Academic Staff
Course Outcome
Data visualization is the study of graphical data representation. The primary goal of data visualization is to communicate information clearly and efficiently to users via graphical artefacts. The course addresses issues, concepts and principles of data and information visualization.
The purpose of this course is the acquisition of knowledge in modern techniques, methods of data and information visualization and familiarization with the appropriate tools. Using paradigms, the essential characteristics are presented to improve the skills of students in visual data representation.
After completing the course the student will have acquired the necessary knowledge and skills to:
Understand data visualization design and procedures.
Be familiar with data models, patterns and colors and their role in visual data representation
Understand the concepts of perception and cognition – recognition of graphic representations
Be able to implement optical data representations.Be familiar with data visualization programming tools
Course Syllabus
-
Introduction to Data and Information Visualization
-
Visualization Design
-
Visualization Procedures
-
Models
-
Graphical Representations Perception
-
Patterns and their role in visualization
-
Colors and their role
-
Cognition - Recognition – Conception
-
Interaction Ι
-
Interaction ΙΙ
-
Applications of visualization (In art, science etc.)
-
Maps
-
Visualization Trees & NetworksVisualization Tools (Prefuse, JFreeChart etc.)
RECOMMENDED BIBLIOGRAPHY
- Few, Stephen (2009): Now You See It: Simple Visualization Techniques for Quantitative Analysis. Analytics Press
- Ware, Colin (2008): Visual Thinking: for Design. Morgan Kaufmann
- Card, Stuart K., Mackinlay, Jock D. and Shneiderman, Ben (eds.) (1999): Readings in Information Visualization: Using Vision to Think. Academic Press
- Tufte, Edward R. (1983): The Visual Display of Quantitative Information. Cheshire, CT, Graphics Press
- Journal: Information Visualization Journal, published quarterly by Palgrave Macmillan,
- Conferences: IEEE's VisWeek, η οποία περιέχει τις InfoVis και VAST (Visual Analytics Science and Technology)
- CHI (Computer-Human Interaction), SIGGRAPH.