FA550 Data Visualization Applications
Course Catalog Description
Introduction
Campus | Fall | Spring | Summer |
---|---|---|---|
On Campus | X | X | |
Web Campus | X | X |
Instructors
Professor | Office | |
---|---|---|
Brian Moriarty | brian.moriarty@stevens.edu | Babbio Center – 629 |
More Information
Course Outcome
- Develop knowledge of tools for visualizing datasets
- Develop a programmatic understanding of translating data into useful visual forms
- Develop a critical vocabulary to engage and discuss information visualization
- Develop an understanding of data visualization theory
- Understanding of ethical considerations for data visualization
Course Resources
Textbook
- Storytelling with Data -- Cole Knaflic; ISBN: 978-1119002253
- R Data Visualization Recipes -- Vitor Bianchi Lanzetta; ISBN: 9781788398312
- GGPlot2 Essentials: Great Data Visualization in R
- R: Recipes for Analysis, Visualization, and Machine Learning -- Viswa Viswanathan, Shanthi Viswanathan, Atmajitsinh Gohil, Chiu Yu- Wei; ISBN: 9781787289598
- Mastering Gephi Network Visualization -- Ken Chevren; ISBN: 9781783987344
- Learning Tableau 2020, 4th Edition -- Milligan, Josh; ISBN: 978-1800200364
Additional References
-
There are many solid texts available through Safari Books Online including, but certainly not limited to:
- Interactive Data Visualization for the Web, by Scott Murray; ISBN: 978-1-4493-3973-9
- Data Visualization with d3.js, by Swizec Teller; ISBN: 978-1-78216-000-7
- Data Visualization: A Successful Design Process, by Andy Kirk; ISBN: 978-1-84969-346-2
- The Functional Art, by Albert Cairo; ISBN: 978-0-13-304118-7
- It is likely more valuable in this course to be concerned with current trends in data visualization. Some good resources include:
- Joshua Milligan’s site, Viz Painter
- Nathan Yau’s Flowing Data
- Michael Sandberg’s Data Visualization Blog
- Towards Data Science
- Various Twitter feeds, including Jeffrey Heer, Mike Bostock, Ola Rosling, Steve Duenes, Stephen Few, David McCandless, Hannah Fairfield, Ben Fry, Kim Rees and many others...
- Podcasts: Data Viz Today, datastori.es
- LinkedIn Groups: Visual Analytics , Data Mining, Statistics, Big Data, and Data Visualization
- Other Resources: bl.ocks.org, Stack Overflow, Google Groups, Visual.ly, Flowing Data, ilovecharts, Visualizing.org ,Information is Beautiful, 538, Visualizing Data, Visual Complexity, Pictures of Numbers
TABLEAU LICENSING:
Are your students new to Tableau? Share our free Data Analytics for University Students guide to help them get started. Students can continue using Tableau after the class is over by individually requesting their own one-year license through the Tableau for Students program here Need help? Find answers to frequently asked questions here.
TABLEAU COURSE MATERIALS: All Tableau course materials are available in the shared Files directory for this course.
Data Sets:
Grading
Grading Policies
Homework 50%
Discussion Board Submissions 10%
Individual Project Proposal 10%
Individual Project Final Submission 30%
Lecture Outline
Topic | Reading | Assignments | |
---|---|---|---|
Week 01 | Introduction to Data Visualization | Required: Knaflic, Introduction and Ch. 1 Lanzetta: Installation and Introduction + Plotting Two Continous Variables | In-Class: Review Syllabus Install R, Tableau, Gephi; Sign up for Datawrapper, Plotly |
Week 02 | Introduction to ggplot2 | Required: Knaflic, Ch. 2 Lanzetta, | In-Class:
ggplot2 overview and
exercises
Understand the Context
exercise Due: ggplot2 assignment due via Canvas |
Week 03 | Introduction to summarizing with dplyr | Required: Knaflic, Ch. 3 | In-Class: additional ggplot2 content dplyr overview and usage Choosing an Effective Visual exercise Presentation of select homework submissions |
Week 04 | General visualization principles using R | Required: Knaflic, Ch. 4 | In-Class: Additional R visualization methods Identify and Eliminate Clutter exercise Due: Assembling an R visualization presentation assignment due via canvas |
Week 05 | Introduction to Creating Charts and Dashboards Using Tableau | Required: Knaflic, Ch. 5 | In-Class: Introduction to Tableau 2020.3 Focus attention exercise Presentation of select homework submissions |
Week 06 | Introduction to Mapping in Tableau | Required: Knaflic, Ch. 6 | In-Class: Introduction to Mapping in Tableau 2020.3 Think like a designer exercise Due: Tableau charts, dashboards, and mapping assignment due via Canvas |
Week 07 | (More) Advanced Topics in Tableau | Required: Knaflic, Ch. 7 | In-Class: Introduction to (more) Advanced topics in Tableau 2020.3 Tell a story exercise Presentation of select homework submissions |
Week 08 | Introduction to Gephi and Network Visualization Solutions | Required: Knaflic, Ch. 8 | In-Class: Introduction to Gephi Storytelling with data process exercise Due: Gephi /Network Visualization assignment submission due via Canvas |
Week 09 | Using R and Tableau as Complementary Tools | Required: Knaflic, Ch. 9 | In-Class: Working with R and Tableau together Developing a story exercise Presentation of select homework submissions |
Week 10 | Introduction to Datawrapper and Online Visualization Tools | Required: Knaflic, Ch. 10 | In-Class: Review of online data visualization tools Real-world scenarios exercise Due: Using online visualization tools assignment due via Canvas |
Week 11 | Visualization Applications 1 | In-Class:
Additional topics in data
visualization
TBD in-class exercise
Presentation of select
homework submissions Due: Final project proposal due via Canvas |
|
Week 12 | Visualization Applications 2 | In-Class: Additional topics in data visualization TBD in-class exercise Presentation of select project proposal submissions | |
Week 13 | Project Review 1 | Final project presentation 1 (Draft) | In-Class: Presentations by cohort 1 of draft project |
Week 14 | Project Review 2 | Final project presentation 2 (Draft) | In-Class: Presentations by cohort 2 of draft project Due: Final project submission due via Canvas |