CP4092 Data Visualization Techniques Syllabus:
CP4092 Data Visualization Techniques Syllabus – Anna University PG Syllabus Regulation 2021
COURSE OBJECTIVES:
To develop skills to both design and critique visualizations.
To introduce visual perception and core skills for visual analysis.
To understand technological advancements of data visualization
To understand various data visualization techniques
To understand the methodologies used to visualize large data sets
UNIT I INTRODUCTION AND DATA FOUNDATION
Basics – Relationship between Visualization and Other Fields -The Visualization Process – Pseudo code Conventions – The Scatter plot. Data Foundation – Types of Data – Structure within and between Records – Data Preprocessing – Data Sets
UNIT II FOUNDATIONS FOR VISUALIZATION
Visualization stages – Semiology of Graphical Symbols – The Eight Visual Variables – Historical Perspective – Taxonomies – Experimental Semiotics based on Perception Gibson‘s Affordance theory – A Model of Perceptual Processing.
UNIT III VISUALIZATION TECHNIQUES
Spatial Data: One-Dimensional Data – Two-Dimensional Data – Three Dimensional Data – Dynamic Data – Combining Techniques. Geospatial Data : Visualizing Spatial Data – Visualization of Point Data -Visualization of Line Data – Visualization of Area Data – Other Issues in Geospatial Data Visualization Multivariate Data : Point-Based Techniques – Line Based Techniques – Region-Based Techniques – Combinations of Techniques – Trees Displaying Hierarchical Structures – Graphics and Networks- Displaying Arbitrary Graphs/Networks.
UNIT IV INTERACTION CONCEPTS AND TECHNIQUES
Text and Document Visualization: Introduction – Levels of Text Representations – The Vector Space Model – Single Document Visualizations -Document Collection Visualizations – Extended Text Visualizations Interaction Concepts: Interaction Operators – Interaction Operands and Spaces – A Unified Framework. Interaction Techniques: Screen Space – Object-Space –Data Space – Attribute Space- Data Structure Space – Visualization Structure – Animating Transformations – Interaction Control.
UNIT V RESEARCH DIRECTIONS IN VISUALIZATIONS
Steps in designing Visualizations – Problems in designing effective Visualizations- Issues of Data. Issues of Cognition, Perception, and Reasoning. Issues of System Design Evaluation , Hardware and Applications
COURSE OUTCOMES:
CO1: Visualize the objects in different dimensions.
CO2: Design and process the data for Visualization.
CO3:Apply the visualization techniques in physical sciences, computer science, applied mathematics and medical sciences.
CO4: Apply the virtualization techniques for research projects.
CO5: Identify appropriate data visualization techniques given particular requirements imposed by the data.
TOTAL: 45 PERIODS
REFERENCES
1. Matthew Ward, Georges Grinstein and Daniel Keim, “Interactive Data Visualization Foundations, Techniques, Applications”, 2010.
2. Colin Ware, “Information Visualization Perception for Design”, 4th edition, Morgan Kaufmann Publishers, 2021.
3. Robert Spence “Information visualization – Design for interaction”, Pearson Education, 2nd Edition, 2007.
4. Alexandru C. Telea, “Data Visualization: Principles and Practice,” A. K. Peters Ltd, 2008.