Collaborative blockchain storage is one of the solutions to the blockchain storage scalability challenge, allowing individual nodes to store partial blockchain data. Collaborative blockchains give up redundancy for scalability. However, redundancy is a determinant of blockchain’s decentralization and data availability. In this article, we study the possibility of balancing the scalability–redundancy tradeoff in collaborative blockchains. We first present a model for the evaluation of a data distribution scheme for its efficiency in terms of redundancy. Then, we present a fully decentralized self-regulated data distribution scheme assuring storage scalability and redundancy for collaborative blockchains based on fully redundant global state. The proposed solution does not incur additional communication. We examine the efficiency of the proposed scheme based on experiments. Our results demonstrate that the proposed system assures a level of redundancy for a given set of nodes and data volume, optimizes storage space utilization, and provides uniform distribution of data.

Counting the number of shortest paths on a grid is a simple procedure with close ties to Pascal’s triangle. We show how path counting can be used to select relatively direct grid paths for AI-related applications involving navigation through spatial environments. Typical implementations of Dijkstra’s algorithm and A* prioritize grid moves in an arbitrary manner, producing paths which stray conspicuously far from line-of-sight trajectories. We find that by counting the number of paths which traverse each vertex, then selecting the vertices with the highest counts, one obtains a path that is reasonably direct in practice and can be improved by refining the grid resolution. Central Dijkstra and Central A* are introduced as the basic methods for computing these central grid paths. Theoretical analysis reveals that the proposed grid-based navigation approach is related to an existing grid-based visibility approach, and establishes that central grid paths converge on clear sightlines as the grid spacing approaches zero. A more general property, that central paths converge on direct paths, is formulated as a conjecture.

A well-designed workplace has a direct and significant impact on our work experiences and productivity. In this paper, we investigate how office interior layouts influence the way we socially experience office buildings. We extend the previous work that examined static social formations of office workers by looking at their dynamic movements during informal desk visiting interactions. With a month of video data collected in the office, we implemented a vision-based analysis system that enables us to examine how people occupy space in social contexts in relation to desk configurations. The results showed that both social territoriality and approach path highlight social comfort in human-building interactions, which are different from efficiency or path optimization. From these findings, we propose the concepts of socio-spatial comfort: social buffers, privacy buffers, and varying proxemics to inform a user-centered way of designing human building interactions and architecture.

The design of a workplace can have a profound impact on the effectiveness of the workforce utilizing the space. When considering dynamic social activities in the flow of work, the constraints of the static elements of the interior reveals the adaptive behaviour of the occupants in trying to accommodate these constraints while performing their daily tasks. To better understand how workplace design shapes social interactions, we ran an empirical study in an office context over a two week period. We collected video from 24 cameras in a dozen space configurations totaling 1,920 hours of recorded activities. We utilized computer vision techniques, to produce skeletonized representations of the occupants, to assist in the annotation and data analysis process. We present our findings of socio-spatial formation patterns and the effects of furniture and interior elements on the observed behaviour of collaborators for both computer-supported work and for unmediated social interaction. Combining the observations with an interview of the occupants' reflections, we discuss dynamics of socio-spatial formations and how this knowledge can support social interactions in the domain of space design systems and interactive interiors.

An instructional approach is presented to improve human performance in solving Bayesian inference problems. Starting from the original text of the classic Mammography Problem, the textual expression is modified and visualizations are added according to Mayer’s principles of instruction. These principles concern coherence, personalization, signaling, segmenting, multimedia, spatial contiguity, and pretraining. Principles of self-explanation and interactivity are also applied. Four experiments on the Mammography Problem showed that these principles help participants answer the questions at significantly improved rates. Nonetheless, in novel interactivity conditions, performance was lowered suggesting that more interaction can add more difficulty for participants. Overall, a leap forward in accuracy was found, with more than twice the participant accuracy of previous work. This indicates that an instructional approach to improving human performance in Bayesian inference is a promising direction.

PhenoLines is a visual analysis tool for the interpretation of disease subtypes, derived from the application of topic models to clinical data. Topic models enable one to mine cross-sectional patient comorbidity data (e.g., electronic health records) and construct disease subtypes-each with its own temporally evolving prevalence and co-occurrence of phenotypes-without requiring aligned longitudinal phenotype data for all patients. However, the dimensionality of topic models makes interpretation challenging, and de facto analyses provide little intuition regarding phenotype relevance or phenotype interrelationships. PhenoLines enables one to compare phenotype prevalence within and across disease subtype topics, thus supporting subtype characterization, a task that involves identifying a proposed subtype's dominant phenotypes, ages of effect, and clinical validity. We contribute a data transformation workflow that employs the Human Phenotype Ontology to hierarchically organize phenotypes and aggregate the evolving probabilities produced by topic models. We introduce a novel measure of phenotype relevance that can be used to simplify the resulting topology. The design of PhenoLines was motivated by formative interviews with machine learning and clinical experts. We describe the collaborative design process, distill high-level tasks, and report on initial evaluations with machine learning experts and a medical domain expert. These results suggest that PhenoLines demonstrates promising approaches to support the characterization and optimization of topic models.

