DS 4200: Information Presentation and Visualization

(CRN:        37442)

Spring 2017 - Prof. Michelle Borkin

Mondays & Wednesdays, 2:50pm - 4:30 pm, Snell Library 035

http://www.ccs.neu.edu/home/borkin/courses/2017Spring/DS4200/

Description

Introduces foundational principles, methods, and techniques of visualization to enable creation of effective information representations suitable for exploration and discovery. Covers the design and evaluation process of visualization creation, visual representations of data, relevant principles of human vision and perception, and basic interactivity principles. Studies data types and a wide range of visual data encodings and representations. Draws examples from physics, biology, health science, social science, geography, business, and economics. Emphasizes good programming practices for both static and interactive visualizations. Creates visualizations in Excel and Tableau as well as Python and open web-based authoring libraries. Requires programming in Python, JavaScript, HTML, and CSS. Requires extensive writing including documentation, explanations, and discussions of the findings from the data analyses and the visualizations.

After completion of the course students should be able to:

Prerequisites

The only required prerequisite course is CS 2510 (or exemption by permission of the instructor).  Topics such as databases, HCI, and data mining (e.g., DS4100) all are very useful for the course but not required prerequisites.  Students should be comfortable with learning new programming languages.

Note: The assignments and projects in this course will expose students to a variety of programming languages including Javascript (i.e., D3) and Python as well as tools including Tableau for visualization design and implementation.

Textbooks

Required

This course will utilize two textbooks:  one to cover basic visualization theory and methodology, and one to cover basic perceptual theory as applied to visualizations.

Visualization Analysis and Design by Tamara Munzner

(**Available for free online through the library.)

Visual Thinking for Design by Colin Ware

Recommended

Although not required, the following books are recommended as additional references to help expand on the visualization theory and skills discussed in class.  These books will be cited and referred to during lecture as appropriate to help direct the student to the appropriate resource.

Design for Information by Isabel Meirelles

The Functional Art: An introduction to information graphics and visualization by Alberto Cairo

Information Visualization: Perception for Design by Colin Ware

Interactive Data Visualization for the Web (free online version) by Scott Murray


The Visual Display of Quantitative Information by Edward Tufte

Course Components

Lectures

Each class will be split into two parts: lecture and class activity.  The lecture component will be ~45-60 minutes in duration covering foundational topics, and the remainder of the class will be devoted to an in-class activity to further explore topics and skills relevant to the course topics.  Activities will include such exercises as programming tutorials, design critiques, journal paper discussions, in-class mini-hacks, and student-led final project update presentations.  

Class Participation

Students are expected to participate both in-class as well as online through the course’s Piazza discussion group.  A student’s participation grade (see Grading section below) will be composed of their in-class participation as well as activity on Piazza.

Readings

Assigned reading will be given to read in advance of each lecture and listed in the Course Schedule online.  Readings will be drawn from the required textbooks as well as online supplemental material.

Homework

There will be ~weekly homework assignments over the course of the semester.  Each assignment will require the student to apply the concepts discussed in the readings and in-class lectures to both programming assignments for the actual building and implementation of static and interactive visualizations as well as short writing assignments (e.g., design critiques).  The homework assignments are an individual assessment and should not be completed in groups.

Final Project

For the term-long final project, students will work in groups of 2-3 people to create an interactive visualization incorporating the concepts discussed in the course.  Throughout the semester there will be mandatory final project progress deadlines including a preliminary project proposal.  The required final project milestones and deliverables will be incorporated into, or sometimes replace, the weekly homework assignment.  As part of the final project, in addition to the final interactive web-based visualization, students will be required to produce a website to host the visualization, a demo video, and an in-class short presentation.  

The final projects will revolve around working with data from and interacting with community non-profit organizations in Boston through partnership with the Northeastern University Center of Community Service.

Grading

Grades will be broken down as follows:

Course Policies

Late Policy
All homework and project related due dates are final and provided in the course schedule.  No assignments will be accepted for credit after the deadline.

If you have a verifiable medical condition or other special circumstances that interfere with your coursework please email (m.borkin@northeastern.edu) as soon as possible.

Academic Integrity Policy
A commitment to the principles of academic integrity is essential to the mission of Northeastern University.  The promotion of independent and original scholarship ensures that students derive the most from their educational experience and their pursuit of knowledge.  Academic dishonesty violates the most fundamental values of an intellectual community and undermines the achievements of the entire University.

For more information, please refer to the Academic Integrity Web page.