T2015-316 A method for providing guidance and feedback during gesture-driven data exploration
A critical challenge in the data exploration process is discovering and issuing the “right” query, especially when the space of possible queries is large. Additionally, increased size and complexity of data can cause users to become overwhelmed. Effective feedback must be provided during an exploratory querying step to guide users to the intended query. This problem of exploratory query specification is exacerbated by the use of interactive user interfaces driven by mouse, touch, or next-generation, three-dimensional, motion capture-based devices; which, are often imprecise due to jitter and sensitivity issues. Therefore, new methods are needed to improve the query environment for users of multiple devices.
Researchers at The Ohio State University developed the SnapToQuery method that guides users through the query space by providing interactive feedback during the query specification process by "snapping" to the users likely intended queries. Feedback is provided to the user during 3-D gestures by "snapping" to the contours of an n-dimensional density representation of data. The researchers posit that users intended quires are aligned with the contour of the cluster is where the data carnality change is large. It allows for them to vastly improve the interactive performance. SnapToQuery focuses on the snapping feedback during data exploration gestures and using the information/ insights from data to provide feedback. The SnapToQuery method has great potential to improve the efficacy of data exploration on multiple devices.