Topics

1. Topics • Introduction to information Space • The concept of meta-object and meta-model • Introduction to Perspective, Classification and “The Tyranny of Words” • Basic meta-object inventory • Containers of normalized Knowledge • Also the basic components from which more complex knowledge is configured

2. BEHAVIOR • RESPONSE TO A GIVEN STIMULUS • HIT METAL SHEET: it bends • HIT GLASS SHEET: it breaks • INVOLVES OBJECTS, EVENTS, CHANGE • CHANGE INVOLVES TIME • TECHNIQUES FOR REPRESENTING BEHAVIOR • BLACK BOX • “INPUT-OUTPUT” VIEW • NODE BRANCH • “ERD TYPE” TECHNIQUES

3. V1 V1 V1 V2 V2 V2 V3 V3 V3 V4 V4 V4 DISCRETE CHANGE • ATTRIBUTE VALUES & RELATIONSHIPS CHANGE IN RESPONSE TO DISCRETE EVENTS • CONSTRAINTS ON ENTITIES CHANGE IN RESPONSE TO DISCRETE EVENTS Time slice (a single state of an instance of an object) Past Instance Time AN OBJECT CLASS IS ALSO AN INSTANCE OF AN OBJECT Time Present • What properties would the class normalize? OBJECT CLASS

4. V1 V1 V1 V2 V2 V2 V3 V3 V3 V4 V4 V4 DISCRETE CHANGE Past Instance Time Effect of hammer strike 1 Effect of hammer strike 2 Effect of hammer strike 3 Present OBJECT CLASS

5. Instance 1/8” 1/4” 1/2” red W W S STATE OF AN OBJECT INSTANCE PROPERTIES OF OBJECT CLASS Thickness Object Instances (Individual glass panes) Instance Instance Color Status: Shattered (S) or Whole (W) blue green Effect of hammer strike 1 Effect of hammer strike 2 Effect of hammer strike 3 Effect of Hammer Strike: Change status of “Whole” glass to “Shattered” OBJECT CLASS (Glass Pane)

6. State Chart PANE Material Wholeness Color Thickness Glass Whole Red Hammer Strike (Whole) Blue Shattered

7. State Chart PANE Material Wholeness Color Thickness Glass Whole Red X Hammer Strike X Blue Broken Shattered Cracked

8. State of a System STATE OF INVENTORY SYSTEM

9. State Space Location of 1/4 inch., 11/2 lb pane in this state space 1/2 inch 1/4 inch THICKNESS 1/8 inch 1 lb 11/2lb 2 lb WEIGHT

10. STATE SPACE IS COLORED BLUE State Space with Ordinal axis Maximum Car Size Infiniti Honda Civic CAR TYPE (Sequence does not matter. Cars can be arranged in any order along this axis) CAR SIZE Minimum Car Size Ford Explorer Second Most Liked Second Most Liked Most Liked Most Liked Least Liked Least Liked JANE’S PREFERENCE JANE’S PREFERENCE (Sequence matters, but not the distance between the broken lines on this axis) A. Example of State Space when one axis maps to a quantitative domain and the other to a qualitative domain (Disjoint Lines) B. Example of State Space when both axes map to qualitative domains (Disjoint Points)

11. THREE DIMENSIONAL STATE SPACE Location in state space of an individual of a particular age, height and weight Height Weight Age • APPEARANCE OF STATE SPACE LOOK IF WE DID NOT CARE ABOUT THE AGE OF A PERSON? • APPEARANCE OF STATE SPACE LOOK IF WE RESTRICTED THE AGE OF “PERSON” TO A SINGLE VALUE?

