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Presentation. On Conceptual Micro-object Modeling. Presented by Neelima Voleti. On Conceptual Micro object Modeling. Author (s): Cecil Eng Huang Chua,  Roger H L Chiang,  Ee-Peng Lim Publication title: Journal of Database Management. Hershey: Jul-Sep 2002. Vol. 13, Issue.  3;  pg. 1, 16 pgs.

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  1. Presentation On Conceptual Micro-object Modeling

  2. Presented by Neelima Voleti

  3. On Conceptual Micro object Modeling Author (s): Cecil Eng Huang Chua,  Roger H L Chiang,  Ee-Peng Lim Publication title: Journal of Database Management. Hershey: Jul-Sep 2002. Vol. 13, Issue.  3;  pg. 1, 16 pgs

  4. Introduction Fundamental modeling issues: • Micro object modeling • Atomicity of Micro-Objects • Best Representation • Modeling Semi-Structured data

  5. Introduction Conceptual Micro-Object Model (CMoM), considers the attribute as the foundation of data modeling. Other constructs such as the Conceptual Data Type Primitive (CDTP) and Attribute Group (AG) are developed to model the constituent components of attributes and objects that can be formed from attributes respectively.

  6. Conceptual micro-object model parallels the structure of matter. Sub-Atomic constructs- Values and constructs Atomic micro-construct- Attribute Molecular micro-objects- Attribute Groups Attribute - values + Restricted context (RC) Attribute Groups- Bond of attributes. Macro-objects- Attributes +Attribute groups. Conceptual Micro-Object Model

  7. Foundation of CMoM. Role of values and context in attribute semantics. Subatomic constructs 1. Conceptual data type primitive (CDTP) 2. Restricted context (RC) 3. Bonded conceptual data type primitive (BCDTP) 4. Bonded Restricted context (BRC) Subatomic Constructs

  8. Restricted Contexts (RC) • Restricted context – restricted domains and functions of CDTP. e.g. : Salary_type RC restricts number to functions such as Annual bonus(),Raise(). Restricts non negative valued numbers.

  9. Restricted Contexts (RC) • Duplicate RCs and CDTPs cannot exist in a bond e.g.: {course type1,course type2,….course_typen} is redundancy and not a bond.{day_type , month_type }can be a bond • Bonding between CDTP and RC ,CDTP and BCDTP, RC and BRC.

  10. BCDTP and BRC • Functionality : e.g.: day_month _type bond with function is_holiday() results December 25th. Day_type and month_type separately are not accepted on functions. • BRC extend context of attribute groups. • Difference between attribute groups and composite attributes.

  11. Conceptual data type primitive (CDTP) • CDTP , A pair of domain I.e., set of elements and function I.e. mapping from one domain to another.

  12. Attributes The sole atomic construct ,attribute is instantiated by values associated with RC context . Attribute is a 4-tuple consisting of N,RC,V,R A= (N,RC,V,R).

  13. Attributes • Attribute Values represented as order sets for three reasons : • Value Repetition: Most attribute values are not unique .Thus attribute values can only be represented using a set of theoretic constructs. • Integration of attributes : e.g.: Individually ‘Salary’ and ‘Employee_name’ has no information about each other. But at molecular and macro level a relationship is enabled.

  14. Attributes • Values cannot contain I-marks . • Modeling of natural order : In traditional data models data is modeled as non atomic attribute or composite attribute. In CMoM it is modeled as attribute word, with RC word type. e.g.: ‘Mary ran quickly’.

  15. Attributes • Semantics of sentence are expressed through ordering. e.g. : Changes in values of words when ‘john and’ was added to ‘Mary ran quickly’ in composite attribute representation and CMoM.

  16. Attribute Groups • Aggregation of attributes that are inter-related with same number of values. • Attribute group – 4 tuple, AG {N, BRC,S,R}.

  17. Rigorous Attribute Modeling • Essentiality of Rigorous representation attributes. • CMoM enhancing the rigor of attribute modeling. • Difference in representing an attribute e.g.: address by Traditional databases and CMOM.

  18. Rigorous Attribute Modeling • Top-Down data modeling approach : An ‘address’ attribute is represented in three ways. a. Single non-atomic attribute b. A large composite attribute. c. Using multiple sub classes.

  19. Rigorous Attribute Modeling • CMoM approach: CMoM focus on the functionality of micro-objects. e.g. : <address_subcomponent = <value>

  20. Complimentarity of CMoM over Macro-Object data models • Resolving model integration Issues like 1. Entity-Relationship (ER) Model: Integrating CMoM with ER Model CMoM provides mechanisms to identify redundancy in ER diagrams . • Relational Data Model: CMoM enhances RD model in four ways- 1. Identifying redundancy within relations 2. CMoM determines Atomicity of attributes, models molecular micro-objects and atomizes non atomic micro-objects.

  21. Complimentarity of CMoM over Macro-Object data models 3. Semi-structured data can me modeled. 4. Subclassed relations are recognized as superior to I-marked relations. • Object-Oriented Models: CMoM provides mechanisms for defining many object-oriented properties like encapsulation,inheritence and aggregation.

  22. Conclusion CMoM for modeling micro-objects. CMoM views data modeling from the perspective of independent attributes. CMoM , an extention , enhancement and complement to traditional databases. CMoM focuses on Rigorous definition of micro-objects. CMoM enhances data modeling in three ways.

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