We are a team of visualization researchers at the University of Utah. Our interests include the process of designing and developing visualizations, visualization for biology, visualization frameworks, and, more generally, visualization of big, heterogeneous, and complex datasets.
Blog And News
Quantitative studies are usually confined to conditions where all factors can be controlled, making them less suitable to evaluate complex visualization systems.
User studies are a powerful tool to evaluate visualization techniques. In our recent CHI paper Evaluating Multivariate Network Visualization Techniques Using a Validated Design and Crowdsourcing Approach we present a crowdsourced study comparing two common network visualization techniques: node link-diagrams and adjacency matrices. We’re hardly the first ones to run such a study (see for example Ghnoiem et al. and Okoe et al.), although ours is different from other work as it focuses on the attributes associated with nodes and links in the networks, and our designs are highly interactive. If you’re a network geek, please check out the full paper, but in short, we found various pros...
In a previous post, Alex reviewed why dashboards are problematic when visualizing COVID-19 data. This week I take a deeper look into how states are using dashboards to communicate with COVID data with their constituents.
Our deep-dive resulted in a grading system that enables a quick comparative overview across states and a more detailed breakdown of the dashboard attributes.
How to Grade a Dashboard?
Luckily for me, the foundation for our grading rubric came in the form of a checklist from the COVID Tracking Project, run by The Atlantic. The Project focuses on grading states by the types and completeness of data they publish and make accessible for public use. While this work is invaluable, as a vis researcher, I wanted to focus on the presentation of this data to the public.
There are three rubrics our dashboard grading system uses:
- Visualization best practices
- What COVID...
The COVID-19 pandemic of 2020 has negatively impacted our lives in many ways. The anxiety felt by many is amplified by the obsessive consultation of the latest numbers and statistics about cases, testing rates, deaths, and so on. Both the public and experts have turned to data visualizations to understand what is going on, as data visualization is a powerful tool to discover and communicate trends and relationships. Government agencies, news organizations, and academic labs have published a plethora of graphs and dashboards tracking minute details, sometimes with deceiving precision.
In addition to graphics such as the famous abstract “flattening the curve” illustration, data visualizations have been widely used to report on COVID-19 cases, death, and related metrics. Visualizations of these datasets have influenced decision making, both on a policy and on a personal level: plots of rapidly increasing cases have contributed to the increasing awareness of the problem and to the adherence to the often difficult counter-measures. The academic...
As of today, the Visualization Design Lab has a blog!
Why another data visualization blog?
A lot of visualization researchers have been avid bloggers for years. Eagereyes was an early academic visualization blog, and now there’s a lot of momentum on Medium, with the Multiple Views blog focusing on academic research, while the Data Vis Societies’ Nightingale blog/journal has a broader, non-academic perspective. Through a blog format, we’re making vis research more accessible to other researchers and practitioners alike!
Why not post on Medium or WordPress?
This blog is on our website, and that’s a deliberate decision. We want to control what we post and how it looks, but most importantly we want to have control over the content and be able to guarantee it is online, even in 20 years. Who knows what Medium’s or WordPress’, other blogging sites’ plans may be. Will they switch to a pay-per-view model? Will they go bankrupt? Using...