DM888: Spatial Data Management

The Study Board for Science

Teaching language: Danish or English depending on the teacher
EKA: N340116102
Assessment: Second examiner: External
Grading: 7-point grading scale
Offered in: Odense
Offered in: Autumn
Level: Master

STADS ID (UVA): N340116101
ECTS value: 5

Date of Approval: 24-02-2022


Duration: 1 semester

Version: Approved - active

Entry requirements

None

Academic preconditions

Students taking the course are expected to:

  • Have knowledge of Database Management Systems, e.g., obtained in DM564
  • Be able to program, e.g., by having followed DM550

Course introduction

During the last years, both the need of processing spatial entities and the abundance of spatial information, have led to the need of efficiently storing, retrieving and analyzing such data. This course focuses on providing the students with fundamental knowledge, both theoretical and practical, on Spatial Data Management Systems.

More specifically, the emphasis will be given on Spatial database design (logical / physical level), access methods for efficient spatial data processing and Geo-visualization techniques.

Furthermore, there will be an introduction on advanced topics, such as Geospatial data analytics and Mobility data processing and analytics. Finally, the students will have the opportunity to gain hands-on experience with systems, such as PostGIS (the popular spatial extension of PostgreSQL), Java Topology Suite (JTS) and Python GeoPandas.
The course builds on the knowledge obtained in DM564 Database Systems.

In relation to the competence profile of the degree the course has explicit focus on:

  • Describing, analyzing and solving advanced computer science problems using the learned models.
  • Analyzing the advantages and disadvantages of different spatial access methods.
  • Providing the students with expert knowledge in the spatial data management and analysis research field.

Expected learning outcome

The learning objective of the course is that the student demonstrates the ability to:
  • Design a Spatial database both on a logical and a physical level.
  • Use advanced spatial access methods for efficient query processing.
  • Use Geo-visualization techniques for data exploration and visualization of processing results.
  • Combine the aforementioned knowledge in order to build a full stack application that uses and analyses spatial data.

Content

The following main topics are contained in the course:
  • lntroduction to Geospatial data.
  • Logical Design of spatial databases.
  • Physical Design of spatial databases.
  • Advance spatial access methods.
  • Geo-visualization techniques.
  • Geospatial data analytics and Mobility data processing and analytics.

Literature

See itslearning for syllabus lists and additional literature references.

Examination regulations

Exam element a)

Timing

Autumn and January

Tests

Project with oral examination

EKA

N340116102

Assessment

Second examiner: External

Grading

7-point grading scale

Identification

Full name and SDU username

Language

Normally, the same as teaching language

Duration

Oral examination 30 minutes

Examination aids

To be announced during the course.

ECTS value

5

Additional information

Individual project, based on which there will be and oral examination.

Indicative number of lessons

40 hours per semester

Teaching Method

At the faculty of science, teaching is organized after the three-phase model ie. intro, training and study phase.
  • Teaching activities are planned for the foliowing amount of hours: Intro phase (lectures): 20 hours.
  • Training phase: 20 hours, of which 10 are hands-on tutorials and 10 are exercises.
The intro phase includes the theoretical foundation of the topics covered in this course. The training phase is divided into hands-on tutorials and exercises, where the students learn the competences that enable them to transtorm their knowledge into solutions to specific real-world problems by using state of the art systems. In the study phase the students work independently with improving their understanding and their competences regarding the contents of the course.

Activities during the study phase: Programming of smalI tasks and little projects.

Teacher responsible

Name E-mail Department
Panagiotis Tampakis ptampakis@imada.sdu.dk Institut for Matematik og Datalogi (00)

Timetable

Administrative Unit

Institut for Matematik og Datalogi (datalogi)

Team at Educational Law & Registration

NAT

Offered in

Odense

Recommended course of study

Profile Education Semester Offer period

Transition rules

Transitional arrangements describe how a course replaces another course when changes are made to the course of study. 
If a transitional arrangement has been made for a course, it will be stated in the list. 
See transitional arrangements for all courses at the Faculty of Science.