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Ontology modeling quick guideExperiences on Taxonomy and Ontology development work
heimo hanninen
Tieto,[email protected]
© 2011 Tieto Corporation
Why do we need better concepts for organizing information?
2 2011-02-09 [email protected]
© 2011 Tieto Corporation
Information is Constantly in Motion –- a need for better management
30% of people’s time is spent searching for
relevant information
Only one-third of CFOs believe that the information is easy to
use, tailored, cost-effective or integrated
17% of IT budgets for storage hardware and storage management software and people
More than 60% of CEOs believe their business needs toaccess and understand information faster to make swift decisions
30–50% of design time is copy management
85% of information is unstructured
Documents
Transactions
Customers
Partners
Employees
OrganizationsFinancials
Products
E-mails
Databases
Media
Webcontent
Reports
37% growth of disk storage in 2005
40% of IT budgets may be spent on integration
Source: IBM [email protected]
© 2011 Tieto Corporation
Corporate information in silos – a need for connecting layer
4 2011-05-11
Partners R&D Production ICT Sales &Marketing
HR
© 2011 Tieto Corporation
What is ontology in IT system scope?
Enterprise Architect Dmitry Bogachev – Topic Maps 2007
-metadata
© 2011 Tieto Corporation
IM Layers (a’la Heimo)
6 2011-05-03
projectproject technologytechnologyserviceservice
document
staffstaff
solutionsolutioncustomercustomer Business Ontology/Domain model:
-Business entities-With associations and
-Properties-Across domains
Taxonomy:-Categorize
-Hierarchical-Domain specific
Information:-with metadata
-identified-content and data
Direct link
Indirect link
Value chain:-Processes
© 2011 Tieto Corporation
Phased modelling work
7 2011-06-17
Preparation iterative iterative
© 2011 Tieto Corporation [email protected]
Recursive ontology development
8 2011-02-09
Visualize
FormalizePopulate
Analyze & Refine
•Biz reqs•Value chain•User study
•Biz reqs•Value chain•User study
•Conceptual modelCmap
•Conceptual modelCmap
•Logical modelUML class diagram
•Logical modelUML class diagram
•Implementation modelRDF(S), OWL, Topic Maps, XML schema
•Implementation modelRDF(S), OWL, Topic Maps, XML schema
testtest
Use case
Prototype
PilotUse case
Processwalk
© 2011 Tieto Corporation
About the design work
• A kind of data modeling and knowledge engineering• 80% of communication, 20% of design
• Top down: business needs the information• Bottom up: inventorying where to get the data• Middle out: start with a motivated gang, a small system• Skills required:
• SMEs, often a guy who has been around long enough (find them)• Communication and facilitation skills• Data modeling (visualization) skills
• Team work: to create understanding on situation and common goal• Deliver something tangible to review (PoC approach)• Focus on the business not on the technology• “Keep stakeholders close and enemies closer”
9 2011-02-09 [email protected]
© 2011 Tieto Corporation
System development with semantic technology approachUnderstanding semantics of biz entities and taking good care of managing identities of entities and information related.1.Understand business (value proposition & 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 Maps4.Analyze and build adapters to sources (mapping)5.Analyze biz app interface and provide methods and6.Create ontology queries and package results for methods
10 2011-03-04 [email protected]
© 2011 Tieto Corporation
Finding critical information assets and mapping them to business objects
1.Biz Process Walk through
2. Describe biz entities, properties and relations in common biz language
3. Identify sources. Understand local glossaries
4. Create mapping from local to global glossary
R&D LogisticsManufac-
turing Marketing Sales
Distri-bution
CustomerSupport
ProductDesign
11
PDM, ERP CMS BI Sales &Marketing
Partner’sdata
CRM
Business ontology
Heimo Hänninen
© 2011 Tieto Corporation [email protected]
Faced problems in the real world• Poor data quality in source systems
• 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
• 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.
• Difficult to calculate the business case. • Not in ICT main stream.
• Educate and lobby managers, train developers to use sem tech
12 2011-03-04
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