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BYU 2003BYU Data Extraction Group Combining the Best of Global-as-View and Local-as-View for Data Integration Li Xu Brigham Young University Funded by.

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Presentation on theme: "BYU 2003BYU Data Extraction Group Combining the Best of Global-as-View and Local-as-View for Data Integration Li Xu Brigham Young University Funded by."— Presentation transcript:

1 BYU 2003BYU Data Extraction Group Combining the Best of Global-as-View and Local-as-View for Data Integration Li Xu Brigham Young University Funded by NSF

2 BYU 2003BYU Data Extraction Group Data Integration A Global Schema Global-as-View (GaV) vs. Local-as-View (LaV) –Query Reformulation –Mapping –Adding New Sources

3 BYU 2003BYU Data Extraction Group Global as View (GaV) Global Schema Car Year Feature PhoneMileage Model Make Source Year Miles Make & Model Feature Car Make & Model Mediation Description Car has Year (x, y) :- s1.Car has Year(x, y) Car has Feature(x, y) :- s1.Car has Feature(x, y) Car has Mileage(x, y) :- s1.Car has Miles(x, y) Car has Make&Model(x, y) :- s1.Car has Make&Model(x, y)

4 BYU 2003BYU Data Extraction Group Local as View (GaV) Year Feature Phone Global Schema Car Mileage Model Make Source Year Miles Feature Car Source Description s1.Car has Year (x, y) :- Car has Year(x, y) s1.Car has Miles (x, y) :- Car has Mileage(x, y) S1.Car has Feature(x, y) :- Car has Feature(x, y)

5 BYU 2003BYU Data Extraction Group Target-based Integration Query System (TIQS) Combining the Best of GaV and LaV –Rule Unfolding –Scalability Schema Matching –Source-to-Target Mappings –Automating Mediation Description

6 BYU 2003BYU Data Extraction Group Schema Matching Mapping Elements –Direct Matches –Indirect Matches Manipulation Operations Mapping Algebra

7 BYU 2003BYU Data Extraction Group Source-to-Target Mapping Year Feature PhoneMileage Model Make Target Schema Car Source Year Miles Make & Model Feature Car Style Color Body Type

8 BYU 2003BYU Data Extraction Group Source-to-Target Mapping (Cont.) Source Evaluation Car Make & Model Feature Style Color Body Type Year Miles Year Feature PhoneMileage Model Make Car Make Model

9 BYU 2003BYU Data Extraction Group Feature’ Source-to-Target Mapping (Cont.) Source Evaluation Car Make Model Make & Model Feature Style Color Body Type Year Miles Year Feature PhoneMileage Model Make Car Source Mapping Expressions s1.Car has Feature’ <= s1.Car has Make <= s1.Car has Model <=

10 BYU 2003BYU Data Extraction Group Source-to-Target Mapping (Cont.) Year Feature Phone Target Car Mileage Model Make Source Car Year Miles Feature Make Model Mediation Description Car has Year (x, y) :- s1.Car has Year(x, y) Car has Feature(x, y) :- s1.Car has Feature’(x, y) Car has Make(x, y) :- s1.Car has Make(x, y) Car has Model(x, y) :- s1.Car has Model(x, y) Car has Mileage(x, y) :- s1.Car has Miles(x, y)

11 BYU 2003BYU Data Extraction Group Query Processing User Queries: Logic Rules Conjunctive Query Conjunctive Query with Arithmetic Comparison Recursive Query Theorem: Query Answers Sound Maximal

12 BYU 2003BYU Data Extraction Group Conclusion A Flexible and Scalable Data Integration Approach A Practical Approach A Correlation of Schema Matching and Data Integration


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