1. MDC Open Information Model West Virginia University CS486 Presentation Feb 18, 2000 Lijian Liu lliu@csee.wvu.edu (OIM: http://www.mdcinfo.com/OIM/index.html)

2. What is Meta Data? Meta Data is descriptive information about the structure and meaning of data and of the applications and processes that manipulate data.

3. Technical Meta Data database structures installed applications server systems and so forth.

4. Business Meta Data provides explanations of business objects and processes to : easy browsing easy navigation simple querying of data

5. The Open Information Model a set of metadata specifications to facilitate sharing and reuse in the application development and data warehousing domains.

6. Why need OIM? Enterprise data, once viewed as merely operational or tactical in nature, is now being used for strategic decision-making at every enterprise business level. Meta data, or information about data, has become the critical enabler for the integrated management of the information assets of an enterprise.

7. Why need OIM? (continued) End-users suffer: inaccessible meta data locked into individual tools. incompatible meta data locked into individual tools.

8. Why need OIM? (continued)  No single tool covers all information processing requirements.  Not all components of an integrated tool set may provide the required functionality or performance.  Organizations may wish or may be required to track meta data for their OLTP or data warehousing environment to make it auditable.

9. OIM Purpose To support tool interoperability across technologies and companies via a shared information model. OIM is described in UML (Unified Modeling Language) and is organized in easy-reuse and easy- to-extend subject areas.

10. Base of OIM data model The Unified Modeling Language (UML) as the formal specification language for OIM The eXtensible Markup Language (XML) as the interchange format for OIM The Structured Query Language(SQL) as the query language for OIM

11. Sub models of OIM Analysis and Design Model Object and Component Model Database and Data Warehousing Model Knowledge Management Model Business Engineering Model

12. Analysis and Design Model in OIM Why need this model?  During each step of the software design, development, and deployment life-cycle, software professionals use analysis and design tools for many disparate reasons: as input tools for documentation purposes as analysis and result-validation tools.  This require that tools are tightly integrated with all the other applications either through meta data interchange or by sharing a common repository.

13. Analysis and Design Model in OIM (continued) Covers the domain of object- oriented modeling and design of software systems. Provides concepts to describe problems and solutions throughout the complete software life-cycle.

14. Object and Component Model in OIM Why need this model? Component-based development is the task of building families of product from kits of interoperable components. Component sharing and reuse has become strategic for enterprises in order to reduce cost and time to deployment. Reuse and sharing requires tracking meta data throughout the whole life-cycle of a component from specification through design and subsequent enhancements.

15. Object and Component Model in OIM (continued) Defines component as "a software package that offers services through interfaces.“ Covers three distinct layers: Specification Implementation (Isn’t defined now) Executable

16. Object and Component Model in OIM (continued) Intends to cover the various aspects of a component implementation, but will not cover the specifics of any particular programming language. A component implementation may be realized using: Java Smalltalk C++

17. Database and Data Warehousing Model in OIM Provides meta data concepts for schema management for database design, schema reuse, and data warehousing. The database part of the model includes concepts found in standard SQL data definitions and similar types of formatted data models. The model focuses on logical databases concepts. It also includes some physical database concepts.

18. Database and Data Warehousing Model in OIM (continued) Data Warehousing-specific packages extend the database schema model in several important directions in order to support data marts and data warehouse applications.

19. Database and Data Warehousing Model in OIM (continued) OLAP schema package captures descriptions of multi-dimensional (OLAP) data cubes used in decision support systems.

20. Database and Data Warehousing Model in OIM (continued) Data Transformations package captures information about data transformations used in moving data from production databases into a data warehouse or data mart.

21. Database and Data Warehousing Model in OIM (continued) Record-Oriented Database Schema package describes data maintained in the files, legacy databases, and so forth, of an enterprise.

22. Database and Data Warehousing Model in OIM (continued) Report Definitions package represents information necessary for data reporting tools and their relationships to the systems they report on.

23. Knowledge management Model in OIM Is the integrated and collaborative process of information asset creation, capture, organization, access, and usage.

24. Knowledge management Model in OIM (continued) Is a centralized source for locating information contained in: documents, spreadsheets, data marts and warehouses, OLTP databases, and group-wise applications.

25. Knowledge management Model in OIM (continued) A combination of technical and business meta data describes what information is available, and provides an context for its understanding: Who gets what information when from where?

26. Knowledge management Model in OIM (continued) Information Directory extensions Semantic Definition extensions

27. Knowledge management Model in OIM (continued) Information Directory extensions provides meta data types to define a controlled vocabulary to classify business information. Allows one to define subject and topic terms and a hierarchy or classification tree of categories. Information objects, such as database tables, queries, reports, and documents, can appear in multiple categories, such as corporate sales, product marketing and finance. The vocabulary of controlled topics and subjects, together with uncontrolled terms, can be used to search the information maintained by the information directory.

28. Knowledge management Model in OIM (continued) Semantic Definition extensions map business terms to the structures of the underlying storage technology. For example, business terms to relational tables and fields. Users are able to extract information from data warehouses using English sentences.

29. Business Engineering Model NOTE: The Meta Data Coalition is currently developing a Business Engineering Model. This model is currently under development by the Technical Subcommittee in preparation for a review by MDC Members.

30. Business Engineering Model (continued) To develop a blueprint depicting how a company or a part of a company operates or should operate. A business is defined as a set of cooperative activities performed by the people or machines or both. Formally and accurately documenting the structure and processes of a business is necessary not only to re-engineer the structure and processes but also to automate or semi- automate the process.

31. Business Engineering Model (continued) This model supports: Modeling tools used by analysts to describe and document the structure, processes, and rules of a business. Process libraries helping to organize and identify templates for the organization and processes of a business. Process animation and simulation to visualize and validate the effects on a business

32. Business Engineering Model (continued) This model supports: (continued) Implementation by workflow management tools that track the business process. Analysis tools that monitor execution and effectiveness of a business process. Interchange of business modeling information between tools and ERP (Enterprise Resource Planning) systems.

33. Business Engineering Model (continued) Business Goals Organizations Business Processes Business Rules

34. Business Engineering Model (continued) Business Goals: Capture information such as: the goals of a business, importance and priorities, how goals are related, what steps must be taken to achieve the goals how to measure the success or failure of the steps taken.

35. Business Engineering Model (continued) Organizations Describes the actors and resources of a business and their relationships. It captures who should perform what activity, the necessary skills, the reporting structure, and responsibility structure.

36. Business Engineering Model (continued) Business Processes Captures the conditions and constraints a business operates under. Captures the business terminology, how facts relate individual business terms, and how individual rules are related.

37. Business Engineering Model (continued) Business Rules Captures business activities and processes and their interrelationships. Shows the conditions and transitions for each activity as well the necessary resources and the flow of information.

38. Thank you! More details: http://www.mdcinfo.com/OIM/index.html