  Despite decision-making being a vital goal of data visualization, little work
has been done to differentiate the decision-making tasks within our field.
While visualization task taxonomies and typologies exist, they are often too
granular for describing complex decision goals and decision-making processes,
thus limiting their potential use in designing decision-support tools. In this
paper, we contribute a typology of decision-making tasks that were iteratively
refined from a list of design goals distilled from a literature review. Our
typology is concise and consists of only three tasks: choose, activate, and
create. Originally proposed by the scientific community, we extend and provide
definitions for these tasks that are suitable for the visualization community.
Our proposed typology offers two benefits. First, it facilitates the
composition of decisions using these three tasks, allowing for flexible and
clear descriptions across varying complexities and domains. Second, diagrams
created using this typology encourage productive discourse between
visualization designers and domain experts by abstracting the intricacies of
data, thereby promoting clarity and rigorous analysis of decision-making
processes. We motivate the use of our typology through four case studies and
demonstrate the benefits of our approach through semi-structured interviews
conducted with experienced members of the visualization community, comprising
academic and industry experts, who have contributed to developing or publishing
decision support systems for domain experts. Our interviewees composed diagrams
using our typology to delineate the decision-making processes that drive their
decision-support tools, demonstrating its descriptive capacity and
effectiveness.
