Presenter: Bijil Abraham Philip

1. Semantic heterogeneity resolution in federated databases by metadata implantation and stepwise evolution GokselAslan, Dennis McLeod Presenter: Bijil Abraham Philip

2. Overview • Introduction • Related work • Schema implantation and semantic evolution • HSDM as the canonical data model • Phases of schema implantation and semantic evolution • Implementation • Comparing the solutions • Conclusion and future works

3. Introduction • The metadata folding problem: integration of remote and local databases in presence of semantic conflicts. Solution? • Most previous approaches propose largely one-step solution. Drawbacks? • Author’s approach: accumulate required knowledge incrementally from information unit owners and maintainers

4. Introduction Metadata folding problem

5. Drawbacks? Related work Global schema approach

6. Drawbacks? Related work Federated databases with global structures

7. Drawbacks? Related work Multi-databases with a multi-database language

8. An example sharing scenario

9. Schema implantation and semantic evolution • Metadata folding problem can be decomposed into 5 sub problems: • Information discovery • Schema transformation • Semantic heterogeneity resolution • Schema/instance importation • Schema/instance customization How does this help?

10. Heterogeneous Semantic Data Model (HSDM) • HSDM is a rich & expressive object based canonical data model • HSDM database is a collection of objects & relationships • Each HSDM class has at most 1 super class • 3 kinds of sub-class-super-class relationships • Every non-primitive object class has class & instance key • Class key: determines place in generalization hierarchy • Instance key: collection of attributes that can distinguish a instance • HSDM supports a number of null values

11. 5 phases of schema implantation & semantic evolution

12. Phases of schema implantation & semantic evolution • Semantic clarification phase Transforms a component conceptual schema from its native model into HSDM • Schema implantation phase Loosely integrates local & remote conceptual schema elements. Two sub-phases: • Superimposing • Hypothesis specification: • Harmonizer- a persistent structure that associates a local abstract class with a remote class • Each harmonizer has name, associated remote class, attribute equivalence assertions

13. Local schema implanted with schema portion Harmonizer Object authors Neurons annotations Physiology data person researchData experiment name startDate contactPerson description title name phone address subject experiment Time_Series_Data Histogram_Data number_of_traces trace_identifiers data_sets data_points scaling

14. Phases of schema implantation & semantic evolution • Semantic evolution phase • Investigates whether previously hypothesized relevance's hold • Configures harmonizers for different local-class-remote class combinations • Activates schema evolution

15. Harmonizers

16. Final local conceptual schema after semantic evolution Object subject experiment person researchData experiment name startDate contactPerson description title name phone address Physiology data authors Neurons annotations Time_Series_Data Histogram_Data data_points scaling number_of_traces trace_identifiers data_sets

17. Implementation • Requires 2 components: 1. Translators: transform database schemas 2. Database tool: HSDM Mediator • HSDM is an extension of PDM. • PDM is based on semantic data model • Functions of HSDM Mediator: • functions as a database modeling tool • allows HSDM databases to interoperate with each other

18. Implementation

19. Implementation

20. Comparing the Solutions Any missing metric?

21. Conclusions • Metadata implantation and stepwise evolution: • Emphasis on incremental acquisition of knowledge • Employs hypothetical processing • Short comings: • Depends on user interaction for building initial harmonizers • Depends on structural properties of a class definition while investigating its relevance to a remote class Any possible solutions?

22. Questions???