M259 Visualizing Information (4 units)


Jieliang (Rodger) Luo | jieliang@ucsb.edu
George Legrady

Lecture/lab: Tues-Thurs 3:30pm-5:20pm Ellings Studio 2611
Office Hours: Tues 2:00pm-3:30pm Ellings Studio 2611

M259 is a project-based course focused on techniques of information retrieval and the language of algorithmic visualization. Course concentration on fundamentals of data visualization and design, with an emphasis on data query, data analysis and processing, and visualization in 2D frequency and 3D interactive spatial visualization.

Data mining, Knowledge Discovery, Culture Analytics through MySQL
Goals: Discover unexpected, interesting patterns in a large dataset
Source: 90 million datasets of library check-outs/check-ins, Seattle Public Library source

2D Frequency Data Mapping - Visual Language Basics with Processing
Goals: Acquire visual language basics, visualize data in java-based Processing
Source: 90 million datasets of library check-outs/check-ins, Seattle Public Library source

3D Interactive Visualization
Goals: Design in 3D, interactive space, implement algorithms in java-based Processing
Source: 90 million datasets of library check-outs/check-ins, Seattle Public Library source

Final Student Project
Goals: Student defined project building on skills acquired through previous assignments
Source: Student determined

Knowledge acquired through the course:
1) Learn to explore and retrieve significant data from a dataset with MySQL
2) Develop skills in the fundamentals of visual language expressed through programming
3) Visualize abstract data to reveal patterns and relationships
4) Normalize data to enhance legibility and coherence
5) Apply algorithms by which to organize data
6) Implement interactivity within 3D volumetric visualization
7) Correlate various data sources through JSON and APIs
8) Exhibit projects online with p5.js or d3.js

Algorithms

FPTree Algorithm [wiki] | Karl FPtree [code]
SOM [demo] | Skupin | Stacy Hespanha [2006] | Godwin [demo] | SOM Package
Google Correlate | Nearest Neighbor article
Principal Component Analysis

minim | processing.sound | History | Frequency Modulation | Moog | Noise | ADSR | soundFile | vocoder | AmbikaDemo

3D Work-in-progress

Graphics of Large Datasets, Unwin, Theus, Hofmann (Statistics & Computing)[UCSB online]
Visualizing Data [Examples] Ben Fry (Online text by the co-author of Processing)