This document provides an overview of business ontology and how it can be used to integrate knowledge for applications. It discusses how business ontology can be used as an approach to model business entities, their properties and relationships to better organize information across different systems. The document is part of a set of presentations on business ontology that cover an overview, how to create a business ontology using a case study, and examples of semantic technology and reference cases.

1. Business ontology – approach to
integrate knowledge for
applications.
Set of presentations:
1. Overview (why, what, how)
2. Creating a business ontology (data modeling
case study)
3. Semantic technology & Reference cases
© 2011 Tieto Corporation

2. Business ontology
1/3 - Overview
Business ontology – approach to
integrate knowledge for applications
© 2011 Tieto Corporation
heimo hanninen
Tieto,
heimo.hanninen@tieto.com

3. What is ontology in IT system
scope?
-metadata
Enterprise Architect Dmitry Bogachev – Topic Maps 2007
© 2011 Tieto Corporation

4. © 2011 Tieto Corporation
matters
Why ontology

5. Why should we care about
organising information?
Our brain will not get any bigger – amount of information will.
5 © 2011 Tieto Corporation 2011-02-09

6. Corporate information in silos –
how to integrate the data?
Partners R&D Production ICT HR Sales &
Marketing
6 © 2011 Tieto Corporation 2011-05-11

7. Information is Constantly in Motion –
- a need for better management
More than 60% of CEOs Only one-third of CFOs
believe their business needs to believe that the information
access and understand information is easy to use, tailored,
faster to make swift decisions cost-effective or integrated
Transactions
Employees
Customers
85% of information 30–50% of design time
is unstructured Products Partners is copy management
Databases
Organizations
17% of IT budgets E-mails
Financials
Web 30% of people’s time
for storage hardware content
is spent searching for
and storage management Documents relevant information
software and people
Reports Media
40% of IT budgets 37% growth of disk storage
may be spent on integration in 2005
Source: IBM Corporation Hänninen
© 2011 Tieto
Heimo

8. Information with metadata • Human likes
descriptions
• Data about the content
• Suitable metadata for each usage
• Computer likes identifiers
© 2011 Tieto Corporation

9. Information without metadata
• Have to open all containers to know the content…
© 2011 Tieto Corporation Heimo Hänninen / 14.11.2007

10. Some jada jada
on ontology
Semantic web approach
© 2011 Tieto Corporation

11. Triangle of meaning: the way we think
and communicate with symbols
CAR
• “concept”
Subjective understanding of object
Heimo
http://psi.tieto.com/taxonomy/
resource/car
<label xml:lang=“se” >
bil</label>
<label xml:lang=“fi” >
• “referent” • “symbol” auto</label>
Real world object Names we give
11 © 2011 Tieto Corporation 2011-06-17

12. Triangle of meaning: different context
 different meaning
CAR
• “concept”
Subjective understanding of object
Nico Rosberg
http://psi.tieto.com/taxonomy/
resource/car
<label xml:lang=“en” >
racing car</label>
<label xml:lang=“fi” >
• “referent” • “symbol” kilpaauto</label>
Real world object Names we give
12 © 2011 Tieto Corporation 2011-06-17

13. Levels of Conceptual
Interoperability Model
Ref. Virginia Modeling Analysis & Simulation Center:
TODAY
© 2011 Tieto Corporation

14. Towards subject centric
computing (semantic web)
• PSI: http://psi.ontopedia.net/Subject-centric_computing
• PSD: Subject-centric computing is a branch of computing
theory and practices which emphasizes the primacy of
subjects (and their interrelationships) in all forms of
information and knowledge management, human-computer
interaction, and operating system design. Its proponents
claim to be realizing Vannevar Bush’s 1945 vision of
computing “as we may think”.
• (Every)Thing has
• published subject identity (PSI) and
• published subject descriptor (PSD) attached
• Information about a Thing can be then found, ”understood”
and merged etc.
14 © 2011 Tieto Corporation 2011-03-04

15. Semantic Web Stack
Learn more from: wikipedia
Or DBpedia http://dbpedia.org/page/Semantic_Web_Stack
15 © 2011 Tieto Corporation 2011-03-04

16. Semantic web today: Linked open
data (http://linkeddata.org/ )
Try APIs: http://airports.dataincubator.org/airports/EFHK.html
http://www.w3.org/wiki/DataSetRDFDumps
16 © 2011 Tieto Corporation 2011-03-04

