We present gravity navigation (GravNav), a family of multi-scale navigation techniques that use a gravity-inspired model for assisting navigation in large visual 2D spaces based on the interest and salience of visual objects in the space. GravNav is an instance of topology-aware navigation, which makes use of the structure of the visual space to aid navigation. We have performed a controlled study comparing GravNav to standard zoom and pan navigation, with and without variable-rate zoom control. Our results show a significant improvement for GravNav over standard navigation, particularly when coupled with variable-rate zoom. We also report findings on user behavior in multi-scale navigation.

The most common techniques for navigating in multiscale visual spaces are pan, zoom, and bird’s eye views. However, these techniques are often tedious and cumbersome to use, especially when objects of interest are located far apart. We present the PolyZoom technique where users progressively build hierarchies of focus regions, stacked on each other such that each subsequent level shows a higher magnification. Correlation graphics show the relation between parent and child viewports in the hierarchy. To validate the new technique, we compare it to standard navigation techniques in two user studies, one on multiscale visual search and the other on multifocus interaction. Results show that PolyZoom performs better than current standard techniques.

We propose the notion of composite visualization views (CVVs) as a theoretical model that unifies the existing coordinated multiple views (CMV) paradigm with other strategies for combining visual representations in the same geometrical space. We identify five such strategies--called CVV design patterns--based on an extensive review of the literature in composite visualization. We go on to show how these design patterns can all be expressed in terms of a design space describing the correlation between two visualizations in terms of spatial mapping as well as the data relationships between items in the visualizations. We also discuss how to use this design space to suggest potential directions for future research.

Finding patterns and trends in spatial and temporal datasets has been a long studied problem in statistics and different domains of science. This paper presents a visual analytics approach for the interactive exploration and analysis of spatiotemporal correlations among multivariate datasets. Our approach enables users to discover correlations and explore potentially causal or predictive links at different spatiotemporal aggregation levels among the datasets, and allows them to understand the underlying statistical foundations that precede the analysis. Our technique utilizes the Pearson's product-moment correlation coefficient and factors in the lead or lag between different datasets to detect trends and periodic patterns amongst them.

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.

Multitouch surfaces are becoming prevalent, but most existing technologies are only capable of detecting the user’s actual points of contact on the surface and not the identity, posture, and handedness of the user. In this paper, we define the concept of extended multitouch interaction as a richer input modality that includes all of this information. We further present a practical solution to achieve this on tabletop displays based on mounting a single commodity depth camera above a horizontal surface. This will enable us to not only detect when the surface is being touched, but also recover the user’s exact finger and hand posture, as well as distinguish between different users and their handedness. We validate our approach using two user studies, and deploy the technique in a scratchpad tool and in a pen + touch sketch tool.

We present a method for automatically building typographic maps that merge text and spatial data into a visual representation where text alone forms the graphical features. We further show how to use this approach to visualize spatial data such as traffic density, crime rate, or demographic data. The technique accepts a vector representation of a geographic map and spatializes the textual labels in the space onto polylines and polygons based on user-defined visual attributes and constraints. Our sample implementation runs as a Web service, spatializing shape files from the OpenStreetMap project into typographic maps for any region.

Electronic games are starting to incorporate in-game telemetry that collects data about player, team, and community performance on a massive scale, and as data begins to accumulate, so does the demand for effectively analyzing this data. In this paper, we use examples from both old and new games of different genres to explore the theory and design space of visualization for games. Drawing on these examples, we define a design space for this novel research topic and use it to formulate design patterns for how to best apply visualization technology to games. We then discuss the implications that this new framework will potentially have on the design and development of game and visualization technology in the future.

There is a growing demand in engineering, business, science, research, and industry for members with visual analytics expertise, but teaching visual analytics is challenging due to the multidisciplinary nature of the topic matter, the diverse backgrounds of the members, and the corresponding requirements on the instructor. We report some best practices from our experience teaching several offerings of a visual analytics graduate course at Purdue University where we leveraged these multidisciplinary challenges to our advantage instead of attempting to mitigate them.

Effective visualization of dynamic graphs remains an open research topic, and many state-of-the-art tools use animated node-link diagrams for this purpose. Despite its intuitiveness, the effectiveness of animation in node-link diagrams has been questioned, and several empirical studies have shown that animation is not necessarily superior to static visualizations. However, the exact mechanics of perceiving animated node-link diagrams are still unclear. In this paper, we study the impact of different dynamic graph metrics on user perception of the animation. After deriving candidate visual graph metrics, we perform an exploratory user study where participants are asked to reconstruct the event sequence in animated node-link diagrams. Based on these findings, we conduct a second user study where we investigate the most important visual metrics in depth. Our findings show that node speed and target separation are prominent visual metrics to predict the performance of event sequencing tasks.

We introduce embodied lenses for visual queries on tabletop surfaces using physical interaction. The lenses are simply thin sheets of paper or transparent foil decorated with fiducial markers, allowing them to be tracked by a diffuse illumination tabletop display. The physical affordance of these embodied lenses allow them to be overlapped, causing composition in the underlying virtual space. We perform a formative evaluation to study users’ conceptual models for overlapping physical lenses. This is followed by a quantitative user study comparing performance for embodied versus purely virtual lenses. Results show that embodied lenses are equally efficient compared to purely virtual lenses, and also support tactile and eyes-free interaction. We then present several examples of the technique, including image layers, map layers, image manipulation, and multidimensional data visualization. The technique is simple, cheap, and can be integrated into many existing tabletop displays.

Time is a universal and essential aspect of data in any investigative analysis. It helps analysts establish causality, build storylines from evidence, and reject infeasible hypotheses. For this reason, many investigative analysis tools provide visual representations designed for making sense of temporal data. However, the field of visual analytics still needs more evidence explaining how temporal visualization actually aids the analysis process, as well as design recommendations for how to build these visualizations. To fill this gap, we conducted an insight-based qualitative study to investigate the influence of temporal visualization on investigative analysis. We found that visualizing temporal information helped participants externalize chains of events. Another contribution of our work is the lightweight evaluation approach used to collect, visualize, and analyze insight.

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