Abstract
In the context of analytics applications, the recall of interaction history often happens when users are identifying the root causes of a given problem based on a visual analytics task, which can be interrupted or suspended. The research of analytic provenance focuses on retrieving users’ interaction history, reinstating their reasoning process so that they can quickly resume an interrupted or suspended task. Although many visualization analytic tools are available, they lack extended capabilities for giving access to users’ interaction history in a natural coupling with their actions. We propose a design framework for instrumenting analytic provenance in a mode allowing users to “re-commit” to their tasks. We realize a first experiment to see how one’s history activities has an impact on the way he/she resolves the task. We investigate the interaction possibilities of two design approaches: the user interface (UI) design in which the history path is considered as “put down” in the environment; the user experience (UX) design considers it as a coupling device between the user and the world, being “in hand” mode. The first part of our analysis shows that users use the history path for supporting their reasoning process. However, the indirect coupling between users’ actions and provenance function keeps them outside of the history path so that they cannot easily link it to their current problem. We hypothesize that the “in hand” mode of interaction history will allow a natural coupling between a user’s action and the provenance function, which may lead to a positive user experience. We then propose the lines for designing dynamic history path interaction tools.
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Yang, L., Morizet-Mahoudeaux, P., Guénand, A., Mouloudi, A. (2018). A Design Framework for Instrumenting Analytic Provenance for Problem-Solving Tasks. In: Lokman, A., Yamanaka, T., Lévy, P., Chen, K., Koyama, S. (eds) Proceedings of the 7th International Conference on Kansei Engineering and Emotion Research 2018. KEER 2018. Advances in Intelligent Systems and Computing, vol 739. Springer, Singapore. https://doi.org/10.1007/978-981-10-8612-0_66
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DOI: https://doi.org/10.1007/978-981-10-8612-0_66
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