About

Data and emotion seem like they are on the opposite ends of the spectrum. Data has an impression of being cold-hard truth, and emotion is a highly subjective feeling. But that’s not always the case. Data is often being collected by someone with certain goals and subjective biases, and emotion is often an objective means to spark action. For the longest time, communication of data prioritised efficiency. In doing so, we confine ourselves to the same visual structures and rob audiences from a deeper level of engagement.

We can begin to break free from this by asking what happens when we think of data-viz as a medium of expression instead of a tool for analysis. I’ve started to see such sparks from influential data-viz practitioners, and my goal is to engage and contribute to the discourse. This sensibility is certainly not appropriate in all contexts, and there are pitfalls of manipulation and weaponization of data where emotion is involved. Which is why I believe having these conversations are important.

At its core, this is a website that anyone can point at, to get an understanding of expressive data visualization, asking how and where it has its place in the communication of information. It’s put together via a collection of conversations with people in the industry, those who practice data-viz day in and day out, accompanied by my own thoughts and sketches conceived from these conversations.

Motivation

The current norm of data-viz, as popularized by Edward Tufte, is to reduce the data to ink ratio, which comes from the actual ink used when printing data visualizations.

Good graphics should include only data-Ink. Non-Data-Ink is to be deleted everywhere where possible. The reason for this is to avoid drawing the attention of viewers of the data presentation to irrelevant elements. The goal is to design a display with the highest possible data-ink ratio (that is, as close to the total of 1.0), without eliminating something that is necessary for effective communication.

This makes sense in the context of efficient communication. But to me, and to many others in the current zeitgeist, efficiency is not the only metric that should be used to gauge communication. Effective communication, especially of data, should have more context, of who collected it, and of what emotion the author is trying to convey. This is more the case when communication is intended to move an audience to take action, or at least consider & think about the topic being conveyed.

In the introduction of his book Data Points, Nathan Yau brings up an apt comparison that connects to a reasoning of the ‘why’ behind this—“Visualization is a way to represent data, an abstraction of the real world, in the same way that the written word can be used to tell different kinds of stories.”

Giorgia Lupi’s work on data humanism has been central to this movement, but we honestly need more conversation to seep into how data communicators think today, and what they default to.

Audience

Folks in the data-viz industry who are looking to explore outside the preset templates of data viz (bar charts, pie charts, etc.) to communicate ideas with an emotional backing.