Improving memorability in fisheye views

Interactive fisheye views use distortion to show both local detail and global context in the same display space. Although fisheyes allow the presentation and inspection of large data sets, the distortion effects can cause problems for users. One such problem is lack of memorability – the ability to find and go back to objects and features in the data. This thesis examines the possibility of improving the memorability of fisheye views by adding historical information to the visualization. The historical information is added visually through visit wear, an extension of the concepts of edit wear and read wear. This will answer the question “Where have I been?” through visual instead of cognitive processing by overlaying new visual information on the data to indicate a user’s recent interaction history. This thesis describes general principles of visibility in a space that is distorted by a fisheye lens and defines some parameters of the design space of visit wear. Finally, a test system that applied the principles was evaluated, and showed that adding visit wear to a fisheye system improved the memorability of the information space

HindSight: Encouraging Exploration through Direct Encoding of Personal Interaction History

Physical and digital objects often leave markers of our use. Website links turn purple after we visit them, for example, showing us information we have yet to explore. These “footprints” of interaction offer substantial benefits in information saturated environments - they enable us to easily revisit old information, systematically explore new information, and quickly resume tasks after interruption. While applying these design principles have been successful in HCI contexts, direct encodings of personal interaction history have received scarce attention in data visualization. One reason is that there is little guidance for integrating history into visualizations where many visual channels are already occupied by data. More importantly, there is not firm evidence that making users aware of their interaction history results in benefits with regards to exploration or insights. Following these observations, we propose HindSight - an umbrella term for the design space of representing interaction history directly in existing data visualizations. In this paper, we examine the value of HindSight principles by augmenting existing visualizations with visual indicators of user interaction history (e.g. How the Recession Shaped the Economy in 255 Charts, NYTimes). In controlled experiments of over 400 participants, we found that HindSight designs generally encouraged people to visit more data and recall different insights after interaction. The results of our experiments suggest that simple additions to visualizations can make users aware of their interaction history, and that these additions significantly impact users\u27 exploration and insights

HindSight: Encouraging Exploration through Direct Encoding of Personal Interaction History

Physical and digital objects often leave markers of our use. Website links turn purple after we visit them, for example, showing us information we have yet to explore. These “footprints” of interaction offer substantial benefits in information saturated environments - they enable us to easily revisit old information, systematically explore new information, and quickly resume tasks after interruption. While applying these design principles have been successful in HCI contexts, direct encodings of personal interaction history have received scarce attention in data visualization. One reason is that there is little guidance for integrating history into visualizations where many visual channels are already occupied by data. More importantly, there is not firm evidence that making users aware of their interaction history results in benefits with regards to exploration or insights. Following these observations, we propose HindSight - an umbrella term for the design space of representing interaction history directly in existing data visualizations. In this paper, we examine the value of HindSight principles by augmenting existing visualizations with visual indicators of user interaction history (e.g. How the Recession Shaped the Economy in 255 Charts, NYTimes). In controlled experiments of over 400 participants, we found that HindSight designs generally encouraged people to visit more data and recall different insights after interaction. The results of our experiments suggest that simple additions to visualizations can make users aware of their interaction history, and that these additions significantly impact users\u27 exploration and insights

