Fang Dezhi, Hohman Fred, Polack Peter, Sarker Hillol, Kahng Minsuk, Sharmin Moushumi, al'Absi Mustafa, Chau Duen Horng
College of Computing, Georgia Tech.
Dept. of Computer Science, University of Memphis.
Proc ACM Int Conf Ubiquitous Comput. 2017 Sep;2017:237-240. doi: 10.1145/3123024.3123170.
We present Discovery Dashboard, a visual analytics system for exploring large volumes of time series data from mobile medical field studies. Discovery Dashboard offers interactive exploration tools and a data mining motif discovery algorithm to help researchers formulate hypotheses, discover trends and patterns, and ultimately gain a deeper understanding of their data. Discovery Dashboard emphasizes user freedom and flexibility during the data exploration process and enables researchers to do things previously challenging or impossible to do - in the web-browser and in real time. We demonstrate our system visualizing data from a mobile sensor study conducted at the University of Minnesota that included 52 participants who were trying to quit smoking.
我们展示了发现仪表盘，这是一个用于探索来自移动医疗领域研究的大量时间序列数据的可视化分析系统。发现仪表盘提供交互式探索工具和一种数据挖掘主题发现算法，以帮助研究人员提出假设、发现趋势和模式，并最终更深入地理解他们的数据。发现仪表盘在数据探索过程中强调用户的自由度和灵活性，并使研究人员能够在网络浏览器中实时完成以前具有挑战性或无法做到的事情。我们展示了我们的系统对明尼苏达大学进行的一项移动传感器研究的数据进行可视化，该研究包括52名试图戒烟的参与者。
