Application of Object Orientation

1. Application of Object Orientation

2. 1.CAD/CAM (Design Engineering) applications

3. 1.CAD/CAM (Design Engineering) applications(cont.) Both versions can have the same interface corresponding to the same commands: • pick up objects • stretch the arm • rotate the hand • …… • OO representation and abstraction closely/directly model such complex, multi-version engineering objects • only operations are relational algebra, using comparators from base types

4. 2.Office Information Systems • Office information systems are inherently complex, dynamic, and goal-oriented (requiring knowledge-level processing and management) • OO Techniques are especially suited to OISs: (i) Office Objects: • forms -> new forms (inheritance between form types) • documents => Chapters =>Sections => paragraphes (part hierarchy: “part inheritance” betweenobject structure) • mailboxes • Editors • spreadsheets <= also potential for exploiting • class inheritance • …

5. 2.Office Information Systems(Cont.) (ii) Office Procedures: -- the routine sequences of operations that are used to manipulate office objects -- often ill-defined and exhibit large number of exceptions; furthermore, they expand in scope and evolve in time => can be supported by object methods! (iii) Knowledge Management -- the organizational regulations, rules -- constraints, migrations, … => call for rule-level processing and management

6. 3. Geographic Information Systems Characterized by - mixture of traditional data with non-traditional data (maps, satellite pictures) • How do we integrate them? • Long fields for nonstandard data such as images: >> Relation can get very large? >> Non-standard size for tuples? - fractals: multiple representations (multi-resolution) due to cartographic generalization (ratio change): • new details become apparent at the larger scale • lines behave as if they have properties of phenomena whose dimension is somewhere between that of a line and an area

7. 3. Geographic Information Systems(cont.) - spatial-temporal query processing: • Queries about line segments >> all segments that intersect a given point or set of points >> all segments that have a given set of endpoints >> segments that intersect a given line segment >> … • Proximity queries >> The nearest line segment to a given point >> All segments within a given distance from a given point (“range/window query”) >> …

8. 3. Geographic Information Systems(cont.) - spatial-temporal query processing: • Queries about line segments >> all segments that intersect a given point or set of points >> all segments that have a given set of endpoints >> segments that intersect a given line segment >> … • Proximity queries >> The nearest line segment to a given point >> All segments within a given distance from a given point (“range/window query”) >> … • Queries involving attributes of line segments >> Given a point, find the closest line segment of a particular type >> Given a point, find all the polygons that are incident on it >> …

9. 3. Geographic Information Systems(cont.) -Special indexing techniques needed: • Need an implicit rather than explicit index >> Cannot foresee all possible queries in advance • New indexing techniques such as: >> Quadtree, >> R-tree >> Pyramid >> …

10. 3. Geographic Information Systems(cont.) -Special operators needed: • Operations on the special indices >> E.g., set operations on Quadtrees (Union, Intersect, etc.) • Operations on Maps >> Spatial join (like map overlay) >> Semi spatial join (“identity overlay”) E.g. Find the soil type in the counties (Impose partition of space induced by County Map on feature values in Soil Map ignoring portion of space induced by the Soil Map) • OO Techniques work better for GIS?!

11. 4. Multimedia Information Systems • Characterized by - mixture of traditional data with media data (image, audio, video, free-text, animation, etc.) • How do we integrate them? - MM objects are complex in structure: • E.g., Video consists of audio and moving/continues images; an MM document can contain everything! • What data model to use?

12. 4. Multimedia Information Systems(Cont.) -spatial-temporal query processing: • Similar to GIS, MM objects are of rich spatial-temporal semantics (think of a video clip!) • Impossible (too costly) to have static, explicit indices on all possible features • Would OO Techniques be useful for MMIS

13. 4. Multimedia Information Systems(Cont.) Answer is YES! Here, we look at MediaView – an object-oriented semantic model for MMIS

14. “Semantic Gap” Problem:

15. Semantic modeling of multimedia -- Why hard?

16. Why hard? (cont.)

17. MediaView – A “Semantic Bridge”

18. Architecture

19. Fundamentals of MediaView • Basic concepts – class vs. MV • View operators – basic functions of MV • View algebra – derivations of MV • Comparison – other “dynamic” object models

20. Basic Concepts Definition 1:Set C as the set of base classes. A base class CiC has a unique class name, a type description, and a set of objects associated with it. The type of Ciisreferred to as type(Ci), which defines a set of properties as the common interface of all the instances of Ci. The set of properties are referred to as properties(Ci), and each property in it can be a value of a simple type, an instance of a certain class, or a method. The set of objects associated with Ci is defined as extent(Ci)= {o | oCi}.

