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Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
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Exploring the Personal Informatics Analysis Gap: "There's a Lot of Bacon".
IEEE Transactions on Visualization and Computer Graphics
|October 5, 2021
Summary
Personal informatics tools often lack flexible data analysis features. This study highlights a gap in supporting diverse user needs for analyzing personal data, especially for health conditions like asthma.
Area of Science:
- Human-Computer Interaction
- Personal Informatics
- Data Visualization
Background:
- Personal informatics (PI) research focuses on self-tracking for self-knowledge.
- Current PI tools emphasize data collection and insight generation, neglecting flexible data analysis.
- This leads to rigid analytical pipelines that don't support diverse user engagement with personal data.
Purpose of the Study:
- To identify and address the personal informatics analysis gap.
- To explore how individuals engage with and analyze personal data in context.
- To inform the design of more flexible and user-centered data analysis tools.
Main Methods:
- Literature review of personal informatics and visualization research.
- Multistage longitudinal study involving asthmatics analyzing personal air quality data.
- Qualitative analysis of participant data engagement patterns and motivations.
Main Results:
- Participants had diverse and evolving goals for data analysis.
- Data exploration patterns included playful and serendipitous discovery.
- Users were often reluctant to use standalone analysis tools independently.
- A significant gap exists in designing flexible personal data analysis tools.
Conclusions:
- Flexible data analysis is crucial for effective personal informatics.
- Future tools should support diverse user goals and exploratory behaviors.
- Designing for serendipity and user-led exploration is key for personal data analysis tools.
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