The support for multi-focus data exploration is vital in collaborative visualization. In these scenarios, which often involve multiple devices and large displays, users may focus on specific information on their individual screens while also sharing contextual views with others. While many visualization techniques developed for single-user applications can be adapted for use in collaborative settings, little research has been done on how to design adaptive versions of these techniques or how they may impact collaborative tasks involving large datasets. In this work, we perform a comparative study of three collaborative visualization techniques (Zooming, Interactive lenses and Overview+Detail) on large displays in three map-based visualization tasks (Exploration, Comparison and Spatial Memorizing). These three collaborative techniques draw on three different classical visualization techniques in a single-user setting. Our results show that these techniques have different impacts on users’ task performance and preferences. The collaborative Overview+Detail technique benefits users most in supporting Spatial Memorizing. Closely coupled groups prefer collaborative Zooming in Target Exploration. Based on these results, we further discuss the design of collaborative visualization techniques and propose suggestions for adapting classical single-user visualization techniques to a collaborative setting.

This paper looks at how mixed reality can be used for the improvement and enhancement of Chinese acupuncture practice through the introduction of an acupuncture training simulator. A prototype system developed for our study allows practitioners to insert virtual needles using their bare hands into a full-scale 3D representation of the human body with labelled acupuncture points. This provides them with a safe and natural environment to develop their acupuncture skills simulating the actual physical process of acupuncture. It also helps them to develop their muscle memory for acupuncture and better develops their memory of acupuncture points through a more immersive learning experience. We describe some of the design decisions and technical challenges overcome in the development of our system. We also present the results of a comparative user evaluation with potential users aimed at assessing the viability of such a mixed reality system being used as part of their training and development. The results of our evaluation reveal the training system outperformed in the enhancement of spatial understanding as well as improved learning and dexterity in acupuncture practice. These results go some way to demonstrating the potential of mixed reality for improving practice in therapeutic medicine.

This paper investigates how we can display multiple user selections on public multi-user wall-mounted large-display information visualization environments. This is done by looking at a prototype metro navigation system that allows different users to plan their route around a public metro system without relying on access to mobile devices by interacting with a large display. Our results show that user selections can be shown on this type of system can be done by using animation to highlight new selections with marching ants for lines and pulsing for points. Marching ants can merge to form a solid line, and pulsing can slow to stop after the user's selection is highlighted. This allows large numbers of users to use the same interface simultaneously as long as no two user's initial interaction occurs at the same time.

Multi-mobile devices connected to large displays afford collaborative exploration of large data sets and make decisions. However, typical interfaces for the large, such as an overview of the whole data set, do not well designed to support collaboration and promote communication. This paper introduces one innovative multiple view on large displays that accommodate multiple individual viewports in different scales in the shared space to facilitate data exchange, data comparison, and support communication. We conducted a controlled study to evaluate our approach to traditional shared display interfaces. The experiment found our techniques improved collaboration effectiveness, and individual detailed viewports during data exploration play an essential role in collaboration. Our work can potentially improve and extend our understanding of how to visualize information on shared displays.

This paper describes the Smart Survey Tool, a novel multi-device application for museum visitor tracking and tracking data visualization. The application allows museum staff to capture detailed information describing how visitors move around an exhibition and interact with individual exhibits. They can then visualize the results of tracking either on a single mobile device or with multiple mobile devices connected to a large display. The platform uses orthogonal views of the exhibition space for tracking and visualization, with a chess-piece icon to represent visitors during tracking, and curved semi-transparent lines with animated semi-circles to communicate the path and direction of visitor movement. Our visualization is novel in its use of an orthogonal projection for pedestrian tracking and animation to communicate the flow of visitors around the exhibition space, as well as allowing users to dynamically switch between views representing different groups of visitors. The design of our application was informed through an extensive requirements analysis study conducted with Nanjing Museum and evaluated by conducting expert interviews with museum managers who considered that the application allowed for more effective and efficient recording and analysis of visitor tracking data.

Abstract This research explores the suitability and effectiveness of two relatively new types of input device for navigating 3D virtual environments. These are infrared motion detection, like the Leap Motion tracker, and electromyographic gesture recognition, like the Myo Armband. Despite the introduction of a variety of new input devices intended to provide a more natural interaction experience, navigation within 3D virtual environments is still normally done on more traditional control devices such as game controllers or the keyboard–mouse combination. This study investigates the potential of new devices to support navigation in 3D environments through an experiment conducted with 27 participants using three different types of input devices to play a ball‐balancing maze‐like game. The input devices tested are a standard game controller, a Leap Motion tracker for infrared motion detection, and the Myo Armband for electromyographic gesture recognition. Results demonstrated the real potential of both types of device to support navigation interaction within 3D environments.

