Text Input on Multitouch Tabletop Displays

Tabletops offer great opportunities for information visualization and visual analytics. Users benefit from possibilities like collaborative analysis and direct touch interaction. Providing interaction techniques that support users in accomplishing tasks is especially important, since “interaction is the fuel for analytic discourse” [Thomas and Cook 2005]. Tasks frequently needed in visual analytics are dynamic querying and query refinement. Text input is of particular relevance for these tasks because the specification of a query is often conducted via textual input. Since tabletops are commonly operated by direct multitouch input, users have to be supplied with text input techniques specifically designed for this domain. However, little research has been done to determine adequate text input techniques for tabletop users. Existing soft keyboard designs are limited to a key map, providing no additional feedback like tactile affordances or visual clues, to the user. However, soft keyboards offer no tactile guidance like physical keyboards do. Hence, typing error detection gets demanding and slow. In order to overcome this obstacle, we have designed two novel text input techniques. Both techniques aim at simplifying error detection by several explicit visual feedback components. We have evaluated both designs in a preliminary user study with six participants. Results show that users benefit from our feedback components when checking for errors. Moreover, we supply a short demo video.