is6125 database analysis and design lecture 4: conceptual data modelling 2: er modelling and beyond...

IS6125 Database Analysis and DesignLecture 4: Conceptual Data Modelling 2: ER Modelling and Beyond the Presentation Layer

Rob Gleasure

[email protected]

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

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

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

The Presentation Layer ER Model

Applying the ER Modelling Grammar to the Conceptual Modelling Process

ER modelling grammar

Presentation Layer ER

model/schema

Design-Specific ER

Model/schema

Coarse-granular ER

Model/schema

Fine-granular ER

Model/schema

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


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

The Presentation Layer ER Model Chen’s notation uses the diamond for relationships and can be a

very intuitive way to create ERDs

BuildingGround-floor

entrance

Is entered through

1 n

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)

Rental car

Customer Valet service

Reserves

n 1

n n

Reserves


Inclusive (one can only exist when the other does also)

Rental car

Staff member

Valet service

1 1

1 n

ReservesBooks valet


Noninclusive (one or both must exist)

Rental car

Staff member Customer

1 n

1 n

Providesmap

Providesmap

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

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

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

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.

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

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

The (min, max) notation

The min-max notation swaps the standard ‘look across’ notation

For a ‘look here’ notation that


entrance

Is entered through

(0, n) (1, 1)


entrance

Is entered through

1 n

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

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


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

Exercise: Draw a Coarse-Granular Design-Specific ER Model for Mary’s Playschool Draw a Coarse-Granular Design-Specific

Create an updated set of semantic integrity constraints with tabularised attribute-level constraints for entity name, attribute name, data type, size, and domain constraint

is6125 database analysis and design lecture 4: conceptual data modelling 2: er modelling and beyond...

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