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Context Addict Presentation

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Context Addict Presentation

  1. 1. Politecnico di Milano Context -ADDICT Context-Aware Data Design,Integration, Customization, Tailoring Context-ADDICT
  2. 2. Motivations and scenarios• Disparate, heterogeneous, independent Data Sources• Semantic schema integration• Context-aware information filtering: Data Tailoring• Common, integrated, semantic access to data• Issues: mobility, data transiency• Multiple scenarios: system adaptability• < add your favourite buzz-word here > Context-ADDICT
  3. 3. Tasks and ChallengesTasks:• Data Source Discovery (later)• Lightweight (Semi)Automatic Data Integration• (Semi)Automatic Semantic Extraction• Context-Aware Data Filtering (focus)• Semantic Distributed Query processingChallenges:• Data Sources: heterogeneous, transient, mobile, unknown at design time• User Mobility• Multiple scenarios: system flexibility and adaptability• Need for high automatism• User Device Constraints (small portable devices) Context-ADDICT
  4. 4. Overall System Architecture Context-ADDICT
  5. 5. Models view Context-ADDICT
  6. 6. Data TailoringData Tailoring, based on the Dimension Tree Instantiation:• Schema Tailoring• Instance Tailoring Context-ADDICT
  7. 7. Data IntegrationDomain ontology - Data source integration:Standard Ontology mapping functionalitiesLightweight, automatic processing (mobile user’s device)Automatic inconsistencies resolution Context-ADDICT
  8. 8. Semantic ExtractionData Source Ontology:• Semantic Extraction: data abstract model + storage model• Supports the query processing• Models isolation (different models can be used separately) Context-ADDICT
  9. 9. Query AnsweringQuery Answering:• Choose an ontology query language (SPARQL, OWL-QL)• Query decomposition• Query translation• Data Fusion• Query Optimization Context-ADDICT
  10. 10. Context-ADDICT projects/thesisWe will managed area­based meeting/presentation:­ Ontology Mapping­ Semantic Extraction ­XML, Relational, Web(crawler)­ Ontology Tailoring­ Query AnsweringAre you interested? (Please rise you hand when asked)We will post the information about the meetings here:feed://www.elet.polimi.it/upload/curino/NEWS/rss.xmlhttp://www.elet.polimi.it/upload/curino/NEWS/NEWS.html Context-ADDICT
  11. 11. Context-ADDICT projects QuickTime and a TIFF (LZW) decompressor are needed to see this picture.­ Dimension Tree + tailoring ­ ER tool integration­ X­SOM: ­ matching modules (neighborhood, subclass, probabilistic,  H­MATCH integration) ­ Protégé plugin and standalone­ Relational Integration ­ use CLIO (or similar) + automatic feeding by domain  ontology­ Query Answering ­ query language selection (expressivity & al) ­ automatic wrapper generation for Relational and XML­ XML2OWL ­ look at the XSLT based approach and enrich it...­ Relational2OWL ­ advanced features on ER generalization ­ Plugin GUI­ Ontology Extraction ­ semantic completeness + labelling vs querying ­ Web 2 OWL ­ ontology extraction from web sources Context-ADDICT
  12. 12. Context-ADDICT teamProf.ssa Cristiana Bolchini (bolchini@elet.polimi.it)Prof. Fabio A. Schreiber (schreibe@elet.polimi.it)Prof.ssa Letizia Tanca (tanca@elet.polimi.it)Dott.ssa Elisa Quintarelli (quintare@elet.polimi.it)Dott.ssa Rosalba Rossato (rossato@elet.polimi.it)Ing. Carlo A. Curino (curino@elet.polimi.it)Ing. Antonio Penta (a.penta@unina.it)Ing. Giorgio Orsi (orsi@elet.polimi.it) Context-ADDICT
  13. 13. Conclusions These projects are part of our research so are: Limited, Challenging, Unique, Work-intensive, Team-managed If you want a project you are welcome on board, please contact: curino@elet.polimi.it orsi@elet.polimi.itOtherwise I’m sorry you have just lost the most challenging and exciting chance you have had in your life! Context-ADDICT

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