During asynchronous collaborative analysis, handoff of partial findings is challenging because externalizations produced by analysts may not adequately communicate their investigative process. To address this challenge, we developed techniques to automatically capture and help encode tacit aspects of the investigative process based on an analyst's interactions, and streamline explicit authoring of handoff annotations. We designed our techniques to mediate awareness of analysis coverage, support explicit communication of progress and uncertainty with annotation, and implicit communication through playback of investigation histories. To evaluate our techniques, we developed an interactive visual analysis system, KTGraph, that supports an asynchronous investigative document analysis task. We conducted a two-phase user study to characterize a set of handoff strategies and to compare investigative performance with and without our techniques. The results suggest that our techniques promote the use of more effective handoff strategies, help increase an awareness of prior investigative process and insights, as well as improve final investigative outcomes.

Cross-sectional phenotype studies are used by genetics researchers to better understand how phenotypes vary across patients with genetic diseases, both within and between cohorts. Analyses within cohorts identify patterns between phenotypes and patients (e.g., co-occurrence) and isolate special cases (e.g., potential outliers). Comparing the variation of phenotypes between two cohorts can help distinguish how different factors affect disease manifestation (e.g., causal genes, age of onset, etc.). PhenoStacks is a novel visual analytics tool that supports the exploration of phenotype variation within and between cross-sectional patient cohorts. By leveraging the semantic hierarchy of the Human Phenotype Ontology, phenotypes are presented in context, can be grouped and clustered, and are summarized via overviews to support the exploration of phenotype distributions. The design of PhenoStacks was motivated by formative interviews with genetics researchers: we distil high-level tasks, present an algorithm for simplifying ontology topologies for visualization, and report the results of a deployment evaluation with four expert genetics researchers. The results suggest that PhenoStacks can help identify phenotype patterns, investigate data quality issues, and inform data collection design.

User-authored annotations of data can support analysts in the activity of hypothesis generation and sensemaking, where it is not only critical to document key observations, but also to communicate insights between analysts. We present annotation graphs, a dynamic graph visualization that enables meta-analysis of data based on user-authored annotations. The annotation graph topology encodes annotation semantics, which describe the content of and relations between data selections, comments, and tags. We present a mixed-initiative approach to graph layout that integrates an analyst's manual manipulations with an automatic method based on similarity inferred from the annotation semantics. Various visual graph layout styles reveal different perspectives on the annotation semantics. Annotation graphs are implemented within C8, a system that supports authoring annotations during exploratory analysis of a dataset. We apply principles of Exploratory Sequential Data Analysis (ESDA) in designing C8, and further link these to an existing task typology in the visualization literature. We develop and evaluate the system through an iterative user-centered design process with three experts, situated in the domain of analyzing HCI experiment data. The results suggest that annotation graphs are effective as a method of visually extending user-authored annotations to data meta-analysis for discovery and organization of ideas.

The egocentric analysis of dynamic networks focuses on discovering the temporal patterns of a subnetwork around a specific central actor (i.e., an ego-network). These types of analyses are useful in many application domains, such as social science and business intelligence, providing insights about how the central actor interacts with the outside world. We present EgoLines, an interactive visualization to support the egocentric analysis of dynamic networks. Using a "subway map" metaphor, a user can trace an individual actor over the evolution of the ego-network. The design of EgoLines is grounded in a set of key analytical questions pertinent to egocentric analysis, derived from our interviews with three domain experts and general network analysis tasks. We demonstrate the effectiveness of EgoLines in egocentric analysis tasks through a controlled experiment with 18 participants and a use-case developed with a domain expert.

The differential diagnosis of hereditary disorders is a challenging task for clinicians due to the heterogeneity of phenotypes that can be observed in patients. Existing clinical tools are often text-based and do not emphasize consistency, completeness, or granularity of phenotype reporting. This can impede clinical diagnosis and limit their utility to genetics researchers. Herein, we present PhenoBlocks, a novel visual analytics tool that supports the comparison of phenotypes between patients, or between a patient and the hallmark features of a disorder. An informal evaluation of PhenoBlocks with expert clinicians suggested that the visualization effectively guides the process of differential diagnosis and could reinforce the importance of complete, granular phenotypic reporting.

