The Typology of Decision-Making Tasks for Visualization

This intermediate representation gives you an easy and flexible way of describing decision problems in visualization.

Visualization systems are often designed to help people make decisions: selecting a treatment, choosing a design, identifying risk, prioritizing resources, or deciding what to do next. Yet many visualization task taxonomies describe low-level analytical activities, such as filtering, searching, comparing, or deriving values, rather than the higher-level decision processes that those activities support.

This typology provides a concise language for describing decision-making in visualization. It focuses on how information is evaluated and transformed during a decision, rather than on a specific domain, dataset, chart type, or interaction technique.

Why use this typology?

Use this typology when you want to:

describe the decision-making process supported by a visualization system;
communicate with domain experts about decision goals;
identify missing support in an existing design;
structure a visualization workflow before sketching the interface;
compare decision-support systems across domains;
translate a complex decision problem into a workflow of user decisions;
evaluate decision-support systems based on their alignment with the decision workflows.

The typology is especially useful because it is domain-agnostic. It can describe decision-making in healthcare, engineering, policy, finance, scientific discovery, urban planning, and many other areas. The same three tasks can describe decisions made by humans, algorithms, or human-AI systems.