1. Degrees of Data Abstraction
Database designer starts with abstracted view, then adds details
ANSI Standards Planning and Requirements Committee (SPARC)
Defined a framework for data modeling based on degrees of data abstraction (1970s):
External
Conceptual
Internal
Database Systems, 9th Edition

2. The External Model End users’ view of the data environment
ER diagrams represent external views
External schema: specific representation of an external view
Entities
Relationships
Processes
Constraints
Database Systems, 9th Edition

3. Database Systems, 9th Edition

4. The External Model (cont’d.)
Easy to identify specific data required to support each business unit’s operations
Facilitates designer’s job by providing feedback about the model’s adequacy
Ensures security constraints in database design
Simplifies application program development
Database Systems, 9th Edition

5. What are entities here ? Relationships? Do you see entity attributes ?
Database Systems, 9th Edition

6. Database Systems, 9th Edition

7. Any examples of the last bullet action?
The Internal Model
Representation of the database as “seen” by the DBMS
Maps the conceptual model to the DBMS
Internal schema depicts a specific representation of an internal model
Depends on specific database software
Change in DBMS software requires internal model be changed
Logical independence: change internal model without affecting conceptual model
Any examples of the last bullet action?
Database Systems, 9th Edition

8. Database Systems, 9th Edition

9. The Physical Model Operates at lowest level of abstraction
Describes the way data are saved on storage media such as disks or tapes
Requires the definition of physical storage and data access methods
Relational model aimed at logical level
Does not require physical-level details
Physical independence: changes in physical model do not affect internal model
Database Systems, 9th Edition

10. Database Systems, 9th Edition

11. Summary
A data model is an abstraction of a complex real-world data environment
Basic data modeling components:
Entities
Attributes
Relationships
Constraints
Business rules identify and define basic modeling components
Database Systems, 9th Edition

12. Summary (cont’d.) Hierarchical model Network data model
Set of one-to-many (1:M) relationships between a parent and its children segments
Network data model
Uses sets to represent 1:M relationships between record types
Relational model
Current database implementation standard
ER model is a tool for data modeling
Complements relational model
Database Systems, 9th Edition

13. Summary (cont’d.)
Object-oriented data model: object is basic modeling structure
Relational model adopted object-oriented extensions: extended relational data model (ERDM)
OO data models depicted using UML
Data-modeling requirements are a function of different data views and abstraction levels
Three abstraction levels: external, conceptual, internal
Database Systems, 9th Edition

14. Entity and Attribute-Level Data Integrity Constraints
At the conceptual tier of data modeling, two types of data integrity constraints pertaining to entity types and attributes are specified
The domain constraint imposed on an attribute to ensure that its observed value is not outside the defined domain
The key (or uniqueness) constraint that requires entities of an entity type to be uniquely identifiable
Chapter 2 – Foundation Concepts

15. Exercise Draw data models for the following entities:
Ship: A ship has a name, registration code, gross tonnage, and a year of construction. Ships are classified as cargo or passenger.
Car: A car has a manufacturer, range name, and style code (e.g., a Honda Accord DX, where Honda is the manufacturer, Accord is the range, and DX is the style). A car also has an identification code, registration code, and color.
Restaurant: A restaurant has an address, seating capacity, phone number, and a style of food.
For each data model, identify domain and key constraints.
For each of the cases above – specify domain contraint ( mark it with “d”) and key constraints ( mark it with “k”). Type your answers.
Chapter 2 – Foundation Concepts

16. More on E-R Modeling Grammar Relationship Type
Conceptualization of association between object types
Binary (degree = 2); ternary (degree = 3); n-ary (degree = n); unary [recursive] (degree = 1)
Chapter 2 – Foundation Concepts

17. n-ary Relationships
Chapter 2 – Foundation Concepts

18. n-ary Relationships (continued)
Example 1. Professor Einstein teaching Physics using Introduction to Physics.
Example 2. Professor Einstein teaching Physics using Principles of Physics.
Example 3. Professor Einstein teaching Math using Principles of Calculus.
Example 4. Professor Chu teaching Math using Introduction to Calculus.

19. n-ary Relationships (continued)
Example 1. Dr. Fields prescribes Advil to treat Sharon Moore for a headache.
Example 2. Dr. Fields prescribes Advil to treat Michelle Li for a headache.

20. n-ary Relationships (continued)
Chapter 2 – Foundation Concepts

21. Relationships have Role Names
Chapter 2 – Foundation Concepts

22. Structural Constraints of a Relationship Type
Two structural constraints define a relationship type
Cardinality constraint (ratio) specifies the maximum number of instances of an entity type that relate to a single instance of an associated entity type through a binary relationship type (i.e., 1:1, 1:n, n:m = maximum cardinality)
Participation constraint is based on whether, in order to exist, an entity of that entity type needs to be related to an entity of the other entity type through a binary relationship type (i.e., total/mandatory or partial/optional = minimum cardinality); total participation = existence dependency
Chapter 2 – Foundation Concepts

23. Cardinality Constraint (Ratio)
Chapter 2 – Foundation Concepts

24. Cardinality Constraint (Ratio) (continued)
Chapter 2 – Foundation Concepts

25. Cardinality Constraint (Ratio) (continued)
Chapter 2 – Foundation Concepts

26. Participation Constraint
Chapter 2 – Foundation Concepts

27. Participation Constraint (continued)
Chapter 2 – Foundation Concepts

28. Cardinality Ratio and Participation Constraints

29. Cardinality Ratio and Participation Constraints
(continued)

30. Cardinality Ratio and Participation Constraints
(continued)

31. Cardinality Ratio and Participation Constraints
(continued)

32. Cardinality Ratio and Participation Constraints
(continued)
Chapter 2 – Foundation Concepts

33. Something To Think About
Think of each entity type and relationship type as a separate table for right now
For example:
Vendor
VenID VenName
Joe Inc
Bill Inc
Supplies
VenID ProdID Cost
2 25 7
1 24 8
1 25 7
Product
ProdID ProdName
Soup
Noodles
Chocolate
Chapter 2 – Foundation Concepts

