Interactive Techniques for Personal Visual Analytics

物联网、在线行为的增加以及互联移动设备的激增导致了与人们日常生活相关的大数据爆炸式增长。与此同时，各国政府、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、重新使用和重新分发。这些变化正在将“大数据”的概念从专家分析师的领域扩展到普通人的领域，但到目前为止，经常有证据表明，数据的提供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，使基于数据的思考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，用于自己的决策，并与他们在日常生活中互动的机构、专业人员、服务和社会组织进行沟通和互动。基于桌面、以任务为中心的视觉分析和专家感知模型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；以及参与度和动机。

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.