21. Basic Concepts (cont’d) Definition 2:A media view MVi is a virtual class that has a unique view name, a type description, and a set of objects associated with it. The type of MVi is referred to as type(MVi), which defines a set of properties properties (MVi) as the common interface of all its instances. Similarly, a property can be a value of a simple type, an instance of a media view, or a method. The set of objects associated with MVi is defined as extent(MVi)= {o | oMVi}.

22. Basic Concepts (cont’d) So, a media view MVi can be represented as a tuple of 4 elements: MVi= <Mi, Piv, Pim, Ri,> Where: Mi - a set of objects that are included into MVi as its members. Each object o∈Mi belongs to a certain source class, and different members of MVi may belong to different source classes. Piv- a set of view-level properties (attributes and methods) applied on MVi itself. Pim- a set of member-level properties (attributes and methods), which are applied on all the members of MVi. Ri- a set of relationships, and each r∈Ri is in the form of <oj, ok, t>, which denotes a relationship of type t between member oj and ok in MVi.

23. Basic Concepts (cont’d) Definition 3:A base class Ci is defined as a subclass of another base class Cj if and only if the following two conditions hold: (1) properties(Cj) properties(Ci), and (2) extent(Ci) extent(Cj). If Ciis the subclass of Cj, we also say that there is an is-a relationship from Ci to Cj. A base schema (BS) is a directed acylic graph G=(V, E), where V is a finite set of vertices and E is a finite set of edges as a binary relation defined on V×V. Each element in V corresponds to a base class Ci. Each edge in the form of e=<Ci, Cj>E represents an is-a relationship from

24. Basic Concepts (cont’d) Definition 4:A media view MVi is a subview of another media view MVj (or there is an is-a relationship from MVi to MVj) if and only if properties(MVj) properties(MVi) and extent(MVi) extent(MVj). A view schema (VS) is a directed acylic graph G={V, E}, where a vertex in V corresponds to a media view MVi, and an edge e=<MVi,MVj>E represents an is-a relationship from MVi to MVj (or MVi is a subview of MVj).

25. Basic Concepts (cont’d) An example…

26. Basic Concepts (cont’d) Semantics-based data reorganization via media views

27. Basic Concepts (cont’d) Definition 5:The semantic graph (SG) is an undirected graph G={V, E}, where V is a finite set of vertices and E is a finite set of edges. Each element ViV corresponds to a multimedia object Oi in the database. E is a ternary relation defined on V×V×N. Each e=<Vi,Vj, n>E represents a semantic link of degree n between object Oi and Oj, where n is the number of media views to which both objects belong. We define n as the correlation factor between Oi and Oj. Definition 6:The correlation matrixM=[Mij] is an adjacency matrix of the semantic graph. Specifically, each element Mijcontains the correlation factor between Oi and Oj, with all the diagonal elements set to zero.

28. Basic Concepts (cont’d) Semantic Graph Model

29. View Operators • A set of operators that take media views and view instances as operands. • Our intension is not to come up with a complete set of operators, but to focus on those that are indispensable in supporting queries and navigation over multimedia objects.

30. View Operators

31. View Operators (cont’d)

32. View Algebra • Functions -- derivation of new MVs from existing MVs Heuristic Enumeration • Blind enumeration • Content-based enumeration • Semantics-based enumeration

33. View Algebra

34. View Algebra

35. Comparison (vs. class)

36. Comparison (vs. class)

37. Comparison (vs. class)

38. 5. Internet/Web Databases • Sometime also called as “Virtual Databases (VDBs)” • VDBs can make the WWW behave as an extension of an enterprise’s existing DBMSs • VDB information can be characterized by: • all the requirements imposed by MISs, plus extra… • Large numbers of data sources which are autonomous (without centralized control) • Data sources can have a mixture of structured data and semi-structured data (e.g., HTML pages) • Dynamism in almost every aspect: • Content • Structure • Links • Formats • …

39. 5. Internet/Web Databases(Cont’) • An increasingly hot-area, with a lot of commercial potentials from the E-commerce application’s point of view But, is OO the best technology for VDBs?