DataTweener: a demonstration of a tweening engine for incremental visualization of data transforms

With the development and advancement of new data interaction modalities, data exploration and analysis has become a highly interactive process situating the user in a session of successive queries. With rapidly changing results, it becomes difficult for the end user to fully comprehend transformations, especially the transforms corresponding to complex queries. We introduce "data tweening" as an informative way of visualizing structural data transforms, presenting the users with a series of incremental visual representations of a resultset transformation. We present transformations as ordered sequences of basic structural transforms and visual cues. The sequences are generated using an automated framework which utilizes differences between the consecutive resultsets and queries in a query session. We evaluate the effectiveness of tweening as a visualization method through a user study.