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SDS 416: Visualization and Advanced Data Structures

Course Title

Visualization and Advanced Data Structures

Course Code

SDS 416

Course Type




Year / Semester

1st / 2nd   (subject to change)

Instructor’s Name

Theodoros Christoudias



Lectures / week

1 (2h)

Laboratories / week

1 (2h)

Course Purpose and Objectives

Train students in managing large data sets of various forms, understand their structure and common methods to manipulate them and apply techniques for their visualization. Applications from computational sciences will be used as a demonstration of visualization of scientific data. 

Learning Outcomes

Students will learn to identify the various types of data, efficiently structure the data and identify features in the data via appropriate analysis and visualization. 



 Requirements  -

Course Content

Data collection and management: Scientific data models and formats, structured and unstructured data, data management, classification, queries, mapping and transforming data, annotations and assigning meta-data. Data visualization: Visualization and plotting packages, methods for visualizing large datasets, geo-spatial and temporal data visualization, interactive and real-time visualization, 3D visualization, contouring and isosurfaces, visualization of vector fields.  

Applications from Computational Sciences: Hands-on visualization examples from computational science applications.

Teaching Methodology

Lectures, Exercises, Project


E. Bethel, H. Childs and C. Hansen, “High Performance Visualization: Enabling

Extreme-Scale Scientific Insight”, ISBN 9781439875728

C. Hansen and C. Johnson, “Visualization Handbook”, ISBN-13: 9780123875822

W. Schroeder, K. Martin and B. Lorensen, “Visualization Toolkit: An Object Oriented Approach to 3D Graphics, 4th Edition”, ISBN-13: 978-1930934191 


25% coursework, 75% exam



Publications & Media