Developing an Extended Task Framework for Exploratory Data Analysis Along the Structure of Time

Abstract

Exploratory data analysis of time-oriented data is an important goal that Visual Analytics has to tackle. When users from real-world domains are asked about time-oriented tasks, they often refer to the unique structure of time (e.g., calendars, primitives, etc.). Several task frameworks have been developed, but none of them combines a complete, systematic approach with explicit attention to the structure of time. To fill this gap, we aim for complementing an established task framework with a rule set that explicitly models the structure of time for tasks. This rule set allows to consistently formulate tasks for evaluating time-oriented data analysis methods.