Here are a collection of resources to start developing a theoretical and critical framework for data visualization. You may also wish to explore opportunities for courses, workshops, and other trainings at Cornell.


Data Points by Nathan Yau
"This book is for those interested in the process of design and analysis, where each chapter represents a step towards visualization that means something. It is about visualization that is more than large printed numbers with clipart. It is about making sense of data. Visualization creation is iterative, and the cycle is always a little different for each new dataset."
"In The Functional Art, instructor Alberto Cairo explains how information graphics and visualizations are cognitive tools that extend our perception and how we can use them to see beyond lists of numbers, variables, and phenomena to identify patterns and trends that would be invisible otherwise."


"“In this tutorial, we discussed best practices for data visualization, including three general principles: (1) design and layout matter: choose a design and layout that facilitate your message to your audience; (2) avoid clutter: the use of ink that does not contribute to your story will likely distract your audience and confuse the message; and (3) use color purposely and effectively: do not overuse color, but use it purposely to convey your message”

Grammar of Graphics is a conceptual framework for thinking about effective data visualization. The premise is to think about visualization as the interlocking and interaction of elements of data, statistical transformations, gemoetric representation, and positional representations. Layered Grammar of Graphics is captures the most recent iteration of Grammar of Graphics, and is written by the developer behind ggplot2.


Feminist Data Visualization: a 2016 talk by D'Ignazio and Klein:

"In this paper, we begin to outline how feminist theory may be productively applied to information visualization research and practice. Other technology- and design-oriented fields such as Science and Technology Studies, Human-Computer Interaction, Digital Humanities, and Geography/GIS have begun to incorporate feminist principles into their research. Feminism is not (just) about women,but rather draws our attention to questions of epistemology – who is included in dominant ways of producing and communicating knowledge and whose perspectives are marginalized. We describe potential applications of feminist theory to influence the information design process as well as to shape the outputs from that process."

From the forthcoming Data Feminism:

"Chapter One: Bring Back the Bodies: Why do data science and visualization need feminism? Because bodies are missing from the data we collect, from the decisions made about their analysis and display, and from the field of data science as a whole. Bringing back the bodies is how we can right this power imbalance." Read a community draft of the forthcoming text.