Interactive Techniques for Personal Visual Analytics

物联网、上网行为的增加以及联网移动设备的激增导致了与人们日常生活相关的“大数据”的爆炸式增长。同时，政府、非营利组织和公司都致力于开放数据，提供随时可用的数据，任何人都可以自由使用、再利用和再分发。这些变化正在将“大数据”的概念从专业分析师的领域扩展到普通人的领域，但迄今为止，经常有证据表明，在提供数据与人们是否理解或受到信息的激励之间存在差距。该项目的研究目标是设计和评估新颖的个人视觉分析技术和服务，以使基于数据的思维更容易为普通人所接受：帮助人们整合和使用外部和个人数据，既用于自己的决策，也用于与日常生活中与之互动的机构、专业人士、服务和社会组织进行沟通和互动。基于桌面的、以任务为中心的可视化分析模型和专家意义构建并不适用于人们在日常生活中使用数据的各种环境，因此本研究将探索PVA的新技术，包括移动、共享和嵌入式应用。它将侧重于对PVA特别重要的三个领域：使用环境；数据和视觉框架；参与和动力。与专业数据分析师不同，人们为了不同的目的，在不同的物理、时间和计算情况下进行数据探索。他们使用适合这些情况的不同设备，例如移动设备和家中的环境显示器。他们的目的可能是快速浏览一下数据，或者进行更长的探索。如何选择和表示数据提出了框架、感知和情境约束以及适当背景的关键问题。这项研究的一个重要方面将涉及以新颖的方式整合不同的数据源（“混搭”）：例如，将个人流动成本和房价与公民密度计划（公民参与）的预测结合起来；或者将日常家庭活动记录与家庭能源使用情况结合起来，为节能工作提供信息。本研究将探索常见信息工具（如日历和地图）中灵活数据混搭的可视化和访问技术。最后，在智力和情感层面上与人们产生共鸣的可视化可以促进参与、兴趣和动机。当可视化的目的是激励（如健康跟踪）或促进对主题或倡议的兴趣（社会参与的关键问题）时，这一点尤为重要。我们将研究情感可视化技术在沟通和参与方面的设计和应用。

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.