We present Mimic, an input capture and visual analytics system that records online user behavior to facilitate the discovery of micro-interactions that may affect problem understanding and decision making. As aggregate statistics and visualizations can mask important behaviors, Mimic can help interaction designers to improve the usability of their designs by going beyond aggregates to examine many individual user sessions in detail. To test Mimic, we replicate a recent crowd-sourcing experiment to better understand why participants consistently perform poorly in answering a canonical conditional probability question called the Mammography Problem. To analyze the micro-interactions, the Mimic web application is used to play back user sessions collected through remote logging of client-side events. We use Mimic to demonstrate the value of using advanced visual interfaces to interactively study interaction data. In the Mammography Problem, issues like user confusion, low confidence, and divided-attention were found based on participants changing their answers, doing repeated scrolling, and overestimating a base rate. Mimic shows how helpful detailed observational data can be and how important the careful design of micro-interactions is in helping users to successfully understand a problem, find a solution, and achieve their goals.

We introduce Splash, a framework reducing development overhead for both data curators and visualization developers of client-server visualization systems. Splash streamlines the process of creating a multiple level-of-detail version of the data and facilitates progressive data download, thereby enabling real-time, on-demand navigation with existing visualization toolkits. As a result, system responsiveness is increased and the user experience is improved. We demonstrate the benefit of progressive loading for user interaction on slower networks. Additionally, case study evaluations of Splash with real-world data curators suggest that Splash supports iterative refinement of visualizations and promotes the use of exploratory data analysis.

Recently, research in 3D computer graphics and interaction has started to move beyond the narrow domain of single object authoring and inspection, and has begun to consider complex multiscale objects and environments. This generalization of problem scope calls for more general solutions, which are more akin to information visualization techniques than traditional computer graphics approaches.

Digital pen systems, originally designed to digitize annotations made on physical paper, are evolving to permit a wider variety of applications. Although the type and quality of pen feedback (e.g., haptic, audio, and visual) have a huge impact on advancing the digital pen technology, dynamic visual feedback has yet to be fully investigated. In parallel, miniature projectors are an emerging technology with the potential to enhance visual feedback for small mobile computing devices. In this paper we present the PenLight system, which is a testbed to explore the interaction design space and its accompanying interaction techniques in a digital pen embedded with a spatially-aware miniature projector. Using our prototype, that simulates a miniature projection (via a standard video projector), we visually augment paper documents, giving the user immediate access to additional information and computational tools. We also show how virtual ink can be managed in single and multi-user environments to aid collaboration and data management. User evaluation with professional architects indicated promise of our proposed techniques and their potential utility in the paper-intensive domain of architecture.

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We present a comprehensive system for multiscale navigation of 3-dimensional scenes, and demonstrate our approach on multiscale datasets such as the Earth. Our system incorporates a novel image-based environment representation which we refer to as the cubemap. Our cubemap allows consistent navigation at various scales, as well as real-time collision detection without pre-computation or prior knowledge of geometric structure. The cubemap is used to improve upon previous work on proximal object inspection (HoverCam), and we present an additional interaction technique for navigation which we call look-and-fly. We believe that our approach to the navigation of multiscale 3D environments offers greater flexibility and ease of use than mainstream applications such as Google Earth and Microsoft Virtual Earth, and we demonstrate our results with this system.

Inspired by our automotive and product design customers using large displays in design centers, visualization studios, and meeting rooms around the world, we have been exploring the use and potential of large display installations for almost a decade. Our research has touched on many aspects of this rich design space, from individual tools to complete systems, and has generally moved through the life cycle of a design artifact: from the creation phase, through communication and collaboration, to presentation and dissemination. As we attempt to preserve creative flow through the phases, we introduce social structures and constraints that drive the design of possible point solutions in the larger context of a digital design studio trail environment built in the lab. Although many of the interactions presented are viable across several design phases, this article focuses primarily on facilitating collaboration. We conclude with critical lessons learned of both what avenues have been fruitful and which roads to avoid. This article lightly covers the whole design process and attempts to inform readers of key factors to consider when designing for designers.