IMPROVING REVISITATION IN LONG DOCUMENTS WITH TWO-LEVEL ARTIFICIAL-LANDMARK SCROLLBARS

Revisitation – returning to previously-visited locations in a document – is commonly done in the digital world. While linear navigation controls provide a spatial representation of the document and allow effective navigation in short documents, they are not effective in long documents, particularly for revisitation. Bookmarks, search and history dialogs, and “read wear” (visual marks left as the user interacts with the document) can all assist revisitation; however, for long documents all of these tools are limited in terms of effort, clutter, and interpretability. Inspired by visual cues such as coloured edges and “thumb indents” in hardcopy books, recent work has proposed artificial landmarks to help users build up natural spatial memory for the locations in a document; in long documents, however, this technique is also limited because of the number of pages each landmark represents. To address this problem, this thesis proposes a Double-Scrollbar design that uses two columns of artificial landmarks that can provide greater specificity for spatial memory and revisitation in long documents. We developed three versions of landmark-augmented Double-Scrollbar, using icons, letters, and digits as landmarks. To assess the performance and usability of the Double-Scrollbar design, two studies were conducted with 21 participants, each visiting and revisiting pages of a long document using each of the new designs, as well as a single-column design and a standard scrollbar. Results showed that two levels of icon landmarks were significantly better for assisting revisitation, and were preferred by participants. The two-level artificial-landmark scrollbar is a new way of improving revisitation in long documents by assisting the formation of more precise spatial memories about document locations

Generating trails automatically, to aid navigation when you revisit an environment

A new method for generating trails from a person’s movement through a virtual environment (VE) is described. The method is entirely automatic (no user input is needed), and uses string-matching to identify similar sequences of movement and derive the person’s primary trail. The method was evaluated in a virtual building, and generated trails that substantially reduced the distance participants traveled when they searched for target objects in the building 5-8 weeks after a set of familiarization sessions. Only a modest amount of data (typically five traversals of the building) was required to generate trails that were both effective and stable, and the method was not affected by the order in which objects were visited. The trail generation method models an environment as a graph and, therefore, may be applied to aiding navigation in the real world and information spaces, as well as VEs

Personalized Navigation Instruments for Map User Interfaces

A map is a big multi-scale information space. The size of a computer display, however, is limited. Users of digital maps often need to repeatedly resize and reposition the map to seek information. These repeated and excess interactions mar the user experience, and create bottlenecks for efficient information processing. We introduce personalized navigation instruments, a class of navigation instruments that leverage personal important spatial entities (e.g., landmarks and routes) to tackle navigation challenges in map user interfaces. Specifically, we contribute the following three instruments, each of which embodies a novel research idea: 1) Personalized Compass (P-Compass) is a multi-needle compass that extends the concept of a conventional compass to help users establish a reference frame. P-Compass localizes an unknown reference point by visualizing its relationship with respect to landmarks. P-Compass leverages what a user knows to help them figure out what they do not know. 2) SpaceTokens are interactive map widgets that represent locations, and help users see and link locations rapidly. With SpaceTokens, users can use locations directly as controls to manipulate a map, or building blocks to link with other locations. SpaceTokens make locations first-class citizens of map interaction. 3) SpaceBar associates a simple linear scrollbar with a complex nonlinear route, thus facilitates efficient route comprehension and interaction. SpaceBar is akin to a scrollbar for a route. We prototyped these three instruments in a custom smartphone application, used the application regularly in daily life, and validated our design in two formal studies. While maps are the focus in this dissertation, our ideas need not be limited to maps. For example, we have prototyped P-Compass with Google Street View and a 3D virtual earth tour application. We conclude this dissertation with several directions for future work, such as AR/VR and personalized spatial information user interfaces involving sound, gestures, and speech

Can animation support the visualisation of dynamic graphs?

Animation and small multiples are methods for visualizing dynamically evolving graphs. Animations present an interactive movie of the data where positions of nodes are smoothly interpolated as the graph evolves. Nodes fade in/out as they are added/removed from the data set. Small multiples presents the data like a comic book with the graph at various states in separate windows. The user scans these windows to see how the data evolves. In a recent experiment, drawing stability (known more widely as the “mental map”) was shown to help users follow specific nodes or long paths in dynamically evolving data. However, no significant difference between animation and small multiples presentations was found. In this paper, we look at data where the nodes in the graph have low drawing stability and analyze it with new error metrics: measuring how close the given answer is from the correct answer on a continuous scale. We find evidence that when the stability of the drawing is low and important nodes in the task cannot be highlighted throughout the time series, animation can improve task performance when compared to the use of small multiples

