Preface Section 1: Conceptual Design and Ontology-based Integration

For the past fifteen years, data warehousing and on line analysis (OLAP) technologies have shown their effectiveness in managing and analyzing a large amount of disparate data. Today, these technologies are confronted with new applications (mobile environments, data integration, data flow, personalization, stream data, sensor network applications, etc.) and new challenges as shown by the increasing success of the EII technologies (Enterprise Information Integration). These technologies are attracting a lot of attention from the database, data warehousing and data mining research communities. Two main particularities of this book are: (i) it covers the whole process of designing and using a data warehouse, which includes requirement specification, conceptual design, logical design, physical design, tuning and evolution management and (ii) it shows the contribution of ontologies in designing and exploiting data warehouses. The primary objective of this book is to give readers in-depth knowledge of data warehouses and their applications. The book is designed to cover a comprehensive range of steps for designing efficient and self administrable data warehouses and managing their evolution. The fact that most of these steps are supported by some commercial DBMS motivates the need for such a book. There was great response to the call for proposals, but due to the limited space only 15 chapters were accepted and selected. These chapters are authored by an outstanding roster of experts in their respective fields, and tackle various issues from different angles, requirements and interests. Their topics include user requirement specification, conceptual design, ontology driven ETL process, physical design and self tuning (materialized view selection, parallel processing, etc.), evolution and maintenance management, and security. The conceptual design concerns both classical and complex data sources (XML and spatial data). The fifteen selected chapters cover the majority of steps executed within data warehouse projects. They can be classified into four sections: Conceptual Design and Ontology-based Integration, Physical Design and Self Tuningt, Evolution and Maintenance Management, and Exploitation of Data Warehouse. The four sections are summarized as follows.