Additional Resources

Key Points

Introduction	Visualizations are an important method of interacting with information. Maps are great examples of visualizations: studying maps can help us understand how to convey information effectively Visualization is about managing the viewer’s attention. Visualizations should be accessible to the widest possible range of viewers. Visualizations are not objective tools of conveying information. They can be misused to manipulate. Context is important: make sure your context and visualization agree with one another!
What makes a visualization effective? Co-creating best practices	All of us have interacted with visualizations in one form or another. Use examples of data visualizations to co-create best practices.
Accessible Visualizations	Accessibility should be a core goal of data visualization. Some viewers may have difficulty distinguishing certain combinations of colours. These colour combinations should be avoided or supplemented by an additional channel of visualization (e.g. shape) to support understanding. Visualizations should include descriptive alternative text for screen readers and link to a machine-readable table for the underlying data.
The Cognition of Visual Information	Visual cognition depends crucially on attention, state of mind, goals, and expectations. There are visual features that our visual system can comprehend in less than 200 ms When conjoining these features, finding a target becomes a serial search and therefore slow and difficult. Our brain can comprehend summaries of ensembles quickly, even without recalling the attributes of individual elements There are feature hierarchies that make certain attributes easier/faster to comprehend than others Humans are prone to blindness to change between images, as well as blind to elements of an image or scene that our attention isn’t focused on.
Space	First key point. Brief Answer to questions. (FIXME)
Working with Colour	First key point. Brief Answer to questions. (FIXME)
Visual Hierarchy and Gestalt Psychology	First key point. Brief Answer to questions. (FIXME)
Choosing a Type of Visualization	Be careful to tailor your choice of visualization to the type of data and the type of information you are trying to convey Pie charts only work for parts-to-whole relationships, i.e. proportional data If relative differences are important in line charts, including the zero-point can be misleading. In bar charts, the area of the bar is proportional to the value displayed, thus leaving out the zero point in these types of charts can lead to confusion.
Interactive Visualizations	FIXME
Data Visualization & Society	First key point. Brief Answer to questions. (FIXME)
Wireframing a Visualization	Wireframing is the practice of designing on paper before going to the computer. Wireframing is common practice in web development, and helps us proto-type and discuss visualizations. We are more likely to give and accept feedback on sketches than on computer designs. Improving a visualization is fun!
Data Visualization: A Walkthrough in Python	matplotlib and seaborn are powerful libraries for generating visualizations Matching the type of visualization to your type of data can drastically improve readability Choosing an informative and high-contrast colour palette can help make the figure viewable to a wide range of viewers
Data Visualization: A Walkthrough in Python with Altair	altair is a powerful library for generating (interactive) visualizations Matching the type of visualization to your type of data can drastically improve readability Choosing an informative and high-contrast colour palette can help make the figure viewable to a wide range of viewers
A Gallery of Figures

This section collects a number of additional resources about data visualizations.

Edward Tufte’s book “The Visual Display of Quantitative Information” is a classic staple of data visualization. it is often available used in second-hand bookstores and well worth a read.
Colin Ware “Information Visualization: Perception for Design” is a great in-depth textbook on how cognition and perception interact with design. It is a textbook, though, so Takes some dedication to read. It makes a pretty good reference, too.
Nature Methods published a series of short articles on data visualization, here’s the whole collection. I don’t know whether they’re freely available, though.
“Calling Bullshit”, a class taught at the University of Washington by Carl Bergstrom and Jevin West, has a number of videos and texts about data visualization, which are free and great
Healy + Enns wrote a great summary paper on pre-attentive processing, which is accessible to people who aren’t visualization researchers and worth a read
The Psychological Bulleting published two reviews on Gestalt Psychology in 2012, with the first part focusing on perceptual grouping and figure-ground organization, and the second part covers modern developments regarding the generaul conceptual and theoretical frameworks that underlie Gestalt ideas.]

Data Visualization: Additional Resources

Key Points

Additional Resources