While existing visualization systems excel in exploring datasets and discovering data patterns and insights, challenges remain in automatically generating infographics from exploration-derived visualizations. We propose VisCollage, a computational pipeline that automatically organizes and renders charts from an exploration in a “visual collage”, which is inspired by data journalism and can be viewed as a kind of “partitioned poster infographic”. By analyzing the relation (e.g., drill-down or comparison) between charts established during exploration, VisCollage groups and merges them to reduce data redundancy. In addition, VisCollage automatically identifies a main chart of the exploration and arranges annotations and background charts around it. User studies evaluated from the perspectives of creators, professional data journalists, and general readers indicate that our system assists creators in generating satisfactory visualization summaries of data events, enables the general audience to extract insights from the data through visual collages, and are well received by professionals.

Data exploration systems have become popular tools with which data analysts and others can explore raw data and organize their observations. However, users of such systems who are unfamiliar with their datasets face several challenges when trying to extract data events of interest to them. Those challenges include progressively discovering informative charts, organizing them into a logical order to depict a meaningful fact, and arranging one or more facts to illustrate a data event. To alleviate them, we propose VisGuide—a data exploration system that generates personalized recommendations to aid users’ discovery of data events in breadth and depth by incrementally learning their data exploration preferences and recommending meaningful charts tailored to them. As well as user preferences, VisGuide’s recommendations simultaneously consider sequence organization and chart presentation. We conducted two user studies to evaluate 1) the usability of VisGuide and 2) user satisfaction with its recommendation system. The results of those studies indicate that VisGuide can effectively help users create coherent and user-oriented visualization trees that represent meaningful data events.