1. Data Dependency Management inHeterogeneous and Dynamic DIS Giorgio Orsi orsi@elet.polimi.it Ph. Day June 26th 2008 Politecnico di Milano Dipartimento di Elettronica e Informazione

2. Motivations Heterogeneous, Independent, Dynamic and Mobile Data Sources. Heterogeneity of models and technologies. Systems designed independently. Real world is not static and changes rapidly. Users and data sources move and the engineer cannot follow them all the day to solve their problems. We need on-the-fly, integrated access to relevant information. PHDAY 08

3. Ontologies at rescue Possible Solution: Domain Ontology Ontology-Based Context-aware Data Integration AccessData Source CA-DLMappingsOntologies Data Sources PHDAY 08

4. Tasks and ChallengesTasks: (User-driven) Automatic Schema Extraction (ROSEX). (User-driven) Lightweight Automatic Data Integration (X-SOM). Cross-Model, Distributed Query processing (SPARQL-Explorer). Context-Aware Data Filtering (CADD Tool).Challenges: Cognitive support to HD-DIS modeling (What you see is what you get). On-the-fly tailoring of relevant data and smart caching (What you get is what you need). Technology gaps: Mobile devices, data streams, sensor networks. PHDAY 08

5. ToolsExtraction: Focus on really used data models (e.g., relational, XML, RDF) and Natural Language. Output: ontological representations of the data sources. Data structures obtained through reverse engineering of best practices in design or through data-mining.Data Integration: Current solutions (DL-Lite, El++) are almost theoretical solutions and are far from being real systems (Kripke frames are not user-friendly). Keep the data where they currently are, use ontologies to get them out! Use data dependencies to optimize query plans.Data Tailoring: Satisfy all the constraints is nor practical nor really needed. The system/user context determines the subset of constraints and data to be considered. PHDAY 08

6. And now... Questions ( where: ~(question => answer) ) PHDAY 08