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Expanding Research Methods for a Realistic Understanding of Personal Visualization
IEEE Computer Graphics and Applications
|March 22, 2017
Summary
Personal visualizations offer everyday benefits but pose evaluation challenges. New empirical methods are needed for a realistic understanding of these unique data tools.
Area of Science:
- Human-Computer Interaction
- Data Visualization
- Personal Informatics
Background:
- Personal visualizations aim to bring data visualization benefits into daily life.
- These visualizations handle diverse personal data and contexts, complicating evaluation.
- Existing empirical methods may not fully address the unique challenges of personal visualizations.
Purpose of the Study:
- To highlight the challenges in evaluating personal visualizations.
- To advocate for new and adapted empirical approaches for this emerging field.
- To promote a more realistic understanding of personal visualization effectiveness.
Main Methods:
- Review of current empirical approaches in visualization research.
- Identification of gaps and limitations in existing methods for personal contexts.
- Proposal for a broader perspective incorporating methods from other disciplines.
Main Results:
- Personal visualizations present unique evaluation hurdles due to their goals, data, and context.
- A wider range of empirical methods is necessary for robust assessment.
- Adaptation of existing methods and development of new ones are crucial.
Conclusions:
- A flexible and open-minded approach to empirical methods is essential.
- Developing tailored evaluation strategies will enhance the understanding and design of personal visualizations.
- This research calls for interdisciplinary collaboration to advance the field.
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