The goal of our research was to understand the effects of display size on interaction zones as it applies to interactive systems. Interaction zone models for interactive displays are often static and do not consider the size of the display in their definition. As the interactive display ecosystem becomes more size diverse, current models for interaction are limited in their applicability. This paper describes the results of an exploratory study in which participants interacted with and discussed expectations with interactive displays ranging from personal to wall-sized. Our approach was open-ended rather than grounded in existing interaction zone models in order to explore potential differences in interaction zones and distances. We found that the existence of different interaction zones and the distance at which these zones are relevant are dependent on display size. In discussion of the results, we explore implications of our findings and offer guidelines for the design of interactive display systems.

Visual exploration of relationships within large, textual datasets is an important aid for human sensemaking. By understanding computed, structural relationships between entities of different types (e.g., people and locations), users can leverage domain expertise and intuition to determine the importance and relevance of these relationships for tasks, such as intelligence analysis. Biclusters are a potentially desirable method to facilitate this, because they reveal coordinated relationships that can represent meaningful relationships. Bixplorer, a visual analytics prototype, supports interactive exploration of textual datasets in a spatial workspace with biclusters. In this paper, we present results of a study that analyzes how users interact with biclusters to solve an intelligence analysis problem using Bixplorer. We found that biclusters played four principal roles in the analytical process: an effective starting point for analysis, a revealer of two levels of connections, an indicator of potentially important entities, and a useful label for clusters of organized information.

As analysts attempt to make sense of a collection of documents, such as intelligence analysis reports, they need to “connect the dots” between pieces of information that may initially seem unrelated. We conducted a user study to analyze the cognitive process by which users connect pairs of documents and how they spatialize connections. Users created conceptual stories that connected the dots using a range of organizational strategies and spatial representations. Insights from our study can drive the design of data mining algorithms and visual analytic tools to support analysts' complex cognitive processes.

When high-dimensional data is visualized in a 2D plane by using parametric projection algorithms, users may wish to manipulate the layout of the data points to better reflect their domain knowledge or to explore alternative structures. However, few users are well-versed in the algorithms behind the visualizations, making parameter tweaking more of a guessing game than a series of decisive interactions. Translating user interactions into algorithmic input is a key component of Visual to Parametric Interaction (V2PI) [13]. Instead of adjusting parameters, users directly move data points on the screen, which then updates the underlying statistical model. However, we have found that some data points that are not moved by the user are just as important in the interactions as the data points that are moved. Users frequently move some data points with respect to some other 'unmoved' data points that they consider as spatially contextual. However, in current V2PI interactions, these points are not explicitly identified when directly manipulating the moved points. We design a richer set of interactions that makes this context more explicit, and a new algorithm and sophisticated weighting scheme that incorporates the importance of these unmoved data points into V2PI.

Large, high-resolution displays have enormous potential to aid in scenarios beyond their current usage. Their current usages are primarily limited to presentations, visualization demonstrations, or conducting experiments. In this paper, we present a new usage for such systems: an everyday workspace. We discuss how seemingly small large-display design decisions can have significant impacts on users' perceptions of these workspaces, and thus the usage of the space. We describe the effects that various physical configurations have on the overall usability and perception of the display. We present conclusions on how to broaden the usage scenarios of large, high-resolution displays to enable frequent and effective usage as everyday workspaces while still allowing transformation to collaborative or presentation spaces.

Cyber analytics focuses on increasing the safety and soundness of our digital infrastructure. The volume, size and velocity of these datasets make the analysis challenging on current work environments and tools. A cyber analytics work environment should enable multiple, simultaneous investigations and information foraging, as well as provide a solution space for organizing data. As such, various workflow visualization tools are used to help users track their analysis, reuse effective workflows, and test hypotheses. Also, the use of large display workspaces can provide new opportunities for improving visual analytics in cyber security. In this work, we present a prototype workspace for analysts where the analytic process is maintained in the workspace. Thus, we are able to present analysts with visual states of their data throughout the investigation, in which real-time changes can be made to any previous state, and analysts can backtrack through their investigation.