Cascon2011_1_intro

ONTORULE

From business knowledge to
ontology- and rule-based
applications

Workshop agenda
8:30 Introduction to the ONTORULE project
9:10 The ONTORULE standard-based architecture
9:30 Hands-on labs
1) acquiring ontology and rules from text
10:30 Coffee break
11:00 Hands-on labs
2) Annotating and indexing ontologies and rules
11:30 Hands-on labs
3) Authoring and executing business rules grounded in
ontology

The ONTORULE project

Ch. de Sainte Marie
IBM

Developing a business rule app (today)

IT application verbalize
developper + Business design Business
Business user
vocabulary user

Business
BOM Rules

XOM
Execute
IT application
developer design Application

Business people...
• ... do not want to see or write this

Business people...
• ... do not want to see or work with this
• They are used
– to look up glossaries
– to apply regulations
– to design policies
– to write rules like
« Customer must be 18 or more to rent a car »
– to read decision tables

Glossary (from EU directive
77/541/EEC)

EU regulation (directive
77/541/EEC)

Business people want...
• To write (and read, and manage) policies and rules
using own or domain-specific language or lexicon
– Natural language, not logic
• Rules and policies communicated unambiguously
across organisation’s or constituency’s branches,
functions, domains
– Same concepts, same semantics, different lexica
• Rules and policies applied consistently accross
organisation or constituency
– Same rules, different applications

Same rule, different applications
• Operative rules may instantiate differently in
different applications
– Policy: « Customer must be 18 or more to rent a car
»
– Decision: Can this customer rent a car?
If this customer is 18 or more
then proceed with rental
– Decision: What shall I do to rent a car?
If (today – birth) < 18 years
then wait ((birth + 18 years) – today)
years

Business people want...
• To write policies and rules using own or domain-specific
language or lexicon
– Natural language, not logic
• Rules and policies communicated unambiguously across
organisation’s or constituency’s branches, functions, domains
– Same concepts, same semantics, different lexica
• Rules and policies applied consistently accross organisation or
constituency
– Same rules, different applications
• ...and implemented as intended in decision-support IT
applications

• But rule engines need formal semantics and data models
– Not natural languages and lexica

How to reconcile them?
• Formalize vocabularies as ontologies
– re-use accross application or implementation
– Map to multiple data models
– Attach to multiple lexica
• Ground natural language policies and rules in formalized
vocabulary
– Formalize the additional semantics separately from the ontology
• Operationalize in rule-based IT application
– Translate formalized rules and policies into (possibly application
specific) implementation-specific executable rules
– Translate ontology into implementation-specific data model...
– ...or ground executable rules into ontology

Additional benefits

 Separate (conceptual) domain knowledge from
(operational) business rules...
 Separate domain knowledge from implementation
dependent data model...
 Separate wide ranging policies from application
specific operational rules
 ...that all have
 Different lifecycles
 Different scope (re-use etc)
 Different owners
 Improving collaboration and quality
 Design
 Interchange, sharing, re-use, re-deployment (on different
platforms)
 Maintenance, evolution

ONTORULE vision
Other applications and other platforms
Ontologies
Terminologies IT developer Application

Vocabulary Rule
Biz OWL
+ engine
user Ontology

Business
Rules RIF

Business Business
user user
: Automatic
Other applications Other platforms
: Semi-automatic

: Manual

Project ONTORULE: fact sheet
 3 years Integrating Project funded by the European Commission
 FP7, ICT call 3, theme 4.2
 Current status: operation
 Grant agreement: FP7 231875
 Started: 1 January 2009
 Duration: 36 months
 Overall budget: >8 M€
 Max. funding: 5,4 M€
 Effort: 644 person.months (~18 FTE)
 Consortium
 Vendors: IBM (ILOG) + Ontoprise
 SBVR consultants: PNA (+ John Hall)
 Use cases: Arcelor Mittal + Audi
 Technology center: CTIC
 Academics: TU Vienna + FU. Bozen/Bolzano + U. Paris 13
 Coordinator: Christian de Sainte Marie (IBM)

Key objectives and innovation

 Acquisition of ontology and rules from text
 Management of heterogeneous knowledge
 Combination of rules and ontologies at run-time
 Standard based integration
 End-to-end pilot applications

www.ontorule-project.eu

ONTORULE demonstrators
Acquisition Maintenance Execution

ORM to OWL
SBVR translation Production Production
Verification (FUB) Rule + OWL Rule + OWL
Simulation maintenance execution
(PNA) (IBM) RIF + OWL (IBM)
documentation
(CTIC)
NLP ObjectLogic ObjectLogic
Knowledge Luis + OWL + OWL
Acquisition maintenance execution
Alice
(U. Paris 13) (ontoprise) Marc Gary (ontoprise)

Marc Gary Gary
Alice Joana

Users of ONTORULE User of the decision-
support application that is
supported by ONTORULE

Workshop agenda
8:30 Introduction to the ONTORULE project
9:10 The ONTORULE standard-based architecture
9:30 Hands-on labs
1) acquiring ontology and rules from text
10:30 Coffee break
11:00 Hands-on labs
2) Authoring and executing business rules grounded in
ontology
12:00 Hands-on labs
3) Annotating and indexing ontologies and rules

Cascon2011_1_intro

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