12. TRAJECTORY IN STATE SPACE The cross section of the river (instance of an object) moves along this trajectory at a certain speed Depth Width

13. TRAJECTORY IN STATE SPACE Location of a cross section of a river in state space at a particular time Depth The cross section of the river (instance of an object) moves along this trajectory at a certain speed Time Depth Width Width The object’s trajectory can be reinterpreted as a region in State Space (a static line in this case) when the time axis is added to its State Space [When only discrete changes are considered, the region consists of a sequence of discrete points ( ) on the trajectory] An object will move along a trajectory in State Space as its state changes with the passage of time

14. TRAJECTORY IN STATE SPACE Location of the firm in state space at a Income particular time The firm (instance of an object) moves along this trajectory at a certain speed Time Income Borrowing Borrowing The object’s trajectory can be reinterpreted as a region in State Space (a line in this case) when the time axis is added to its State Space [When only discrete changes are considered, the region consists of a sequence of discrete points ( ) on the trajectory] An object will move along a trajectory in State Space as its state changes with the passage of time

15. Instance Instance Instance V1 V1 V1 Time Time Time V2 V2 V2 V3 V3 V3 E1 E1 E1 OBJECT CLASS OBJECT • OBJECT INSTANCE = SET OF VARIABLES • A single occurrence • Based on business meaning • Person, place, category, concept or event relevant to the business • PROPERTY OF AN OBJECT (EXPANDED DEFINITION OF DATA ATTRIBUTES) • A single meaning • Data Attribute/value • State/Relationship • Effect of event • OBJECT CLASS = SET OF LIKE INSTANCES • TIME DIMENSION INTRINSIC TO BEHAVIOR OF THE OBJECT/CHANGES TO SPECIFIC PROPERTIES

16. A • B C C • A SUBTYPING GAS POISON Age Height Weight PERSON A B-A Subtype of B set difference set intersection Subtype of A-B POISON GAS (Inherited) Age Height Weight MALE PERSON subset of A C • A implies all members of C are also members of A, but not vice-versa. • Inheritance (Data, behavior & constraints) • A • B is the set of objects that are members of both A and B. • Multiple inheritance

17. PARTITIONING CRITERIA Irreducible fact: Partitioning Criterion: Our ownership of organizations Irreducible fact: Partitioning Criterion: Permanence of organizations SUB- TYPE SUB- TYPE EXHAUSTIVITY SUB- TYPE SUB- TYPE SUB- TYPE Irreducible fact: Subtypes are not exhaustively defined in this partition: Organizations in which we have minority shares are not shown (Non-exhaustive Partition) Irreducible fact: Subtypes are exhaustively defined in partition (Exhaustive Partition) e.g., Organization OBJECT GENERALIZATION & ROLE PLAYING e.g., Organizations we own fully partitioned by partitioned by OBJECT partition of partition of (eg: organization) .......PARTITION ....PARTITION e.g., Organizations in which we own the majority of shares e.g., Temporary organization (e.g.: Task force, Project team etc.) * e.g., Permanent. Organization (e.g.: Corporation, human resources department etc.) e.g., Organization we do not own. Non-exhaustive Partition Exhaustive Partition PROPERTIES OF PARTITIONS

18. CONSTRAINTS BETWEEN SUBTYPES OBJECT OBJECT Every instance of subtype A must also be an instance of subtype B (not necessarily vice-versa) PARTITION PARTITION PARTITION PARTITION Every instance of subtype A must also be an instance of subtype B (not necessarily vice-versa) SUB- TYPE A SUB- TYPE B SUB- TYPE A SUB- TYPE B Every instance of subtype B must also be an instance of subtype A (not necessarily vice-versa) Another subtype Another subtype Another subtype Another subtype Every instance in one subtype must be in the other subtype but not necessarily vice-versa Every instance in one subtype must be in the other subtype and vice-versa, I.e.,the two sets are equal OBJECT PARTITION An instance of subtype A must not be an instance of subtype B (mutually exclusive sets) PARTITION SUB- TYPE A SUB- TYPE B X Another subtype Another subtype Subtypes A and B are mutually exclusive even though they are in different partitions

19. Subtyping Criteria SUBTYPING CRITERIA Attributes Relationships Constraints Initial Conditions (Default State) Effects Constraints on Attribute Values Constraints on Relationships Constraints on History Constraints on Initial Conditions Guard Conditions

