Sheelagh Carpendale

Empirical Studies in Information Visualization: Seven Scenarios

We take a new, scenario-based look at evaluation in information visualization. Our seven scenarios, evaluating visual data analysis and reasoning, evaluating user performance, evaluating user experience, evaluating environments and work practices, evaluating communication through visualization, evaluating visualization algorithms, and evaluating collaborative data analysis were derived through an extensive literature review of over 800 visualization publications. These scenarios distinguish different study goals and types of research questions and are illustrated through example studies. Through this broad survey and the distillation of these scenarios, we make two contributions. One, we encapsulate the current practices in the information visualization research community and, two, we provide a different approach to reaching decisions about what might be the most effective evaluation of a given information visualization. Scenarios can be used to choose appropriate research questions and goals and the provided examples can be consulted for guidance on how to design ones own study.

Evaluating Information Visualizations

Information visualization research is becoming more established, and as a result, it is becoming increasingly important that research in this field is validated. With the general increase in information visualization research there has also been an increase, albeit disproportionately small, in the amount of empirical work directly focused on information visualization. The purpose of this chapter is to increase awareness of empirical research in general, of its relationship to information visualization in particular; to emphasize its importance; and to encourage thoughtful application of a greater variety of evaluative research methodologies in information visualization.

Beyond Mouse and Keyboard: Expanding Design Considerations for Information Visualization Interactions

The importance of interaction to Information Visualization (InfoVis) and, in particular, of the interplay between interactivity and cognition is widely recognized [12, 15, 32, 55, 70]. This interplay, combined with the demands from increasingly large and complex datasets, is driving the increased significance of interaction in InfoVis. In parallel, there have been rapid advances in many facets of interaction technologies. However, InfoVis interactions have yet to take full advantage of these new possibilities in interaction technologies, as they largely still employ the traditional desktop, mouse, and keyboard setup of WIMP (Windows, Icons, Menus, and a Pointer) interfaces. In this paper, we reflect more broadly about the role of more “natural” interactions for InfoVis and provide opportunities for future research. We discuss and relate general HCI interaction models to existing InfoVis interaction classifications by looking at interactions from a novel angle, taking into account the entire spectrum of interactions. Our discussion of InfoVis-specific interaction design considerations helps us identify a series of underexplored attributes of interaction that can lead to new, more “natural,” interaction techniques for InfoVis.

Rotation and translation mechanisms for tabletop interaction

A digital tabletop offers several advantages over other groupware form factors for collaborative applications. However, users of a tabletop system do not share a common perspective for the display of information: what is presented right side up to one participant is upside down for another. In this paper, we survey five different rotation and translation techniques for objects displayed on a direct touch digital tabletop display. We analyze their suitability for interactive tabletops in light of their respective input and output degrees of freedom, as well as the precision and completeness provided by each. We describe various tradeoffs that arise when considering which, when and where each of these techniques might be most useful.

The bohemian bookshelf: supporting serendipitous book discoveries through information visualization

Serendipity, a trigger of exciting yet unexpected discoveries, is an important but comparatively neglected factor in information seeking, research, and ideation. We suggest that serendipity can be facilitated through visualization. To explore this, we introduce the Bohemian Bookshelf, which aims to support serendipitous discoveries in the context of digital book collections. The Bohemian Bookshelf consists of five interlinked visualizations each offering a unique overview of the collection. It aims at encouraging serendipity by (1) offering multiple visual access points to the collection, (2) highlighting adjacencies between books, (3) providing flexible visual pathways for exploring the collection, (4) enticing curiosity through abstract, metaphorical, and visually distinct representations of books, and (5) enabling a playful approach to information exploration. A deployment at a library revealed that visitors embraced this approach of utilizing visualization to support open-ended explorations and serendipitous discoveries. This encourages future explorations into promoting serendipity through information visualization.

