JCSE, vol. 1, no. 2, pp.161-161, 2007

DOI:

Preface for the special issue of DaWaK 2007

Johann Eder, Tho Manh Nguyen, and Il-Yeol Song
University of Vienna, Austria|Vienna University of Technology, Austria|Drexel University, USA

Abstract: Data Warehousing and Knowledge Discovery are established key technologies in many application domains. Enterprises and organizations improve their abilities in data analysis, decision support, and the automatic extraction of knowledge from data; for scientific applications to analyze collected data, for medical applications for quality assurance and for steps to individualized medicine, to mention just a few examples. With the exponentially growing amount of information to be included in the decision making process, the data to be processed become more and more complex in both structure and semantics. Consequently, the process of retrieval and knowledge discovery from this huge amount of heterogeneous complex data constitutes the reality check for research in the area.
During the past years, the International Conference on Data Warehousing and Knowledge Discovery (DaWaK) has become one of the most important international scientific events to bring together researchers, developers and practitioners in the research areas. The DaWaK conferences served as a prominent forum for discussing latest research issues and experiences in developing and deploying data warehousing and knowledge discovery systems, applications, and solutions. The 9th International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2007), builds on this tradition of facilitating the crossdisciplinary exchange of ideas, experience and potential research directions. DaWaK 2007 seeks to disseminate innovative principles, methods, algorithms and solutions to challenging problems faced in the development of data warehousing, knowledge discovery and data mining applications.
The selection of papers in this special issue is the result of a stratified selection process starting from 150 papers submitted from researchers from 38 countries. Among them, 45 papers have been selected for presentation at the conference in Regensburg, Germany, and are published in the conference proceedings (Springer Verlag, LNCS 4654). The best papers among the 45 presented papers have been invited to submit extended versions of their papers to this special issue, and then the following 4 were approved by the reviewers:

- Fast Conditional Independence Bayesian Classifier Algorithm
by Estevam R. Hruschka Jr. and Sebastian D. C. de O. Galvao
- A Data Mining Approach for Selecting BitMap Join Indices
by Ladjel, Rokia, Hamid Necir, and Habiba Drias
- A Clustered Dwarf Structure to Speed up Queries on Data Cubes
by Yubin Bao, Fangling Leng, Daling Wang and Ge Yu
- Trajectory Data Warehouse: Design and Implementation Issues
by S. Orlando, R. Orsini, A. Raffaeta, A. Roncato, C. Silvestri
We express our gratitude to all who contributed to this endeavour the most visible result of which is this special issue of selected best papers: all the authors who sent their latest research results, the reviewers of both the conference papers and the extended versions of the selected papers, and last but not least the DEXA organisation team headed with great experience and oversight by Gabriela Wagner.

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