Personal Visualization and Personal Visual Analytics

Abstract

Data surrounds each and every one of us in our daily lives, ranging from exercise logs, to archives of our interactions with others on social media, to online resources pertaining to our hobbies. There is enormous potential for us to use these data to understand ourselves better and make positive changes in our lives. Visualization (Vis) and visual analytics (VA) offer substantial opportunities to help individuals gain insights about themselves, their communities and their interests; however, designing tools to support data analysis in non-professional life brings a unique set of research and design challenges. We investigate the requirements and research directions required to take full advantage of Vis and VA in a personal context. We develop a taxonomy of design dimensions to provide a coherent vocabulary for discussing personal visualization and personal visual analytics. By identifying and exploring clusters in the design space, we discuss challenges and share perspectives on future research. This work brings together research that was previously scattered across disciplines. Our goal is to call research attention to this space and engage researchers to explore the enabling techniques and technology that will support people to better understand data relevant to their personal lives, interests, and needs.

Personal Informatics, Self-Insight, and Behavior Change: A Critical Review of Current Literature

“…A specialized field of "personal visual analytics" or "personal visualizations" is now emerging, which focuses specifically on presenting personally relevant information in the most productive way (Huang et al, 2015). However, there are possible barriers to such a presentation having the intended effect of creating actionable insight and subsequent changes in behavior.…”

The personal cockpit

“…These tasks are closer in nature to microinteractions than the personal analytic task scenarios given above since they demand less attention. However, such monitoring or awareness tasks may nonetheless include an analytic component, where people make use of information visualizations to support insitu decision making [100].…”

“…This opportunity has been recently exploited by industry with the introduction of numerous tracking devices and has resulted in the recent 'quantified self' movement -the collection and analysis of one's own personal data -aimed at making use of this data [100], for example to benefit users' health. However, the activities of data collection and analysis are primarily conducted separately, for instance by periodic recommendations (e.g.…”

“…In contrast, we posit that supporting in-situ analysis -allowing users to analyse data directly in the situations where they are applied -will help users gain the most benefit from their data. Based on their in-depth survey, Huang et al [100] suggest that incorporating analysis tasks into users' daily activities can help encourage adoption of analysis tools. For instance, presenting data about commuting habits at the time of the activity [69] can help users make informed choices.…”

“…For example, two extensive surveys on interactive information visualization, one by Heer and Shneiderman [89] and another by Yi et al [212] describe how interactions such as item selection, exploration of different representations, data filtering, and navigating through various levels of abstraction are essential to sensemaking in visual analytics. Although personal information visualization occupies a smaller scope than intensive domain expert analytic tasks, Huang et al [100] note that human input can help to overcome the limitations of using automated data-mining techniques to identify patterns. Further, these operations should be coordinated across multiple views.…”