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COMP30110

Academic Year 2024/2025

Spatial Information Systems (COMP30110)

Subject:
Computer Science
College:
Science
School:
Computer Science
Level:
3 (Degree)
Credits:
5
Module Coordinator:
Professor Michela Bertolotto
Trimester:
Spring
Mode of Delivery:
Blended
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

Spatial Information Systems are becoming increasingly important. While traditionally spatial datasets were used only by experts in specific professional fields (e.g., Cartography, Geography, etc.), nowadays they are employed in the more varied application contexts (e.g., trip planning, crime mapping, etc.). As a consequence, the research in Spatial Information Systems and theory is receiving a lot of attention.This is a module for all students interested in understanding issues related to spatial information handling. In this module students will learn the fundamentals of spatial information theory, spatial querying, spatial information systems, geometric problems involved in a spatial information system. They will learn details about the spatial data formats (raster and vector), spatial relations (with particular emphasis on topological relations), spatial data structures, digital terrain modelling, geometric problems arising in spatial information systems and algorithms to solve them. They will develop a critical understanding of the different approaches to storing and manipulating spatial data: loosely coupled approach of classical GIS versus the integrated approach of spatial database management systems. They will analyse the Oracle Spatial object-relational model for storing and indexing spatial data. These notions will complement their knowledge of other types of information systems seen throughout their Computer Science courses. The knowledge of basic concepts of databases and information systems is a pre-requisite for this course.

About this Module

Learning Outcomes:

On completion of this module students should be able to:- formulate, explain, link and compare the fundamental concepts and terminology related to spatial information - analyse data structures for spatial data and evaluate them in terms of storage requirements and efficiency - categorise spatial queries depending on the type of relations and basic algorithms they involve and reflect on their application - critically discuss the different approaches for spatial data storage and manipulation - identify, discuss and critically evaluate indexing techniques for accessing and querying different types of spatial data - identify, explain and generalise algorithms from the computational geometry literature for solving problems discussed in the course (e.g., topological querying, digital terrain modelling, visibility problems, etc.)

Student Effort Hours:
Student Effort Type Hours
Lectures

24

Specified Learning Activities

15

Autonomous Student Learning

75

Total

114


Approaches to Teaching and Learning:
Problem solving; example exercises done in class;
MCQs with solutions;
Sample of exam paper.

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Pre-requisite:
COMP20070 - Databases and Info. Systems I


 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Exam (In-person): In-class test Week 7, Week 8, Week 9 Graded No
30
No
Exam (In-person): Final exam End of trimester
Duration:
2 hr(s)
Graded No
70
No

Carry forward of passed components
No
 

Resit In Terminal Exam
Autumn No
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Online automated feedback
• Self-assessment activities

How will my Feedback be Delivered?

Exercises with solutions.

Name Role
Dr Anh Vu Vo Lecturer / Co-Lecturer

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Spring Lecture Offering 1 Week(s) - 20, 21, 23, 24, 25, 26, 29, 30, 31, 32 Mon 15:00 - 15:50
Spring Lecture Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Thurs 16:00 - 16:50