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We present the results of a comprehensive analysis of visualization paper keywords supplied for 4366 papers submitted to five main visualization conferences. We describe main keywords, topic areas, and 10-year historic trends from two datasets: (1) the standardized PCS taxonomy keywords in use for paper submissions for IEEE InfoVis, IEEE Vis-SciVis, IEEE VAST, EuroVis, and IEEE PacificVis since 2009 and (2) the author-chosen keywords for papers published in the IEEE Visualization conference series (now called IEEE VIS) since 2004. Our analysis of research topics in visualization can serve as a starting point to (a) help create a common vocabulary to improve communication among different visualization sub-groups, (b) facilitate the process of understanding differences and commonalities of the various research sub-fields in visualization, (c) provide an understanding of emerging new research trends, (d) facilitate the crucial step of finding the right reviewers for research submissions, and (e) it can eventually lead to a comprehensive taxonomy of visualization research. One additional tangible outcome of our work is an application that allows visualization researchers to easily browse the 2600+ keywords used for IEEE VIS papers during the past 10 years, aiming at more informed and, hence, more effective keyword selections for future visualization publications.

[poster]; International audience; Physical visualizations have been around for several decades and remained mostly unnoticed. They recently became popular in the form of data sculptures, due to a proliferation of data-driven artifacts produced by the art and design communities, and to a wider availability of rapid prototyping facilities such as fab labs. It has been recently suggested that such physical data representations are suitable for demonstrative, artistic or communicative purposes. But can physical visualizations also help carry out actual information visualization tasks? We describe the design of the first user study whose goals are to assess the efficiency of physical visualizations compared to on-screen visualizations - with a focus on the challenges posed by 3D visualizations - and to better understand how people use physical data representations to answer visual questions.

International audience; This paper presents a technique for visualizing the differences between two graphs. The technique assumes that a unique labeling of the nodes for each graph is available, where if a pair of labels match, they correspond to the same node in both graphs. Such labeling often exists in many application areas: IP addresses in computer networks, namespaces, class names, and function names in software engineering, to name a few. As many areas of the graph may be the same in both graphs, we visualize large areas of difference through a graph hierarchy. We introduce a path-preserving coarsening technique for degree one nodes of the same classification. We also introduce a path-preserving coarsening technique based on betweenness centrality that is able to illustrate major differences between two graphs.

International audience; Many graph visualization systems use graph hierarchies to organize a large input graph into logical components. These approaches detect features globally in the data and place these features inside levels of a hierarchy. However, this feature detection is a global process and does not consider nodes of the graph near a feature of interest. TugGraph is a system for exploring paths and proximity around nodes and subgraphs in a graph. The approach modifies a pre-existing hierarchy in order to see how a node or subgraph of interest extends out into the larger graph. It is guaranteed to create path-preserving hierarchies, so that the abstraction shown is meaningful with respect to the structure of the graph. The system works well on graphs of hundreds of thousands of nodes and millions of edges. TugGraph is able to present views of this proximal information in the context of the entire graph in seconds, and does not require a layout of the full graph as input.

Guiding gaze using near-peripheral vision improves gaze-contingent-display efficiency by reducing display response latency. We propose a new approach for controlling exploration of static displays through near-peripheral stimuli, and report results of an evaluation of its effectiveness. 10 participants viewed full screen displays of 60 blurred pictures (Gaussian filtering). As soon as a fixation (first strategy) or a gaze sample (second strategy) was detected next to the current stimulus, the area surrounding it was deblurred. An image was totally deblurred when all stimuli had thus attracted the user's gaze. Stimuli are blinking deblurred circles (radius: 1 deg visual angle). They appear in predefined positions on the screen, one at a time. For each picture, successive stimulus positions on the screen reproduce observed gaze patterns. The current stimulus is visible only if the visual angle between its position on the screen and the position of the user's current fixation is superior to 8 deg (to avoid users noticing it) and inferior to 14 deg. (near-periphery upper limit). Eye movements are detected through an ASL-H6 eye-tracker (120 Hz). Stimulus saliency is estimated, for each picture and stimulus, from contrast ratio and sum of squared differences between blurred and deblurred area around the stimulus.