We describe a novel approach to inferring 3D curves from perspective drawings in an interactive design tool. Our methods are based on a traditional design drawing style known as analytic drawing , which supports precise image-space construction of a linear 3D scaffold. This scaffold in turn acts as a set of visual constraints for sketching 3D curves. We implement analytic drawing techniques in a pure-inference sketching interface which supports both single-and multi-view incremental construction of complex scaffolds and curve networks. A new representation of 3D drawings is proposed, and useful interactive drawing aids are described. Novel techniques are presented for deriving constraints from single-view sketches drawn relative to the current 3D scaffold, and then inferring 3D line and curve geometry which satisfies these constraints. The resulting analytic drawing tool allows 3D drawings to be constructed using exactly the same strokes as one would make on paper.

We describe a new type of graphical user interface widget called the "PieCursor." The PieCursor is based on the Tracking Menu technique and consists of a radial cluster of command wedges, is roughly the size of a cursor, and replaces the traditional cursor. The PieCursor technique merges the normal cursor function of pointing with command selection into a single action. A controlled experiment was conducted to compare the performance of rapid command and target selection using the PieCursor against larger versions of Tracking Menus and a status quo Toolbar configuration. Results indicate that for small clusters of tools (4 and 8 command wedges) the PieCursor can outperform the toolbar by 20.8% for coarse pointing. For fine pointing, the performance of the PieCursor degrades approximately to the performance found for the Toolbar condition.

Typical commercial 3D CAD tools provide modal tools such as pan, zoom, orbit, look, etc. to facilitate freeform navigation in a 3D scene. Mastering these navigation tools requires a significant amount of learning and even experienced computer users can find learning confusing and error-prone. To address this we have developed a concept called "Safe 3D Navigation" where we augment these modal tools with properties to reduce the occurance of confusing situations and improve the learning experience. In this paper we describe the major properties needed for safe navigation, the features we implemented to realize these properties, and usability tests on the effectiveness of these features. We conclude that indeed these properties do improve the learning experience for users that are new to 3D. Furthermore, many of the features we implemented for safe navigation are also very popular with experienced 3D users. As a result, these features have been integrated into six commercial 3D CAD applications and we recommend other application developers include these features to improve 3D navigation.

Literally hundreds of thousands of users of 2D computer-aided design (CAD) tools are in the difficult process of transitioning to 3D CAD tools. A common problem for these users is disorientation in the abstract virtual 3D environments that occur while developing new 3D scenes. To help address this problem, we present a novel in-scene 3D widget called the ViewCube as a 3D orientation indicator and controller. The ViewCube is a cube-shaped widget placed in a corner of the window. When acting as an orientation indicator, the ViewCube turns to reflect the current view direction as the user re-orients the scene using other tools. When used as an orientation controller, the ViewCube can be dragged, or the faces, edges, or corners can be clicked on, to easily orient the scene to the corresponding view. We conducted a formal experiment to measure the performance of the ViewCube comparing: (1) ArcBall-style dragging using the ViewCube for manual view switching, (2) clicking on face/edge/corner elements of the ViewCube for automated view switching and (3) clicking on a dedicated row of buttons for automated view switching. The results indicate that users prefer and are almost twice as fast at using the ViewCube with dragging compared to clicking techniques, independent of a number of ViewCube representations that we examined.

We describe a new interactive system for 3D design review, built to exploit the visual perception cue of motion parallax, in order to enhance shape perception and aesthetic evaluation. Traditional CAD applications typically use "bookmarked" static views for design evaluation. In our system, we replace static views with moving "shots" interspersed with cinematic visual transitions. Furthermore, users can access shots by picking object features on the 3D model, which invokes a spatial search over all shots, selects the ones deemed relevant to the feature, and plays back those shots. In this paper we describe the rationale behind this system, the main components, the implementation of the search technique, and the initial user evaluation of the system.

We describe a new interaction technique, called a spotlight, for directing the visual attention of an audience when viewing data or presentations on large wall-sized displays. A spotlight is simply a region of the display where the contents are displayed normally while the remainder of the display is somewhat darkened. In this paper we define the behavior of spotlights, show unique affordances of the technique, and discuss design characteristics. We also report on experiments that show the benefit of using the spotlight a large display and standard desktop configuration. Our results suggest that the spotlight is preferred over the standard cursor and outperforms it by a factor of 3.4 on a wall-sized display.

We describe a new interaction technique, called HoverCam, for navigating around 3D objects at close proximity. When a user is closely inspecting an object, the camera motions needed to move across its surface can become complex. For tasks such as 3D painting or modeling small detail features, users will often try to keep the camera a small distance above the surface. To achieve this automatically, HoverCam intelligently integrates tumbling, panning, and zooming camera controls into a single operation. This allows the user to focus on the task at hand instead of continuously managing the camera position and orientation. In this paper we show unique affordances of the technique and define the behavior and implementation of HoverCam. We also show how the technique can be used for navigating about data sets without well-defined surfaces such as point clouds and curves in space.

