Database Management Systems - B AD 84082 - Section 001

Spring 2008

A404 BSA

1:00-3:30 pm Monday

PhD Status

In-depth investigation of intelligent database management systems in support of business decision making. An understanding of relational databases is assumed. Object-oriented and semantic databases will be explored. Prerequisite: doctoral standing and permission of instructor.

Dr. Alan Brandyberry

BSA A425

(330)672-1146

3:30-6:15 PM Mon. (and by appointment)

Under Construction

Journal and other readings to be assigned.

A solid understanding of relational databases and their management is assumed.

 

 

Preparation of students to teach and do research in the data management area.  Teaching: Ensure students are prepared to teach database concepts at the undergraduate and master's levels.  Research: Acquaint students with the variety of active data management research topics and develop an in-depth understanding of a few.

 

 

Teaching: We will spend the first several weeks reviewing database concepts to ensure proficiency in the context of ensuring the ability to teach in the area (approximately two-four weeks). 

Research: Following this portion of the course we will alternate weeks between students to lead discussions on more advanced data management topics.  Each student will select a data management related topic (get oral approval for topic from instructor), create a short bibliography (10 minimum, 20 maximum) of what appears to be the most important scholarly papers on this topic, and select four of these papers as readings to be discussed in class.  Students should pass out their bibliography with the selected readings designated the week prior to the discussion. 

The student should plan on leading the discussion on the topic and the other student(s) (along with the instructor) should be prepared to participate in the discussion.  As the discussion leader you may want to present certain aspects of the paper but this should always be done with the assumption that the rest of the class have carefully read these papers.  You should also have discussion points prepared to help guide the discussion.  You may decide to bring in material not in scholarly journals (e.g. text book, web page, etc.) to add to the discussion.  If it is necessary to have the other members look at this prior to the discussion please distribute it early.  Each topic will be presented over two weeks (two papers and any support material per week).  Two topics will always be prepared for each week.  If discussion on the first topic is sufficiently interesting the second topic may be pushed to the following week or started and finished the next week.  We will confirm who will need to be prepared for the next week at the end of each session.  I will attempt to make sure that everyone presents the same number.  This may require teaming up on topics toward the end of semester.

Finally, concurrently with above, each student will select one topic for further research.  This may be one of the topics you presented, one of the topics a colleague has presented (students have first rights to the topics they presented - make sure the student who presented it will not be using it themselves), or a data management topic not presented (obtain approval).  Each student will describe one empirical and one conceptual research topic related to their described topic.  A moderately thorough, generic,  literature review will be written that could support either research idea.  The literature review should be approximately 3000-4000 words, not including bibliography.  The balance of class time will be spent on individual and class discussion and consultation on these topics.

 

 

Attendance at each class meeting is required.  Unexcused absences will adversely affect overall grade.  Non-emergency absences should be cleared with instructor prior to the absence.  Emergencies will be dealt with on an individual basis.

Attendance & Participation

33%

Topic Presentations

33%

Final Project.

34%