We present PolyChrome, an application framework for creating web-based collaborative visualizations that can span multiple devices. The framework supports (1) co-browsing new web applications as well as legacy websites with no migration costs (i.e., a distributed web browser); (2) an API to develop new web applications that can synchronize the UI state on multiple devices to support synchronous and asynchronous collaboration; and (3) maintenance of state and input events on a server to handle common issues with distributed applications such as consistency management, conflict resolution, and undo operations. We describe PolyChrome's general design, architecture, and implementation followed by application examples showcasing collaborative web visualizations created using the framework. Finally, we present performance results that suggest that PolyChrome adds minimal overhead compared to single-device applications.

Collaborative work is characterized by participants seamlessly transitioning from working together (coupled) to working alone (decoupled). Groupware should therefore facilitate smoothly varying coupling throughout the entire collaborative session. Towards achieving such transitions for collaborative exploration and search, we propose a protocol based on managing revisions for each collaborator exploring a dataset. The protocol allows participants to diverge from the shared analysis path (branch), study the data independently (explore), and then contribute back their findings onto the shared display (merge). We apply this concept to collaborative search in multidimensional data, and propose an implementation where the public view is a tabletop display and the private views are embedded in handheld tablets. We then use this implementation to perform a qualitative user study involving a real estate dataset. Results show that participants leverage the BEM protocol, spend significant time using their private views (40% to 80% of total task time), and apply public view changes for consultation with collaborators.

We present an evaluation of text entry methods for tabletop displays given small display space allocations, an increasingly important design constraint as tabletops become collaborative platforms. Small space is already a requirement of mobile text entry methods, and these can often be easily ported to tabletop settings. The purpose of this work is to determine whether these mobile text entry methods are equally useful for tabletop displays, or whether there are unique aspects of text entry on large, horizontal surfaces that influence design. Our evaluation consists of two studies designed to elicit differences between the mobile and tabletop domains. Results show that standard soft keyboards perform best, even at small space allocations. Furthermore, occlusion-reduction methods like Shift do not yield significant improvements to text entry; we speculate that this is due to the low ratio of resolution per surface units (i.e., DPI) for current tabletops.

Analysts are increasingly encountering datasets that are larger and more complex than ever before. Effectively exploring such datasets requires collaboration between multiple analysts, who more often than not are distributed in time or in space. Mixed-presence groupware provide a shared workspace medium that supports this combination of co-located and distributed collaboration. However, collaborative visualization systems for such distributed settings have their own cost and are still uncommon in the visualization community. We present Hugin, a novel layer-based graphical framework for this kind of mixed-presence synchronous collaborative visualization over digital tabletop displays. The design of the framework focuses on issues like awareness and access control, while using information visualization for the collaborative data exploration on network-connected tabletops. To validate the usefulness of the framework, we also present examples of how Hugin can be used to implement new visualizations supporting these collaborative mechanisms.