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

Rita Sevastjanova; Hanna Schafer; Jurgen Bernard; Daniel Keim; Mennatallah El-Assady

doi:10.1109/MLUI52769.2019.10075563

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

Rita Sevastjanova^*, Hanna Schafer, Jurgen Bernard, Daniel Keim, Mennatallah El-Assady

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

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.

Original language	English
Title of host publication	2019 IEEE Workshop on Machine Learning from User Interaction for Visualization and Analytics, MLUI 2019
Publisher	IEEE
ISBN (Electronic)	9781665440646
DOIs	https://doi.org/10.1109/MLUI52769.2019.10075563
Publication status	Published - 2019
Externally published	Yes
Event	2019 IEEE Workshop on Machine Learning from User Interaction for Visualization and Analytics, MLUI 2019 - Vancouver, Canada Duration: 20 Oct 2019 → …

Publication series

Name	2019 IEEE Workshop on Machine Learning from User Interaction for Visualization and Analytics, MLUI 2019

Conference

Conference	2019 IEEE Workshop on Machine Learning from User Interaction for Visualization and Analytics, MLUI 2019
Country/Territory	Canada
City	Vancouver
Period	20/10/19 → …

Bibliographical note

Funding Information:
We gratefully acknowledge the German Research Foundation (DFG) for financial support within the projects FOR 2111: Questions at the Interfaces (Project-ID 240796339) and Knowledge Generation in Visual Analytics (Project-ID 350399414).

Publisher Copyright:
© 2019 IEEE.

Funding

We gratefully acknowledge the German Research Foundation (DFG) for financial support within the projects FOR 2111: Questions at the Interfaces (Project-ID 240796339) and Knowledge Generation in Visual Analytics (Project-ID 350399414).

Keywords

Gameful Design
Visual Analytics

Access to Document

10.1109/MLUI52769.2019.10075563

Cite this

Sevastjanova, R., Schafer, H., Bernard, J., Keim, D., & El-Assady, M. (2019). Shall we play? - Extending the Visual Analytics Design Space through Gameful Design Concepts. In 2019 IEEE Workshop on Machine Learning from User Interaction for Visualization and Analytics, MLUI 2019 (2019 IEEE Workshop on Machine Learning from User Interaction for Visualization and Analytics, MLUI 2019). IEEE. https://doi.org/10.1109/MLUI52769.2019.10075563

Sevastjanova, Rita ; Schafer, Hanna ; Bernard, Jurgen et al. / Shall we play? - Extending the Visual Analytics Design Space through Gameful Design Concepts. 2019 IEEE Workshop on Machine Learning from User Interaction for Visualization and Analytics, MLUI 2019. IEEE, 2019. (2019 IEEE Workshop on Machine Learning from User Interaction for Visualization and Analytics, MLUI 2019).

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title = "Shall we play? - Extending the Visual Analytics Design Space through Gameful Design Concepts",

abstract = "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.",

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author = "Rita Sevastjanova and Hanna Schafer and Jurgen Bernard and Daniel Keim and Mennatallah El-Assady",

note = "Funding Information: We gratefully acknowledge the German Research Foundation (DFG) for financial support within the projects FOR 2111: Questions at the Interfaces (Project-ID 240796339) and Knowledge Generation in Visual Analytics (Project-ID 350399414). Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE Workshop on Machine Learning from User Interaction for Visualization and Analytics, MLUI 2019 ; Conference date: 20-10-2019",

year = "2019",

doi = "10.1109/MLUI52769.2019.10075563",

language = "English",

series = "2019 IEEE Workshop on Machine Learning from User Interaction for Visualization and Analytics, MLUI 2019",

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Sevastjanova, R, Schafer, H, Bernard, J, Keim, D & El-Assady, M 2019, Shall we play? - Extending the Visual Analytics Design Space through Gameful Design Concepts. in 2019 IEEE Workshop on Machine Learning from User Interaction for Visualization and Analytics, MLUI 2019. 2019 IEEE Workshop on Machine Learning from User Interaction for Visualization and Analytics, MLUI 2019, IEEE, 2019 IEEE Workshop on Machine Learning from User Interaction for Visualization and Analytics, MLUI 2019, Vancouver, Canada, 20/10/19. https://doi.org/10.1109/MLUI52769.2019.10075563

Shall we play? - Extending the Visual Analytics Design Space through Gameful Design Concepts. / Sevastjanova, Rita; Schafer, Hanna; Bernard, Jurgen et al.
2019 IEEE Workshop on Machine Learning from User Interaction for Visualization and Analytics, MLUI 2019. IEEE, 2019. (2019 IEEE Workshop on Machine Learning from User Interaction for Visualization and Analytics, MLUI 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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N1 - Funding Information: We gratefully acknowledge the German Research Foundation (DFG) for financial support within the projects FOR 2111: Questions at the Interfaces (Project-ID 240796339) and Knowledge Generation in Visual Analytics (Project-ID 350399414). Publisher Copyright: © 2019 IEEE.

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Sevastjanova R, Schafer H, Bernard J, Keim D, El-Assady M. Shall we play? - Extending the Visual Analytics Design Space through Gameful Design Concepts. In 2019 IEEE Workshop on Machine Learning from User Interaction for Visualization and Analytics, MLUI 2019. IEEE. 2019. (2019 IEEE Workshop on Machine Learning from User Interaction for Visualization and Analytics, MLUI 2019). doi: 10.1109/MLUI52769.2019.10075563

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

Abstract

Publication series

Conference

Bibliographical note

Funding

Keywords

Access to Document

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