George Mason University School of Computational Sciences

CSI 710 Scientific and Statistical Databases Fall Semester 2005

·   Course Website:  http://classweb.gmu.edu/kborne/csi710/ 

·   Online Course Material - please log into http://webct41.gmu.edu/ every week to get updates, lecture slides, assignments.  

·   Group Projects: Email and Documents to be stored at http://webct41.gmu.edu/  

·   Cross-listed Course Number:  IT 864

·   Lecture Day/Time:  Tuesday 4:30-7:10 PM  (August 30 – December 6)

·   Lecture Place:  Room 131, Science & Technology I

·   Course Instructor:  Kirk Borne, Associate Professor, Astrophysics and Computational Science

·   Office:   David King Hall, Room 1014A,  703-993-8402 (with voicemail)

·   Office Hours:  by appointment

·   E-mail:  kborne@gmu.edu

·   Mail box:  SCS Office, Room 101, Science & Technology I

Required Textbooks:

• Korth, Silberschatz, & Sudarshan, Database System Concepts, McGraw-Hill, 2005 (5th edition is preferred; but 4th edition is okay).  ISBN: 0-07-295886-3
• Daconta, Obrst, & Smith, The Semantic Web: A Guide to the Future of XML, Web Services, and Knowledge Management, Wiley, 2003.  ISBN: 0-471-43257-1

 

Course Description (from GMU course catalog):

• Study of database support for scientific data management. Covers requirements and properties of scientific databases, data models for statistical and scientific databases, semantic and object-oriented modeling of application domains, statistical database query languages and query optimization, advanced logic query languages, and case studies such as the human genome project and Earth-orbiting satellites.
• Prerequisites:    INFS 614 (Database Management), or equivalent, or permission of instructor

 

Grading:

• 20% = Group Project Team Paper
• 20% = Group Project Team Presentation
• 40% = Final Exam (take-home)
• 20% = Homework and Class Participation

 

Course Objectives:

1.      to analyze database and data management concepts and technologies that benefit scientific research;

2.      to become familiar with a variety of large scientific database projects – goals & implementation;

3.      to become capable in using database and data management techniques to solve scientific problems; and

4.      to acquire knowledge in database and data management techniques that will enable the student to progress to more advanced courses, research projects, and employment opportunities that require database skills and data management capability.