We present Gesture Morpher, a tool for prototyping and testing multi-touch interactions based on video recordings of target application behaviors, e.g., a sequence of screenshots recorded by a screen capture tool. Gesture Morpher extracts continuous behaviors from video recordings, such as transformations of UI content, and suggests a set of multi-touch interactions that are suitable for achieving these behaviors. Designers can easily test different interactions on a touch device with visual response that is automatically synthesized from the video recording, all without any programming. We discuss a range of multi-touch interaction scenarios Gesture Morpher supports, our method for extracting continuous interaction behaviors from video recordings, and techniques for associating touch-input with the output effect extracted from the videos.

Selection is a fundamental operation in interactive visualization applications. Although techniques such as clicking and lassoing items of interest are sufficient for basic selections, a more sophisticated interaction mechanism is required for expressing complex queries to modify or generalize existing selections. The ability to perform these advanced selections is critical for effective analysis within visualization systems. On touch-based devices such as tablets, however, expressing advanced selections is difficult due to the absence of a cursor and modifier keys. In this work, we address this limitation by presenting new interaction techniques that leverage a person's non-dominant hand. We use these techniques for advanced selection operations such as expanding, modifying, and replicating existing selections. Further, we introduce a method for performing generalized selection on tablet devices that provides a fluid mechanism to control the attributes and parameters of selection.

Abstract The use of multiple coordinated views (MCV) in data visualization provides analytic power because it allows a person to explore data under a variety of different perspectives. Since this design pattern utilizes multiple visualizations and requires coordinated interactions across the views, a clever use of screen space is vital and many synchronized interface operations must be provided. Bringing this design pattern to tablet computers is challenging due to their small display size and the absence of keyboard and mouse input. In this article, we explain important design considerations for MCV visualization on tablets and describe a prototype MCV visualization system we have built for the iPad. The design is based on the principles of maximizing screen space for data presentation, promoting consistent interactions across visualizations, and minimizing occlusion from a person's hands.

Tablet computers now offer screen sizes and computing capabilities that are competitive with traditional desktop PCs. Their popularity has grown tremendously, but we are just beginning to see information visualization applications designed for this platform. One potential reason for this limited development is the challenge of designing and implementing a multi-touch interface for visualizations on mobile, tablet devices. In this work, we identify the primary challenges that touch screen interactions pose for information visualization applications. We explore the design space of multi-touch interactions for visualizations and present a prototype information visualization application using a specific technique, a dynamic scatterplot, for an iPad.

Visualizing sets to reveal relationships between constituent elements is a complex representational problem. Recent research presents several automated placement and grouping techniques to highlight connections between set elements. However, these techniques do not scale well for sets with cardinality greater than one hundred elements. We present OnSet, an interactive, scalable visualization technique for representing large-scale binary set data. The visualization technique defines a single, combined domain of elements for all sets, and models each set by the elements that it both contains and does not contain. OnSet employs direct manipulation interaction and visual highlighting to support easy identification of commonalities and differences as well as membership patterns across different sets of elements. We present case studies to illustrate how the technique can be successfully applied across different domains such as bio-chemical metabolomics and task and event scheduling.

As more applications move from the desktop to touch devices like tablets, designers must wrestle with the costs of porting a design with as little revision of the UI as possible from one device to the other, or of optimizing the interaction per device. We consider the tradeoffs between two versions of a UI for working with data on a touch tablet. One interface is based on using the conventional desktop metaphor (WIMP) with a control panel, push buttons, and checkboxes -- where the mouse click is effectively replaced by a finger tap. The other interface (which we call FLUID) eliminates the control panel and focuses touch actions on the data visualization itself. We describe our design process and evaluation of each interface. We discuss the significantly better task performance and preference for the FLUID interface, in particular how touch design may challenge certain assumptions about the performance benefits of WIMP interfaces that do not hold on touch devices, such as the superiority of gestural vs. control panel based interaction.