Interactive Techniques for Personal Visual Analytics

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The Internet of Things, increase in online behavior, and a proliferation of connected mobile devices has resulted in an explosion of “big data” related to people's daily lives. Concurrently governments, non-profit organizations and companies are committed to Open Data, providing ready access data that can be freely used, re-used and redistributed by anyone. These changes are extending the concepts of “big data” from the sphere of the expert analyst to the domain of the ordinary person, but to date there is often evidence of a gap between the provision of data and whether people understand or are motivated by the information. The research in this project will target the design and evaluation of novel personal visual analytics techniques and services for making data-based thinking more accessible to the average person: to help people integrate and use external and personal data both for their own decision making and to communicate and interact with the institutions, professionals, services and social organizations with whom they interact in their daily lives. The desktop-based, task-centric model of visual analytics and expert sense-making does not apply to the various contexts in which people can use data in their daily lives, so this research will explore novel techniques for PVA, including mobile, shared and embedded applications. It will focus on three areas particularly important to PVA: context of use; data and visual framing; and engagement and motivation. ***Unlike professional data analysts, people undertake data exploration for different purposes and in different physical, temporal and computing situations. They use different devices appropriate to these situations, such as mobile devices and ambient displays in their homes. Their purpose may be met with a quick glimpse of the data or a more prolonged exploration. How the data are chosen and represented presents key questions of framing, perceptual and situational constraints and appropriate context. An important aspect of this research will involve integration of different data sources (“mashups”) in novel ways: for example, combining personal mobility costs and house prices with projections for civic density initiatives (citizen engagement); or combining daily domestic activity records with energy use in the home to inform conservation efforts. This research will explore visualization and access techniques for flexible data mashups in common information tools like calendars and maps. Finally, visualizations that resonate with people on both an intellectual and emotional level promote engagement, interest, and motivation. This is particularly important when the purpose of the visualization is motivational (such as health tracking) or to promote interest in a topic or initiative ( a key issue in social engagement). We will examine the design and utility of affective visualization techniques for both communication and engagement.