We describe a new widget and interaction technique, known as a "Frisbee," for interacting with areas of a large display that are difficult or impossible to access directly. A frisbee is simply a portal to another part of the display. It consists of a local "telescope" and a remote "target". The remote data surrounded by the target is drawn in the telescope and interactions performed within it are applied on the remote data. In this paper we define the behavior of frisbees, show unique affordances of the widget, and discuss design characteristics. We have implemented a test application and report on an experiment that shows the benefit of using the frisbee on a large display. Our results suggest that the frisbee is preferred over walking back and forth to the local and remote spaces at a distance of 4.5 feet.

We describe a new type of graphical user interface widget, known as a "tracking menu." A tracking menu consists of a cluster of graphical buttons, and as with traditional menus, the cursor can be moved within the menu to select and interact with items. However, unlike traditional menus, when the cursor hits the edge of the menu, the menu moves to continue tracking the cursor. Thus, the menu always stays under the cursor and close at hand.In this paper we define the behavior of tracking menus, show unique affordances of the widget, present a variety of examples, and discuss design characteristics. We examine one tracking menu design in detail, reporting on usability studies and our experience integrating the technique into a commercial application for the Tablet PC. While user interface issues on the Tablet PC, such as preventing round trips to tool palettes with the pen, inspired tracking menus, the design also works well with a standard mouse and keyboard configuration.

We review the Boom Chameleon, a novel input/output device consisting of a flat-panel display mounted on a tracked mechanical armature. The display acts as a physical window into 3D virtual environments, through which a one-to-one mapping between real and virtual space is preserved. The Boom Chameleon is further augmented with a touch-screen and a microphone/speaker combination. We created a 3D annotation application that exploits this unique configuration in order to simultaneously capture viewpoint, voice and gesture information. Results of an informal user study show that the Boom Chameleon annotation facilities have the potential to be an effective, and intuitive system for reviewing 3D designs.

Previous systems have explored the challenges of designing an interface for automotive styling which combine the metaphor of 2D drawing using physical tape with the simultaneous creation and management of a corresponding virtual 3D model. These systems have been limited to only 2D planar curves while typically the principal characteristic curves of an automotive design are three dimensional and non-planar. We present a system which addresses this limitation. Our system allows a designer to construct these non-planar 3D curves by drawing a series of 2D curves using the 2D tape drawing technique and interaction style. These results are generally applicable to the interface design of 3D modeling applications and also to the design of arm's length interaction on large scale display systems

This paper describes StyleCam, an approach for authoring 3D viewing experiences that incorporate stylistic elements that are not available in typical 3D viewers. A key aspect of StyleCam is that it allows the author to significantly tailor what the user sees and when they see it. The resulting viewing experience can approach the visual richness and pacing of highly authored visual content such as television commercials or feature films. At the same time, StyleCam allows for a satisfying level of interactivity while avoiding the problems inherent in using unconstrained camera models. The main components of StyleCam are camera surfaces which spatially constrain the viewing camera; animation clips that allow for visually appealing transitions between different camera surfaces; and a simple, unified, interaction technique that permits the user to seamlessly and continuously move between spatial-control of the camera and temporal-control of the animated transitions. Further, the user's focus of attention is always kept on the content, and not on extraneous interface widgets. In addition to describing the conceptual model of StyleCam, its current implementation, and an example authored experience, we also present the results of an evaluation involving real users.

We introduce the Boom Chameleon, a novel input/output device consisting of a flat-panel display mounted on a tracked mechanical boom. The display acts as a physical window into 3D virtual environments, through which a one-to-one mapping between real and virtual space is preserved. The Boom Chameleon is further augmented with a touch-screen and a microphone/speaker combination. We present a 3D annotation application that exploits this unique configuration in order to simultaneously capture viewpoint, voice and gesture information. Design issues are discussed and results of an informal user study on the device and annotation software are presented. The results show that the Boom Chameleon annotation facilities have the potential to be an effective, easy to learn and operate 3D design review system.

We present an alternate interface for 3D modeling for use on large scale displays. The interface integrates several concepts specifically selected and enhanced for large scale interaction. These include 2D construction planes spatially integrated in a 3D volume, enhanced orthographic views, smooth transitions between 2D and 3D views, tape drawing as the primary curve and line creation technique, visual viewpoint markers, and continuous two-handed interaction.