1. Data Modeling [Comparison of data modeling techniques ]By
Renjini
Sindhuri

2. Contents Introduction E-R modeling Peter Chen Information Engineering
Barkers Notation
IDEFIX
UML modeling
XML modeling
X- Entity modeling
XUML
Conclusion

3. Introduction
Data modeling is the act of exploring data oriented structures.
Examines and compares different data modeling techniques
In the data modeling techniques we have traditional modeling and object oriented modeling of data

4. E-R modeling
It is a conceptual data model that views the real world as consisting of entities and relationships
It is used to transform relational tables that are easy to understand that enables easy communication with the end user
Peter –Chen developed E-R model

5. Peter –Chen notation
Entities are represented in the squared cornered and circles as attributes
Many –Many relationships can be represented without associative entity
Relationship itself has attributes and are considered as objects
It failed to represent unique identifier

6. Peter Chen’s Model

7. Information Engineering model
Developed by Clive Finkelstein
Entities are represented in the squared cornered and attributes are not shown at all they are shown in a separate list called entity list
Relationships like mandatory 1 and many can be represented
Unique identifiers are not represented

8. Information Engineering model diagram

9. Barkers Notation Adopted by Oracle corporation for its CASE method
Entities can be represented by round cornered rectangle
Same entity can be represented for role an interaction or another kind of association
Relationship names are prepositions and not verbs
Unique identifiers can be represented by hash marks next to the attribute

10. Barkers Notation diagram

11. IDEFIX Notation
It is a modeling technique that is used by many branches of the United States Federal government
A relationship name is a verb
IDEFIX shows subtypes as separate entity boxes
IDEFIX permits multiple inheritance and multiple type hierarchies

12. IDEFIX diagram

13. UML UML is an object modeling technique
It models object classes instead of entities
In the object oriented world the relationships are called as associations
Cardinality and optionality in UML is conveyed by characters or numbers
Express in the form of more complex upper and lower limits
UML introduces a small flag that includes text describing any business rules

14. UML diagram

15. XML Notation
Describing data and interchanging structured and unstructured data on the Internet
It is a universal language of data on web
XML tags are used to create data structures
XML documents have been widely used for interchanging data between heterogeneous systems.

16. XML notation An example of XML notation

17. X-Entity model
Conceptual model of XML uses X entity model in order to represent additional features
The entity can be denoted by ‘E’
({A1,….An},{R1,…Rm},{D1,….Dk})
Each attribute A is associated with a domain Dom(Ai)
Which specifies its value set
Cardinality is denoted by Card(Ai)=(min,max)

18. X entity model diagram

19. XUML XUML comprises the characteristics of XML and UML2.
It is used to express the containment semantics more explicitly
Supporting the concept of Business Components
Specifying the data dependencies in multiple context

20. XUML diagram
UML and XUML model of a book store

21. Comparison of data modeling techniques
S.No
Modeling Technique
Peter Chen
Information Engineering
IDEFIX
Richard Barker’s notation
UML 1.
Entities
squared cornered and circles as attributes
Squared cornered, attributes are not shown at all.
Round or square cornered rectangle
Round cornered rectangle
Models object classes 2.
Relationship
Nouns. So the relationships can be represent as objects and has attributes
Verbs
Verb or verb phrase
Preposition not verb
Associations 3.
Constraints between relationships
Failed to represent the constraints directly exclusive or)
Can represent
Constraints exclusive or ,inclusive
Cannot represent
Constraints exclusive or)
Constraints exclusive or )

22. Comparison of Data modeling techniques
S.No
Modeling Technique
Peter Chen
Information Engineering
IDEFIX
Richard Barker’s notation
UML 4.
Cardinality
Many to Many relationships can be represented between the entities without the associative entity
Can represent
Can represent in different ways
Can represent zero or more ,atleast
at least one
up to many,
up to one
relationships
express more complex upper limits, zero, 3, 6-7, or 9 5.
Sub types/ Super Types
Cannot represent the sub types and super type
sub-types can be represented inside their super-type box
Sub types can be represented as separate entity boxes separate from its super type. 6.
Unique Identifier
Cannot represent
Represented in the form of primary key
Represented in the form of hash next to the attribute

23. Comparison of Data Modeling techniques
S.No
Modeling Technique
Peter Chen
Information Engineering
IDEFIX
Richard Barker’s notation
UML 7.
Aggregation
Cannot represent
Can represent only binary aggregations 8.
Business Rules / Components
Cannot Represent
Can Represent

24. Comparison of Data Modeling techniques
S.No
Modeling Technique
Peter Chen
Information Engineering
IDEFIX
Richard Barker’s notation
UML 9.
Aesthetic Simplicity Score
High
Medium
Low
10.
Completeness Score
medium
11.
Language Notation Score
low

25. Advantages of XUML
XUML can express the containment semantics more accurately.
Support the concept of Business Component.
Can specify the data dependencies in
multiple context.

26. Contd.. XUML is more expressive, precise and understandable.
More rigorous and accurate.

27. Conclusion
By comparing the aesthetic simplicity, completeness, language notation (relationship) Mr. Barker's notation is favorable for requirement analysis model
XML is used in recent trends it follows a standard format for representing structured and semi structured data on web
X-Entity model has the advantages of both XML schemas and extends the ER model so that it can explicitly represent important features of XML schemas
The distinctive features of XUML made this technique of data modeling the latest trend for conceptual modeling of data.

28. References
1. Conceptual Modeling of XML schemas, Bernadette Farias Losio,Ana Carolina Salgado , Year: 2003,Publisher: ACM
2. XML conceptual modeling with XUML, HongXing Liu HuaZhong University of Science and Technology, P. R. China, YanSheng Lu HuaZhong University of Science and Technology, P. R. China,Qing Yang Wuhan Uni Pages: 973 – 976, Year of Publication: 2006, Publisher: ACM Press
3. PETER PIN-SHAN CHEN, “The Entity Relationship Model-Toward a Unified View of Data” , Massachusetts Institute of Technology, ACM Transactions on Data base System Volume1, Issue 1,Publisher-ACM
4. Data modeling in the understanding database course: adding UML and XML modeling to the traditional content. Journal of Computing Sciences in Colleges, Volume 17, Issue 5 (April 2002)

29. References 5. Data Modeling101.
6.A comparison of Data Modeling ,David C Hay,Essential Strategies
Inc,October 1999.