Roland Fernandez

Effectiveness of Animation in Trend Visualization

Animation has been used to show trends in multi-dimensional data. This technique has recently gained new prominence for presentations, most notably with Gapminder Trendalyzer. In Trendalyzer, animation together with interesting data and an engaging presenter helps the audience understand the results of an analysis of the data. It is less clear whether trend animation is effective for analysis. This paper proposes two alternative trend visualizations that use static depictions of trends: one which shows traces of all trends overlaid simultaneously in one display and a second that uses a small multiples display to show the trend traces side-by-side. The paper evaluates the three visualizations for both analysis and presentation. Results indicate that trend animation can be challenging to use even for presentations; while it is the fastest technique for presentation and participants find it enjoyable and exciting, it does lead to many participant errors. Animation is the least effective form for analysis; both static depictions of trends are significantly faster than animation, and the small multiples display is more accurate.

Visualizations everywhere: A Multiplatform Infrastructure for Linked Visualizations

In order to use new visualizations, most toolkits require application developers to rebuild their applications and distribute new versions to users. The WebCharts Framework take a different approach by hosting Javascript from within an application and providing a standard data and events interchange.. In this way, applications can be extended dynamically, with a wide variety of visualizations. We discuss the benefits of this architectural approach, contrast it to existing techniques, and give a variety of examples and extensions of the basic system.

Cross-species translation of the Morris maze for Alzheimer’s disease

Analogous behavioral assays are needed across animal models and human patients to improve translational research. Here, we examined the extent to which performance in the Morris water maze - the most frequently used behavioral assay of spatial learning and memory in rodents - translates to humans. We designed a virtual version of the assay for human subjects that includes the visible-target training, hidden-target learning, and probe trials that are typically administered in the mouse version. We compared transgenic mice that express human amyloid precursor protein (hAPP) and patients with mild cognitive impairment due to Alzheimers disease (MCI-AD) to evaluate the sensitivity of performance measures in detecting deficits. Patients performed normally during visible-target training, while hAPP mice showed procedural learning deficits. In hidden-target learning and probe trials, hAPP mice and MCI-AD patients showed similar deficits in learning and remembering the target location. In addition, we have provided recommendations for selecting performance measures and sample sizes to make these assays sensitive to learning and memory deficits in humans with MCI-AD and in mouse models. Together, our results demonstrate that with careful study design and analysis, the Morris maze is a sensitive assay for detecting AD-relevant impairments across species.

Refinery: visual exploration of large, heterogeneous networks through associative browsing

Browsing is a fundamental aspect of exploratory information‐seeking. Associative browsing represents a common and intuitive set of exploratory strategies in which users step iteratively from familiar to novel bits of information. In this paper, we examine associative browsing as a strategy for bottom‐up exploration of large, heterogeneous networks. We present Refinery, an interactive visualization system informed by guidelines for associative browsing drawn from literature on exploratory information‐seeking. These guidelines motivate Refinerys query model, which allows users to simply and expressively construct queries using heterogeneous sets of nodes. This system computes degree‐of‐interest scores for associated content using a fast, random‐walk algorithm. Refinery visualizes query nodes within a subgraph of results, providing explanatory context, facilitating serendipitous discovery, and stimulating continued exploration. A study of 12 academic researchers using Refinery to browse publication data demonstrates how the system enables discovery of valuable new content, even within existing areas of expertise.

GroupBanter: Supporting Serendipitous Group Conversations with IM

This paper describes GroupBanter, a tool for supporting serendipitous group conversations using instant messaging. We investigated the potential of ephemeral group conversations by providing awareness of friends’ IM conversations, serving as an implicit invitation to join a group conversation. We present our vision and describe our prototype system. Results from two field studies carried out in different contexts show that users valued GroupBanter and that it provided new opportunities for communication that aren’t well served by traditional IM, email, or face-to-face communication. Our results indicate there is potential in providing a lightweight communication channel that lies between traditional, private IM conversations and more public IRC-like conversations.

ATOM: A Grammar for Unit Visualizations

Unit visualizations are a family of visualizations where every data item is represented by a unique visual mark—a visual unit—during visual encoding. For certain datasets and tasks, unit visualizations can provide more information, better match the users mental model, and enable novel interactions compared to traditional aggregated visualizations. Current visualization grammars cannot fully describe the unit visualization family. In this paper, we characterize the design space of unit visualizations to derive a grammar that can express them. The resulting grammar is called Atom, and is based on passing data through a series of layout operations that divide the output of previous operations recursively until the size and position of every data point can be determined. We evaluate the expressive power of the grammar by both using it to describe existing unit visualizations, as well as to suggest new unit visualizations.