Cascon2011_1_intro

ONTORULEFrom business knowledge to ontology- and rule-based applications

Workshop agenda8:30 Introduction to the ONTORULE project9:10 The ONTORULE standard-based architecture9:30 Hands-on labs 1) acquiring ontology and rules from text10:30 Coffee break11:00 Hands-on labs 2) Annotating and indexing ontologies and rules11:30 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 verbalizedevelopper + Business design BusinessBusiness user vocabulary user Business BOM Rules XOM ExecuteIT 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)

AA frequent flyer program

From the AAdvantage Web site

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 + engineuser 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 demonstratorsAcquisition Maintenance Execution ORM to OWL SBVR translation Production ProductionVerification (FUB) Rule + OWL Rule + OWLSimulation 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 agenda8:30 Introduction to the ONTORULE project9:10 The ONTORULE standard-based architecture9:30 Hands-on labs 1) acquiring ontology and rules from text10:30 Coffee break11:00 Hands-on labs 2) Authoring and executing business rules grounded in ontology12:00 Hands-on labs 3) Annotating and indexing ontologies and rules

http://ontorule-project.eu	340
http://www.ontorule-project.eu	9
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Cascon2011_1_intro

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