Time Schedule:
Brett E. Shelton
INFO 498
Seattle Campus
Various topics in informatics.
Class description
Introduces principles and techniques for the visualization of content and relationships in large datasets of quantitative and symbolic data. Survey includes sense making and perceptual aspects of data visualization, including graphical methods for specialized types of data (time series, categorical data, etc.), and appropriate software and computer systems for data visualization, including interactive, dynamic graphics. Specific issues include paradigms for information display and human/computer interfaces.
Student learning goals
General method of instruction
Through a combination of lectures, demonstrations and hands-on lab exercises, students learn to: • Identify appropriate data visualization techniques given particular requirements imposed by the data. • Interpret meaning from various multidimensional formats and presentation techniques. • Create multiple versions of technology-based visualizations using techniques from various software packages
Recommended preparation
Prerequisites: Experience with basic functions of the computer interface. Students are encouraged to either be in the process of preparing data or have access to data appropriate for their particular field of interest, although this is not required.
Class assignments and grading
Course Overview - Lecture We will be exploring the question of what is a visualization and why should we use visualizations for quantitative data. In doing so, we will address theoretical concepts and examine case studies that show the importance of effective visualizations in real world settings.
Next, we look at how to interpret meaning in visualizations. Elements of cognitive science theory are addressed, and we will practice techniques to help with our interpretations.
An additional objective will center on how to create meaning with your own visualizations. We will examine appropriate forms for representation and review design considerations.
Course Overview – Lab In the lab portion of the course, the main objective is to expose you to a variety of common and different digital visualization software tools, and to provide you with an opportunity become familiar with the different kinds of interfaces. Lab assignments will focus on providing practice using real-world data.
Although software availability may change slightly, lab assignments will utilize the following software: • Excel • Illustrator • ArcView • SPSS • MatLab • Others? – Visio, etc.
The idea behind providing exposure and implementation of various software methods and techniques is that it provides practice for creative recognition. You will think about ways of visually representing ideas in ways that you previously were not able to, and have the confidence to initiate a variety of software through your experiences.
The various requirements for the course will be weighted as follows when computing grades:
Weekly quizzes 20% Weekly assignments 20 Proposal for final project 5 Final project 35 Presentation of final project 10 Participation in class and lab 10