Supporting exploratory browsing with visualization of social interaction history

This thesis is concerned with the design, development, and evaluation of information visualization tools for supporting exploratory browsing. Information retrieval (IR) systems currently do not support browsing well. Responding to user queries, IR systems typically compute relevance scores of documents and then present the document surrogates to users in order of relevance. Other systems such as email clients and discussion forums simply arrange messages in reverse chronological order. Using these systems, people cannot gain an overview of a collection easily, nor do they receive adequate support for finding potentially useful items in the collection. This thesis explores the feasibility of using social interaction history to improve exploratory browsing. Social interaction history refers to traces of interaction among users in an information space, such as discussions that happen in the blogosphere or online newspapers through the commenting facility. The basic hypothesis of this work is that social interaction history can serve as a good indicator of the potential value of information items. Therefore, visualization of social interaction history would offer navigational cues for finding potentially valuable information items in a collection. To test this basic hypothesis, I conducted three studies. First, I ran statistical analysis of a social media data set. The results showed that there were positive relationships between traces of social interaction and the degree of interestingness of web articles. Second, I conducted a feasibility study to collect initial feedback about the potential of social interaction history to support information exploration. Comments from the participants were in line with the research hypothesis. Finally, I conducted a summative evaluation to measure how well visualization of social interaction history can improve exploratory browsing. The results showed that visualization of social interaction history was able to help users find interesting articles, to reduce wasted effort, and to increase user satisfaction with the visualization tool

Use of Landmarks to Improve Spatial Learning and Revisitation in Computer Interfaces

Efficient spatial location learning and remembering are just as important for two-dimensional Graphical User Interfaces (GUI) as they are for real environments where locations are revisited multiple times. Rapid spatial memory development in GUIs, however, can be difficult because these interfaces often lack adequate landmarks that have been predominantly used by people to learn and recall real-life locations. In the absence of sufficient landmarks in GUIs, artificially created visual objects (i.e., artificial landmarks) could be used as landmarks to support spatial memory development of spatial locations. In order to understand how spatial memory development occurs in GUIs and explore ways to assist users’ efficient location learning and recalling in GUIs, I carried out five studies exploring the use of landmarks in GUIs – one study that investigated interfaces of four standard desktop applications: Microsoft Word, Facebook, Adobe Photoshop, and Adobe Reader, and other four that tested artificial landmarks augmented two prototype desktop GUIs against non-landmarked versions: command selection interfaces and linear document viewers; in addition, I tested landmarks’ use in variants of these interfaces that varied in the number of command sets (small, medium, and large) and types of linear documents (textual and video). Results indicate that GUIs’ existing features and design elements can be reliable landmarks in GUIs that provide spatial benefits similar to real environments. I also show that artificial landmarks can significantly improve spatial memory development of GUIs, allowing support for rapid spatial location learning and remembering in GUIs. Overall, this dissertation reveals that landmarks can be a valuable addition to graphical systems to improve the memorability and usability of GUIs

The state of the art in empirical user evaluation of graph visualizations

While graph drawing focuses more on the aesthetic representation of node-link diagrams, graph visualization takes into account other visual metaphors making them useful for graph exploration tasks in information visualization and visual analytics. Although there are aesthetic graph drawing criteria that describe how a graph should be presented to make it faster and more reliably explorable, many controlled and uncontrolled empirical user studies flourished over the past years. The goal of them is to uncover how well the human user performs graph-specific tasks, in many cases compared to previously designed graph visualizations. Due to the fact that many parameters in a graph dataset as well as the visual representation of them might be varied and many user studies have been conducted in this space, a state-of-the-art survey is needed to understand evaluation results and findings to inform the future design, research, and application of graph visualizations. In this paper, we classify the present literature on the topmost level into graph interpretation, graph memorability, and graph creation where the users with their tasks stand in focus of the evaluation not the computational aspects. As another outcome of this work, we identify the white spots in this field and sketch ideas for future research directions