Abstract-This paper presents scented widgets, graphical user interface controls enhanced with embedded visualizations that facilitate navigation in information spaces. We describe design guidelines for adding visual cues to common user interface widgets such as radio buttons, sliders, and combo boxes and contribute a general software framework for applying scented widgets within applications with minimal modifications to existing source code. We provide a number of example applications and describe a controlled experiment which finds that users exploring unfamiliar data make up to twice as many unique discoveries using widgets imbued with social navigation data. However, these differences equalize as familiarity with the data increases. Index Terms-Information visualization, user interface toolkits, information foraging, social navigation, social data analysis. The success of an interactive visualization depends not only on the visual encodings, but also on the mechanisms for navigating the visualized information space. These navigational mechanisms can take many forms, including panning and zooming, text queries, and dynamic query widgets. However, effective navigation relies on more than input techniques alone; appropriate visual navigation cues can aid users by guiding and refining their exploration. Both psychological and sociological considerations suggest approaches for improving navigation cues. Pirolli and Card's information foraging theory [17] models the cost structure of human information gathering analogously to that of animals foraging for food. One result of this theory is the concept of information scent-a user's "(imperfect) perception of the value, cost, or access path of information sources obtained from proximal cues" [17] . Improving information scent through better proximal cues lowers the cost structure of information foraging and improves information access. While effective information scent cues may be based upon the underlying information content (e.g., when the text in a web hyperlink describes the content of the linked document, it serves as a scent), others may involve various forms of metadata, including usage patterns. In the physical world, we often navigate in response to the activity of others. When a crowd forms we may join in to see what the source of interest is. Alternatively, we may intentionally avoid crowds or well-worn thoroughfares, taking "the road less travelled" to uncover lesser-known places of interest. In the context of information spaces, such social navigation can direct our attention to hot spots of interest or to under-explored regions. Our current interest in visual navigation cues is motivated by our experience building and deploying asynchronous collaborative visualization systems, in which groups of users perform visual data analysis by authoring comments and annotations within the visualizations [12, 20] . Usage studies of the sense.us collaborative visualization system [12] show that users fluidly switch between data-centric analysis and social navigation. After exhausting a line of inquiry, participants mine listings of comments left by other users to find new views of potential interest and to understand which areas have been explored. However, without explicit social navigation cues, users must continuously switch between the visualization and a separate list of comments. In this paper we show that social activity cues can improve such social data analysis by enabling social navigation within the analytic environment of the visualization. We introduce scented widgets; enhanced user interface widgets with embedded visualizations that provide information scent cues for navigating information spaces (see Figure 1 for examples). We propose design guidelines for adding embedded visualizations to common user interface controls such as radio buttons, sliders, and combo boxes. We then present a Java-based toolkit-level software framework, developed according to these guidelines, that allows scented widgets to be added to user interfaces and bound to backing data sources. This framework allows visual navigation aids to be added to existing applications with minimal modifications to application source code. We also provide results from an initial evaluation of scented widgets in a social data analysis application. The results show that using scented widgets to provide social navigation cues help users make up to twice as many unique discoveries in unfamiliar datasets, but that these benefits equalize as users become more familiar with the data. Numerous navigation mechanisms have been proposed to improve human-information interaction. In such interfaces, users may navigate along both spatial and semantic data dimensions. Examples of spatial navigation include maps and virtual worlds; examples of semantic navigation include web hyperlinks and dynamic query filters [1] . Navigation cues may be derived from the information content being explored (e.g., data distribution or landmarks) or from metadata, such as accumulated usage patterns. This last scenario is an example of social navigation [9] , in which aggregated activity patterns are presented to promote awareness of other users' actions within the information space. All such navigation cues provide proximal information that helps users stay oriented and gauge the relevance of distal information content. One class of navigation aids seeks to facilitate browsing in geometric spaces, such as zoomable 2D canvases. Overview displays are one common approach, while other approaches embed navigation cues directly in focal display regions. For example, Halo [2] and City Lights [22] use marks near the periphery of a display to provide information about the relative position of off-screen elements. Semantic navigation examples provide cues based on the information content itself. In visualization, histogram sliders [8] and
For instance, Scented Widgets REF embed visual cues and simple visualizations into user interface elements.
Scented Widgets: Improving Navigation Cues with Embedded Visualizations
IEEE Transactions on Visualization and Computer Graphics
IEEE Transactions on Visualization and Computer Graphics
Computer Science Medicine