Download OIM - West Virginia University

MDC Open Information Model
West Virginia University
CS486 Presentation
Feb 18, 2000
Lijian Liu
[email protected]
(OIM: http://www.mdcinfo.com/OIM/index.html)
What is Meta Data?
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Meta Data is descriptive information
about the structure and meaning of
data and of the applications and
processes that manipulate data.
Technical Meta Data
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database structures
installed applications
server systems
and so forth.
Business Meta Data
provides explanations of business
objects and processes to:
 easy browsing
 easy navigation
 simple querying of data
The Open Information
Model
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a set of metadata specifications to
facilitate sharing and reuse in the
application development and data
warehousing domains.
Why need OIM?
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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.
Why need OIM? (continued)
End-users suffer:
 inaccessible meta data locked into
individual tools.
 incompatible meta data locked into
individual tools.
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.
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 easyto-extend subject areas.
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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

Sub models of OIM
Analysis and Design Model
 Object and Component Model
 Database and Data Warehousing
Model
 Knowledge Management Model
 Business Engineering Model

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.
Analysis and Design Model
in OIM (continued)
Covers the domain of objectoriented modeling and design of
software systems.
 Provides concepts to describe
problems and solutions throughout
the complete software life-cycle.

Object and Component
Model in OIM
Why need this model?
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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.
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
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:
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• Java
• Smalltalk
• C++
Database and Data
Warehousing Model in OIM
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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.
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.
Database and Data Warehousing
Model in OIM (continued)

OLAP schema package captures
descriptions of multi-dimensional
(OLAP) data cubes used in decision
support systems.
Database and Data Warehousing
Model in OIM (continued)
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Data Transformations package
captures information about data
transformations used in moving data
from production databases into a
data warehouse or data mart.
Database and Data Warehousing
Model in OIM (continued)
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Record-Oriented Database Schema
package describes data maintained
in the files, legacy databases, and
so forth, of an enterprise.
Database and Data Warehousing
Model in OIM (continued)
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Report Definitions package
represents information necessary for
data reporting tools and their
relationships to the systems they
report on.
Knowledge management
Model in OIM
Is the integrated and collaborative process
of information asset
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creation,
capture,
organization,
access,
and usage.
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.
Knowledge management
Model in OIM (continued)
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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?
Knowledge management
Model in OIM (continued)
Information Directory extensions
 Semantic Definition extensions
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Knowledge management
Model in OIM (continued)
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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.
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.
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Business Engineering Model
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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.
Business Engineering Model
(continued)
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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 semiautomate the process.
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
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.
Business Engineering Model
(continued)
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Business Goals
Organizations
Business Processes
Business Rules
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.
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.
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.
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.
Thank you!
More details:

http://www.mdcinfo.com/OIM/index.html