context addict presentation
DESCRIPTION
TRANSCRIPT
Context-ADDICT
Context -ADDICTContext -ADDICT
Politecnico di MilanoPolitecnico di Milano
Context-Aware Data Design, Integration, Customization, Tailoring
Context-ADDICT
Motivations and scenariosMotivations 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
Tasks and ChallengesTasks and Challenges
Tasks:Tasks:
• Data Source Discovery (later)
• Lightweight (Semi)Automatic Data Integration
• (Semi)Automatic Semantic Extraction
• Context-Aware Data Filtering (focus)
• Semantic Distributed Query processing
Challenges:Challenges:
• 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
Overall System ArchitectureOverall System Architecture
Context-ADDICT
Models viewModels view
Context-ADDICT
Data TailoringData Tailoring
Data Tailoring, based on the Data Tailoring, based on the Dimension Tree InstantiationDimension Tree Instantiation::
• Schema Tailoring
• Instance Tailoring
Context-ADDICT
Data IntegrationData Integration
Domain ontology - Data source integration:
Standard Ontology mapping functionalities
Lightweight, automatic processing (mobile user’s device)
Automatic inconsistencies resolution
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Semantic ExtractionSemantic Extraction
Data Source Ontology:
• Semantic Extraction: data abstract model + storage model
• Supports the query processing
• Models isolation (different models can be used separately)
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Query AnsweringQuery Answering
Query Answering:
• Choose an ontology query language (SPARQL, OWL-QL)
• Query decomposition
• Query translation
• Data Fusion
• Query Optimization
Context-ADDICT
Context-ADDICT projects/thesisContext-ADDICT projects/thesis
We will managed areabased meeting/presentation: Ontology Mapping Semantic Extraction
XML, Relational, Web(crawler) Ontology Tailoring Query Answering
Are 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
Context-ADDICT projectsContext-ADDICT projects 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
QuickTime and aTIFF (LZW) decompressor
are needed to see this picture.
Context-ADDICT
Context-ADDICT teamContext-ADDICT team
Prof.ssa Cristiana Bolchini ([email protected])
Prof. Fabio A. Schreiber ([email protected])
Prof.ssa Letizia Tanca ([email protected])
Dott.ssa Elisa Quintarelli ([email protected])
Dott.ssa Rosalba Rossato ([email protected])
Ing. Carlo A. Curino ([email protected])
Ing. Antonio Penta ([email protected])
Ing. Giorgio Orsi ([email protected])
Context-ADDICT
ConclusionsConclusions
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:
Otherwise I’m sorry you have just lost the most challenging and exciting chance you have had in your life!