When people browse online news, small thumbnail images accompanying links to articles attract their attention and help them to decide which articles to read. As an increasing proportion of online news can be construed as data journalism, we have witnessed a corresponding increase in the incorporation of visualization in article thumbnails. However, there is little research to support alternative design choices for visualization thumbnails, which include resizing, cropping, simplifying, and embellishing charts appearing within the body of the associated article. We therefore sought to better understand these design choices and determine what makes a visualization thumbnail inviting and interpretable. This paper presents our findings from a survey of visualization thumbnails collected online and from conversations with data journalists and news graphics designers. Our study reveals that there exists an uncharted design space, one that is in need of further empirical study. Our work can thus be seen as a first step toward providing structured guidance on how to design thumbnails for data stories.
Beyond web search and email reading, thumbnails also appear in the context of navigating other forms of media, from file systems @cite_9 to documents @cite_13 and videos @cite_0 . Prior work in the visualization and visual analytics community has also incorporated thumbnails into the sensemaking process as a means of leveraging the unique advantages of spatial memory @cite_4 @cite_6 @cite_12 .
@cite_4 @cite_9 @cite_6 @cite_0 @cite_13 @cite_12
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Sensemaking is described as the process in which people collect, organize and create representations of information, all centered around some problem they need to understand. People often get lost when solving complicated tasks using big datasets over long periods of exploration and analysis. They may forget what they have done, are unaware of where they are in the context of the overall task, and are unsure where to continue. In this paper, we introduce a tool, SenseMap, to address these issues in the context of browser-based online sensemaking. We conducted a semi-structured interview with nine participants to explore their behaviors in online sensemaking with existing browser functionality. A simplified sensemaking model based on Pirolli and Card's model is derived to better represent the behaviors we found: users iteratively collect information sources relevant to the task, curate them in a way that makes sense, and finally communicate their findings to others. SenseMap automatically captures provenance of user sensemaking actions and provides multi-linked views to visualize the collected information and enable users to curate and communicate their findings. To explore how SenseMap is used, we conducted a user study in a naturalistic work setting with five participants completing the same sensemaking task related to their daily work activities. All participants found the visual representation and interaction of the tool intuitive to use. Three of them engaged with the tool and produced successful outcomes. It helped them to organize information sources, to quickly find and navigate to the sources they wanted, and to effectively communicate their findings. Effective management of documents on computers has been a central user interface problem for many years. One common approach involves using 2D spatial layouts of icons representing the documents, particularly for information workspace tasks. This approach takes advantage of human 2D spatial cognition. More recently, several 3D spatial layouts have engaged 3D spatial cognition capabilities. Some have attempted to use spatial memory in 3D virtual environments. However, there has been no proof to date that spatial memory works the same way in 3D virtual environments as it does in the real world. We describe a new technique for document management called the Data Mountain, which allows users to place documents at arbitrary positions on an inclined plane in a 3D desktop virtual environment using a simple 2D interaction technique. We discuss how the design evolved in response to user feedback. We also describe a user study that shows that the Data Mountain does take advantage of spatial memory. Our study shows that the Data Mountain has statistically reliable advantages over the Microsoft Internet Explorer Favorites mechanism for managing documents of interest in an information workspace. Online streaming video systems have become extremely popular, yet navigating to target scenes of interest can be a challenge. While recent techniques have been introduced to enable real-time seeking, they break down for large videos, where scrubbing the timeline causes video frames to skip and flash too quickly to be comprehendible. We present Swifter, a new video scrubbing technique that displays a grid of pre-cached thumbnails during scrubbing actions. In a series of studies, we first investigate possible design variations of the Swifter technique, and the impact of those variations on its performance. Guided by these results we compare an implementation of Swifter to the previously published Swift technique, in addition to the approaches utilized by YouTube and Netfilx. Our results show that Swifter significantly outperforms each of these techniques in a scene locating task, by a factor of up to 48 . Scrolling is the standard way to navigate through many types of digital documents. However, moving more than a few pages can be slow because all scrolling techniques constrain visual search to only a small document region. To improve document navigation, we developed Space-Filling Thumbnails (SFT), an overview display that eliminates most scrolling. SFT provides two views: a standard page view for reading, and a thumbnail view that shows all pages. We tested SFT in three experiments that involved finding pages in documents. The first study (n=13) compared seven current scrolling techniques, and showed that SFT is significantly faster than the other methods. The second and third studies (n=32 and n=14) were detailed comparisons of SFT with thumbnail-enhanced scrollbars (TES), which performed well in the first experiment. SFT was faster than TES across all document types and lengths, particularly when tasks involved revisitation. In addition, SFT was strongly preferred by participants.