Database Integration: the Key to Data Interoperability

Most of new databases are no more built from scratch, but re-use existing data from several autonomous data stores. To facilitate application development, the data to be re-used should preferably be redefined as a virtual database, providing for the logical unification of the underlying data sets. This unification process is called database integration. This chapter provides a global picture of the issues raised and the approaches that have been proposed to tackle the problem

Resolving horizontal partitioning and schematic variances using metadatabase approach.

by Poon, Koon-hei.Thesis (M.Phil.)--Chinese University of Hong Kong, 2000.Includes bibliographical references (leaves 80-83).Abstracts in English and Chinese.Chapter CHAPTER 1 --- INTRODUCTION --- p.6Chapter CHAPTER 2 --- LITERATURE REVIEW --- p.13Chapter 2.1. --- BACKGROUND --- p.13Chapter 2.2. --- example systems --- p.20Chapter 2.2.1 --- Multibase --- p.20Chapter 2.2.2. --- Mermai d --- p.23Chapter 2.2.3. --- The Metadatabase Approach --- p.26Chapter 2.3. --- SUMMARY --- p.29Chapter CHAPTER 3 --- THE METADATABASE APPROACH --- p.31Chapter 3.1. --- Two-Stage Entity Relationship (TSER) model --- p.31Chapter 3.2. --- The GIRD --- p.34Chapter 3.3. --- The Metadatabase system in action --- p.36Chapter 3.3. --- global query formulations and processing in the metadatabase system --- p.37Chapter CHAPTER 4 --- PROBLEM OUTLINES FOR HORIZONTAL PARTITIONING AND ITS VARIANTS --- p.39Chapter 4.1. --- Horizontal partitioning --- p.39Chapter 4.2. --- Level of abstraction --- p.41Chapter 4.3. --- Schematic variances --- p.42Chapter 4.4. --- Summary --- p.43Chapter 4.5. --- The Scenario --- p.44Chapter 4.6. --- Populating the Metadatabase --- p.48Chapter CHAPTER 5 --- THE ENHANCEMENTS FOR GLOBAL QUERY WITH HORIZONTAL PARTITIONED DATA OBJECTS --- p.51Chapter 5.1. --- Identifying partitioned data objects --- p.51Chapter 5.2. --- Additional metadata for the horizontal partitioned data objects --- p.52Chapter 5.3. --- Complications of horizontal partitioning problem --- p.54Chapter 5.3.1. --- Level of abstraction --- p.55Chapter 5.3.2. --- Schematic variances --- p.57Chapter 5.4. --- Global query with horizontal partitioning data objects --- p.59Chapter 5.5. --- Housing the new metadata --- p.68Chapter 5.6. --- Example --- p.72Chapter CHAPTER 6 --- ANALYSIS --- p.75Chapter CHAPTER 7 --- CONCLUSION AND FUTURE WORKS --- p.78REFERENCES --- p.80APPENDICES --- p.84Chapter A. --- GIRD Definitions --- p.84Chapter A1. --- GIRD Model --- p.84Chapter A2. --- GIRD/SER Contents --- p.84Chapter A3. --- GIRD/OER Constructs --- p.87Chapter A4. --- Definition of Meta-attributes --- p.89Chapter B. --- Problems Representations in Relation Algebra --- p.96Chapter B1. --- Horizontal problem --- p.96Chapter B2. --- Level of abstraction --- p.96Chapter B3. --- Schematic Variance --- p.97Chapter C. --- Details of local systems --- p.9

A Structure Based Schema Integration Methodology

The process of integrating the schemas of several databases into an integrated schema is not easy, due to semantic heterogeneities. We present a method to detect class similarities by following a strategy and applying comparison criteria, that exploits the semantically rich structures of the schemas (previously enriched), along both the generalization/specialization and the aggregation dimensions. Relaxations may be applied to conform a pair of classes, resulting in penalizations in the computation of the degree of similarity. Our approach needs less comparisons than methods based on attribute comparison