Visual Analystics Information Visualization--Table of contents

Blog content from the University of Sydney (University of Sydney) COMP5048 Visual Analytics class notes, copyright owner Prof. Seokhee Hong

Topics

Approximate schedule: Topics is subject to the change

Week 1:introduction

• Visual analysis and visualization of information
• Visual Analytics Visualization
• Information Visualization Information visualization
• Network visualization (Graph Drawing) Web visualization
• Aesthetics Aesthetic Requirements
• Graph Drawing Algorithms Drawing algorithm
• Research challenges challenges
• Big Complex Data Large complex
• Visualisation Challenge Visualization Challenge

Week 2:hierarchical Data Visualisation

• Tree Drawing Algorithms algorithm
1. Terminology
2. Layered Drawing
3. Radial Drawing
4. Hv-drawing
5. Other representation
• Tree Visualisation Methods method
1. Dendrogram system tree Diagram (tree-like plot representing kinship)
2. Hyperbolic tree Browser hyperbola
3. Space-filling tree space-filled trees
4. Treemap
5. Icicle Trees (adjacency Diagram)
6. Information Slice and Sunburst diagrams
7. Cone Tree cone of trees
8. Polyplane
9. Phyllo Tree
10. Beamtree Tree with columnar body
11. Collapsible cylindrical Trees detachable cylinder tree
12. Botanical Tree of Botany

Week 3:visual Analytics Guest lecturesweek4:drawing undirected Graphs:force Directed Methods Force-guided method to draw a non-directed graph

Force-directed Methods

Many variations
1. Spring & Electrical Force
2. Barycenter method
3. Force simulating graph theoretic distance
4. Magnetic field
5. General Energy function
6. Constraints

Week 4:network data visualisationweek 5:multivariate/multidimensional data visualisationweek 6:temporal/dynamic data Vi Sualisationweek 7:big/complex Data visualisationweek 8:hci Evaluation methodsintroduction

Visual Analytics aims to facilitate the data analytics process using information visualisation.

Information Visualisation aims to make good pictures of abstract information, such as stock prices, health data, Social networks, and software diagrams.

The Challenge for Visual Analytics are to design and implement effective visualisation methods T Hat produce geometric representation of complex data so, data analysts from various domains can visually inspect compl Ex data and carry out critical decision making.

This unit would provide Visualisaiton techniques and fundamental algorithms to achieve good visualisation of abstract information.

The purpose of visual analysis is to analyze the characteristics of data by highlighting the information visualization technology.

The purpose of information visualization is to make the abstract information easy to observe, and the purpose is to observe;

The main challenge of visual analysis is to find efficient visualization methods .

There will be a number of visualization techniques and basic algorithms , hoping that the user can have basic data structure , algorithm , programming Foundation.

Basic Knowledge in
Data Structures
algorithms
programming?

Visual Analystics Information Visualization--Catalog