Foreword to 

Data Mining for Scientific and Engineering Applications

Data Mining is automatic or semi-automatic discovery of buried knowledge in massive amounts of data. The field grew out of the need to discover useful information from ever growing data warehouses in commercial enterprises, and has roots in established disciplines such as statistics, artificial intelligence and machine learning, and pattern recognition. The scalability requirements imposed by the size of the business applications required the use of data base technology and high performance computing in data mining applications. Given the success of data mining in commercial areas, it didn't take much time for the scientists and engineers to discover the usefulness of data mining techniques in scientific disciplines.  For example, analysis of massive simulation data sets generated by computational simulations of physical and engineering systems is difficult and time consuming using traditional approaches. Indeed, much of the output of computational simulations is simply stored away on disks and is never analyzed at all. Availability of suitable Data Mining techniques can allow engineers and scientists to analyze such data and gain fundamental insights into the underlying mechanisms of the physical processes involved.

The two workshops held at the AHPCRC in 1999 and 2000 were among the first steps towards exploring the promise of the data mining technology to the scientific and engineering domains.  I commend the editors of this book for their efforts in putting together a fine volume based up on the presentations at the two workshops.  The book provides a good balance between articles that cover scientific applications as well as those that cover algorithms suited for scientific and engineering applications. In addition, many of the techniques and algorithms covered in this book have applicability far beyond the scientific and engineering domains.  I am confident that the book will be a valuable resource for scientists and engineers interested in exploring the use of data mining.  In addition, the book will help data mining researchers to better understand the requirements of the scientific and engineering applications and motivate them to develop new techniques for such applications.

Dr. N. Radhakrishnan
Director and Corporate Information Officer
Computational and Information Sciences Directorate
US Army Research Laboratory