1. Politecnico di Milano
Context -ADDICT
Context-Aware Data Design,
Integration, Customization, Tailoring
Context-ADDICT
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. Tasks and Challenges
Tasks:
• Data Source Discovery (later)
• Lightweight (Semi)Automatic Data Integration
• (Semi)Automatic Semantic Extraction
• Context-Aware Data Filtering (focus)
• Semantic Distributed Query processing
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
6. Data Tailoring
Data Tailoring, based on the Dimension Tree Instantiation:
• Schema Tailoring
• Instance Tailoring
Context-ADDICT
7. Data Integration
Domain ontology - Data source integration:
Standard Ontology mapping functionalities
Lightweight, automatic processing (mobile user’s device)
Automatic inconsistencies resolution
Context-ADDICT
8. Semantic Extraction
Data Source Ontology:
• Semantic Extraction: data abstract model + storage model
• Supports the query processing
• Models isolation (different models can be used separately)
Context-ADDICT
9. Query Answering
Query Answering:
• Choose an ontology query language (SPARQL, OWL-QL)
• Query decomposition
• Query translation
• Data Fusion
• Query Optimization
Context-ADDICT
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
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.it
Otherwise I’m sorry you have just lost the most challenging
and exciting chance you have had in your life!
Context-ADDICT