34. Base/Strong vs. Weak Entity Types
Chapter 2 – Foundation Concepts

35. Base/Strong vs. Weak Entity Types (continued)
Base (or strong) entity types are those where the entities have independent existence (i.e., each entity is unique)
A base entity type has a unique identifier
Weak entity types are those where entities have a dependent existence (i.e., duplicate entity instance may be present)
A weak entity type does not have a unique identifier
A weak entity type has an “identifying relationship” with an identifying parent entity type
A weak entity type has a “partial key” – also known as a “discriminator”
Chapter 2 – Foundation Concepts

36. Partial Key (Discriminator) Defined
An attribute, atomic or composite, in a weak entity type, which in conjunction with a unique identifier of the parent entity type in the identifying relationship type, uniquely identifies weak entities is called the partial key of a weak entity type.
Chapter 2 – Foundation Concepts

37. Figure 2.23 Weak entity type: an example
Sample Data Sets for BUILDING and APARTMENT
Building Data Set
Bldg_no #Floors Size (sq. ft) Vacancy S S N N
APARTMENT Data Set*
Apt_no #bedrooms #bathrooms Size (sq. ft) Rent
*The first four apartments listed are located in Building Number S51 while the fifth apartment is located
in Building Number N51.
Figure 2.23 Weak entity type: an example

38. Exercises
What will be a relationship cardinality in the following cases ?
A farmer can have many cows, but a cow belongs to only one farmer.
A nation can have many states and a state many cities.
A patient can have many physicians, and a physician can have many patients.
A dairy farmer has several herds of cows. He has assigned each cow to a particular herd. In each herd, the farmer has one cow that is his favorite.
For each data model, identify cardinality ratio, participation constraints, as well as domain and key constraints
Chapter 2 – Foundation Concepts

39. Vignette 1
Chapter 2 – Foundation Concepts

40. Vignette 1 (continued)
Chapter 2 – Foundation Concepts

41. Vignette 1 (continued) Semantic Problems:
A college offers many courses and also has several instructors.
The attribute Name occurs twice in the COLLEGE entity type.
Chapter 2 – Foundation Concepts

42. Vignette 1 (continued)
Chapter 2 – Foundation Concepts

43. Vignette 1 (continued) Another semantic problem:
An instructor is capable of teaching a variety of courses, but this is not shown in Figure 2.28b.
Chapter 2 – Foundation Concepts

44. Vignette 1 (continued)
Chapter 2 – Foundation Concepts

45. Vignette 1 (continued) Syntactic problem:
While Figure 2.28c depicts a relationship between courses and instructors, a syntactical rule of the ER modeling grammar is violated. A relationship between attributes of an entity type is not permitted in the grammar.
Chapter 2 – Foundation Concepts

46. Vignette 1 (continued)
Chapter 2 – Foundation Concepts

47. Vignette 1 (continued)
The syntactic error in Figure 2.28c is corrected by modeling COURSE and INSTRUCTOR as independent entity types related to the COLLEGE entity type, and establishing a relationship between the COURSE and INSTRUCTOR entity types.
In addition, since courses are offered every term, Term is modeled as an optional multi-valued attribute of COURSE.
Chapter 2 – Foundation Concepts

48. Vignette 1 (continued)
Chapter 2 – Foundation Concepts

49. Vignette 1 (continued)
Chapter 2 – Foundation Concepts

50. Vignette 1 (continued)
Figure 2.28f is good, but the fact that courses are offered over the four terms, and in each term one or more of the courses are offered, is yet to be incorporated in the ER diagram.
In addition, the business rule that the same course is never taught by more than one instructor in a specific term is not incorporated in the conceptual model either.
Chapter 2 – Foundation Concepts

51. Vignette 1 (continued)
Chapter 2 – Foundation Concepts

52. Vignette 1 (continued)
Note that a syntactic error is created in the attempt to convey the business rule that says the same course is never taught by more than one instructor in a specific term.
It is illegal to express a relationship between the relationship type Assigned and another relationship type Offered.
Chapter 2 – Foundation Concepts

53. Vignette 1 (continued)
Chapter 2 – Foundation Concepts

54. Quick Quiz
What is an object type and how different/similar it is from an object? Give example of an object type and an object which belongs to it.
What is an entity ?
What is a property ? What if an attribute ? WER: Data integrity.
: attribute
What is the mandatory attribute ? Optional attribute ? Give examples for an entity you choose.
ANSWER: Hierarchical.
What is a relationship ? Give an example. ANSWER: Relational.
ANSWER: Entity-Relationship (ER) diagrams.

55. Quick Quiz What is a cardinality constraint ? ANSWER: True SWER: File.
What would be the domain of the attribute County_Name in the state of Texas ? WER: Data integrity.
: attribute
What is the difference between a relationship that exhibits a 1:1 cardinality constraint and a binary relationship which exhibits a 1:N cardinality constraint? ANSWER: Hierarchical.
Why roles names are important to describe the participation of an entity type in a relationship type ?
ANSWER: True
ANSWER: SQL

56. Quick Quiz
Give an example or recursive relationship of 1:1 type, 1:N type.
What is a business rule and how does an analysts /database designer determine business rules in a business ?
What is a value of a model if any ? What database model types do you know ?
What is a conceptual model ? ANSWER: True
SWER: File.