17. Ontology in IT
business
Approach to build IM system
© 2011 Tieto Corporation

18. System development with
semantic technology approach
Understanding semantics of biz entities and taking good care
of managing identities of entities and information related.
1. Understand business process
2. Extract info objects needed in process:
• Entities,
• their relationship,
• properties and
• info resources (links to docs)
3. Model the formal ontology in W3C: RDF/OWL or ISO: Topic
Maps
4. Analyze and build adapters to sources (mapping)
5. Analyze biz app interface and provide methods and
6. Create ontology queries and package results for methods
18 © 2011 Tieto Corporation 2011-03-04

19. Finding critical information assets and
mapping them to business objects
1.Biz Process
Product Manufac- Distri- Customer
Walk through R&D
Design
Logistics
turing
Marketing Sales
bution Support
2. Describe biz entities,
properties and relations
Cat1
Cat1 Cat4
Cat4
Cat2
in common biz Cat3
Cat6
Cat2
Cat5 Cat4
Cat1 Cat5
language Cat2 Cat3
Cat5 Cat6
Business ontology
4. Create
mapping from
local to global
glossary
3. Identify
sources.
PDM, ERP CMS CRM BI Sales & Partner’s
Marketing data
Understand
local glossaries
Heimo Hänninen
Luottamuks
ellinen © 2011 Tieto Corporation
19

20. Why ontology in IM?
• one stop shopping for "knowledge intense" logic 
consistent and holistic view for users
• Add metadata and semantics  findability, reuse of info
• biz logic in service component,  reuse of logic
• layered architecture, decoupling sources and biz apps 
secure investments
• extendable, flexible information integration
• mapping local glossaries to common, virtually any domain can be
integrated (vs. MDM thinking)
• more and more external data sources available (open linked data) 
secure investments and evolution friendly
• powerful query languages covering local ontology plus
external sources (end points) discovers “hidden
knowledge”
• knowledge in std format,  safe to own and share
• unstructured information gets metadata  integrate
20
documents to BI system
© 2011 Tieto Corporation 2011-03-04

21. Faced problems in the real world
• Poor data quality of sources
• Bad or missing metadata, no identifiers, ad hoc field naming etc.
• Security mgt.
• do you have to copy ACL or request it while user runs a query?
• Performance
• if running complex queries, if carrying on access management
• Governance
• difficult to define, who owns centralized knowledge service (it's not CMS, nor DW, nor
CRM, nor PDM but can benefit from those all).
• Usage: everyone want to ride on a bus but nobody wants to run the bus company.
• Ontology is redundant metadata about data in other systems.
• Not good for real time critical systems. Virtual ontology engine which reads data
directly from source is not here yet.
• Ontology may get out-dated, out of synch of business pulse
• World around evolves, so does business and information  evolve your ontology
• Based on evolution theory, a mechanism of mutations and natural selection should be built in 
• Difficult to calculate the business case, often no quick wins on table
• Not in the ICT main stream
• Educate and lobby managers, train developers to use semantic technologies
• Limited number or mature tools
21 • Stick to standards
© 2011 Tieto Corporation and evaluate tools and services. 2011-03-04

22. Apps
Architectural
Bus Ontology
service
view
Sources
knowledge map layer between
sources and business applications
© 2011 Tieto Corporation

23. Knowledge Map abstraction layer
Enterprise Architect Dmitry Bogachev – Topic Maps 2007
© 2011 Tieto Corporation

24. Three Layers of Information
Architecture
User in
situations, a task
User Experience at hand
& Business Applications Content Viewers
Business Processes
customer community
network solution Knowledge Map:
service products
-business objects
Conceptual staff project -info in context
doc report -across silos
Information
Logical Structures Semantics
Management
-metadata
Content
Implementation feeds Emails Intra ERP CMS and Data
IA layers
Heimo Hänninen
© 2011 Tieto Corporation

25. IM Layers Value chain:
Phase 1 Phase 2 Phase 3 Phase n -Processes
customer
solution Business Ontology/Domain model:
-Business entities
service
technology -With associations and
staff project
-Properties
document Indirect link -Across domains
Doc type Technology
Direct link
plans process customer Taxonomy:
Platform Process Application management
-Categorize
project guide
agreemen
t
-Hierarchical
application business user information -Domain specific
business quality report
communication application developer application
risk
Information:
-with metadata
-identified
-content and data
© 2011 Tieto Corporation 25 2011-05-03

26. Connecting user to biz ontology and
information to ontology
Customer in
situations,
Profile
Use context
Implicit Info in context
Explicit
Events
Publication process Start Phase Phase Phase End Rules
interest
Targeting
Business
customer
profile
Categorization,
Knowledge map logic
advertisement
Ontology
channel
High level semantics
News
editor Advertiser
material
source Standard structures
Link to resource Extracted metadata Low level semantics
Content and data
feeds Emails Intra ERP CMS
26 © 2011 Tieto Corporation Heimo Hänninen