Pairgrams: Understanding Collaborative Analysis Behavior with Visualization

Proceedings of the CHI Workshop on Analytic Provenance: Process + Interaction+ Insight.International audienceWe report on our work towards understanding analytic rea soning processes in face-to-face collaborative analysis using visualization techniques. How analysts reason is an active topic of research and in our community we know even less about how a group forms an understanding, insight, and reasons about data. We report on our effort in capturing the richness of reasoning activities through mixed-method approaches and show how Pairgrams-a visualization of interactions with an analytics workspace by pairs of participants-helped us to understand collaborative analysis and reasonin

Animated Edge Textures in Node-Link Diagrams: a Design Space and Initial Evaluation

International audienceNetwork edge data attributes are usually encoded using color, opacity, stroke thickness and stroke pattern, or some combination thereof. In addition to these static variables, it is also possible to animate dynamic particles flowing along the edges. This opens a larger design space of animated edge textures, featuring additional visual encodings that have potential not only in terms of visual mapping capacity but also playfulness and aesthetics. Such animated edge textures have been used in several commercial and design-oriented visualizations, but to our knowledge almost always in a relatively ad hoc manner. We introduce a design space and Web-based framework for generating animated edge textures, and report on an initial evaluation of particle properties – particle speed, pattern and frequency – in terms of visual perception

Trust me, I'm partially right: incremental visualization lets analysts explore large datasets faster

Queries over large scale (petabyte) data bases often mean waiting overnight for a result to come back. Scale costs time. Such time also means that potential avenues of exploration are ignored because the costs are perceived to be too high to run or even propose them. With sampleAction we have explored whether interaction techniques to present query results running over only incremental samples can be presented as sufficiently trustworthy for analysts both to make closer to real time decisions about their queries and to be more exploratory in their questions of the data. Our work with three teams of analysts suggests that we can indeed accelerate and open up the query process with such incremental visualizations

Studies of Automated Collection of Email Records

There are few quantitative techniques for directly measly p3 email usi atterns5 This a er des165p'3 an automated tool that, with a us29 s ermis4p'38 reads their mail databas4 to create a one-time s- s-ti and gathers relevant s p29203p' and behavioral information. We s49927p fully collected im ortant sant p1996 about mest p2 threading, foldersn and mail volume. Our techniques are relevant to the further develo ment of mail sil p354 and to future sture p of email behavior

Animation for visualization: Opportunities and drawbacks

DOes AnimAtiOn help build richer, more vivid, and more understandable visualizations, or simply confuse things? The use of Java, Flash, Silverlight, and JavaScript on the Web has made it easier to distribute animated, interactive visualizations. Many visualizers are beginning to think about how to make their visualizations more compelling with animation. There are many good guides on how to make static visualizations more effective, and many applications support interactivity well. But animated visualization is still a new area; there is little consensus on what makes for a good animation. The intuition behind animation seems clear enough: if a two-dimensional image is good, then a moving image should be better. Movement is familiar: we are accustomed to both moving through the real world and seeing things in it move smoothly. All around us, items move, grow, and change color in ways that we understand deeply and richly. In a visualization, animation might help a viewer work through the logic behind an idea by showing the intermediate steps and transitions, or show how data collected over time changes. A moving image might offer a fresh perspective, or invite users to look deeper into the data presented. An animation might also smooth the change between two views, even if there is no temporal component to the data. As an example, let's take a look at Jonathan Harris and Sep Kamvar's We Feel Fine animated visualization (http://wefeelfine.org). In this visualization, blog entries mentioning feelings are represented as bubbles. As users move between views, the bubble