1. Course Desc<x>ription
<br>This course covers the essential concepts, principles, 
<br>techniques, and mechanisms associated with databa<x>se systems. The state-
<br>of-the-art techniques, including traditional approaches as well as recent 
<br>research developments, would be introduced in this course.  The course is 
<br>intended to provide basic understanding of the issues involved in databa<x>se 
<br>systems, knowledge of currently practical techniques for satisfying such needs, 
<br>and the current research approaches that are likely to provide a basis for 
<br>tomorrow's solutions.
<br>
<br>
<br>
<br>2.Text Books
<br><TABLE><TR><TD><B>DATAba<x>se MANAGEMENT SYSTEMS</B>, Third Edition
<br>by Raghu Ramakrishnan and Johannes Gehrke</TD></TR></TABLE>
<br>
<br>
<br>3.References
<br>
<br><TABLE><TR><TD>
<br><UL>
<br><LI>Jim Gray. "Evolution of Data Management." Computer v29 n10 (October 
<br>1996):38-46.
<br><LI>Alin Deutsch et. al. "Querying xm<x>l Data" Bulletin of Data 
<br>Engineering, 
<br>v22, 
<br>n3, Sep. 1999 
<br><LI>Ralf Hartmut Guting. "An Introduction to Spatial Databa<x>se Systems." 
<br>VLDB 
<br>Journal 3(4): 357-399, 1994. 
<br><LI>Antomn Guttman. "R-TREES. A DYNAMIC INDEX STRUCTURE FOR SPATIAL 
<br>SEARCHING." 
<br>Proceedings of ACM SIGMOD, pp.47-57, 1984. 
<br><LI>Hanan Samet. "Spatial Data Structures." Appears in Modern Databa<x>se 
<br>Systems: 
<br>The ob<x>ject Model, Interoperability, and Beyond, W.Kim, ed., Addison 
<br>Wesley/ACM 
<br>Press, Reading, MA, 1995, 361-385. 
<br><LI>Timos Sellis, Nick Roussopoulos and Chrishtos Faloutsos. "THE R+-TREE: A 
<br>DYNAMIC INDEX FOR MULTI-DIMENSIONAL ob<x>jectS." Proceedings of the 13th 
<br>VLDB 
<br>Conference, Brighton 1987. 
<br><LI>xm<x>l 1.0 (http://www.w3.org/TR/REC-xm<x>l) 
<br><LI>XQuery 1.0: An xm<x>l Query Language ( http://www.w3.org/TR/NOTE-xm<x>l-
<br>ql/)
<br><LI>S. S. Chawathe "Describing and Manipulating xm<x>l Data" Bulletin of 
<br>Data 
<br>Engineering, v22, n3, Sep. 1999 
<br><LI>Storing a Collection of Polygons Using Quadtrees. Hanan Samet, Rober E. 
<br>Webber.  ACM Transactions on Graphics (TOG) ,pages 182-222, 1995</UL>
<br></TD></TR></TABLE>
<br>
<br>
<br>
<br>4. Teaching Method
<br>
<br><TABLE><TR><TD>
<br><UL><LI>90% Lectures
<br><LI>10% Student Presentations</UL>
<br></TD></TR></TABLE>
<br>
<br>5.Syllabus
<br>
<br><TABLE><TR><TD>Introduction and overview  
<br><UL>
<br><LI>ER data model and Relational data model (review)
<br><LI>SQL (review)  
<br><LI>OR-DBMS
<br><LI>Spatial Databa<x>ses
<br><LI>Databa<x>se Connectivity
<br><LI>Spatial Index structures
<br><LI>xm<x>l
<br><LI>XQuery
<br><LI>Multimedia Databa<x>ses
<br><LI>Multidimensional Databa<x>ses
<br></UL>
<br></TD></TR></TABLE>
<br>
<br>6.Grading Policy
<br>Grading for those who pass the orientation exam
<br>Several quizzes: 10%
<br>One Assignment: 10%
<br>Two short presentations: 10%
<br>One project: 20%
<br>One exam: 50%
<br>Participation: 5%
<br>
<br>Grading for those who fail the orientation exam
<br>Above policy and the following one
<br>Deduction: -100% (-3% for every late record)
<br>
<br>7. AI Policy in the Classes
<br>During the examination and in the coding assignments, the use of AI tools is 
<br>strictly prohibited. However, these tools are permissible for assistance in 
<br>composing reports. It is crucial to ensure that you are the authentic author of 
<br>your work and to openly declare any instances of AI usage.
<br>
<br>8. E-Learning platform
<br>Teams: 
<br>https://teams.microsoft.com/l/team/19%3ahv5ED7QPsLPw1EoOuRCswIkJltA0I_kBtgJn62hF
<br>ZUc1%40thread.tacv2/conversations?groupId=201a4f5a-4894-4a27-a94e-
<br>0982e05a8673&tenantId=6c3bc511-43c7-4596-baeb-2335c69c41f1
<br>