Information Integration with Ontologies: Experiences from an Industrial Showcase
暫譯: 使用本體進行資訊整合：來自產業展示的經驗

Description:

Disparate information, spread over various sources, in various formats, and with incon­sistent semantics is a major obstacle for enterprises to use this information at its full potential. Information Grids should allow for the effective access, extraction and linking of dispersed information. Currently Europe’s coporations spend over 10 Billion € to deal with these problems. 

This book will demonstrate the applicability of grid technologies to industry. To this end, it gives a detailed insight on how on­tology technology can be used to manage dispersed information assets more efficiently. The book is based on experiences from the COG (Corporate Ontology Grid) project, carried out jointly by three leading industrial players and the Digital Enterprise Research Institute Austria. Through comparisons of this project with alternative technologies and projects, it provides hands-on experience and best practice examples to act as a reference guide for their development.

Information Integration with Ontologies: Ontology based Information Integration in an Industrial Setting is ideal for technical experts and computer researchers in the IT-area looking to achieve integration of heterogeneous information and apply ontology technologies and techniques in practice. It will also be of great benefit to technical decision makers seeking infor­mation about ontology technologies and the scientific audience, interested in achievements towards the application of ontologies in an industrial setting.

Table of Contents:

Foreword.

1 Introduction.

1.1 Finding A Way out of the Dilemma.

1.2 The Background to this Book.

1.3 The Structure of the Book.

2 Data Modelling and Ontologies.

2.1 The Information Integration Problem.

2.2 Semantic Information Management.

2.3 Conclusions.

3 Information Integration with Relational Databases and XML.

3.1 Introduction.

3.2 Relational Database Integration.

3.3 XML-Based Integration.

3.4 Conclusions.

4 The Show Case.

4.1 Data Sources.

4.2 Identifying overlaps between the Data Sources.

4.3 Current ways of dealing with Heterogeneity.

5 Semantic Information Integration.

5.1 Approaches in Information Integration.

5.2 Mapping heterogeneous data sources.

5.3 Other Methods and Tools.

5.4 Comparison of the Methods.

5.5 Conclusions and Future Work.

6 Data Source Queries.

6.1 Querying disparate data sources using the Unicorn Workbench.

6.2 Querying disparate data source.

6.3 Related Work.

6.4 Conclusions.

7 Generating Transformations.

7.1 Information transformation in the COG project.

7.2 Other information transformation approaches.

7.3 Conclusions, limitations and extensions.

8 Best Practices and Methodologies employed.

8.1 Best Practices.

8.2 Lessons Learned.

8.3 Conclusions.

9 Conclusion.

References.

Glossary.