You will find various links to resources that will be helpful for this course. Additional resources will be added throughout the semester.


Here are some reference books recommended for this course:

Here are some other books related to visualization that are highly recommended:

Here are some books that are available for free online:

And, although not a book per se, the InfoVis Wiki is an amazing resource:


We will also reference several books that are available freely online for USF students through the library and Safrai Books Online:

The online availability of some of these books on Safari Books Online may change over time.


We will primarily be using Processing and D3 in this class. However, we will explore and use other visualization languages and toolkits.

  • Processing
    A free, open source programming language and environment. Allows for rapid prototyping of visual, interactive programs.

  • Data-Driven Documents (d3)
    A free, small Javascript library well suited for interactive data visualization on the web.

  • Many Eyes
    A free online visualization tool that allows users to upload data, select a visualization technique, and share the resulting visualization. Provided by IBM Research and the IBM Cognos software group.

  • Tableau Public
    A free service allowing uses to publish interactive data visualizations to the web.

    A website that allows users to create and share visualizations, and hosts datasets and visualization challenges.

For homework and projects, make sure to double-check whether you must use Processing or if you can use a visualization toolkit instead.

Data Sets

Many of the toolkits/websites listed above host datasets as well. We will need a wide variety of data sets for this course. There is no shortage of data, but finding data sets that we can work with in this course can be difficult. We need well-formatted data that is moderate in size.

Here are a few resources where you can download free-to-use datasets:

You are also welcome to generate your own data sets. For an example of what can be done by tracking day-to-day details, see the Feltron Report.


There are many other data visualization courses with different takes on the field.

This unordered list is by no means a comprehensive collection of data visualization courses, and the links may disappear over time.


There are many videos, especially from TED, covering topics in data visualization.

Additional videos will be added as they are shown in class.


There are many web articles about data visualization that we will discuss in class.

The list above is unsorted. Keep in mind that many of these links may disappear over time.

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