A standard (single-column) bar chart can effectively visualize a sorted list of numeric records. However, the chart height limits the number of visible records. To show more records, the bars could be made thinner (which could hinder identifying records individually), and scrolling requires interaction to see the overview. Treemaps have been used in practice in non-hierarchical settings for dense visualization of numeric data. Alternatively, we consider wrapped bars, a multi-column bar chart that uses length instead of area to encode numeric values. We compare treemaps and wrapped bars based on their design characteristics, and graphical perception performance for comparison, ranking, and overview tasks using crowdsourced experiments. Our analysis found that wrapped bars perceptually outperform treemaps in all three tasks for dense visualization of non-hierarchical, sorted numeric data.

Despite its grounding in creativity techniques, merging multiple source sketches to create new ideas has received scant attention in design literature. In this paper, we identify the physical operations that in merging sketch components. We also introduce cognitive operations of reuse, repurpose, refactor, and reinterpret, and explore their relevance to creative design. To examine the relationship of cognitive operations, physical techniques, and creative sketch outcomes, we conducted a qualitative user study where student designers merged existing sketches to generate either an alternative design, or an unrelated new design. We compared two digital selection techniques: freeform selection, and a stroke-cluster-based "object select" technique. The resulting merge sketches were subjected to crowdsourced evaluation of these sketches, and manual coding for the use of cognitive operations. Our findings establish a firm connection between the proposed cognitive operations and the context and outcome of creative tasks. Key findings indicate that reinterpret cognitive operations correlate strongly with creativity in merged sketches, while reuse operations correlate negatively with creativity. Furthermore, freeform selection techniques are preferred significantly by designers. We discuss the empirical contributions of understanding the use of cognitive operations during design exploration, and the practical implications for designing interfaces in digital tools that facilitate creativity in merging sketches.

Collaborative visual analytics (CVA) involves sensemaking activities within teams of analysts based on coordination of work across team members, awareness of team activity, and communication of hypotheses, observations, and insights. We introduce a new type of CVA tools based on the notion of "team-first" visual analytics, where supporting the analytical process and needs of the entire team is the primary focus of the graphical user interface before that of the individual analysts. To this end, we present the design space and guidelines for team-first tools in terms of conveying analyst presence, focus, and activity within the interface. We then introduce InsightsDrive, a CVA tool for multidimensional data, that contains team-first features into the interface through group activity visualizations. This includes (1) in-situ representations that show the focus regions of all users integrated in the data visualizations themselves using color-coded selection shadows, as well as (2) ex-situ representations showing the data coverage of each analyst using multidimensional visual representations. We conducted two user studies, one with individual analysts to identify the affordances of different visual representations to inform data coverage, and the other to evaluate the performance of our team-first design with exsitu and in-situ awareness for visual analytic tasks. Our results give an understanding of the performance of our team-first features and unravel their advantages for team coordination.

People generally remember locations in visual spaces with respect to spatial features and landmarks. Geographical maps provide many spatial features and hence are easy to remember. However, graphs are often visualized as node-link diagrams with few spatial features. We evaluate whether adding static spatial features to node-link diagrams will help in graph revisitation. We discuss three strategies for embellishing a graph and evaluate each in a user study. In our first study, we evaluate how to best add background features to a graph. In the second, we encode position using node size and color. In the third and final study, we take the best techniques from the first and second study, as well as shapes added to the graph as virtual landmarks, to find the best combination of spatial features for graph revisitation. We discuss the user study results and give our recommendations for design of graph visualization software.

Today's large and high-resolution displays coupled with powerful graphics hardware offer the potential for highly realistic 3D virtual environments, but also cause increased target acquisition difficulty for users interacting with these environments. We present an adaptation of semantic pointing to object picking in 3D environments. Essentially, semantic picking shrinks empty space and expands potential targets on the screen by dynamically adjusting the ratio between movement in visual space and motor space for relative input devices such as the mouse. Our implementation operates in the image-space using a hierarchical representation of the standard stencil buffer to allow for real-time calculation of the closest targets for all positions on the screen. An informal user study indicates that subjects perform more accurate pointing with semantic 3D pointing than without.