CS6604 Advanced Topics in Data and Information: Spatial Data Management

Instructor: Chang-Tien Lu
Office: NVC Room 312
Tel: 703-538-8373
Email: ctlu@vt.edu
Office Hour: Monday 11AM-noon, Wednesday 4-5PM, or by appointment.

Class Time and Location: Tuesday 5-7:45PM  NVC R325

Course Description:

This course treats a specific advanced topic of current research interest in the area of spatial data and information. The key objectives of this course are two-fold: (1) to teach the fundamental concepts of spatial data management and (2) to provide extensive hands-on experience in applying the concepts to real-world applications. Core research skills of literature analysis, innovation, evaluation of new ideas, and communication are emphasized via homeworks and projects. Most students may like to get a broad overview of the research topics, methodologies, major results, open problems and potential future research directions.

Topics:

Textbooks:

Spatial Databases: A Tour
Shashi Shekhar and Sanjay Chawla
Prentice Hall, 2003
ISBN-10: 0130174807
ISBN-13: 9780130174802


Foundations of Multidimensional and Metric Data Structures
Hanan Samet
Morgan Kaufmann, 2006
ISBN 0-12-369446-9

 

Spatial Databases: with Application to GIS
Philippe Rigaux, Michel Scholl, and Agnes Voisard
Morgan Kaufmann, 2001
ISBN 1-55860-588-6

 

Supplementary Material

A collection of papers.

Prerequisite:

                The equivalent of CS 5604 or CS 5614 is a prerequisite. Therefore you should be familiar with Entity-Relationship Model, File Organizations, Index Structures for Files, Basic Queries in SQL, Query Processing, Query Optimization, and Concurrency Control Techniques. You are responsible for determining if you have satisfied the prerequisite. 

Tentative Schedule:

                The schedule indicates the concepts and material to be covered in each week under the column labeled "Topics".

Week Date Lecture Topics Read Due
1 8/24 Class overview, Introduction to Spatial Databases Ch.1  
2 8/31 Spatial Concepts and Data Models Ch.2  
3 9/7 Spatial Query Languages Ch.3 HW1 (Paper Summary)
4 9/14 Spatial Access Methods

(Ref.Ch.6)

 
5 9/21 Spatial Storage and Indexing Ch.4, Foundation Ch.2 Project Proposal
6 9/28 Quiz    
7 10/5 Query Processing & Query Optimization (Ref Ch.7), Ch.5  
8 10/12 Spatial Network Ch.6 HW2 (Paper Review)
9 10/19 Introduction to Spatial Data Mining Ch.7  
10 10/26 Spatial Data Warehouses Ch.8 Project Checkpoint
11 11/2 Midterm    
12 11/9 Spatial Data Mining (Clustering) Ch.7, Papers

 

13 11/16 Spatiotemporal Event Forecasting   15-min Project Presentation
14 11/23 No Class (Thanksgiving Holiday)    
15 11/30

Spatiotemporal Event Forecasting + Invited Talk (Dr. Jing Dai, Google)

Ch.8 SPOT Survey
16 12/7 Final Project Presentation I    
17 12/14 Final Project Presentation II   Project Report (Due 12/15, 8PM)


Examinations and Assignments:

There are three homework assignments. Homework assignments are due at the start of class. If you have an excused absence from a class, turn in the homework assignment prior to the class session. All assignments must have your name, student ID and course name/ number. 

The weighting scheme used for grading is: 3 HW Assignments: 20%, including HW1(2%), HW2(8%), and HW3(Research Presentation, 10%), Quiz: 15%, Midterm: 30%, Final Project: 35% (Final Presentation: 10%, Final Report: 25%), Class Discussion and Participation: 5%. Students are responsible for all material covered in lectures. Examinations will heavily emphasize conceptual understanding of the material.

Late Submission Policy: 

Assignments must be handed in at the beginning of the class on the specified due date (Thursday of designated week).A penalty of 30% will be deducted from your score for the first 24-hour period if your assignment is late. A penalty of 70% will be deducted from your score for >= 24-hour period. Late¬†submission after 3 days will not be accepted. Weekend days will be counted. For assignments, you are encouraged to type your answers. 

Honor System: 

All work is to be done under the provisions of the Virginia Tech Honor System. Students can discuss the interpretation of an assignment, however, the actual solution to problems must be one's own. The tenets of the Virginia Tech Graduate Honor Code will be strictly enforced in this course, and all assignments shall be subject to the stipulations of the Graduate Honor Code. Whenever I learn that a student has violated the honor code, I am obligated to report the violation. For more information on the Graduate Honor Code, please refer to the GHS Constitution, located online at http://graduateschool.vt.edu/academics/expectations/graduate-honor-system/ghs-constitution.html.

Disabilities:

Any student that is in need of special accommodations due to a disability, as recognized by the Americans with Disabilities Act, should contact the Services for Students with Disabilities (SSD) in the Dean of Students Office. Students with disabilities are responsible for self-identification.  To be eligible for services, documentation of the disability from a qualified professional must be presented to SSD upon request. Academic adjustments may include, but are not limited to: priority registration, auxiliary aids, program and course adjustment, exam modifications, oral or sign language interpreters, cassette taping of text/materials, note takers/readers, or assistive technology.

If you need adaptation or accommodations because of a disability (learning disability, attention deficit disorder, psychological, physical, etc.), if you have emergency medical information to share with me, or if you need special arrangements in case the building must be evacuated, please make an appointment with me as soon as possible. If you need captioning for videos, please let me know no later than two weeks in advance of date on syllabus for reviewing.

Helpful Comments: 

This class is Very Interesting and Useful for audience interested in spatial database systems research as well as in Master/Doctoral projects. We will explore a number of current research areas which are very important yet fairly open for research. Spatial databases continue to be the heart of information management in areas ranging from business to scientific domains (e.g., earth observation systems, genomics).

To get full benefit out of the class you have to work independently and regularly. Read the textbook and papers before the meeting and bring comments for discussion. Plan to spend at least 12 hrs a week (a little more during first few weeks till you feel comfortable with geographic information and queries) on this class doing projects or reading.

Good Luck, and Welcome to CS 6604!
Chang-Tien Lu