Title: Combining the Best of Global-as-View and Local-as-View for Data Integration
1Combining the Best of Global-as-View and
Local-as-View for Data Integration
- Li Xu
- Brigham Young University
Funded by NSF
2Data Integration
- A Global Schema
- Global-as-View (GaV) vs. Local-as-View (LaV)
- Query Reformulation
- Mapping
- Adding New Sources
3Global as View (GaV)
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 MakeModel(x, y)
- s1.Car has MakeModel(x, y)
Year
Feature
Make
Model
Phone
Mileage
4Local as View (GaV)
Year
Feature
Make
Model
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)
Phone
Mileage
5Target-based Integration Query System (TIQS)
- Combining the Best of GaV and LaV
- Rule Unfolding
- Scalability
- Schema Matching
- Source-to-Target Mappings
- Automating Mediation Description
6Schema Matching
- Mapping Elements
- Direct Matches
- Indirect Matches
- Manipulation Operations
- Mapping Algebra
7Source-to-Target Mapping
Color
Year
Year
Feature
Make
Feature
Make Model
Model
Body Type
Style
Miles
Phone
Mileage
Source
8Source-to-Target Mapping (Cont.)
Color
Year
Feature
Body Type
Car
Style
Miles
Source Evaluation
9Source-to-Target Mapping (Cont.)
Color
Year
Feature
Body Type
Car
Style
Miles
Source Evaluation
10Source-to-Target Mapping (Cont.)
Year
Year
Feature
Make
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)
Model
Car
Phone
Mileage
Miles
Source
11Query Processing
- User Queries Logic Rules
- Conjunctive Query
- Conjunctive Query with Arithmetic Comparison
- Recursive Query
- Theorem Query Answers
- Sound
- Maximal
12Conclusion
- A Flexible and Scalable Data Integration Approach
- A Practical Approach
- A Correlation of Schema Matching and Data
Integration