Your Data, Your Vis: Personalizing Personal Data Visualizations
Abstract
Personal Visualizations (PV) provide visual feedback on personal data, e.g., regarding physical activity or energy consumption. They are a vital part of many behavior change technologies (BCT) and Personal Informatics tools. Feedback can be presented in various ways, for example using counts and graphs, stylized displays, metaphoric displays, narrative information, data physicalisations, or even living plants. The properties of a PV are likely to influence its effectiveness towards reaching a goal. However, users’ perceptions and preferences regarding different PVs seem to vary strongly, rendering a one-size-fits-all approach unsuitable. To investigate whether preferences for certain PVs coincide with personality or gender, we conducted a lab study with three example PVs: Donut, Glass, and Creature. Indeed, the results of our lab study are a first indicator that there is a relationship between personality traits and preferences for different PVs. High scores on extraversion and openness, for example, positively correlated with a preference for Creature. In contrast, high scores in conscientiousness negatively correlated with a preference for Creature. Further research is necessary to better understand how truly personalized PVs can be realized, which, in turn, might fit better into people’s lives and thereby be more effective.
Domains
Computer Science [cs]Origin | Files produced by the author(s) |
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