Many (if not all) visualizations are about making comparisons in the data. I’ve spent a lot of effort to come up with ways of thinking about comparisons, or (if you prefer) to think about visualization in terms of comparison. These were summarized in a 2017 paper (it has a 2018 publication data) “Considerations for Visualizing Comparison”.

The paper gives a “process” for developing a visualization in terms of comparison: first identify what the comparison problem is, figure out what the abstract comparative challenge is (number of items, size of items, complexity of relationships), choose a scalability strategy to address the challenge (scan sequentially, select subset, summarize somehow), and choose a comparative design (juxtaposition, superposition, explicit encoding). I call these last 3 the “three threes” and they give a categorization of comparative challenges and strategies.

The paper An Algebraic Process for Visualization Design by Gordon Kindlmann and Carlos Scheidegger is something that influenced my thinking a lot. It is a great example of visualization formalism that has a big and practical payoff in how we think about visualizations. It came back to mind recently.

The paper has a concise message that fits well in the “re-papering” format: changes to the data should correspond/correlate to changes in the visualization. The paper holds up well to time (it is from 2014).

A quick walkthrough of showing how to get started with Tableau. The data set is one we will use in CS765 Fall 2025: Life expectancy data from around the world. I won’t get as far as making “good” visualizations - but it will give you some hints on how to get started with the data set, and with Tableau.

This is a tutorial on how to get started with Tableau. It is targeted for CS765 students (but should be OK for anyone). I am using the Census Data set I used in my 2024 Class. The tutorial will walk you through what I did to make a few initial pictures. This will show you some of the quirks of Tableau, and the dataset.

Let’s look at the “Airline Route Maps” (the ones that are in the back of an airline magazine) as a way to explore the importance of task and how understanding task and data can lead to novel designs. It will show us a different way to think about node link diagrams more generally.

Core lesson: think about what a visualization makes easy to see. Different representations make some things easier, and harder. And some issues with dealing with geographic data in the US.

This comes from a New York Times story from August, 2024 The Geography of Unequal Recovery. Curiously, this page doesn’t show up well in my web browser, the images are from the mobile app (on an iPad).

Here is the “headline” (what appeared in the app “front page” that intrigued me):

This is a lesson on Axis Truncation for Line Graphs. It was inspired by a graph in the New York Times.

Don’t make the wrong thing easy to see. Here’s a real example from my own work where a seemingly innocent line graph was misleading, and needed some serious redesign.

Line charts can be used (with caution) even when the X axis is neither interval or continuous.

In this snack, we look at “value over time” graphs in two different iPhone apps. It’s a good opportunity to connect design and task with a comparative critique.

I believe that critique is a valuable skill for both practicing and learning Visualization (see Tutorial 4: Critique). The book Discussing Design is a great resource to learn it.

Critique is the practice of examining something carefully to understand it and learn, often in a “discussion” format. Critique is a key tool in learning about Vis, and in improving design (for Vis, and in general). It is also a generally useful skill that can be learned with practice.

If you need to pick a book to get started, I recommend Alberto Cairo’s the The Truthful Art.

A surprising amount of visualization design and analysis can be wrapped up in the single question “What does this visualization make easy to see?”

This is the closest thing to a “primary textbook” for my class. The course shares a similar philosophy to the book, and we’ll read almost all of the chapters. The UW library has electronic copies, so students do not need to buy it.