Syllabus for CSci 8715, Spatial Databases, Spring 2010

Monday and Wednesday 04:00 P.M. - 05:15 P.M., MechE 102
Role: Name Office & Hours Phone Email
Instructor: Prof. Shashi Shekhar EE/CS 5-203
Mon,Wed: 2:30P.M.-3:30P.M.		 624-8307 shekhar@cs.umn.edu
Volunteer TA: Pradeep Mohan EE/CS 5-202
Mon,Wed: 2:30P.M.-3:30P.M.		 626-7703 mohan@cs.umn.edu
Volunteer TA: Jim Kang EE/CS 5-202
Mon,Wed: 2:30P.M.-3:30P.M.		 626-7703 jkang@cs.umn.edu
Class Web Site: http://www.spatial.cs.umn.edu/Courses/Spring10/8715/
Schedule: lecture, homework and examination schedule
Web Pages: Class notes, Project Resources, Announcements (TA (Updated: 04/21/10), Instructor), HW Feedbacks (Updated: 2/16/10), Group info.
Pre-requisite: Familiarity with Relational Databases or Geographic Information Systems.
Reading List:
  • Text Book: Spatial Databases: A Tour, S. Shekhar and S. Chawla, Prentice Hall, 2003, ISBN 013-017480-7 .
  • Supplementary Material: A collection of general sources and research papers.
    Topics: 1. Application Domains of Geographical Information Systems (GIS), Common GIS data types and analysis.
    2. Conceptual Data Models for spatial databases (e.g. pictogram enhanced ERDs).
    3. Logical data models for spatial databases: rastor model (map algebra), vector model (OGIS/ SQL1999).
    4. Physical data models for spatial databases: Clustering methods (space filling curves), Storage methods (R-tree, Grid files), Concurrency control (R-link trees), Compression methods for rastor and vector data.
    5. Query Optimization: strategies for range query, nearest neighbor query, spatial joins (e.g. tree matching), cost models for new strategies, impact on rule based optimization.
    6. Spatial networks: Conceptual, logical, and physical data models, query languages, graph algorithms, access methods.
    7. Mining spatial database: auto-correlation, co-location, spatial outliers, classification (SAR, MRF).
    8. Rastor databases: Raster image operations, content-based retrieval, spatial data warehouses.
    9. Platform Trends: Cloud computing, Geo-sensor networks, mobile computing, P2P etc.
    10. Application Trends: Spatio-temporal Databases, Location based services, Social media, Crowd Sourcing, Global climate change etc.
    Examinations and Assignments: The main objective of this class is to study research methods and literature in spatial database systems. Core research skills of literature analysis, innovation, evaluation of new ideas, and communication are emphasized via homeworks and projects.UNITE students should email their homeworks to unite@umn.edu or fax it to 612-626-0761 (UNITE office - 514 Vincent Hall). Email is preferred. Various acivities in a research seminar courses are linked to the goals of the audience. Many students may like to get a broad overview of the research topics, methodologies, major results, open problems and potential future directions. In-class written examinations on survey papers from the reading list will be useful towards this purpose. Ph.D. students in this course may benefit from analyzing research papers relevant to their projects. Potential sources for the paper would be conference proceedings or journals such as those listed above.Honors undergradaute students as well as M.S. students in the course may benefit from projects and term papers similar to those for their thesis requirements. A project broken down in several steps will be relevant here.
    Cheating/ Collaboration:Getting help from services like general debugging service (GDS), buying term papers from web-sites (e.g. cheaters.com), copying someone else's assignment, or the common solution of written or programming assignments will be considered cheating. The purpose of assignments is to provide individual feedback as well to get you thinking. Interaction for the purpose of understanding a problem is not considered cheating and will be encouraged. However, the actual solution to problems must be one's own.
    Helpful Comments: This class is Very Interesting and Useful for audience interested in database systems research as well as in honors/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 (e.g. google earth, navigation device) to scientific domains (e.g. Global climate change, epidemiology, crime mapping).
    To get full benefit out of the class you have to work independently and regularly. Read the papers before the meeting and bring comments for discussion. Plan to spend at least 6 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 CSci 8715!
    Shashi Shekhar