Creation and Collaboration: Engaging New Audiences for Information Visualization

In recent years we have seen information visualization technology move from an advanced research topic to mainstream adoption in both commercial and personal use. This move is in part due to many businesses recognizing the need for more effective tools for extracting knowledge from the data warehouses they are gathering. Increased mainstream interest is also a result of more exposure to advanced interfaces in contemporary online media. The adoption of information visualization technologies by lay users --- as opposed to the traditional information visualization audience of scientists and analysts --- has important implications for visualization research, design and development. Since we cannot expect each of these lay users to design their own visualizations, we have to provide them tools that make it easy to create and deploy visualizations of their datasets.

Personal Visualization and Personal Visual Analytics

Data surrounds each and every one of us in our daily lives, ranging from exercise logs, to archives of our interactions with others on social media, to online resources pertaining to our hobbies. There is enormous potential for us to use these data to understand ourselves better and make positive changes in our lives. Visualization (Vis) and visual analytics (VA) offer substantial opportunities to help individuals gain insights about themselves, their communities and their interests; however, designing tools to support data analysis in non-professional life brings a unique set of research and design challenges. We investigate the requirements and research directions required to take full advantage of Vis and VA in a personal context. We develop a taxonomy of design dimensions to provide a coherent vocabulary for discussing personal visualization and personal visual analytics. By identifying and exploring clusters in the design space, we discuss challenges and share perspectives on future research. This work brings together research that was previously scattered across disciplines. Our goal is to call research attention to this space and engage researchers to explore the enabling techniques and technology that will support people to better understand data relevant to their personal lives, interests, and needs.

Examination of Text-Entry Methods for Tabletop Displays

Although text entry is a vital part of day-to-day computing familiar to most people, not much research has been done to enable text entry on large interactive tables. One might assume that a good approach would be to choose an existing technique known to be fast, ergonomic, and currently preferred by the general population, but there are many additional factors to consider in this specific domain. We consider a variety of existing text-entry methods and examine their viability for use on tabletop displays. We discuss these techniques not only in terms of their general characteristics, performance, and adoption, but introduce other evaluative criteria, including: environmental factors unique to large digital tables and the support for multi-user simultaneous interaction. Based on our analysis we illustrate by example how to choose appropriate text-entry methods for tabletop applications with differing requirements, whether by selection from existing methods, or through a combination of desirable elements from a variety of methods. Our criteria can also be used as heuristics during the iterative design of a completely new text-entry technique.

Understanding Pen and Touch Interaction for Data Exploration on Interactive Whiteboards

Current interfaces for common information visualizations such as bar graphs, line graphs, and scatterplots usually make use of the WIMP (Windows, Icons, Menus and a Pointer) interface paradigm with its frequently discussed problems of multiple levels of indirection via cascading menus, dialog boxes, and control panels. Recent advances in interface capabilities such as the availability of pen and touch interaction challenge us to re-think this and investigate more direct access to both the visualizations and the data they portray. We conducted a Wizard of Oz study to explore applying pen and touch interaction to the creation of information visualization interfaces on interactive whiteboards without implementing a plethora of recognizers. Our wizard acted as a robust and flexible pen and touch recognizer, giving participants maximum freedom in how they interacted with the system. Based on our qualitative analysis of the interactions our participants used, we discuss our insights about pen and touch interactions in the context of learnability and the interplay between pen and touch gestures. We conclude with suggestions for designing pen and touch enabled interactive visualization interfaces.

Achieving higher magnification in context

The difficulty of accessing information details while preserving context has generated many different focus-in-context techniques. A common limitation of focus-in-context techniques is their ability to work well at high magnification. We present a set of improvements that will make high magnification in context more feasible. We demonstrate new distortion functions that effectively integrate high magnification within its context. Finally, we show how lenses can be used on top of other lenses, effectively multiplying their magnification power in the same manner that a magnifying glass applied on top of another causes multiplicative magnification. The combined effect is to change feasible detail-in-context magnification factors from less than 8 to more than 40.