Scientific Data Mining and Knowledge Discovery : Principles and Foundations With the evolution in data storage large databases have stimulated researchers from many areas especially machine learning and statistics to adopt and develop new techniques for data analysis in different fields of science. In particular there have been notable successes in the use of statistical computational and machine learning techniques to discover scientific knowledge in the fields of biology chemistry physics and astronomy. With the recent advances in ontologies and knowledge representation automated scientific discovery (ASD) has further great prospects in the future. The contributions in this book provide the reader with a complete view of the different tools used in the analysis of data for scientific discovery. Gaber has organized the presentation into four parts: Part I provides the reader with the necessary background in the disciplines on which scientific data mining and knowledge discovery are based. Part II details applications of computational methods used in geospatial chemical and bioinformatics applications. Part III is about data mining applications in geosciences chemistry and physics. Finally in Part IV future trends and directions for research are explained. The book serves as a starting point for students and researchers interested in this multidisciplinary field. It offers both an overview of the state of the art and lists areas and open issues for future research and development.