20. THE PRINCIPLE OF SUBTYPING BY ADDING INFORMATION INCLUSION INHERITANCE VARIATION INHERITANCE

21. POLYMORPHISM • First identified by Christopher Strachey in 1967. • Context specific behavior normalized by generalizing or subtyping objects. • For example, the exact meaning of length depends on whether the object in question is a word or a room. “Word” and “Room” are parameters of length that fixes its meaning and properties more precisely than the generic concept of length: • The length of a word is the number of letters in it, which can only be an integer • The length of a room may be any real number. E.G. PERSON E.G. EVENT EMPLOYEE PARENT CUSTOMER ETC. TASK MEETING BIRTHDAY ETC.. Polymorphism is the quality of appearing in several apparently different forms. E.G. INFORMATION E.G. COUNT RULE GUIDELINE DESCRIPTION ETC. BY TWOS BY ONES BY THREES ETC. E.G. MOVE E.G. ENERGY RUN HOP ROLL ETC. LIGHT HEAT KINETIC ETC..

22. Adaptation through Inclusion Polymorphism parameters OBJECT • Object=Frog; Move=Hop • Object=Wheel; Move=Roll • Object may be Frog or Wheel • Move may be Hop or Roll

23. Kinds of Polymorphism

24. (See endnote on kinds of inheritance in your text book) KINDS OF INHERITANCE • Subtype Inheritance: Mutually exclusive subtypes inherit behavior of the parent class • Extension Inheritance: State space of the subtype extends the state space of the parent into additional dimensions (has additional properties) • Restriction Inheritance: Constraint is added to parent to restrict its state space in the subtype • Lawful vs. Conceivable state space • View Inheritance: Object is an instance of two or more different subtypes simultaneously and inherits properties and restrictions of all. Eg: • Parent and Employee are two roles (subtypes/polymorphisms) of Person • An individual may simultaneously have a pay rate and children if he or she is an employee and a parent at the same time

25. The Problem of Perspective What you see or think depends on how you see or think GOOD BAD WITHOUT THE UNIVERSAL PERSPECTIVE THERE WOULD BE NO SHARED UNDERSTANDING DOES A UNIVERSAL PERSPECTIVE EXIST ? BAD GOOD

26. Information and business services hub for semantic interoperability • Remember the Principle of Parsimony • Generalized Classes and Interactions; Information Sparse • Remember the principle of subtyping by adding information Universal Perspective

27. TRUTH DEPENDS ON CONTEXT • CONTEXT ADDS INFORMATION • PERSPECTIVE PROVIDES INFORMATION • IS A KIND OF OBJECT CONTEXT 1 GOOD BAD CONTEXT 2 BAD GOOD

28. THE TYRANNY OF WORDS OBJECT 2 (meaning) OBJECT 1 (meaning) NAME (synonym) NAME (synonym) NAME (synonym) NAME (synonym & homonym) NAME (synonym) OBJECT 1 (meaning) OBJECT 2 (meaning) NAME (synonym) NAME (synonym) NAME (synonym) NAME (synonym) Synonyms and Homonyms NAME (homonym) NAME (homonym)

29. Primary Name vs Alias PERSPECTIVE 3 ALIAS (synonym) ALIAS (synonym) PERSPECTIVE 1 PERSPECTIVE 2 ALIAS (synonym) ALIAS (synonym & homonym) ALIAS (synonym) OBJECT 1 PRIMARY NAME OBJECT 2 PRIMARY NAME ALIAS (synonym) ALIAS (synonym) ALIAS (synonym) ALIAS (synonym)

30. Aliases and Perspectives Each concept must have a name, and may have many Each name must be in a a context and may be the same in many contexts Each perspective must be held by at least one person or organization and may be held by many CONCEPT (object) PERSON/ or ORGANIZATION (Key stake holders: Persons and Groups) NAME (synonyms, i.e., Aliases) PERSPECTIVE or CONTEXT (Model) Each name must be the name of at least one object, perhaps many Each perspective must have at least one named concept, probably more Each person or organization must hold at least one perspective, perhaps more

31. The Metamodel of Object

33. What We Have Covered • The concepts of object class and object instance • The fundamental containers of reusable knowledge • Also the fundamental meta-component from which other components of knowledge are forged • The concept of meta-object and meta-model • State and state space • Subtyping Partitions and Polymorphism • Shared Understanding, Perspective, Classification and “The Tyranny of Words” • A basic meta-object inventory • Containers of normalized Knowledge • Also the basic components from which more complex knowledge is configured