.e., the business rules) have been accounted for in the ER model

15. Example narrative: Mary’s Playschool
A parent registers their child or children at the school with a special registration form, which records the parent, the child, a contact phone number, and any special needs, allergies, etc. the child has. A parent submits one registration form for each child but they may have more than one child at the school. Each room in the school is assigned an age group. Children under 4 years of age go in different rooms from children over 4. A child is assigned to a room based on their age and the capacity of the room. This capacity depends on the room’s size and the experience of the teacher (which may be low, intermediate, or high) but total room capacity capped at 30. A room may be assigned one or more teachers but a teacher must only be assigned to one room. The school also employs assistants to help the teachers (they tend to have favourites they pair up with repeatedly), who must also be assigned to exactly one room. At all times, each room must have an assistant and/or a teacher associated with it. Some part-time teachers also act as assistants on free days.

16. Example narrative: Mary’s Playschool
Draw a Presentation Layer ERD using Chen’s notation
List any semantic integrity constraints at
An attribute level
An entity level
A business level

17. The Coarse-Granular Design-Specific ER Model
Once a design is negotiated with the user community, more details will have to be added to actually implement the database
These include
Collection of more characteristics for attributes (i.e., data type, size, and range)
Use of the technically more precise (min, max) notation for the specification of relationships
Mapping deletion rules to the ER diagram

18. The (min, max) notation
The min-max notation swaps the standard ‘look across’ notation
For a ‘look here’ notation that
Is entered through
Building
Ground-floor entrance 1 n
Is entered through
Building
Ground-floor entrance
(0, n)
(1, 1)

19. Data types/ranges for attributes: updated integrity constraints
Many attribute-level semantic integrity constraints are resolved at this layer by tabularising them according to entity name, attribute name, data type, size, and domain constraint
E.g. at the Presentation Level for Mary’s Playschool, we may have had the following attribute-level semantic integrity constraint
Teachers’ experience ranges from low to intermediate to high
This could now become
Entity
Attribute
Data type
Size
Domain constraint
Teacher
Experience
Numeric 1
1=low, 2=intermediate, 3=high

20. Deletion constraints
Restrict Rule (R): If a parent entity in a relationship is deleted and if all child entities related to this parent in this relationship should not be deleted, then the deletion of the parent should be disallowed
Cascade Rule (C): If a parent entity in a relationship is deleted and if all child entities related to this parent in this relationship should also be deleted, the cascade rule applies
Note: Conventionally, when a deletion constraint is not specified, the restrict rule is implied by default

21. Deletion constraints
Set Null Rule (N): If a parent entity in a relationship is deleted and if all child entities related to this parent in this relationship should be retained but no longer referenced to this parent, the ‘set null’ rule applies
Set Default Rule (D): If a parent entity in a relationship is deleted and if all child entities related to this parent in this relationship should be retained but no longer referenced to this parent but should be referenced to a predefined default parent, the ‘set default’ rule applies

22. Deletion constraints
Image from Data Modeling and Database Design, By Narayan Umanath, Richard Scamell

23. Deletion constraints
Image from Data Modeling and Database Design, By Narayan Umanath, Richard Scamell

24. Exercise: Draw a Coarse-Granular Design-Specific ER Model for Mary’s Playschool
Create an updated set of semantic integrity constraints with tabularised attribute-level constraints for entity name, attribute name, data type, size, and domain constraint