Shall we play? - Extending the Visual Analytics Design Space through Gameful Design Concepts

Many interactive machine learning workflows in the context of visual analytics encompass the stages of exploration, verification, and knowledge communication. Within these stages, users perform various types of actions based on different human needs. In this position paper, we postulate expanding th...

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Bibliographic Details
Published in2019 IEEE Workshop on Machine Learning from User Interaction for Visualization and Analytics (MLUI) pp. 1 - 9
Main Authors Sevastjanova, Rita, Schafer, Hanna, Bernard, Jurgen, Keim, Daniel, El-Assady, Mennatallah
Format Conference Proceeding
LanguageEnglish
Published IEEE 20.10.2019
Subjects
Gameful Design
Visual Analytics
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Summary:Many interactive machine learning workflows in the context of visual analytics encompass the stages of exploration, verification, and knowledge communication. Within these stages, users perform various types of actions based on different human needs. In this position paper, we postulate expanding this workflow by introducing gameful design elements. These can increase a user's motivation to take actions, to improve a model's quality, or to exchange insights with others. By combining concepts from visual analytics, human psychology, and gamification, we derive a model for augmenting the visual analytics processes with game mechanics. We argue for automatically learning a parametrization of these game mechanics based on a continuous evaluation of the users' actions and analysis results. To demonstrate our proposed conceptual model, we illustrate how three existing visual analytics techniques could benefit from incorporating tailored game dynamics. Lastly, we discuss open challenges and point out potential implications for future research.
DOI:10.1109/MLUI52769.2019.10075563