Standard user applications provide a range of cross-cutting interaction techniques that are common to virtually all such tools: selection, filtering, navigation, layer management, and cut-and-paste.We present VisDock, a JavaScript mixin library that provides a core set of these cross-cutting interaction techniques for visualization, including selection (lasso, paths, shape selection, etc), layer management (visibility, transparency, set operations, etc), navigation (pan, zoom, overview, magnifying lenses, etc), and annotation (point-based, region-based, data-space based, etc). To showcase the utility of the library, we have released it as Open Source and integrated it with a large number of existing web-based visualizations. Furthermore, we have evaluated VisDock using qualitative studies with both developers utilizing the toolkit to build new web-based visualizations, as well as with end-users utilizing it to explore movie ratings data. Results from these studies highlight the usability and effectiveness of the toolkit from both developer and end-user perspectives.

We present Munin, a software framework for building ubiquitous analytics environments consisting of multiple input and output surfaces, such as tabletop displays, wall-mounted displays, and mobile devices. Munin utilizes a service-based model where each device provides one or more dynamically loaded services for input, display, or computation. Using a peer-to-peer model for communication, it leverages IP multicast to replicate the shared state among the peers. Input is handled through a shared event channel that lets input and output devices be fully decoupled. It also provides a data-driven scene graph to delegate rendering to peers, thus creating a robust, fault-tolerant, decentralized system. In this paper, we describe Munin's general design and architecture, provide several examples of how we are using the framework for ubiquitous analytics and visualization, and present a case study on building a Munin assembly for multidimensional visualization. We also present performance results and anecdotal user feedback for the framework that suggests that combining a service-oriented, data-driven model with middleware support for data sharing and event handling eases the design and execution of high performance distributed visualizations.

Building a distributed user interface (DUI) application should ideally not require any additional effort beyond that necessary to build a non-distributed interface. In practice, however, DUI development is fraught with several technical challenges such as synchronization, resource management, and data transfer. In this paper, we present three case studies on building distributed user interface applications: a distributed media player for multiple displays and controls, a collaborative search system integrating a tabletop and mobile devices, and a multiplayer Tetris game for multi-surface use. While there exist several possible network architectures for such applications, our particular approach focuses on peer-to-peer (P2P) architectures. This focus leads to a number of challenges and opportunities. Drawing from these studies, we derive general challenges for P2P DUI development in terms of design, architecture, and implementation. We conclude with some general guidelines for practical DUI application development using peer-to-peer architectures.