Expressive Authoring of Node-Link Diagrams With Graphies.

Expressive design environments enable visualization designers not only to specify chart types and visual mappings, but also to customize individual graphical marks, as they would in a vector graphics drawing tool. Prior work has mainly investigated how to support the expressive design of a wide range of charts generated from tabular data: bar charts, scatterplots, maps, etc. We focus here on an expressive design environment for node-link diagrams generated from multivariate networks. Such data structures raise specific challenges and opportunities in terms of visual design and interactive authoring. We discuss those specificities and describe the user-centered design process that led to Graphies, a prototype environment for expressive node-link diagram authoring. We then report on a study in which participants successfully reproduced several expressive designs, and created their own designs as well.

A Comparison of Visualizations for Identifying Correlation over Space and Time.

Observing the relationship between two or more variables over space and time is essential in many domains. For instance, looking, for different countries, at the evolution of both the life expectancy at birth and the fertility rate will give an overview of their demographics. The choice of visual representation for such multivariate data is key to enabling analysts to extract patterns and trends. Prior work has compared geo-temporal visualization techniques for a single thematic variable that evolves over space and time, or for two variables at a specific point in time. But how effective visualization techniques are at communicating correlation between two variables that evolve over space and time remains to be investigated. We report on a study comparing three techniques that are representative of different strategies to visualize geo-temporal multivariate data: either juxtaposing all locations for a given time step, or juxtaposing all time steps for a given location; and encoding thematic attributes either using symbols overlaid on top of map features, or using visual channels of the map features themselves. Participants performed a series of tasks that required them to identify if two variables were correlated over time and if there was a pattern in their evolution. Tasks varied in granularity for both dimensions: time (all time steps, a subrange of steps, one step only) and space (all locations, locations in a subregion, one location only). Our results show that a visualization's effectiveness depends strongly on the task to be carried out. Based on these findings we present a set of design guidelines about geo-temporal visualization techniques for communicating correlation.

Animation Plans for Before-and-After Satellite Images.

Before-and-after image pairs show how entities in a given region have evolved over a specific period of time. Satellite images are a major source of such data, that capture how natural phenomena or human activity impact a geographical area. These images are used both for data analysis and to illustrate the resulting findings to diverse audiences. The simple techniques used to display them, including juxtaposing, swapping and monolithic blending, often fail to convey the underlying phenomenon in a meaningful manner. We introduce Baia, a framework to create advanced animated transitions, called animation plans, between before-and-after images. Baia relies on a pixel-based transition model that gives authors much expressive power, while keeping animations for common types of changes easy to create thanks to predefined animation primitives. We describe our model, the associated animation editor, and report on two user studies. In the first study, advanced transitions enabled by Baia were compared to monolithic blending, and perceived as more realistic and better at focusing viewer's attention on a region of interest than the latter. The second study aimed at gathering feedback about the usability of Baia's animation editor.

GraphDiaries: Animated Transitions andTemporal Navigation for Dynamic Networks.

Identifying, tracking and understanding changes in dynamic networks are complex and cognitively demanding tasks. We present GraphDiaries, a visual interface designed to improve support for these tasks in any node-link based graph visualization system. GraphDiaries relies on animated transitions that highlight changes in the network between time steps, thus helping users identify and understand those changes. To better understand the tasks related to the exploration of dynamic networks, we first introduce a task taxonomy, that informs the design of GraphDiaries, presented afterwards. We then report on a user study, based on representative tasks identified through the taxonomy, and that compares GraphDiaries to existing techniques for temporal navigation in dynamic networks, showing that it outperforms them in terms of both task time and errors for several of these tasks.

Exploratory analysis of time-series with ChronoLenses.

Visual representations of time-series are useful for tasks such as identifying trends, patterns and anomalies in the data. Many techniques have been devised to make these visual representations more scalable, enabling the simultaneous display of multiple variables, as well as the multi-scale display of time-series of very high resolution or that span long time periods. There has been comparatively little research on how to support the more elaborate tasks associated with the exploratory visual analysis of timeseries, e.g., visualizing derived values, identifying correlations, or discovering anomalies beyond obvious outliers. Such tasks typically require deriving new time-series from the original data, trying different functions and parameters in an iterative manner. We introduce a novel visualization technique called ChronoLenses, aimed at supporting users in such exploratory tasks. ChronoLenses perform on-the-fly transformation of the data points in their focus area, tightly integrating visual analysis with user actions, and enabling the progressive construction of advanced visual analysis pipelines.

Representation-independent in-place magnification with sigma lenses.

Focus+context interaction techniques based on the metaphor of lenses are used to navigate and interact with objects in large information spaces. They provide in-place magnification of a region of the display without requiring users to zoom into the representation and consequently lose context. In order to avoid occlusion of its immediate surroundings, the magnified region is often integrated in the context using smooth transitions based on spatial distortion. Such lenses have been developed for various types of representations using techniques often tightly coupled with the underlying graphics framework. We describe a representation-independent solution that can be implemented with minimal effort in different graphics frameworks, ranging from 3D graphics to rich multiscale 2D graphics combining text, bitmaps, and vector graphics. Our solution is not limited to spatial distortion and provides a unified model that makes it possible to define new focus+context interaction techniques based on lenses whose transition is defined by a combination of dynamic displacement and compositing functions. We present the results of a series of user evaluations that show that one such new lens, the speed-coupled blending lens, significantly outperforms all others.

Selecting biological data sources and tools with XPR, a path language for RDF.

As the number, richness and diversity of biological sources grow, scientists are increasingly confronted with the problem of selecting appropriate sources and tools. To address this problem, we have designed BioGuidel, a user-centric framework that helps scientists choose sources and tools according to their preferences and strategy, by specifying queries through a user-friendly visual interface. In this paper, we provide a complete RDF representation of BioGuide and introduce XPR (eXtensible Path language for RDF), an extension of FSL2 that is expressive enough to model all BioGuide queries. BioGuide queries modeled as XPR expressions can then be saved, compared, evaluated and exchanged through the Web between users and applications.