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Maurizio Vincini UniMORE Researcher Università di Modena e Reggio Emilia

WINK System: Intelligent Integration Framework. Maurizio Vincini UniMORE Researcher Università di Modena e Reggio Emilia. service description. service description. WINK Architecture. WHALES. Client tier. Web Server. Web Application Virtual Integrated Cockpit. Business logic tier.

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Maurizio Vincini UniMORE Researcher Università di Modena e Reggio Emilia

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  1. WINK System: Intelligent Integration Framework Maurizio Vincini UniMORE Researcher Università di Modena e Reggio Emilia

  2. service description service description WINK Architecture WHALES Client tier Web Server Web Application Virtual Integrated Cockpit Business logic tier WHALES MIKS requestor provider client service service provider requestor client Data sources Shared Data Data tier

  3. WINK Integration Framework MIKS is an Agent mediator-based system for integrating multiple enterprises’ data sources into a single portal system. • Semantic reconciliation of multiple heterogeneous ontologies • Information fusion and query Agent support • Mobile Agents support in order to improve system • flexibility and query performance (based on JADE) Distributed information stored in multiple, heterogeneous sources Global view Integration process References I. Benetti, D. Beneventano, S. Bergamaschi, F. Guerra, M. Vincini,‘An Information Integration Framework for E-Commerce’. IEEE Intelligent Systems Magazine, January/February 2002.

  4. Semantic Information Integration process Local schemata Common Thesaurus Clusters Global Virtual View with mapping tables Artificial Intelligence reasoning (Description Logic) Cluster technique Lexical relationships (WordNet)

  5. Common Thesaurus (Domain Ontology) • Set of terminological relationships between classes and attributes names (terms) • expresses both intra-schema and inter-schema knowledge • Relationships added to Common Thesaurus: • schema derived • lexicon derived (WordNet) • designer supplied • inferred exploiting ODB-Tools capabilities

  6. Semantic Information Integration process Local schemata Common Thesaurus Clusters Global Virtual View with mapping tables Artificial Intelligence reasoning (Description Logic) Cluster technique Lexical relationships (WordNet)

  7. Mapping table Alenia test case GVV

  8. Runtime: Query Processing Management • Discovering the relevant local sources • Query rewriting w.r.t. local sources • Independent local data retrieving • Unified data answers In MIKS (WINK Integration Framework): • OQL-like query over GVV • Query Reformulation/Optimization • Local sub-queries execution • Mediated query result obtained by object fusion

  9. User Query: • Select Activity, Effort • from Activity • where Requirement=‘IC-5’ and Closed=‘Y’ • AIVDB: Q1 • Select PROD_ID • from VER_DOC_LINK • where REQ_SEQ=‘IC-5’ and REOPENING=‘Y’ • WHALES: Q2 • Select Activity, Effort, Test_ID • from Work_Plan • Fusion • Select Activity, Effort • from Q1, Q2 • where Q1.PROD_ID= Q2.Test_ID Query Example GVV

  10. ASP requestor client Business Logic XSL WINK Integration Framework service provider XML Service Agent Query Agents GVV WHALES Storage DB AIVDB+ Wrapper Agent NCRDB Wrapper Agent SAP Wrapper Agent Wrapper Agent Wrapper Agent WINK Integration Framework WINK Project Collaboration Portal HTTP HTML WINK Agency

  11. Agent-based vs. Service-centric applications Expected advantages: • Agent Mobility • Distributed computation • Decreased communication costs • Increased information availability even during network failure • Mediation: Intelligence and coordination • Semantic view of the physical query • Enables asynchronous processing • Warning on source data structure changes

  12. DEMO • Collaboration Portal: • Home Page • Project Plans (from MS Project 2000) • Function and Reports • Agent-based user-defined queries • Purchase Requests

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