The 5th generation wireless system 5G will support Internet of Things IoT by increasing the interconnectivity of electronic devices to support a variety of new and promising networked applications such as the home of the future, environmental monitoring networks, and infrastructure management systems. The potential benefits of the IoT are as profound as they are diverse. However, the benefits of the IoT come with some significant challenges. Not the least of these is that the increased interconnectivity integral to an IoT network increases its vulnerability to malevolent attacks. There is still no proven methodology for the design of security frameworks with device authentication and access control. This paper attempts to address this problem through the development of a prototype security framework with robust and transparent security protection. This includes an investigation into the security requirements of three different characteristic IoT scenarios concretely, body IoT, home IoT, and hotel IoT, a design of new authentication mechanisms, and an access control subsystem with fine-grained roles and risk indicators. Our prototype security framework gives us an insight into some of the major difficulties of IoT security as well as providing some feasible solutions. Copyright © 2015 John Wiley & Sons, Ltd.

This paper presents a novel visual analytics technique developed to support exploratory search tasks for event data document collections. The technique supports discovery and exploration by clustering results and overlaying cluster summaries onto coordinated timeline and map views. Users can also explore and interact with search results by selecting clusters to filter and re-cluster the data with animation used to smooth the transition between views. The technique demonstrates a number of advantages over alternative methods for displaying and exploring geo-referenced search results and spatio-temporal data. Firstly, cluster summaries can be presented in a manner that makes them easy to read and scan. Listing representative events from each cluster also helps the process of discovery by preserving the diversity of results. Also, clicking on visual representations of geo-temporal clusters provides a quick and intuitive way to navigate across space and time simultaneously. This removes the need to overload users with the display of too many event labels at any one time. The technique was evaluated with a group of nineteen users and compared with an equivalent text based exploratory search engine.

BACKGROUND: High throughput gene expression time-course experiments provide a perspective on biological functioning recognized as having huge value for the diagnosis, treatment, and prevention of diseases. There are however significant challenges to properly exploiting this data due to its massive scale and complexity. In particular, existing techniques are found to be ill suited to finding patterns of changing activity over a limited interval of an experiments time frame. The Time-Series Explorer (TSE) was developed to overcome this limitation by allowing users to explore their data by controlling an animated scatter-plot view. MaTSE improves and extends TSE by allowing users to visualize data with missing values, cross reference multiple conditions, highlight gene groupings, and collaborate by sharing their findings. RESULTS: MaTSE was developed using an iterative software development cycle that involved a high level of user feedback and evaluation. The resulting software combines a variety of visualization and interaction techniques which work together to allow biologists to explore their data and reveal temporal patterns of gene activity. These include a scatter-plot that can be animated to view different temporal intervals of the data, a multiple coordinated view framework to support the cross reference of multiple experimental conditions, a novel method for highlighting overlapping groups in the scatter-plot, and a pattern browser component that can be used with scatter-plot box queries to support cooperative visualization. A final evaluation demonstrated the tools effectiveness in allowing users to find unexpected temporal patterns and the benefits of functionality such as the overlay of gene groupings and the ability to store patterns. CONCLUSIONS: We have developed a new exploratory analysis tool, MaTSE, that allows users to find unexpected patterns of temporal activity in gene expression time-series data. Overall, the study acted well to demonstrate the benefits of an iterative software development life cycle and allowed us to investigate some visualization problems that are likely to be common in the field of bioinformatics. The subjects involved in the final evaluation were positive about the potential of MaTSE to help them find unexpected patterns in their data and characterized MaTSE as an exploratory tool valuable for hypothesis generation and the creation of new biological knowledge.

This paper presents a novel vertical timeline information-visualization technique developed to support the analysis of human-computer dialogue data. The technique uses combined linked views including distorted views to effectively communicate the timing of dialogue events while presenting text in such a manner that it is easily readable. A prototype has been implemented and tested to demonstrate the technique's effectiveness for supporting exploration and revealing previously unsuspected patterns.

Current techniques for visualising large-scale microarray data are unable to present temporal features without reducing the number of elements being displayed. This paper introduces a technique that overcomes this problem by combining a novel display technique, which operates over a continuous temporal subset of the time series, with direct manipulation of the parameters defining the subset.